This document discusses methods for improving the selectivity of surface electromyography (EMG) recordings of facial muscles. It aims to reduce crosstalk between muscles using electrode parameters while minimizing drawbacks. The study examines two electrode parameters - electrode contact shape and bipolar spacing - while recording EMG from 8 sites on 20 subjects viewing pictures. Results found the parameters affected signal amplitude but no consistent increase in selectivity as measured by the Selective Value. However, the Selective Value alone may not reliably measure selectivity.
Electromyography Analysis for Person IdentificationCSCJournals
Physiological descriptions of the electromyography signal and other literature say that when we make a motion, the motor neurons of respective muscle get activated and all the innervated motor units in that zone produce motor unit action potential. These motor unit action potentials travel through the muscle fibers with conduction velocity and superimposed signal gets recorded at the electrode site. Here we have taken an analogy from the speech production system model as the excitation signal travels through vocal tract to produce speech; similarly, an impulse train of firing rate frequency goes through the system with impulse response of motor unit action potentials and travels along the muscle fiber of that person. As the vocal tract contains the speaker information, we can also separate the muscle fiber pattern part and motor unit discharge pattern through proper selection of features and its classification to identify the respective person. Cepstral and non uniform filter bank features models the variation in the spectrum of the signals. Vector quantization and Gaussian mixture model are the two techniques of pattern matching have been applied.
pediatric electrodiagnostic for cerebral palsy,
A diagnosis of CP is often made based on MRI, delay of motor milestones and the presence of gait abnormalities in young children
Although the initial brain injury is non-progressive, the musculoskeletal impairments and functional limitations associated with CP are progressive
Three main classes of CP include spastic, dyskinetic and ataxic
1. The document discusses the use of EMG to guide and evaluate lumbar spine manual therapy. Several studies have used real-time EMG to monitor paraspinal muscle activity during manual therapy techniques.
2. One study found increased spinal stiffness and positive neuromuscular responses during thrust techniques compared to those with less back pain. Another found increased paraspinal muscle strength immediately following spinal manipulation.
3. A third study observed paraspinal EMG patterns mimicking stretching responses during myofascial treatments, relating clinical effectiveness to tonic muscle reactions detected by EMG.
During limb movement and changes in position, the tissues around the relevant joints will be deformed, including skin, muscles, tendons, fascia, joint capsules, and ligaments
All these tissues are innervated by mechanically sensitive receptors, and their density varies across muscles and regions of the body
Muscle spindles play the major role in kinesthesia, with some skin receptors providing additional information
Golgi tendon organs contribute to proprioception, including the senses of force and heaviness
Neural adaptations to aerobic and resistance exercise training in geriatric p...Mohammad azharuddin
The document discusses several neural adaptations that can occur with anaerobic training:
1) Increased motor cortex activity leads to greater motor unit activation and recruitment of fast-twitch motor units.
2) Adaptations in the spinal cord allow for enhanced recruitment of fast-twitch motor units to support higher force production.
3) Motor units can adapt through increased firing rates and recruitment of more motor units to generate greater force. Orderly recruitment is governed by the size principle from low to high threshold motor units.
4) The neuromuscular junction may also adapt through changes induced by high-intensity versus low-intensity exercise training.
The document discusses the multifidus muscle and its importance for spinal stability and motor control. It provides details on its anatomy and function, explaining how weakness or dysfunction of the multifidus can contribute to spinal issues. The document also discusses approaches to strengthening the multifidus through specific stabilization exercises and motor learning principles to help patients regain control and function.
Electromyography Analysis for Person IdentificationCSCJournals
Physiological descriptions of the electromyography signal and other literature say that when we make a motion, the motor neurons of respective muscle get activated and all the innervated motor units in that zone produce motor unit action potential. These motor unit action potentials travel through the muscle fibers with conduction velocity and superimposed signal gets recorded at the electrode site. Here we have taken an analogy from the speech production system model as the excitation signal travels through vocal tract to produce speech; similarly, an impulse train of firing rate frequency goes through the system with impulse response of motor unit action potentials and travels along the muscle fiber of that person. As the vocal tract contains the speaker information, we can also separate the muscle fiber pattern part and motor unit discharge pattern through proper selection of features and its classification to identify the respective person. Cepstral and non uniform filter bank features models the variation in the spectrum of the signals. Vector quantization and Gaussian mixture model are the two techniques of pattern matching have been applied.
pediatric electrodiagnostic for cerebral palsy,
A diagnosis of CP is often made based on MRI, delay of motor milestones and the presence of gait abnormalities in young children
Although the initial brain injury is non-progressive, the musculoskeletal impairments and functional limitations associated with CP are progressive
Three main classes of CP include spastic, dyskinetic and ataxic
1. The document discusses the use of EMG to guide and evaluate lumbar spine manual therapy. Several studies have used real-time EMG to monitor paraspinal muscle activity during manual therapy techniques.
2. One study found increased spinal stiffness and positive neuromuscular responses during thrust techniques compared to those with less back pain. Another found increased paraspinal muscle strength immediately following spinal manipulation.
3. A third study observed paraspinal EMG patterns mimicking stretching responses during myofascial treatments, relating clinical effectiveness to tonic muscle reactions detected by EMG.
During limb movement and changes in position, the tissues around the relevant joints will be deformed, including skin, muscles, tendons, fascia, joint capsules, and ligaments
All these tissues are innervated by mechanically sensitive receptors, and their density varies across muscles and regions of the body
Muscle spindles play the major role in kinesthesia, with some skin receptors providing additional information
Golgi tendon organs contribute to proprioception, including the senses of force and heaviness
Neural adaptations to aerobic and resistance exercise training in geriatric p...Mohammad azharuddin
The document discusses several neural adaptations that can occur with anaerobic training:
1) Increased motor cortex activity leads to greater motor unit activation and recruitment of fast-twitch motor units.
2) Adaptations in the spinal cord allow for enhanced recruitment of fast-twitch motor units to support higher force production.
3) Motor units can adapt through increased firing rates and recruitment of more motor units to generate greater force. Orderly recruitment is governed by the size principle from low to high threshold motor units.
4) The neuromuscular junction may also adapt through changes induced by high-intensity versus low-intensity exercise training.
The document discusses the multifidus muscle and its importance for spinal stability and motor control. It provides details on its anatomy and function, explaining how weakness or dysfunction of the multifidus can contribute to spinal issues. The document also discusses approaches to strengthening the multifidus through specific stabilization exercises and motor learning principles to help patients regain control and function.
1) Muscle tone is a state of partial contraction of resting muscle that maintains body posture through continuous motor impulses from reflexes.
2) Muscle spindles are stretch receptors that provide sensory feedback on muscle length and rate of stretch. Their afferents signal to the CNS and regulate motor neuron activity.
3) Spasticity results from loss of supraspinal control over reflexes after upper motor neuron injury, causing velocity-dependent increases in tonic stretch reflexes and impaired voluntary movement.
This document provides an overview of the muscular system, including the different types of muscles and skeletal muscle structure and function. It discusses the sliding filament theory of muscle contraction and the role of calcium, troponin, tropomyosin, ATP, myosin, and actin. It also addresses muscle fatigue, specificity of muscle fiber recruitment, and different muscle fiber types. Injury such as delayed onset muscle soreness is also summarized.
1) Musculoskeletal pain can cause changes in motor activity and control, including both increases and decreases in muscle activity.
2) Experimental evidence shows that nociception affects motor function through changes in muscle activity, neuronal control mechanisms, proprioception, and local muscle morphology.
3) Various models have been proposed to explain motor responses to pain, including the vicious cycle model and pain adaptation model, but these do not fully capture the complex scenario seen clinically, particularly in chronic pain.
The document discusses different types of disorders of muscle tone including spasticity, rigidity, flaccidity, and atonia. It describes how damage to different pathways in the motor system can result in these disorders and their associated signs and symptoms. The effects of lesions to specific cranial and spinal nerves involved in motor speech are also reviewed, and how this can impact the structures and functions of the oral speech mechanism.
Neuromuscular coordination allows the nervous system and muscles to work together to enable body movement. It functions on two levels: intra-muscular coordination which controls individual muscle fiber activation, and inter-muscular coordination which coordinates muscle groups. Neuromuscular coordination depends on factors like rate coding of motor unit firing, recruitment of more motor units through resistance training, and synchronization of motor unit discharge. Strength training exercises can improve neuromuscular coordination by increasing rate coding, recruitment, and synchronization.
This document discusses muscle plasticity, which refers to the ability of skeletal muscle to adapt structurally and functionally in response to environmental changes such as increased or decreased activity levels. It provides definitions and history of the concept. It describes the effects of chronic low frequency electrical stimulation on muscles, including fiber type transformations, increased mitochondria and vascularization, and changes to contractile properties. Over time periods of hours to weeks, stimulated muscles demonstrate metabolic and structural adaptations that increase their fatigue resistance and transform them from fast-twitch to slow-twitch phenotypes. Several studies are summarized that investigate muscle adaptations to long-term stimulation in animals and humans.
The term Spinal Cord Injury is used to refer to neurological damage of the spinal cord
Any lesion involving the spinal cord result a syndrome called a “myelopathy”
Spinal cord injuries are defined as complete or incomplete according to the International Standards for the Neurological Classifification of SCI and the American Spinal Injuries Association Impairment Scale (AIS)
Complete lesions are defifined as AIS A, and incomplete lesions are defifined as AIS B, AIS C, AIS D or AIS E (Harvey, 2016)
This document defines and describes different types of muscle tone abnormalities. Muscle tone is the resistance offered by muscles to passive stretch. Hypertonia includes spasticity and rigidity, where there is increased resistance to stretch. Spasticity is velocity-dependent and involves exaggerated reflexes. Rigidity is resistance throughout range of motion. Hypotonia involves decreased or absent resistance and flaccidity. Specific types of hypertonia and hypotonia are further described based on their neurological causes and clinical presentations.
Electromyography (EMG) is a diagnostic test that assesses muscle and nerve health by measuring electrical activity in muscles. During an EMG, a provider inserts small needle electrodes into a patient's muscle to record electrical signals both at rest and during muscle activation. The test helps evaluate conditions causing tingling, numbness, and weakness. It takes 30 to 60 minutes to complete and may cause minor bruising or tenderness at the needle sites.
This document provides an overview of spasticity, including:
- Definitions and descriptions of spasticity and the underlying pathophysiology.
- Common causes of spasticity like cerebral palsy, stroke, multiple sclerosis, and spinal cord injury.
- Methods for assessing spasticity severity, including the Ashworth scale and pendulum tests.
- Goals and approaches for managing spasticity, which may involve eliminating triggers, non-pharmacological interventions, medications, and occasionally surgery.
This document provides an introduction to kinesiological electromyography (EMG). It discusses the basics of EMG including:
- The origin of the EMG signal from motor unit action potentials generated by muscle fiber membranes.
- How the EMG signal is detected using surface electrodes and processed to analyze muscle activation patterns.
- Key concepts for interpreting the EMG signal including recruitment, firing frequency, and the interference pattern resulting from the superposition of multiple motor unit action potentials.
- Guidelines for proper EMG signal acquisition and processing to obtain meaningful data on muscle function.
The document discusses motor control theories, specifically reflex theory. Reflex theory proposes that reflexes are the basic building blocks of movement, where a sensory stimulus triggers a stereotypical motor response. However, reflex theory has limitations in explaining voluntary movements, movements without sensory input, fast sequential movements, and the ability to override or modify reflexes. The document also discusses clinical implications of reflex theory and neurofacilitation approaches that were developed based on reflex and hierarchical theories of motor control.
This document discusses the structure and function of the three main types of muscle in the human body: skeletal, smooth, and cardiac muscle. It describes the microscopic structure of skeletal muscle including sarcomeres, actin and myosin filaments, and the sliding filament model of contraction. It also outlines the macroscopic components of skeletal muscle including muscle fibers, fiber bundles, and muscle bellies. Finally, it discusses the coordinated action of agonist, antagonist, synergist and fixator muscles to produce movement.
This document provides an overview of muscle and neural physiology, covering topics such as gross muscle structure, microstructure, muscle contractions, and factors that affect force production. It describes the layers that make up muscle tissue from the epimysium on the outside to the endomysium surrounding each muscle fiber. On the microscopic level, it details the components of the sarcomere including actin, myosin, and proteins involved in muscle contraction. It explains the sliding filament theory of muscle contraction and types of contractions. Factors discussed that can influence force production include cross-sectional area, velocity of shortening, angle of pennation, sarcomere length, and muscle fiber type. The document also reviews research on muscle fiber
4. lectura caracteristicas del sistema nerviosos para produccion de movimientoPaulo Osmar
This document summarizes key aspects of the neuromuscular system involved in movement production. It discusses 3 main topics:
1) Muscle properties including excitation, contraction mechanisms, force-length and force-velocity relationships, and motor unit organization.
2) Neuronal properties such as action potential conduction and myelination which facilitates signal transmission.
3) Sensory receptors that provide feedback to the CNS, including muscle spindles and Golgi tendon organs. Reflexes and central processing of afferent signals are also covered.
The document provides an overview of the basic physiology underlying motor control systems in the body.
The document discusses principles of body mechanics and muscle physiology related to function. It covers topics like stability, equilibrium, effort distribution, muscle fiber types, motor unit recruitment, and roles of different muscles. Some key points are:
- The wider the base of support and lower the center of gravity, the greater the stability. Equilibrium is maintained as long as gravity passes through the base.
- Using larger muscle groups and keeping the center of gravity close to the work load prevents strain. Different muscle fiber types (slow oxidative, fast oxidative, fast glycolytic) support different functions.
- A motor unit is all the fibers innervated by a motor neuron. Maximum strength occurs when all motor units fire together
Neuromuscular coordination is the ability of the central nervous system to control muscles to execute multi-limb movements. It involves coordination between nerves and muscles at the neuromuscular junction, where motor neurons activate individual muscle fibers or groups of fibers within motor units. There are two types of coordination: intermuscular, which involves individual muscle activation; and intermuscular, which involves interaction between agonist, antagonist, synergist and fixator muscle groups to perform smooth, rhythmical movements for specific tasks. A lack of coordination is called incoordination and can be caused by neurological conditions like flaccidity, spasticity, cerebral ataxia, loss of proprioception, or tabes dorsalis, resulting
The document describes the nervous system and its divisions. It includes:
1) The nervous system has two main divisions - the central nervous system (CNS) made up of the brain and spinal cord, and the peripheral nervous system (PNS) made up of nerves outside the CNS.
2) Neurons are the basic functional units and come in sensory, motor, and interneuron types. Neuroglia are supportive glial cells like astrocytes and oligodendrocytes.
3) The CNS contains gray matter with neuron cell bodies and white matter with myelinated axon tracts. The PNS contains ganglia with neuron cell bodies and nerves with bundled axons.
This document provides an overview of skeletal muscle structure and function. It discusses that muscles contain bundles of muscle fibers surrounded by connective tissue. Each muscle fiber contains myofibrils which are made up of repeating contractile units called sarcomeres. Sarcomeres contain thin actin filaments and thick myosin filaments; muscle contraction occurs when myosin heads use ATP to pull on actin filaments, shortening the sarcomere. The document outlines other structural features of muscle fibers and sarcomeres that enable contraction, including regulatory proteins, cytoskeletal elements, and the sarcoplasmic reticulum which regulates calcium levels. Force production and speed of contraction vary depending on the load and type of contraction.
Supporting relationships with awareness systemsOnno Romijn
The paper describes the design of a novel end-to-end communication system for helping elderly people and their grandchildren keep in touch in a pleasurable, low-pace interaction. The paper focuses on the requirements gathering process that combined diaries with field testing of prototypes and interviews; thereby bringing elements of more ‘playful’ design to a well- structured requirements engineering process.
Supporting social presence through asynchronous awareness systemsOnno Romijn
This chapter discusses research conducted to understand the requirements of elderly for informal social telecommunication media that may be addressed through awareness technologies. It discusses the relation between the concept of social presence and the notion of awareness that the class of systems studied supports. Finally, we draw attention to the research method used which we feel is the most appropriate for gauging the social effects of technologies introduced to support social activities through ICT
1) Muscle tone is a state of partial contraction of resting muscle that maintains body posture through continuous motor impulses from reflexes.
2) Muscle spindles are stretch receptors that provide sensory feedback on muscle length and rate of stretch. Their afferents signal to the CNS and regulate motor neuron activity.
3) Spasticity results from loss of supraspinal control over reflexes after upper motor neuron injury, causing velocity-dependent increases in tonic stretch reflexes and impaired voluntary movement.
This document provides an overview of the muscular system, including the different types of muscles and skeletal muscle structure and function. It discusses the sliding filament theory of muscle contraction and the role of calcium, troponin, tropomyosin, ATP, myosin, and actin. It also addresses muscle fatigue, specificity of muscle fiber recruitment, and different muscle fiber types. Injury such as delayed onset muscle soreness is also summarized.
1) Musculoskeletal pain can cause changes in motor activity and control, including both increases and decreases in muscle activity.
2) Experimental evidence shows that nociception affects motor function through changes in muscle activity, neuronal control mechanisms, proprioception, and local muscle morphology.
3) Various models have been proposed to explain motor responses to pain, including the vicious cycle model and pain adaptation model, but these do not fully capture the complex scenario seen clinically, particularly in chronic pain.
The document discusses different types of disorders of muscle tone including spasticity, rigidity, flaccidity, and atonia. It describes how damage to different pathways in the motor system can result in these disorders and their associated signs and symptoms. The effects of lesions to specific cranial and spinal nerves involved in motor speech are also reviewed, and how this can impact the structures and functions of the oral speech mechanism.
Neuromuscular coordination allows the nervous system and muscles to work together to enable body movement. It functions on two levels: intra-muscular coordination which controls individual muscle fiber activation, and inter-muscular coordination which coordinates muscle groups. Neuromuscular coordination depends on factors like rate coding of motor unit firing, recruitment of more motor units through resistance training, and synchronization of motor unit discharge. Strength training exercises can improve neuromuscular coordination by increasing rate coding, recruitment, and synchronization.
This document discusses muscle plasticity, which refers to the ability of skeletal muscle to adapt structurally and functionally in response to environmental changes such as increased or decreased activity levels. It provides definitions and history of the concept. It describes the effects of chronic low frequency electrical stimulation on muscles, including fiber type transformations, increased mitochondria and vascularization, and changes to contractile properties. Over time periods of hours to weeks, stimulated muscles demonstrate metabolic and structural adaptations that increase their fatigue resistance and transform them from fast-twitch to slow-twitch phenotypes. Several studies are summarized that investigate muscle adaptations to long-term stimulation in animals and humans.
The term Spinal Cord Injury is used to refer to neurological damage of the spinal cord
Any lesion involving the spinal cord result a syndrome called a “myelopathy”
Spinal cord injuries are defined as complete or incomplete according to the International Standards for the Neurological Classifification of SCI and the American Spinal Injuries Association Impairment Scale (AIS)
Complete lesions are defifined as AIS A, and incomplete lesions are defifined as AIS B, AIS C, AIS D or AIS E (Harvey, 2016)
This document defines and describes different types of muscle tone abnormalities. Muscle tone is the resistance offered by muscles to passive stretch. Hypertonia includes spasticity and rigidity, where there is increased resistance to stretch. Spasticity is velocity-dependent and involves exaggerated reflexes. Rigidity is resistance throughout range of motion. Hypotonia involves decreased or absent resistance and flaccidity. Specific types of hypertonia and hypotonia are further described based on their neurological causes and clinical presentations.
Electromyography (EMG) is a diagnostic test that assesses muscle and nerve health by measuring electrical activity in muscles. During an EMG, a provider inserts small needle electrodes into a patient's muscle to record electrical signals both at rest and during muscle activation. The test helps evaluate conditions causing tingling, numbness, and weakness. It takes 30 to 60 minutes to complete and may cause minor bruising or tenderness at the needle sites.
This document provides an overview of spasticity, including:
- Definitions and descriptions of spasticity and the underlying pathophysiology.
- Common causes of spasticity like cerebral palsy, stroke, multiple sclerosis, and spinal cord injury.
- Methods for assessing spasticity severity, including the Ashworth scale and pendulum tests.
- Goals and approaches for managing spasticity, which may involve eliminating triggers, non-pharmacological interventions, medications, and occasionally surgery.
This document provides an introduction to kinesiological electromyography (EMG). It discusses the basics of EMG including:
- The origin of the EMG signal from motor unit action potentials generated by muscle fiber membranes.
- How the EMG signal is detected using surface electrodes and processed to analyze muscle activation patterns.
- Key concepts for interpreting the EMG signal including recruitment, firing frequency, and the interference pattern resulting from the superposition of multiple motor unit action potentials.
- Guidelines for proper EMG signal acquisition and processing to obtain meaningful data on muscle function.
The document discusses motor control theories, specifically reflex theory. Reflex theory proposes that reflexes are the basic building blocks of movement, where a sensory stimulus triggers a stereotypical motor response. However, reflex theory has limitations in explaining voluntary movements, movements without sensory input, fast sequential movements, and the ability to override or modify reflexes. The document also discusses clinical implications of reflex theory and neurofacilitation approaches that were developed based on reflex and hierarchical theories of motor control.
This document discusses the structure and function of the three main types of muscle in the human body: skeletal, smooth, and cardiac muscle. It describes the microscopic structure of skeletal muscle including sarcomeres, actin and myosin filaments, and the sliding filament model of contraction. It also outlines the macroscopic components of skeletal muscle including muscle fibers, fiber bundles, and muscle bellies. Finally, it discusses the coordinated action of agonist, antagonist, synergist and fixator muscles to produce movement.
This document provides an overview of muscle and neural physiology, covering topics such as gross muscle structure, microstructure, muscle contractions, and factors that affect force production. It describes the layers that make up muscle tissue from the epimysium on the outside to the endomysium surrounding each muscle fiber. On the microscopic level, it details the components of the sarcomere including actin, myosin, and proteins involved in muscle contraction. It explains the sliding filament theory of muscle contraction and types of contractions. Factors discussed that can influence force production include cross-sectional area, velocity of shortening, angle of pennation, sarcomere length, and muscle fiber type. The document also reviews research on muscle fiber
4. lectura caracteristicas del sistema nerviosos para produccion de movimientoPaulo Osmar
This document summarizes key aspects of the neuromuscular system involved in movement production. It discusses 3 main topics:
1) Muscle properties including excitation, contraction mechanisms, force-length and force-velocity relationships, and motor unit organization.
2) Neuronal properties such as action potential conduction and myelination which facilitates signal transmission.
3) Sensory receptors that provide feedback to the CNS, including muscle spindles and Golgi tendon organs. Reflexes and central processing of afferent signals are also covered.
The document provides an overview of the basic physiology underlying motor control systems in the body.
The document discusses principles of body mechanics and muscle physiology related to function. It covers topics like stability, equilibrium, effort distribution, muscle fiber types, motor unit recruitment, and roles of different muscles. Some key points are:
- The wider the base of support and lower the center of gravity, the greater the stability. Equilibrium is maintained as long as gravity passes through the base.
- Using larger muscle groups and keeping the center of gravity close to the work load prevents strain. Different muscle fiber types (slow oxidative, fast oxidative, fast glycolytic) support different functions.
- A motor unit is all the fibers innervated by a motor neuron. Maximum strength occurs when all motor units fire together
Neuromuscular coordination is the ability of the central nervous system to control muscles to execute multi-limb movements. It involves coordination between nerves and muscles at the neuromuscular junction, where motor neurons activate individual muscle fibers or groups of fibers within motor units. There are two types of coordination: intermuscular, which involves individual muscle activation; and intermuscular, which involves interaction between agonist, antagonist, synergist and fixator muscle groups to perform smooth, rhythmical movements for specific tasks. A lack of coordination is called incoordination and can be caused by neurological conditions like flaccidity, spasticity, cerebral ataxia, loss of proprioception, or tabes dorsalis, resulting
The document describes the nervous system and its divisions. It includes:
1) The nervous system has two main divisions - the central nervous system (CNS) made up of the brain and spinal cord, and the peripheral nervous system (PNS) made up of nerves outside the CNS.
2) Neurons are the basic functional units and come in sensory, motor, and interneuron types. Neuroglia are supportive glial cells like astrocytes and oligodendrocytes.
3) The CNS contains gray matter with neuron cell bodies and white matter with myelinated axon tracts. The PNS contains ganglia with neuron cell bodies and nerves with bundled axons.
This document provides an overview of skeletal muscle structure and function. It discusses that muscles contain bundles of muscle fibers surrounded by connective tissue. Each muscle fiber contains myofibrils which are made up of repeating contractile units called sarcomeres. Sarcomeres contain thin actin filaments and thick myosin filaments; muscle contraction occurs when myosin heads use ATP to pull on actin filaments, shortening the sarcomere. The document outlines other structural features of muscle fibers and sarcomeres that enable contraction, including regulatory proteins, cytoskeletal elements, and the sarcoplasmic reticulum which regulates calcium levels. Force production and speed of contraction vary depending on the load and type of contraction.
Supporting relationships with awareness systemsOnno Romijn
The paper describes the design of a novel end-to-end communication system for helping elderly people and their grandchildren keep in touch in a pleasurable, low-pace interaction. The paper focuses on the requirements gathering process that combined diaries with field testing of prototypes and interviews; thereby bringing elements of more ‘playful’ design to a well- structured requirements engineering process.
Supporting social presence through asynchronous awareness systemsOnno Romijn
This chapter discusses research conducted to understand the requirements of elderly for informal social telecommunication media that may be addressed through awareness technologies. It discusses the relation between the concept of social presence and the notion of awareness that the class of systems studied supports. Finally, we draw attention to the research method used which we feel is the most appropriate for gauging the social effects of technologies introduced to support social activities through ICT
The Customer Experience Compass brings together the key elements that influence the customer experience. This whitepaper describes the elements of the model in more detail to help assess and shape the customer experience roadmap of your organization.
This document discusses the analysis of surface electromyography (EMG) parameters. It begins with an introduction to EMG and its uses. It then outlines the three phases of the project: literature review and hardware design, understanding bio-correlations and designing hardware, and signal processing and parameter extraction. Details are provided on electrode placement, signal acquisition methods, sources of noise, pre-processing techniques, and parameters to be extracted in both time and frequency domains. The timeline for the project is also presented.
Electromyography (EMG) measures the electrical activity produced by muscle contractions. Surface EMG (sEMG) uses electrodes on the skin to detect muscle activation, while fine wire EMG inserts electrodes directly into muscles. EMG can indicate which muscles are active during motions like gait, but does not determine strength, movement type, or whether activity is compensatory. Proper electrode positioning, skin preparation, and signal processing are needed to obtain accurate, repeatable EMG data for analysis of muscle function.
Electromyography (EMG) is a technique that evaluates and records the electrical activity of skeletal muscles using an electromyograph instrument. EMG detects the electrical potentials generated by muscle cells during contraction. An EMG examination involves using electrodes to detect these potentials from muscles at rest and during varying degrees of contraction. The recorded signals provide information about motor unit potentials, recruitment, and other features that can help diagnose neuropathies and myopathies. EMG analysis may be qualitative by visual inspection or quantitative by measuring amplitude, duration, and frequency.
Azad Almuthaffer B.D.S., M.Sc. prosth.
Babylon university College of dentistry
Prosthodontic department
Third class
FOURTH EDITION 2015-2016 You can download these lectures from: (moodle) electronic-learning platform. or use this link: www.uobabylon.edu.iq/uobcoleges/default.aspx?fid=4 E-mail of lecturer: azadontics@gmail.com
Micro Expressions are brief, involuntary facial expressions shown on the face of humans according to emotions experienced.
They occur when a person is consciously trying to conceal all signs of how he or she is feeling, or when a person does not consciously know how he or she is feeling.
In this deck, a brief history of micro expressions is introduced, along with a detailed analysis of the 7 universal facial expressions that could be found in almost anyone walking on this Earth.
Nathalie Nahai - The secret psychology of persuasive copy (Conversion Confere...Nathalie Nahai
In this keynote presentation for Conversion Conference (Las Vegas, 2015), I explain the psychology behind some of the world’s most persuasive copy, and how you can use these techniques in your own content.
In the talk we’ll cover:
1. Psychological keyword optimisation
2. Trigger words and how to use them
3. The hidden drivers of human behaviour
4. Powerful heuristics and how to leverage them
5. How to use your values to create trust
I also explain the scientific basis behind each principle, and illustrate how to apply them with numerous case studies from a variety of industries.
Want more?
Download the slides here: http://bit.ly/persuasive_copy
And checkout more resources at my website: http://www.thewebpsychologist.com/
An immersive workshop at General Assembly, SF. I typically teach this workshop at General Assembly, San Francisco. To see a list of my upcoming classes, visit https://generalassemb.ly/instructors/seth-familian/4813
I also teach this workshop as a private lunch-and-learn or half-day immersive session for corporate clients. To learn more about pricing and availability, please contact me at http://familian1.com
TEDx Manchester: AI & The Future of WorkVolker Hirsch
TEDx Manchester talk on artificial intelligence (AI) and how the ascent of AI and robotics impacts our future work environments.
The video of the talk is now also available here: https://youtu.be/dRw4d2Si8LA
Non-uniform electromyographic activity during fatigue and recovery of the vas...Nosrat hedayatpour
The aim of the study was to investigate EMG signal features
during fatigue and recovery at three locations of the vastus
medialis and lateralis muscles.
This document discusses the use of surface electromyography (EMG) in biomechanics. It reviews many factors that can influence the EMG signal and force produced by a muscle, including intrinsic physiological factors like motor unit firing characteristics and extrinsic technical factors like electrode placement. The document focuses on three main applications of surface EMG: determining muscle activation timing, relating EMG to muscle force, and using EMG as a fatigue index. It provides recommendations for proper use and identifies outstanding challenges in the field.
This study investigated how localized muscle fatigue of the ankle plantarflexors affects spatial electromyography (EMG) patterns in the medial gastrocnemius muscle during walking and running. The researchers recorded high-density EMG from the medial gastrocnemius before and after subjects performed a calf raise task to induce fatigue. They found that after fatigue, peak EMG activity decreased but mean power frequency increased during locomotion. Additionally, the location of peak EMG shifted proximally compared to the pre-fatigue location, suggesting altered motor unit recruitment to distribute muscle loads. Despite these EMG changes, lower limb biomechanics were similar before and after fatigue.
Work-related neck and shoulder pains are highly prevalent in jobs with low physical exposure. Myalgia of the trapezius muscle is one of the most prevalent work-related neck-shoulder disorders and muscle fatigue is widely considered a precursor of such disorders. There is evidence that long-lasting low-level activity of the trapezius muscle appears as a crucial link in the pathway from workplace physiological and psychological
demands to the development of work related neck pain. A possible approach to reduce the risks associated with muscle fatigue is to disrupt the monotonous muscle activity by adding frequent, active breaks during the working task. In the first phase of our investigation the long lasting component of trapezius muscle fatigue resulting from low level, sustained working task and spatio-temporal distribution of EMG activity are
investigated in two conditions including passive break or active disruption of muscle contraction.
Muscle fatigue develops and persists after the end of the workday. It appears that the alteration of force control may be associated with the corresponding fatigue. However, these phenomena seem to be counteracted by disruption of muscle contraction monotony by active interventions during the workday. Indeed, the presence of active disruptions also induces changes in the timing and degree of EMG activity as well as features of trapezius active areas. The extent of these adaptations appears to be subject and work task dependent but seem to be beneficial for the reduction of muscle fatigue.
Electromyography (EMG) is the study of muscle electrical activity. Key developments included:
- In the 1600s, Redi documented electric rays as a source of muscle electricity.
- In 1773, Walsh showed eels' muscle tissue could generate sparks.
- In the 1790s, Galvani provided direct evidence linking muscle contraction and electricity by stimulating muscles with static electricity.
- Volta later concluded Galvani's findings were due to dissimilar metals touching muscle, not muscle itself.
- In the 1800s, techniques like using galvanometers to study nerve and muscle electrical activity advanced the field.
- Modern SEMG allows noninvasive quantification of muscle electrical activity through sensors
This study aimed to investigate the neuromotor effects of transverse friction massage (TFM) on the quadriceps femoris tendon using surface electromyography, force sensors, and ultrafast ultrasound. Fourteen healthy males received TFM on their quadriceps tendon while fifteen controls rested. Signals were recorded before and after TFM/resting to analyze time delays related to excitation-contraction coupling, force transmission, and electromechanical delay during voluntary contractions. Results showed TFM increased the time of excitation-contraction coupling and electromechanical delay, while decreasing time of force transmission, suggesting TFM influences neuro-motor mechanisms and changes muscle and tendon stiffness. The study provides insight into how TFM applied
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Effect of Endurance on Gastrocnemius Muscle with Exercise by Employing EMG Am...ijtsrd
Muscle fatigue is a common experience in daily life. Many authors have defined it as the incapacity to maintain the required or expected force, and therefore, force, power and torque recordings have been used as direct measurements of muscle fatigue. In addition, the measurement of these variables combined with the measurement of surface electromyography sEMG recordings which can be measured during all types of movements during exercise may be useful to assess and understand muscle fatigue. EMG signal can be easily analyzed in time domain, frequency domain and time frequency domain. The time domain features are the most popular in EMG pattern recognition because they are easy and quick to calculate and they do not require a transformation. The purpose of this study was to analyze the fatigue and to study the endurance occurrence in the Gastrocnemius muscle with a pre defined exercise protocol for the targeted muscle. For this purpose, sEMG Amplitude parameters were characterized. Relation between EMG features like mean, force, standard deviation, etc. is verified for fatigue detection as well as to identify the Endurance developed in the Gastrocnemius muscle. Gaurav Patti | Poonam Kumari "Effect of Endurance on Gastrocnemius Muscle with Exercise by Employing EMG Amplitude Parameters" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-5 , August 2020, URL: https://www.ijtsrd.com/papers/ijtsrd33222.pdf Paper Url :https://www.ijtsrd.com/engineering/other/33222/effect-of-endurance-on-gastrocnemius-muscle-with-exercise-by-employing-emg-amplitude-parameters/gaurav-patti
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
This document discusses electroMyoGRAPHY (EMG), which is the process of recording electrical activity in skeletal muscles using electrodes. An electroMyoGRAM is the recording produced, while an electroMyoGRAPH is the instrument used. EMG can be performed using needle EMG electrodes inserted into muscles or surface EMG electrodes placed on the skin. EMG analysis examines motor unit action potentials (MUAPs) to assess parameters like duration, morphology, and amplitude which can provide information about muscle and nerve health.
2 Brain activation and exhaustion - Kilty et al 2011-annotated.pdfJorgeSilva638591
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This document describes the development and testing of an EMG-driven musculoskeletal model to estimate muscle forces and knee joint moments in vivo. The model uses EMG and joint kinematic data as inputs to estimate individual muscle forces and resulting knee joint moments. The model was calibrated for six individuals by adjusting physiological parameters to match net flexion/extension muscle moments measured through inverse dynamics. Once calibrated, the model predicted knee joint moments across over 200 dynamic tasks with high accuracy (average R2 of 0.91), demonstrating the model's ability to estimate muscle forces and joint moments over a wide range of dynamic conditions.
This master's thesis explores long-latency post-stimulus effects (PStEs) observed in stimulus-triggered averages of electromyography (EMG) recordings following intracortical microstimulation of the primary motor cortex in rhesus monkeys. The author develops a novel statistical method to identify significant long-latency PStEs up to 60ms after stimulation. Facilitatory PStEs were bimodal at 16ms and 46ms, while suppressive PStEs were bimodal at 14ms and 29ms. This work takes initial steps to characterize long-latency PStEs and investigate the neural pathways that may generate them.
This document discusses estimating hand muscle power using surface electromyography (EMG). EMG is used to evaluate electrical activity in muscles during activities to grade muscle strength. The research aims to develop an automatic method for grading muscle power. EMG is acquired from hand muscles during different activities and analyzed. Analysis includes root mean square, maximum amplitude, and burst time of EMG signals. Results from fifty young subjects show these metrics increase with greater muscle contraction and resistance, allowing muscle strength grading. The method could improve on manual muscle testing which depends on examiner judgment.
The document discusses the NEMES-BOSCO SYSTEM, a whole-body vibration training machine. It works by applying high-frequency vibrations to the body, causing involuntary muscle contractions through tonic vibration reflex. This activates muscles at levels 200-300% higher than voluntary contractions alone. Vibration training provides muscle and strength gains similar to resistance training, but in a much shorter time and without overloading joints or tendons. It has applications in sports training, rehabilitation, and addressing issues like osteoporosis or mobility for elderly individuals.
This document describes a study that evaluates Laser Doppler Myography (LDM) as a non-contact method for measuring muscle contraction by comparing LDM signals to standard surface electromyography (sEMG) signals. LDM uses laser Doppler vibrometry to detect vibrations from contracting muscles without touching the skin. The study found that LDM and sEMG signals were similar in timing of muscle activation and that LDM signal amplitude increased with higher force production levels, suggesting LDM can reliably measure muscle contraction characteristics without contact. LDM may have advantages over sEMG such as being less prone to electrical artifacts and more directly related to muscle force.
The document summarizes the organization and function of skeletal muscle. It discusses how:
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EEG based Brain Computer Interface (BCI) establishes a new channel between human brain and the
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This paper will review the works on Surface Electromyography (SEMG) signal acquisition and controlling as well as the uses of SEMG signals analysis for Transfemoral amputee's people. In the beginning, this paper will briefly go through the basic theory of myoelectric signal generation. Next, the signal acquisition & filtering techniques applied for SEMG signal will be explained. Then after this EMG signal control or actuate the myoelectric leg who was suffering from Transfemoral amputee using microcontroller. This paper gives the better controlling SEMG signal and also very smooth and easy controlling of the Prosthetic leg motor using Myoelectric Controller.
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2. Improving the selectivity of surface EMG recordings
Improving the Selectivity
of Surface EMG Recordings of Facial Muscles:
Effects of Electrode Parameters
2
3. 3
Improving the selectivity of surface EMG recordings
Table of contents
Abstract
4
Introduction
5
What does facial behavior express?
5
Scoring facial behavior
5
Facial Action Coding System
6
Surface electromyography of facial muscles
6
The physiological basis of surface EMG
7
The composition of the surface EMG signal
9
Characteristics of surface EMG recordings: cross-talk
9
Reducing cross-talk: a practical approach
16
Aims of the present study
Methods
17
19
Subjects and experimental task
19
EMG recording
20
Electrodes
20
EMG analysis
22
Statistical analysis
25
Results
28
Amplitude
28
Selectivity
30
Discussion
45
Conclusions
48
References
49
Acknowledgments
54
Appendix
55
4. Improving the selectivity of surface EMG recordings
4
Abstract
Facial behavior may provide a measure of the mental state of an individual. Surface EMG is
an objective method that is able to reveal non-visible changes in facial muscle tone. However,
cross-talk may hamper the interpretation of EMG records. The aim of this study is to reduce
cross-talk between facial muscles with a minimum number of concomitant drawbacks. Two
electrode parameters were examined: shape of the electrode contacts and bipolar spacing. The
EMG of twenty subjects was bilaterally recorded from 8 sites while they viewed 48 pictures,
which were presented in series. Although the parameters do affect the amplitude of the
myoelectric signal, no consistent results were found that point to an increase in selectivity of
the EMG signal as measured by the Selective Value (SV). However, it may be argued that the
SV by itself is not a reliable measure for selectivity.
5. Improving the selectivity of surface EMG recordings
5
Introduction
What does facial behavior express?
In daily life, face-to-face discussions are characterized by a seemingly inexhaustible variety
of facial expressions. Presumably, facial expressions play an important role in interindividual
communication (e.g. Ekman, 1979). However, several studies (e.g. Ekman, 1972; Fridlund,
1991) indicate that social context is not a prerequisite for spontaneous facial expressions,
although it may be facilitating (e.g. Chapman, 1974).
As Darwin (1872) and James (1890) already noted, facial expressions might not merely serve
the goal of conveying information to the social environment. Darwin (1872) stated that
expressions might influence subjective feelings and other mental processes. Thus, facial
expressions may serve both as a read-out system of mental state in inter-individual interaction
(feed forward process) and as a sensory feedback system for the intra-individual experience
(e.g. Izard, 1977, 1981).
For this reason, facial behavior may provide a measure of the mental state of an individual.
(e.g. see Ekman & Friesen, 1978; Van Boxtel & Jessurun, 1993). However, in order to make
valid inferences about an individual’s mental state, one should at least be able to qualify and
quantify the exhibited facial behavior reliably.
Scoring facial behavior
Since facial behavior is brought about by facial muscle activity (e.g. Duchenne, 1862;
Hjorstjo, 1970; Lightoller, 1925) a scoring technique that encompasses the musculature of the
face ought to be preferred over techniques that merely focus on facial appearance (e.g.
Birdwhistell,1970; Blurton Jones, 1971; McGrew, 1972; Grant 1969; Brannigan &
Humphries, 1972). Ekman (1979) points out that some of these latter methods present
descriptions that are anatomically incorrect and therefore render error in classification.
6. Improving the selectivity of surface EMG recordings
6
Facial Action Coding System
Ekman and Friesen (1978) presented a method that does take the anatomical constraints of the
facial musculature into account. They focused on determining the independent units of facial
action. The Facial Action Coding System (FACS; Ekman & Friesen, 1978) analyzes facial
behavior by observing its component elements: Action Units (AU). Any complex facial
behavior can be broken down into a set of single AU scores following the guidelines in the
corresponding manual. Although this method may be useful as a descriptive tool, it has at
least five considerable drawbacks that limit its usability:
1. the description of facial behavior is limited to visual movements;
2. the classification is somewhat subjective, for it requires an observer;
3. the quantification of intensity is restricted to a three point scale;
4. the process of describing facial behavior is time consuming;
5. the method is not a direct measure of facial muscle activity but instead looks at its
resultants, which are mediated by physiognomic factors such as wrinkles, bulges and
pouches.
Surface Electromyography of facial muscles
EMG recordings are less vulnerable to the aforementioned weaknesses, and may therefore be
a more desirable method of assessing facial behavior. However, this technique is far from
flawless (see the sections on cross-talk) and Ekman and Friesen (1978) question the general
usefulness of EMG: “…we think it is unlikely that surface electrodes could distinguish the
variety of visible movements which most other methods delineate”. Whether it is favorable to
describe the appearance of the face (FACS) or to measure the activity of the underlying
muscular tissue (EMG) remains a point of dispute. However, both the scientific demand of
objectivity and the utility in the case of covert facial movements put a heavy burden on the
Facial Action Coding System.
Before turning to the electromyographic signal, the physiological basis of surface EMG will
be briefly discussed.
7. Improving the selectivity of surface EMG recordings
7
The physiological basis of surface EMG
The motor unit
Each striated muscle is innervated by a single motor nerve whose cell bodies are primarily
located in the ventral horn of the spinal cord or, in the case of the muscles of the head, in the
cranial nerves of the brain stem (Cacioppo et al., 1990). This motor nerve consists of
numerous individual motoneurons (Cacioppo et al., 1990), which divide into a number of
branches, termed axon fibrils, just before reaching the muscle. Each of these axon fibrils
forms a junction, termed a motor end plate, on an individual muscle fiber. As a result, a
motoneuron innervates a number of muscle fibers.
A motor unit (MU) consists of a cell body of the motoneuron, its axon, its axon fibrils and the
individual muscle fibers innervated by these axon fibrils. As Cacioppo et al. (1990) point out:
“An important functional consequence of this structure is that muscle fibers do not contract
individually but rather there is a concerted action by each set of muscle fibers innervated by a
single motoneuron”. The fibers of multiple motor units tend to be interspersed throughout the
muscle (e.g. Loeb & Gans, 1986).
The number of muscle fibers innervated by one motor neuron is termed the innervation ratio
and varies considerably between muscles. Low innervation ratios are found in muscles
involved in precisely controlled movements (e.g. Eccles & Sherington, 1930), whereas higher
– up to a factor 300 - innervation ratios can be found in the more slowly and grossly acting
postural muscles (Basmajian & DeLuca, 1985).
Although striated muscle fibers receive their stimulation via the motor end plates, which are
usually near the midpoint of each fiber (e.g. Loeb & Gans, 1986), the innervation is not
necessarily in the middle of the muscle (Roeleveld, 1997). The motor endplates may be
distributed along widely scattered zones (e.g. Masuda & DeLuca, 1991).
To increase the vigor of a muscle contraction, more MUs are activated (e.g. Henneman et al.,
1965) together with an increase in firing rate (e.g. Clamman, 1970).
8. Improving the selectivity of surface EMG recordings
8
How muscles generate electricity
Loeb and Gans (1986) state that the muscle fiber can be thought of as a large-diameter,
unmyelinated nerve axon. The muscle fiber, like any neuron, actively maintains its
intracellular environment by means of a sodium-potassium pump. This mechanism collects
potassium ions and evicts sodium ions, thereby rendering a resting potential of about 80 mV
negative with respect to its surroundings (Loeb & Gans, 1986). The depolarization of a
motoneuron results in the release of acetylcholine at its motor end plates (DeLuca, 1989).
This excitation changes the fiber membrane’s permeability to both potassium and sodium
ions, causing the resting potential to drop temporarily (e.g. 1 ms; DeLuca, 1989).
Subsequently, voltage-sensitive channels, admitting sodium ions only, are opened (Gans &
Loeb, 1986). Soon afterwards, channels that let potassium ions pass are opened, enabling the
outward flow of potassium ions. As a resultant, the resting potential is restored. This whole
chain of events moves bi-directionally down the muscle fiber at about 2 to 5 m per second. As
the action potential travels along the muscle fiber, a small portion of this electrical activity
(see the section on bipolar electrode spacing) passes through the extracellular fluids to the
skin (DeLuca, 1989).
The series of bioelectrical events that give rise to a recorded voltage are as follows (Loeb &
Gans, 1986):
1. Changing conductivities in the membranes cause action currents to flow across the
membranes and in the extracellular fluids around active cells.
2. The extracellular currents cause potential gradients as they flow through the resistive
fluids.
3. The changing potential gradients give rise to electrical currents in the electrode leads
by capacitive conductance across the metal/electrolyte interface of the electrode
contacts. The currents actually flow through the high-impedance circuits of the
amplifier input stage.
4. The amplifier converts these weak currents into large output voltages.
9. Improving the selectivity of surface EMG recordings
9
The composition of the surface EMG signal
The measured EMG is dependent on the total amount of activity in the pick-up range of the
surface electrodes. This amount of activity depends on the number of recruited MUs and their
firing rates.
Motor Unit Action Potentials
As pointed out in the previous section, surface electrodes can record the electrical activity that
passes through the extracellular fluids to the skin. However, the recorded voltage changes do
not emanate from a single Muscle-fiber Action Potential (MAP) but from aggregated Motor
Unit Action Potentials (MUAPs, e.g. DeLuca, 1989). A MUAP is the summation of action
potentials of all muscle fibers belonging to a specific Motor Unit (Roeleveld, 1997). Owing to
temporal and spatial differences between single MAPs, the MUAP is not simply the highamplitude version of a single MAP (e.g. Roeleveld, 1997). Since the recorded Compound
Motor Action Potentials (CMAPs) in surface EMG are the sum of MUAPs, which, in turn, are
the sum of single MAPs, “we can expect the waveform of the EMG signal to be highly
complex and random in its details” (Loeb & Gans, 1986, p.50).
Characteristics of surface EMG recordings: cross-talk
Surface electrodes are always at least some millimeters away from the closest active fibers
(e.g. Roeleveld, 1997). Therefore, MUAPs will be recorded with a relatively low spatial
resolution compared to invasive needle EMG (e.g. Nandedkar et al., 1985). The details of the
individual MUAPs and MAPs are lost, as well as their precise muscular origins (DeLuca,
1989).
The low degree of spatial resolution constitutes the major drawback of surface electrodes in
comparison to (indwelling) wire electrodes. Since surface electrodes have relatively large
pick-up areas, they are less selective (Barkhaus & Nandedkar, 1994). This means that signals
from muscles, other than the ones the electrodes are meant for, can also be registered
(O’Connell & Gardner, 1963). This phenomenon is termed cross-talk and has been described
by Denny-Brown as early as 1949. Note, that although this phenomenon prevails in surface
EMG, it may be apparent in (indwelling) wire EMG as well (e.g. Mangun et al., 1986;
Solomonow et al., 1994).
10. Improving the selectivity of surface EMG recordings
10
Factors underlying cross-talk: physiological characteristics of the recording site
Mangun et al. (1986) point out that “Cross-talk can cause misinterpretations of muscle
function”. In one study, DeLuca (1988) estimated that as much as 16.6 % of the EMG of an
active muscle can be picked up at an electrode above a non-active neighboring muscle. Koh
and Grabiner (1992) reported comparable findings. Although Solomonow et al. (1994) point
out that the level of cross-talk is presumably over-estimated, he makes clear that “surface
electrodes are heavily contaminated with cross-talk if a subcutaneous layer of fat is located
under the electrodes”. Solomonow assumes that, in this case, as much as 37% of the mean
absolute value of the EMG may be due to cross-talk from adjacent muscles.
Several other factors besides volume conduction by adipose tissue affect the extent of crosstalk in EMG recordings. The characteristics of both the recording site and the recording
device influence the spatial selectivity of the EMG recording.
Mangun et al. (1986) pointed out that cross-talk is more probable to occur in recordings from
small muscles or from those muscles which are relatively small as compared to neighboring
muscles with which they are in intimate contact. Clearly, the extent of intimate contact
depends for a great deal on the proximity of the neighboring muscle. In addition, since the
effect of the non-target muscle EMG signal depends on the amplitude of the target muscle
EMG signal, Mangun et al. (1986) noted that cross-talk is more probable when relatively
inactive muscles are recorded during a motor act that results in large activation of neighboring
muscles.
Barkhaus and Nandedkar (1994) noted that the amplitude of the MUAPs depends on the
distance between the electrode and the muscle fiber (see figure 3). When this distance
increases the amplitude decreases. They pointed out that this distance may be in a horizontal
plane as well as in a vertical plane (i.e. depth of the MUAP generator). Although a
neighboring muscle may be at considerable (horizontal) distance from the target muscle, its
relative effect on the surface EMG signal depends on the amplitude of the target-signal and
therefore on the depth of the target MUs. This depth is partly a result of both the skin and
adipose tissue thickness (Barkhaus & Nandedkar, 1994).
An experimenter is often not able to manipulate the conductive characteristics of the adipose
tissue, the skin thickness or the relative location of target as well as non-target muscles (see
also the section on reducing cross-talk). Furthermore, the experimenter is limited in his
capacity to exert influence on the activation of neighboring muscles through task
11. Improving the selectivity of surface EMG recordings
11
manipulations. Nevertheless, there are a number of other factors that affect the extent of
cross-talk in the EMG signal, which can be manipulated more easily. These factors are related
to electrode parameters and to the employed method of analysis.
Factors underlying cross-talk: considering electrode parameters
Electrode placement
Cacioppo et al. (1990) note that electrodes should be arranged to span maximally the gradient
desired (e.g., in line with the underlying target-muscle) to maximize the recording of its
activity. Loeb and Gans (1986) point out that the bipolar electrode should be oriented parallel
to the voltage gradient to be measured. Therefore, electrodes should be aligned parallel to the
course of the muscle fibers. In addition, the electrodes should preferably be arranged distal
and perpendicular to gradients of extraneous signal sources (e.g. proximal non-target muscles)
to attenuate the recording of non-target activity. Figure 3 shows the effect of electrode
orientation.
A number of authors (e.g. Fridlund and Cacioppo, 1986; Tassinary et al., 1987; Tassinary et
al., 1989; Van Boxtel et al., 1984) have drawn up guidelines for an optimal electrode
montage. Note, however, that an optimal placement may require a compromise between the
two requirements mentioned above.
Dimensions of the electrode contacts
De Luca (1997) noted that the greater the number of fibers covered by the detection surface,
the greater the amplitude of the EMG signal turns out to be. Thus, both shape and size seem to
play a role. However, Jonas et al. (1999) report findings that indicate that this assumption
does not always hold. They argued that in a large muscle the size of the recording area indeed
determines the number of motor units actually collected, whereas in a small muscle this is not
the case. They found higher amplitudes with smaller recording areas and attributed this
difference to a decrease in phase cancellation with smaller electrodes.
Loeb and Gans (1986, p. 70) state that, in general, each recording contact should be as large
as feasible. They point out that “the notion that small electrode contacts provide greater
selectivity is basically wrong for bipolar electrodes”. According to Loeb and Gans (1986, p.
12. Improving the selectivity of surface EMG recordings
12
70) the use of small registration contacts “adds only to noise and unduly biases the recordings
by concentrating on the signals from a few fibers”. Nonetheless, Winter et al. (1994) found
that decreasing the electrode’s recording area does reduce cross-talk. Apparently the optimal
electrode dimension depends partly on the underlying musculature and as Loeb and Gans
(1986) make clear, on the bipolar inter-electrode distance. As a rule of thumb they suggest
that the electrode’s contact dimensions should not be reduced below half the bipolar interelectrode distance.
Electrical characteristics of the two recording contacts
Since bipolar electrodes are used with a differential amplifier, which subtracts the two signals
prior to amplification, the two input signals should be as similar in size, electrical impedance
and physical environment as possible (Loeb & Gans, 1986). Loeb and Gans (1986) point out
that bipolar electrodes with dissimilar contacts are generally inferior in terms of common
mode rejection of remote electrical noise (e.g. cross-talk).
Bipolar electrode spacing
A large number of studies (e.g. Lynn et al., 1978; Reucher et al., 1987; Winter et al., 1994)
have shown that reduced bipolar spacing improves the selectivity of the EMG recording.
However, reduced bipolar spacing generally results in a decrease in amplitude of the recorded
EMG signal (e.g. Loeb & Gans, 1986; Jonas et al., 1999). In order to give insight into the
rationale behind determining the optimal bipolar spacing the flow of extracellular currents
that are picked up by surface electrodes will be described in more detail.
Loeb and Gans (1986) make clear that when the action potential starts to propagate from the
innervation point, the inward flow of positive sodium ions is temporarily restricted to this
region. This makes the region surrounding the innervation point look like a sink. From an
electrical point of view, “the circuit from outside to inside must be completed by a
complementary source of current”(Loeb & Gans, 1986, p.47), i.e. the source. This current
arises in the regions most adjacent to the sink, which are having their cations stripped from
the outer surface and their anions stripped from the inner surface of the membrane (see figure
1). “An instant later, these adjacent, passively depolarizing regions themselves become sinks
for sodium ions, with the passive source lying still further out to the ends of the muscle fiber.”
13. Improving the selectivity of surface EMG recordings
13
The active current source (i.e. the outward flow of potassium ions) repolarizes the membrane
potential in the region that was first to depolarize (i.e. the innervation point).
Figure 1.
Propagation of an action potential along a muscle fiber. Note the leading
edge at the top right of the figure. See text for details. Adapted from Loeb and
Gans (1986, p. 46).
An electrode in the extracellular fluid around such a discharging muscle fiber placed at some
distance from the innervation point would alternatively find itself near a current source
(cathode), then a current sink (anode) again followed by again a current source (see figure 1).
Suppose that the two recording contacts are positioned so that, at one instant, one lies right
over a current sink and the other over an active current sink. “At that instant a maximal
potential difference will be measured. The amplitude of this potential is the product of the
action current times the resistance of the local extracellular fluid through which the current
(mostly) flows.” The optimal bipolar spacing of the two recording contacts would be the
distance between the current source and sink (i.e. the dipole spacing). The process of
depolarization and repolarization back to resting level each takes about 0.5 ms (Loeb & Gans,
1986, p. 48) and thus about 1 ms in total (e.g. Cacioppo et al., 1990). If the disturbance is
known to be moving in tandem (i.e. sink followed by source) down the fiber at 5 m per
14. Improving the selectivity of surface EMG recordings
14
second – the chain of events moves down the muscle fiber at about 2 to 5 m per second (Loeb
& Gans, 1986, p. 48-49)- then the length of the patch acting as a source or sink must be 0.5
times 5 mm per ms (=2.5 mm). Since the repolarizing action follows immediately on the heels
of the depolarizing action the dipole spacing will measure 2.5 mm as well. However, surface
electrodes cannot be placed right on top of a discharging muscle fiber. To describe the effect
of these more remote contact surfaces Loeb and Gans (1986) stated that only some of the
current can squeeze through the limited amount of resistive extracellular fluid right up next to
the fiber. The remaining current will have to take the long way around, thereby resembling
the magnetic flux lines surrounding a short bar magnet (see figure 2).
Figure 2.
Current flow in the extracellular fluids around a muscle fiber generating an
action potential. See text for details. Adapted from Loeb and Gans (1986, p.
48).
Assuming that the detection surface runs parallel to the axis of the dipole, it becomes clear
that the distance from dipole axis to detection surface affects the bipolar spacing for
recordings of maximum amplitude. Hence, since the dipole spacing appears to be larger at the
detection surface due to the current taking the long way around, the two electrodes should
also be more widely spaced in order to record signals at maximum amplitude. Figure 3
shows the effects of the distance between the electrode and the source, electrode orientation
and bipolar spacing on the amplitude of the recorded EMG signal.
15. Improving the selectivity of surface EMG recordings
Figure 3.
15
Effects of bipolar spacing, electrode orientation and spacing between source
and electrode on the amplitude of the recorded EMG signal. The dipole
source is shown as a plus sign and a small circle. Adapted from Loeb and
Gans (1986, p. 63).
As a first approximation of the bipolar spacing, Loeb and Gans (1986) suggest that a
reasonable bipolar spacing can be calculated by taking the square of the perpendicular
distance from the electrodes to the fiber and adding it to the value of the dipole spacing for the
specific fiber.
The increase in selectivity due to a reduced bipolar spacing is based on the principle described
above. Since non-target fibers are presumably more remote from the dipole axis than target
fibers, their optimal bipolar spacing is larger than for the more adjacent target fibers.
Therefore, the amplitude of the EMG signal stemming from the more remote fibers will be
relatively low compared to the amplitude of the EMG stemming from the more adjacent
fibers. As a rule of thumb Loeb and Gans (1986) point out that, in order to record selectively,
the effective conductive path from dipole source to bipolar electrode (i.e. the path through the
extracellular volume-conductive tissues) should be equal to or less than the bipolar spacing.
Furthermore they note that, in order to reject selectively, the electrical path from dipole source
to bipolar electrode should be greater than four times the dipole spacing of the source.
Reducing the bipolar spacing works because “the amplitude of the potentials coming from
sources lying closer to the electrodes than the bipole separation only decreases linearly as the
16. Improving the selectivity of surface EMG recordings
16
separation is made shorter than their dipole moments. For potentials that originate further than
four times the bipole separation from the electrode, the amplitude decreases as the square of
the distance” (Loeb & Gans, 1986, p. 70).
Reducing cross-talk: a practical approach
In order to reduce the extent of cross-talk, Loeb and Gans (1986) propose a procedure that
centers round the physiological basis of cross-talk: volume conduction of the myoelectrical
signal. They describe a method that isolates the target-muscle from non-target muscles by
placing a non-conductive barrier between the muscle-groups. Note that this procedure is
invasive. In general however, it is far more convenient to alter recording characteristics
(including electrode parameters) and methods of analysis than to manipulate the physiological
characteristics of the recording site.
As stated in the previous section, electrode placing, electrode orientation, electrode size,
bipolar spacing and the electrical properties of the electrode contacts may be altered to
increase spatial selectivity.
De Luca (1997) describes a method to reduce and possibly even eliminate cross-talk: the
double differential technique (see also Broman et al., 1985). This technique consists of using
a surface electrode that has (at least) three detection surfaces equally spaced apart. Initially,
two differential signals are obtained: one from detection surfaces 1 and 2 and another from
detection surfaces 2 and 3. Subsequently, a differential signal is obtained from these two. This
procedure decreases the pick-up volume of the electrode, thus filtering out more remote
signals from non-target muscles. The fact that additional equipment is required constitutes the
major drawback of this method.
The aforementioned methods focus on the acquisition of EMG signals rather than on the
analysis of EMG signals. However, there are several ways to reduce the extent of cross-talk
by means of data analysis.
Since cellular media act as a low pass filter (e.g. Mangun et al., 1986), signals stemming from
more remote muscles are characterized by a lower frequency spectrum (e.g. De Luca, 1997).
This characteristic can be used to rid cross-talk from the target signal by applying a high-pass
filter (90 or 100 Hz) to the data (e.g. Cacioppo et al., 1990). Bear in mind that subjecting the
data to an external high-pass filter results in the elimination of a significant portion of the
17. Improving the selectivity of surface EMG recordings
17
EMG signal. Note that closely spaced bipolar electrodes have intrinsic high-pass filtering
characteristics. Thus, a reduced bipolar spacing results in an increase in both the bandwith and
in the peak frequency of the EMG spectrum (e.g. Loeb & Gans, 1986; McLeod et al., 1976).
Another approach to reducing cross-talk is to record all of the adjacent potential cross-talk
sites simultaneously (e.g. De Luca, 1997; Loeb & Gans, 1986) and somehow remove the
cross-correlated signal originating in non-target muscles from the EMG record of the target
muscle. Note that the term “non-target muscles” refers to muscles that are not of interest to
the experimenter. Even if the adjacent muscles are synergists, there should be little or no
overlap in the precise timing of peaks and valleys in the EMG signal. However, for this
method to be effective, it is necessary to determine where the cross-related signal originates.
Although this remains somewhat speculative, this question could be answered by focusing on
the amplitude of the cross-related signal in all records: the cross-related EMG signal from
non-target muscles is likely to display a lower amplitude than the cross-correlated EMG from
target muscles (see section on bipolar spacing). Unfortunately, this method has a few
disadvantages. Firstly, it is necessary to place electrodes on all potential cross-talk sites and to
perform computations on the EMG dataset making the method somewhat cumbersome.
Secondly, De Luca (1997) points out that the properties of the conduction volume may cause
the signal to be scrambled in the frequency domain, which may cause the signals to appear
uncorrelated. Furthermore, it is not fully clear how to correct the data reliably for cross-talk.
Aims of the present study
Since facial muscles are 1) fairly small 2) in close proximity to one another and 3) may be
covered by adipose tissue, the recorded surface EMG is bound to suffer from cross-talk. This
hampers the interpretation of the recorded EMG. Several authors (see previous section) have
sought ways to reduce cross-talk in EMG recordings, but they have not specifically focused
on the facial region. Each of the available methods described in the previous section appears
to be accompanied by considerable drawbacks (e.g. cumbersome, eliminating significant
portion of the EMG signal, reducing signal amplitude, requiring additional equipment). This
study is aimed at reducing cross-talk between facial muscles at the level of data acquisition
with a minimum number of concomitant disadvantages.
The study centers round bipolar spacing, since this electrode parameter has shown to affect
the extent of cross-talk in EMG recordings considerably.
18. Improving the selectivity of surface EMG recordings
18
Hypotheses
Main hypothesis:
I. The two electrode types yield different EMG signals.
However, two sub hypotheses are of specific interest:
II. The amplitude of the surface EMG signal is lower for surface electrodes with a small
bipolar spacing than for surface electrodes with a larger bipolar spacing.
III. Recordings of EMG with surface electrodes with a small bipolar spacing display a
higher degree of spatial selectivity than recordings with electrodes with a larger
bipolar spacing.
19. Improving the selectivity of surface EMG recordings
19
Methods
Subjects and experimental task
Twenty healthy undergraduate students (10 males and 10 females, mean age: 22.2, SD: 3.5)
participated in the experiment. Testing took place in an electrically shielded, sound
attenuating cabin. During the experiment, subjects were seated in a comfortable reclining
chair. They received study credits for their voluntary cooperation.
The subject pool was divided into two groups of 10 subjects each (5 males and 5 females, see
section on EMG recordings). All subjects were asked to view 48 pictures from the IAPS
dataset (Lang et al., 1999; see appendix for details). The pictures were presented serially, thus
one at a time, on a monitor placed in front of the subjects. The distance between the subject
and the screen measured approximately 1.5 m
Each picture appeared on the screen for a 6 s period. Following each picture, subjects rated
the affective value of the picture on six five-point scales (see appendix for details), presented
on the monitor in series. In order to move the cursor on the screen, a response manipulandum
was affixed to the right-hand armrest of the chair. The manipulandum consisted of three
buttons placed in a triangular fashion. The buttons that made up the horizontal base of the
triangle were used to move the cursor horizontally whereas the top button was pressed to
enter their choice. As a default, the cursor was positioned at the first point of the five-point
scale. The manipulandum could be operated with a single finger.
The inter trial interval (ITI) is defined as the period between the last rating and the subsequent
picture and could range from 9 to 19 s. The interval between picture offset and the
presentation of the first scale measured 2.5 s. The first five scales were followed by an
interval of 1.5 s during which subjects watched a darkened screen. Subjects had to respond
within 9 s. The location of the cursor that conveyed their judgment was stored, even if they
failed to enter before the 9 s time-out. After 7 s subjects received a visual incitement to
respond by means of a change in font color. Subjects could control the length of the trial by
timing their responses. Theoretically, the absolute minimal interval between pictures
measured 19 s: subjects then had to respond within 1 ms and the ITI had to measure 9 s (viz.,
2.5 + (5* 1.5) + 9 = 19). However, this interval could measure up to 83 s when the subject
always required the maximum response interval and when the ITI measured 19 s (viz., 2.5 +
(5*1.5) + (6*9) + 19 = 83).
20. Improving the selectivity of surface EMG recordings
20
The experiment was divided into 3 blocks. The first block counted 17 pictures, the subsequent
two blocks 16 pictures (the third block contained a picture already shown in block 1). A 5min rest period separated each block. The experiment took approximately 50 minutes in total,
apart from electrode montage and instructions.
EMG recording
EMG signals were differentially recorded (sampling rate of 1024 Hz) on a trial basis starting
from 4 seconds preceding stimulus presentation to 1 s post stimulus presentation (11 seconds
in total). The 4 s interval preceding stimulus presentation served as a baseline interval
whereas the 6 s period during stimulus presentation represented the active interval. EMG
signals were amplified and band-pass filtered (-3dB high-pass cutoff frequency at 3.8 Hz and
attenuation rate 31 dB per octave; -3 dB low-pass cutoff frequency at 520 Hz and attenuation
rate 13.5 dB per octave) and stored on a local harddisk.
Electrodes
Two types of electrodes were used in the experiment: conventional Ag-AgCl electrodes
(diameter recording surface: 2 mm) and custom built Ag bar electrodes (recording surface:
width1 mm, length 7 mm). The bipolar electrode spacings measured 15 mm (from center to
center) for the conventional electrodes and 5 mm for the custom built bar electrodes (figure
4). The casing of the custom built bar electrode was made of synthetic resin (width 10 mm,
length 10 mm, height 5 mm) and had indentations (width 1mm, length 7mm, depth 0.6 mm ±
0.2 mm) in which the Ag bars were placed. These indentations served as an electrolyte
reservoir. The reference electrode (diameter Ag-AgCl recording surface: 10 mm) was placed
on the forehead.
To prevent the detection surfaces of the bar electrodes from being electrically shunted, a biadhesive non-conductive barrier was placed between the two indentations.
21. Improving the selectivity of surface EMG recordings
Figure 4.
21
Design of the bar electrode.
EMG from 8 facial muscles was bilaterally recorded, rendering 16 EMG electrode-pair sites
(figure 5). Electrode locations on corrugator supercilii, orbicularis oculi, zygomaticus major,
levator labii superioris alaeque nasi, masseter, orbicularis oris and mentalis were in
accordance with the guidelines presented by Fridlund and Cacioppo (1986). Electrodes on the
frontalis muscle were placed on an imaginary vertical line traversing the pupil of the eye, with
the lower electrode (in the case of the conventional electrodes) 15 mm above the upper border
of the eyebrow. The bar electrodes were placed in the center of the imaginary axis of the
conventional electrodes.
22. Improving the selectivity of surface EMG recordings
Figure 5.
22
Electrode configuration.
In one group of subjects (N= 10: 5 male, 5 female) the conventional electrodes were placed
over the musculature of the left side of the face, whereas the custom built bar electrodes were
placed on the right side of the face. In the second group (N=10: 5 male, 5 female), the
electrodes were mounted vice versa. Thus, electrode montage was counterbalanced.
EMG analysis
In order to answer the research question reliably, a lengthy path of analysis should be
followed. As pointed out in the section on reducing cross-talk, it is possible if not essential to
focus on different aspects of the EMG signal to reveal and eliminate cross-talk. This paper
will describe an initial explorative analysis of one of the characteristics of the recorded EMG
signal aspects: the mean absolute value (MAV).
The experiment consisted of 48 trials per subject. The total number of trials is therefore (48 *
20 =) 960 trials. All trials were visually inspected in order to detect possible artifacts. These
could be clear non-physiological signals, disturbances caused by the movement of the
23. Improving the selectivity of surface EMG recordings
23
electrode relative to the skin and excessive muscle activity on multiple channels. Trials with
artifacts were removed from the dataset. This procedure resulted in 902 valid trials.
For each channel, the EMG activity in both the baseline interval and the active interval was
rectified and averaged over the length of the respective interval to calculate the MAV.
The MAV of the active interval was then compared to the MAV of the baseline interval. Two
distinct methods of comparison were employed:
1. Expressing the active MAV as a percentage of the baseline MAV: MAVperc
2. Subtracting the baseline MAV from the active MAV: MAVdelta
In the first method, z-scores of the MAVperc for each separate trial were calculated for each
of the 8 muscles in both electrode types. A trial yielded 8 z-scores for each electrode type: the
8 muscles in the subpopulation on which the z-scores were based. Thus, the z-scores were
based on the mean and the standard deviation of the 8 MAVsperc per trial. This process
resulted in (N pictures * N muscles * N electrode types * Nsubjects - (N rejected trials * 8 *
2) = 48 * 8 * 2 * 20 – 928 =) 14432 z-scores in total.
In the second method, z-scores of the MAVdelta for each separate trial were calculated for
each of the 8 muscles in both electrode types. A trial yielded 8 z-scores for each electrode
type: the 8 muscles in the subpopulation on which the z-scores were based. Thus, the z-scores
were based on the mean and the standard deviation of the 8 MAVsdelta per trial. This
procedure again resulted in 14432 z-scores in total.
These z-scores allow for a direct comparison between the two types of electrodes. Comparing
non-standardized scores seems pointless since the magnitude of both MAVperc and
MAVdelta are likely to differ substantially between electrode types, resulting in biased
measures. By calculating the MAVperc z-score and the MAVdelta z-score of a particular
muscle (as described above) this problem is circumvented.
24. Improving the selectivity of surface EMG recordings
24
Cross-talk is expected to prevail in neighboring muscles (see sections on cross-talk).
Therefore, the EMG signal at the following muscle-pairs was assumed to suffer from crosstalk:
•
frontalis and corrugator
•
orbicularis oculi and levator
•
orbicularis oculi and zygomaticus
•
zygomaticus and levator
•
zygomaticus and masseter
•
orbicularis oris and mentalis
In addition, one may hypothesize that cross-talk will occur in the following muscle-pairs:
•
orbicularis oris and masseter
•
orbicularis oris and zygomaticus
To test whether the two electrode types do render different EMG signals, as the main
hypothesis (I) suggests, the MAVperc z-score of one of the two muscles in a muscle-pair was
subtracted from the other muscle’s MAVperc z-score. This was done for each trial. Thus, one
electrode type yielded 902 subtractions for each muscle-pair. The resultant of this procedure
was termed Dominant Muscle Value (DMV) and indicates which muscle of the two has a
higher MAVperc. This procedure was repeated for the MAVdelta z-scores. A difference in
DMV would confirm the main hypothesis (I) especially if the dominant muscle differs
between the two types of electrodes.
To compare the effectiveness of the electrode-types with regard to selectivity (as opposed to
cross-talk) the selective value (SV) was calculated. This was done as follows. Whenever the
subtraction described above (i.e. the subtraction per trial) rendered a negative measure its
value was converted into its opposite value. This procedure was repeated for the MAVdelta zscores. Thus, the SV does not reflect which of the two muscles in the muscle-pair is dominant
but only how large the difference between the two is. The electrode type that has the highest
SV is assumed to yield the more selective EMG recording. A difference in SV between the
two electrode types would confirm the main hypothesis (I). Furthermore, if the SV turns out
to be higher for the new electrodes hypothesis III would be confirmed.
25. Improving the selectivity of surface EMG recordings
25
Bear in mind that there are two DMVs and two SVs: DMVperc, DMVdelta, SVperc, and
SVdelta.
In order to test hypothesis (II) the MAVs in the baseline as well as in the active interval of
one electrode type are compared with the corresponding MAVs of the other electrode type.
Note that if the MAVs in both intervals turn out to be lower in the new electrodes, both
hypothesis I and II are confirmed.
To test whether the employed measure for selectivity (SV) is reliable, a muscle-pair that is
very unlikely to suffer from reciprocal cross-talk was encompassed in the analysis:
•
corrugator and mentalis
Statistical analysis
To test whether the MAVs differed between electrode types (hypothesis I and II), a paired ttest was performed on both the baseline MAV and the active MAV between electrode-type
for each muscle group.
To test whether the new electrodes rendered a more selective EMG recording (hypothesis I
and III), the SV of the bar electrodes was compared with the SV of the conventional
electrodes by means of a paired t-test over all trials.
To test whether the dominant muscle differed between the two electrode types (hypothesis I) a
t-test was performed on DMVperc in the cases where one of the two electrode types rendered
a DMVperc with a negative value while the other produced a positive value. A statistically
significant difference between the DMVperc in these cases indicates that the dominant muscle
differed between the two electrode types. This procedure was repeated for the DMVsdelta.
It may be hypothesized that the level of cross-talk is linearly related to the level of activity of
the signal source muscle (e.g. Solomonov et al., 1994). Therefore, four additional datasets
were created: a high MAVperc dataset, a low MAVperc dataset, a high MAVdelta dataset
and a low MAVdelta dataset. The datasets were created as follows. For each muscle in the
muscle pair the z-score over all 902 trials was computed. If the MAVperc of at least one of
the muscles in the muscle-pair differs from the mean (N=902) by more than one standard
26. Improving the selectivity of surface EMG recordings
26
deviation, the trial is added to the high MAVperc dataset, which is termed the “>1 SD
dataset”. Note that there are 4 MAVsperc that have to be considered: muscle 1 and muscle 2
measured with conventional electrodes and muscle 1 and 2 measured with the new bar
electrodes. This procedure is repeated for the MAVsdelta. If the MAVperc of none of the
muscles in the muscle-pair differs from the mean (N=902) by more than one standard
deviation, the trial is added to the low MAVperc dataset, which is termed “< 1 SD dataset”.
This procedure was again repeated for the MAVsdelta.
A paired t-test on the SVperc between new and old electrodes was carried out for each
muscle-pair in both the “> 1 SD dataset” and the “< 1 SD dataset” for both the MAVsperc and
the MAVsdelta. This was done to test whether the new electrodes rendered a more selective
EMG recording (hypothesis I and III) in one of the two additional datasets. This procedure
was repeated for the SVsdelta.
To test whether the dominant muscle differed between the two electrode types (hypothesis I)
in the two additional datasets, a t-test was performed on DMVperc in the cases where one of
the two electrode types rendered a DMVperc with a negative value while the other produced a
positive value. A statistically significant difference between the DMVperc in these cases
indicates that the dominant muscle differed between the two electrode types. This procedure
was repeated for the DMVsdelta.
To test whether the differences in SVperc between the two electrode types were caused by
several outliers with a high MAVperc, a non parametric test (binomial test) was performed in
all three datasets. In order to perform this test the SVsperc of the new electrodes were
subtracted from the SVsperc of the old electrodes. A negative value therefore denotes a
higher SVperc for the new electrodes. These Differential Scores (DS) were then converted to
a dichotomous dataset in which DSperc < 0 becomes -1 and DSperc > 0 becomes 1. The
binomial test was performed on this dichotomous dataset and was equivalent to a signtest.
This procedure was repeated for the SVsdelta.
The following scheme provides a summary of the statistical analyses carried out for each
target muscle-group:
Unconstraint dataset
•
t-test baseline MAV new and baseline MAV old
•
t-test active MAV new and active MAV old
27. Improving the selectivity of surface EMG recordings
•
t-test between SVperc new and SVperc old
•
t-test between SVdelta new and SVdelta old
•
t-test between DMVperc new and DMVperc old
•
t-test between DMVdelta new and DMVdelta old
•
signtest on (SVperc old minus SVperc new)
•
signtest on (SVdelta old minus SVdelta new)
> 1 SD dataset
•
t-test between SVperc new and SVperc old
•
t-test between DMVperc new and DMVperc old
•
signtest on (SVperc old minus SVperc new)
< 1 SD dataset
•
t-test between SVperc new and SVperc old
•
t-test between DMVperc new and DMVperc old
•
signtest on (SVperc old minus SVperc new)
> 1 SD dataset
•
t-test between SVdelta new and SVdelta old
•
t-test between DMVdelta new and DMVdelta old
•
signtest on (SVdelta old minus SVdelta new)
< 1 SD dataset
•
t-test between SVdelta new and SVdelta old
•
t-test between DMVdelta new and DMVdelta old
•
signtest on (SVdelta old minus SVdelta new)
27
28. 28
Improving the selectivity of surface EMG recordings
Results
Amplitude
The MAVs old in both the baseline interval and active interval were significantly higher than
the MAVs new for all eight muscles (see figure 6 and 7, respectively). Table 1 and 2 provide
an overview of the performed paired t-tests on the MAVs between old and new electrodes in
the baseline and active interval, respectively.
80
70
60
MAV
50
40
30
20
10
Figure 6.
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0
MAV in the baseline interval for old and new electrodes. Note that the new
electrodes are characterized by a significantly lower MAV for all 8 muscles.
29. 29
Improving the selectivity of surface EMG recordings
70
60
50
MAVs
40
30
20
10
Figure 7.
m
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0
MAV in the active interval for old and new electrodes. Note that the new
electrodes are characterized by a significantly lower MAV for all 8 muscles.
Muscle-pair
t
df
p
frontalis_old vs frontalis_new
27.22
901
< 0.001
corrugator_old vs corrugator_new
37.75
901
< 0.001
orb. oculi_old vs orb. oculi_new
27.05
901
< 0.001
levator_old vs levator_new
34.11
901
< 0.001
zygomaticys_old vs zygomaticus_new
25.75
901
< 0.001
masseter_old vs masseter_new
17.74
901
< 0.001
orb. oris_old vs orb. oris_new
23.52
901
< 0.001
mentalis_old vs mentalis_new
34.72
901
< 0.001
Table 1.
Results of the paired t-tests between new and old electrodes on the MAVs in
the baseline interval for all 8 muscles.
30. 30
Improving the selectivity of surface EMG recordings
Muscle-pair
t
df
p
frontalis_old vs frontalis_new
28.30
901
< 0.001
corrugator_old vs corrugator_new
38.08
901
< 0.001
orb. oculi_old vs orb. oculi_new
25.19
901
< 0.001
levator_old vs levator_new
26.48
901
< 0.001
zygomaticus_old vs zygomaticus_new
23.20
901
< 0.001
masseter_old vs masseter_new
16.36
901
< 0.001
orb. oris_old vs orb. oris_new
25.21
901
< 0.001
mentalis_old vs mentalis_new
33.93
901
< 0.001
Table 2.
Results of the paired t-tests between new and old electrodes on the MAVs in
the active interval for all 8 muscles.
Selectivity
Unconstraint dataset
Figure 8 shows the SVperc of all muscle-pairs for both electrode types in the unconstraint
dataset. Note that the SVperc is significantly higher for the new electrodes in the muscle-pairs
frontalis/corruagator, oris/mentalis, oris/zygomaticus and corrugator/mentalis. In the
oculi/zygomaticus, oculi/levator, zygomaticus/levator muscle-pairs the SVperc turns out to be
significantly higher for the old electrodes than for the new electrodes. The paired t-tests did
not reveal any differences in the SVperc between old and new electrodes in the
zygomaticus/masseter and oris/masseter muscle-pairs. Table 3 provides an overview of the
performed paired t-tests on the SVsperc between old and new electrodes.
In addition, the DMVperc in both the oris/zygomaticus and the oris/mentalis muscle-pair has
a negative value for the old electrodes and a positive value for the new electrodes pointing to
differences in the muscle exhibiting preponderant activity. The difference in the DMVsperc
between the two electrode types are statistically significant: t (1, 901) = -3.54, p <0.001 and
t (1, 901) = -2.74, p < 0.001, respectively.
31. 31
Improving the selectivity of surface EMG recordings
1.6
1.4
1.2
SVperc
1
0.8
0.6
0.4
0.2
fro
n/
co
r
r_
O
fro
n/
co
rr_
oc
N
ul
/z
yg
o_
O
oc
ul
/z
yg
o_
N
oc
ul
/le
va
_O
oc
ul
/le
va
_N
zy
go
/le
va
_O
zy
go
/le
va
zy
_N
go
/m
as
s_
zy
O
go
/m
as
s_
or
N
is
/m
en
t_
O
or
is
/m
en
t_
or
N
is
/m
as
s_
O
or
is
/m
as
s_
N
or
is
/z
yg
o_
O
or
is
/z
yg
o_
co
N
rr/
m
en
t_
O
co
rr/
m
en
t_
N
0
Figure 8.
SVperc of all muscle-pairs for both electrode types in the unconstraint
dataset (N=902).
Muscle-pair
t
df
p
fron/corr_old vs fron/corr_new
-3.56
901
< 0.001
ocul/zygo_old vs ocul/zygo_new
6.73
901
< 0.001
ocul/leva_old vs ocul/leva_new
5.07
901
< 0.001
zygo/leva_old vs zygo/leva_new
5.92
901
< 0.001
zygo/mass_old vs zygo/mass_new
0.51
901
0.609
oris/ment_old vs oris/ment_new
-6.94
901
< 0.001
oris/mass_old vs oris/mass_new
0.04
901
0.965
oris/zygo_old vs oris/zygo_new
-2.89
901
< 0.001
corr/ment_old vs corr/ment_new
-5.38
901
< 0.001
Table 3.
Results of the paired t-tests between new and old electrodes on the SVperc for
all muscle-pairs in the unconstraint dataset.
32. Improving the selectivity of surface EMG recordings
32
Figure 9 shows the SVdelta of all muscle-pairs for both electrode types in the unconstraint
dataset. Note that the SVdelta is significantly higher for the new electrodes in the musclepairs oris/masseter and oris/zygomaticus. The SVdelta turns out to be higher for the old
electrodes in the muscle-pairs frontalis/corrugator, oculi/zygomaticus, zygomaticus/levator
and corrugator/mentalis. The paired t-tests did not reveal any differences in the SVperc
between old and new electrodes in the oculi/levator, zygomaticus/masseter and oris/mentalis
muscle-pairs. Table 4 provides an overview of the performed paired t-tests on the SVperc
between old and new electrodes.
In addition, the DMV in the masseter/oris muscle-pair has a negative value for new electrodes
and a positive value for old electrodes indicating that the muscle displaying preponderant
activity differs between electrodetypes. The difference in the DMVdelta between the two
electrode types in the masseter/oris muscle-pair is statistically significant: t (1, 901) = 4.59, p
< 0.001.
1.8
1.6
1.4
SVdelta
1.2
1
0.8
0.6
0.4
0.2
fro
n/
co
r
r_
O
fro
n/
co
rr_
oc
N
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yg
o_
O
oc
ul
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o_
N
oc
ul
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_O
oc
ul
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va
_N
zy
go
/le
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zy
go
/le
va
zy
_N
go
/m
as
s_
zy
O
go
/m
as
s_
or
N
is
/m
en
t_
O
or
is
/m
en
t_
or
N
is
/m
as
s_
O
or
is
/m
as
s_
N
or
is
/z
yg
o_
O
or
is
/z
yg
o_
co
N
rr/
m
en
t_
O
co
rr/
m
en
t_
N
0
Figure 9.
SVdelta of all muscle-pairs for both electrode types in the unconstraint
dataset (N=902).
33. 33
Improving the selectivity of surface EMG recordings
Muscle-pair
t
df
p
fron/corr_old vs fron/corr_new
6.58
901
< 0.001
ocul/zygo_old vs ocul/zygo_new
2.71
901
0.007
ocul/leva_old vs ocul/leva_new
0.74
901
0.462
zygo/leva_old vs zygo/leva_new
3.49
901
0.001
zygo/mass_old vs zygo/mass_new
0.10
901
0.918
oris/ment_old vs oris/ment_new
-0.19
901
0.852
oris/mass_old vs oris/mass_new
-3.60
901
< 0.001
oris/zygo_old vs oris/zygo_new
-6.21
901
< 0.001
corr/ment_old vs corr/ment_new
6.50
901
< 0.001
Table 4.
Results of the paired t-tests between new and old electrodes on the SVdelta
for all muscle-pairs in the unconstraint dataset.
The signtest on SVperc in the unconstraint dataset (see table 5) indicates that the new
electrodes are more often characterized by a higher SVdelta than the old electrodes in the
oris/mentalis, oris/zygomaticus and corrugator/mentalis muscle-pairs. The opposite holds for
the oculi/zygomaticus, oculi/levator and zygomaticus/levator muscle-pairs. No statistically
significant differences were found for the frontalis/corrugator, zygomaticus/masseter and
oris/masseter muscle-pairs.
Muscle-
N
N
N
observed p
pair
(SV new>SV old)
(SV new<SV old)
total
(SV new>SV old)
fron/corr
478
424
902
0.53
0.078
ocul/zygo
373
529
902
0.41
<0.001
ocul/leva
380
522
902
0.42
<0.001
zygo/leva
376
526
902
0.42
<0.001
zygo/mass
457
445
902
0.51
0.714
oris/ment
528
374
902
0.59
<0.001
oris/mass
451
451
902
0.50
1.000
oris/zygo
493
409
902
0.55
<0.001
corr/ment
501
401
902
0.56
<0.001
Table 5.
p
Results of the signtest on (SVperc_old minus SVperc_new) for all musclepairs in the unconstraint dataset.
34. 34
Improving the selectivity of surface EMG recordings
The signtest on SVdelta in the unconstraint dataset (see table 6) indicates that the new
electrodes are more often characterized by a higher SVdelta than the old electrodes in the
oris/zygomaticus muscle-pair. The opposite holds for the frontalis/corrugator,
oculi/zygomaticus, oculi/levator, zygomaticus/levator, corrugator/mentalis. No statistically
significant differences were found for the zygomaticus/masseter, oris/mentalis and
oris/masseter muscle-pairs.
Muscle-
N
N
N
observed p
pair
(SV new>SV old)
(SV new<SV old)
total
(SV new>SV old)
fron/corr
357
545
902
0.40
<0.001
ocul/zygo
405
497
902
0.45
0.002
ocul/leva
392
510
902
0.43
<0.001
zygo/leva
385
517
902
0.43
<0.001
zygo/mass
450
452
902
0.50
0.973
oris/ment
458
444
902
0.55
0.665
oris/mass
470
432
902
0.52
0.218
oris/zygo
540
362
902
0.60
<0.001
corr/ment
370
532
902
0.41
<0.001
Table 6.
p
Results of the signtest on (SVdelta_old minus SVdelta_new) for all musclepairs in the unconstraint dataset.
Dataset > 1 SD
Figure 10 shows the SVperc of all muscle-pairs for both electrode types in the “>SD dataset”.
Note that the SVperc is significantly higher for the new electrodes in the frontalis/corrugator,
oris/mentalis and corrugator/mentalis muscle-pairs. In the oculi/levator and the
zygomaticus/levator muscle-pairs the SVperc turns out to be significantly higher for the old
electrodes than for the new electrodes. The paired t-tests did not reveal any differences in the
SVperc between old and new electrodes in the oculi/zygomaticus, zygomaticus/masseter,
oris/masseter and oris/zygomaticus muscle-pairs. Table 7 provides an overview of the
performed paired t-tests on the SVsperc between old and new electrodes.
No significant differences between the DMVperc were found.
35. 35
Improving the selectivity of surface EMG recordings
2
1.8
1.6
1.4
SVperc
1.2
1
0.8
0.6
0.4
0.2
fro
n/
co
r
r_
O
fro
n/
co
rr_
oc
N
ul
/z
yg
o_
O
oc
ul
/z
yg
o_
N
oc
ul
/le
va
_O
oc
ul
/le
va
_N
zy
go
/le
va
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zy
go
/le
va
zy
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/m
as
s_
zy
O
go
/m
as
s_
or
N
is
/m
en
t_
O
or
is
/m
en
t_
or
N
is
/m
as
s_
O
or
is
/m
as
s_
N
or
is
/z
yg
o_
O
or
is
/z
yg
o_
co
N
rr/
m
en
t_
O
co
rr/
m
en
t_
N
0
Figure 10.
SVperc of all muscle-pairs for both electrode types in the “> 1 SD dataset”.
Muscle-pair
t
df
p
fron/corr_old vs fron/corr_new
-4.51
334
<0.001
ocul/zygo_old vs ocul/zygo_new
1.69
205
<0.093
ocul/leva_old vs ocul/leva_new
2.53
202
0.012
zygo/leva_old vs zygo/leva_new
4.63
140
<0.001
zygo/mass_old vs zygo/mass_new
0.56
148
<0.574
oris/ment_old vs oris/ment_new
-3.80
204
<0.001
oris/mass_old vs oris/mass_new
0.01
189
0.990
oris/zygo_old vs oris/zygo_new
-1.29
175
0.198
corr/ment_old vs corr/ment_new
-4.32
273
<0.001
Table 7 .
Results of the paired t-tests between new and old electrodes on the SVperc for
all muscle-pairs in the “>1 SD dataset”.
36. Improving the selectivity of surface EMG recordings
36
Figure 11 shows the SVdelta of all muscle-pairs for both electrode types in the “> 1SD
dataset”. Note that the SVdelta is significantly higher for the new electrodes in the
oris/zygomaticus muscle-pair. The SVdelta turns out to be higher for the old electrodes in the
frontalis/corrugator and corrugator/mentalis muscle-pairs. The paired t-tests did not reveal
any differences in the SVdelta between old and new electrodes in the remaining muscle-pairs.
Table 8 provides an overview of the performed paired t-tests on the SVdelta between old and
new electrodes.
In addition, the DMV in the oculi/levator, zygomaticus/levator muscle-pairs has a positive
value for new electrodes and a negative value for old electrodes and vice versa for the
masseter/oris muscle pair. Thus, for the three muscle-pairs the muscle displaying
preponderant activity differs between the two types of electrodes. The difference in the
DMVdelta between the two electrode types in the three muscle-pair is statistically significant:
t(1, 167) = -2.19, p = 0.03; t(1, 133) = -2.22, p = 0.028 and t(1, 229) = 3.76, p < 0.001,
respectively.
37. 37
Improving the selectivity of surface EMG recordings
2.5
2
SVdelta
1.5
1
0.5
fro
n/
co
r
r_
O
fro
n/
co
rr_
oc
N
ul
/z
yg
o_
O
oc
ul
/z
yg
o_
N
oc
ul
/le
va
_O
oc
ul
/le
va
_N
zy
go
/le
va
_O
zy
go
/le
va
zy
_N
go
/m
as
s_
zy
O
go
/m
as
s_
or
N
is
/m
en
t_
O
or
is
/m
en
t_
or
N
is
/m
as
s_
O
or
is
/m
as
s_
N
or
is
/z
yg
o_
O
or
is
/z
yg
o_
co
N
rr/
m
en
t_
O
co
rr/
m
en
t_
N
0
Figure 11.
SVdelta of all muscle-pairs for both electrode types in the “>1 SD dataset”.
Muscle-pair
t
df
p
fron/corr_old vs fron/corr_new
4.39
318
<0.001
ocul/zygo_old vs ocul/zygo_new
1.25
188
0.212
ocul/leva_old vs ocul/leva_new
-0.16
167
0.873
zygo/leva_old vs zygo/leva_new
1.71
133
0.090
zygo/mass_old vs zygo/mass_new
0.973
172
0.332
oris/ment_old vs oris/ment_new
-1.44
209
0.153
oris/mass_old vs oris/mass_new
-1.58
229
0.115
oris/zygo_old vs oris/zygo_new
-4.64
202
<0.001
corr/ment_old vs corr/ment_new
2.48
290
0.014
Table 8 .
Results of the paired t-tests between new and old electrodes on the SVdelta
for all muscle-pairs in the “>1 SD dataset”.
38. 38
Improving the selectivity of surface EMG recordings
The signtest on SVperc in the “>1 SD dataset” (see table 9) indicates that the new electrodes
are more often characterized by a higher SVperc than the old electrodes in the
frontalis/corrugator, oris/mentalis and corrugator/mentalis muscle-pairs. The opposite holds
for the oculi/levator and zygomaticus/levator muscle-pairs. No statistically significant
differences were found for the oculi/zygomaticus, zygomaticus/masseter, oris/masseter and
oris/zygomaticus muscle-pairs.
Muscle-
N
N
N
observed p
pair
(SV new>SV old)
(SV new<SV old)
total
(SV new>SV old)
fron/corr
208
127
335
0.62
<0.001
ocul/zygo
93
113
206
0.45
0.186
ocul/leva
84
119
203
0.41
0.017
zygo/leva
46
95
141
0.33
<0.001
zygo/mass
75
74
149
0.50
1.000
oris/ment
123
82
205
0.60
0.005
oris/mass
98
92
190
0.52
0.717
oris/zygo
100
76
176
0.56
0.083
corr/ment
158
116
274
0.58
0.013
Table 9.
p
Results of the signtest on (SVperc_old minus SVperc_new) for all musclepairs in the“>1 SD dataset”.
The signtest on SVdelta in the “>1 SD dataset” (see table 10) indicates that the new electrodes
are more often characterized by a higher SVdelta than the old electrodes in the
oris/zygomaticus muscle-pair. The opposite holds for the frontalis/corrugator, oculi/levator
and corrugator/mentalis muscle-pairs. No statistically significant differences were found for
the oculi/zygomaticus, zygomaticus/levator, zygomaticus/masseter, oris/mentalis and
oris/masseter muscle-pairs.
39. 39
Improving the selectivity of surface EMG recordings
Muscle-
N
N
N
observed p
pair
(SV new>SV old)
(SV new<SV old)
total
(SV new>SV old)
fron/corr
137
182
319
0.43
0.014
ocul/zygo
85
104
189
0.45
0.190
ocul/leva
68
100
168
0.40
0.017
zygo/leva
73
61
134
0.54
0.342
zygo/mass
75
98
173
0.43
0.094
oris/ment
113
97
210
0.54
0.301
oris/mass
119
111
230
0.48
0.644
oris/zygo
135
68
203
0.67
<0.001
corr/ment
121
170
291
0.42
0.005
Table 10.
p
Results of the signtest on (SVdelta_old minus SVdelta_new) for all musclepairs in the “>1 SD dataset”.
Dataset < 1 SD
Figure 12 shows the SVperc of all muscle-pairs for both electrode types in the “< 1SD
dataset”. Note that the SVperc is significantly higher for the new electrodes in the
frontalis/corrugator, oris/mentalis, oris/zygomaticus and corrugator/mentalis muscle-pairs.
Note that the difference between old and new electrodes is marginally significant in the
frontalis/corrugator muscle-pair. The SVperc turns out to be higher for the old electrodes in
the oculi/zygomaticus, oculi/levator and zygomaticus/levator muscle-pairs. The paired t-tests
did not reveal any differences in the SVperc between old and new electrodes in the
zygomaticus/masseter and oris/masseter muscle-pairs. Table 11 provides an overview of the
performed paired t-tests on the SVperc between old and new electrodes.
In addition, the DMV in the oris/zygomaticus muscle-pair has a positive value for new
electrodes and a negative value for old electrodes, indicating that the muscle displaying
preponderant activity differs between the two types of electrodes. The difference in the
DMVperc between the two electrode types in the three muscle-pair is statistically significant:
t(1, 173) = -2.80, p = 0.005.
40. 40
Improving the selectivity of surface EMG recordings
1.4
1.2
1
SVperc
0.8
0.6
0.4
0.2
fro
n/
co
r
r_
O
fro
n/
co
rr_
oc
N
ul
/z
yg
o_
O
oc
ul
/z
yg
o_
N
oc
ul
/le
va
_O
oc
ul
/le
va
_N
zy
go
/le
va
_O
zy
go
/le
va
zy
_N
go
/m
as
s_
zy
O
go
/m
as
s_
or
N
is
/m
en
t_
O
or
is
/m
en
t_
or
N
is
/m
as
s_
O
or
is
/m
as
s_
N
or
is
/z
yg
o_
O
or
is
/z
yg
o_
co
N
rr/
m
en
t_
O
co
rr/
m
en
t_
N
0
Figure 12.
SVperc of all muscle-pairs for both electrode types in the
“< 1 SD dataset”.
Muscle-pair
t
df
p
fron/corr_old vs fron/corr_new
-1.95
590
0.051
ocul/zygo_old vs ocul/zygo_new
6.85
700
<0.001
ocul/leva_old vs ocul/leva_new
4.01
709
<0.001
zygo/leva_old vs zygo/leva_new
3.93
774
<0.001
zygo/mass_old vs zygo/mass_new
-0.59
772
0.552
oris/ment_old vs oris/ment_new
-6.63
716
<0.001
oris/mass_old vs oris/mass_new
-1.16
747
0.247
oris/zygo_old vs oris/zygo_new
-2.80
731
0.005
corr/ment_old vs corr/ment_new
-4.32
649
<0.001
Table 11.
Results of the paired t-tests between new and old electrodes on the SVperc for
all muscle-pairs in the “<1 SD dataset”.
41. Improving the selectivity of surface EMG recordings
41
Figure 13 shows the SVdelta of all muscle-pairs for both electrode types in the “< 1SD
dataset”. Note that the SVdelta is significantly higher for the new electrodes in the
zygomaticus/masseter, oris/masseter and oris/zygomaticus muscle-pairs. The SVdelta turns
out to be higher for the old electrodes in the frontalis/corrugator, oculi/zygomaticus,
zygomaticus/levator and corrugator/mentalis muscle-pairs. The paired t-tests did not reveal
any differences in the SVdelta between old and new electrodes in the oculi/levator and
oris/mentalis muscle-pairs. Table 12 provides an overview of the performed paired t-tests on
the SVperc between old and new electrodes.
In addition, the DMV in the oris/mentalis muscle-pair has a positive value for new electrodes
and a negative value for old electrodes, and vice versa for the masseter/oris muscle pair. This
indicates that the muscle displaying preponderant activity differs between the two types of
electrodes. The difference in the DMVdelta between the two electrode types in the three
muscle-pair is statistically significant: t(1, 709) = -2.05, p = 0.041; t(714) = 3.83, p <0.001,
respectively.
42. 42
Improving the selectivity of surface EMG recordings
1.6
1.4
1.2
SVdelta
1
0.8
0.6
0.4
0.2
fro
n/
co
r
r_
O
fro
n/
co
rr_
oc
N
ul
/z
yg
o_
O
oc
ul
/z
yg
o_
N
oc
ul
/le
va
_O
oc
ul
/le
va
_N
zy
go
/le
va
_O
zy
go
/le
va
zy
_N
go
/m
as
s_
zy
O
go
/m
as
s_
or
N
is
/m
en
t_
O
or
is
/m
en
t_
or
N
is
/m
as
s_
O
or
is
/m
as
s_
N
or
is
/z
yg
o_
O
or
is
/z
yg
o_
co
N
rr/
m
en
t_
O
co
rr/
m
en
t_
N
0
Figure 13.
SVdelta of all muscle-pairs for both electrode types in the “< 1SD dataset”.
Muscle-pair
t
df
p
fron/corr_old vs fron/corr_new
4.00
614
<0.001
ocul/zygo_old vs ocul/zygo_new
2.34
716
0.020
ocul/leva_old vs ocul/leva_new
0.409
741
0.683
zygo/leva_old vs zygo/leva_new
2.60
775
0.010
zygo/mass_old vs zygo/mass_new
-2.72
762
0.007
oris/ment_old vs oris/ment_new
0.21
709
0.835
oris/mass_old vs oris/mass_new
-5.48
714
<0.001
oris/zygo_old vs oris/zygo_new
-4.66
705
<0.001
corr/ment_old vs corr/ment_new
5.52
627
<0.001
Table 12.
Results of the paired t-tests between new and old electrodes on the SVdelta
for all muscle-pairs in the “<1 SD dataset”.
43. 43
Improving the selectivity of surface EMG recordings
The signtest on SVperc in the “<1 SD dataset” (see table 13) indicates that the new electrodes
are more often characterized by a higher SVperc than the old electrodes in the oris/mentalis,
oris/zygomaticus and corrugator/mentalis muscle-pairs. The opposite holds for the
oculi/zygomaticus, oculi/levator, zygomaticus/levator muscle-pairs. No statistically
significant differences were found for the frontalis/corrugator, zygomaticus/masseter and
oris/masseter muscle-pairs.
Muscle-
N
N
N
observed p
pair
(SV new>SV old)
(SV new<SV old)
total
(SV new>SV old)
fron/corr
294
297
591
0.50
0.934
ocul/zygo
284
417
701
0.41
<0.001
ocul/leva
304
406
710
0.43
<0.001
zygo/leva
340
435
775
0.44
0.001
zygo/mass
399
374
773
0.52
0.388
oris/ment
424
293
717
0.59
<0.001
oris/mass
384
364
748
0.51
0.487
oris/zygo
398
334
732
0.54
0.020
corr/ment
364
286
650
0.56
0.003
Table 13.
p
Results of the signtest on (SVperc_old minus SVperc_new) for all musclepairs in the“<1 SD dataset”.
The signtest on SVdelta in the “<1 SD dataset” (see table 14) indicates that the new electrodes
are more often characterized by a higher SVperc than the old electrodes in the oris/masseter
and oris/zygomaticus muscle-pairs. The opposite holds for the frontalis/corrugator,
oculi/zygomaticus, oculi/levator, zygomaticus/levator and corrugator/mentalis muscle-pairs.
No statistically significant differences were found for the zygomaticus/masseter and
oris/mentalis muscle-pairs.
44. 44
Improving the selectivity of surface EMG recordings
Muscle-
N
N
N
observed p
pair
(SV new>SV old)
(SV new<SV old)
total
(SV new>SV old)
fron/corr
245
370
615
0.40
<0.001
ocul/zygo
323
394
717
0.45
0.009
ocul/leva
332
410
742
0.45
0.005
zygo/leva
332
444
776
0.43
<0.001
zygo/mass
407
356
763
0.53
0.070
oris/ment
358
352
710
0.50
0.851
oris/mass
392
323
715
0.45
0.011
oris/zygo
412
294
706
0.58
<0.001
corr/ment
262
366
628
0.42
<0.001
Table 14.
p
Results of the signtest on (SVdelta_old minus SVdelta_new) for all musclepairs in the “<1 SD dataset”.
45. Improving the selectivity of surface EMG recordings
45
Discussion
To test whether a reduction of the bipolar spacing results in an increase in spatial selectivity
of EMG recordings in the facial region a comparative study between two electrode types was
performed. EMG from 8 facial muscles was bilaterally recorded, rendering 16 EMG
electrode-pair sites in total. Twenty subjects viewed 48 pictures presented in series while the
EMG from the electrode-pair sites was recorded.
The MAV of the new electrodes was lower than the MAV of the old electrodes in all eight
muscle-pairs both in the baseline interval and in the active interval. This finding supports the
notion that a small bipolar spacing causes a decrease in amplitude of the EMG signal (e.g.
Loeb & Gans, 1986; Jonas et al., 1999; Zedka et al., 1997). Note that the two electrode types
differed in more ways than just bipolar spacing. For instance, it is not clear what the effect of
the shape of the contacts on the amplitude of the EMG signal was (compare e.g. De Luca,
1997 with Jonas et al., 1999).
Although the Selectivity Values (SV) differed significantly between the two electrode types in
many cases, there does not appear to be a general effect of electrode-type on selectivity as
measured by the SV. Whereas some muscles-pairs show a higher SV when recorded with new
electrodes, others show a higher SV when old electrodes are used (see table 15). In general,
the old electrodes seem to have higher SVs.
The length of the bar electrodes may be a disadvantage in small muscles. The contacts may
intersect non-target muscles as well. Furthermore, the selective effect of electrode orientation
in such closely spaced bar electrodes may be less outspoken due to the configuration of the
contacts. However, there are a number of other factors that could lead to the reported results.
Since the electrode parameters were equal in all muscles one could hypothesize that this
finding may be a result of physiological properties of the recording site. Since the SV is
calculated by subtracting the MAVsperc (or delta) from one muscle of the muscle-pair from
the other, the MAVsperc (or delta) of both muscles determine the SV. If the MAVperc (or
delta) of one of the muscles is relatively low compared to the other this results in a relatively
high SV. If the MAVsperc (or delta) of both muscles are comparable, the SV will be fairly
low. Bear in mind that if the MAV in the active interval does not differ much from the MAV
in the baseline interval, the MAVperc (or delta) of that muscle will be low. The MAVsperc
(or delta) are standardized and relative (i.e. compared to a baseline) measures and thus
46. Improving the selectivity of surface EMG recordings
46
account for the magnitude of the absolute amplitude. However, in the case of an electrodepair that is not capable of detecting a reliable myoelectric signal both the active MAV and the
baseline MAV may be low although the muscle could be more active in the active interval.
The depth of the active muscle fibers and the relative placement on the muscle may cause
such a poor pick-up (e.g. Loeb & Gans, 1986). This could result in a high SV or in a low SV
depending on the MAVperc (or delta) of the other muscle in the muscle-pair. Note that the
new electrodes are more prone to suboptimal recording and placement due to their
dimensions. This could also explain the differences in Dominant Muscle Value between the
two electrode types.
In general, the results of the signtests seem to coincide with the results of the t-tests indicating
that the reported differences are not due to outliers. However, note that there are differences
between the results of both tests (see table 15) pointing to a lack of robustness of the SV
concept.
Table 15 shows that the three distinct datasets differ in the SVold and SVnew. Since the
MAVperc (or delta) is a relative measure, the absolute amplitude of the EMG signal is not an
issue. Therefore, it is well possible to find a MAVperc (or delta) that is fairly high but is
derived from two MAVs that are so low that they could be considered error. The “> 1 SD
dataset” is therefore believed to be the most valid dataset. Furthermore, Solomonow et al.
(1994) stated that lower amplitude EMG yields much lower cross-talk in neighboring
muscles. The differences in selectivity between the two electrode types were therefore
expected to be more outspoken in the “> 1 SD dataset”. Table 15 shows that this latter
assumption does not seem to hold. Note that there are few consistent results within each
dataset for the different tests and quantification methods (i.e. perc or delta). It is not clear
which method of quantification leads to a better measure of selectivity. The differences again
point to a lack of robustness of the SV concept.
47. 47
Improving the selectivity of surface EMG recordings
unconstraint dataset
> 1 SD dataset
< 1 SD dataset
t%
tΔ
s%
sΔ
t%
tΔ
s%
sΔ
t%
tΔ
s%
sΔ
fron/corr
n
o
.
o
n
o
n
o
n
o
.
o
ocul/zygo
o
o
o
o
.
.
.
.
o
o
o
o
ocul/leva
o
.
o
o
o
.
o
o
o
.
o
o
zygo/leva
o
o
o
o
o
.
o
.
o
o
o
o
zygo/mass
.
.
.
.
.
.
.
.
.
n
.
.
oris/ment
n
.
n
.
n
.
n
.
n
.
n
.
oris/mass
.
n
.
.
.
.
.
.
.
n
.
n
oris/zygo
n
n
n
n
.
n
.
n
n
n
n
n
corr/ment
n
o
n
o
n
o
n
o
n
o
n
o
Tabel 15.
Overview of the comparisons between new and old electrodes on SVperc
(denoted by “ %”) and SVdelta (denoted by “Δ” ) in the three distinct
datasets. Results on both t-tests (denoted by “t”) and signtests (denoted by
“s”) are presented. “n” reflects a higher SV for the new electrodes whereas
“o” reflects a higher SV for the old electrodes. A dot (“.”) indicates that the
old and new electrodes did not differ significantly on SV.
There are several reasons why the SV concept is not robust. Firstly, the SV is based on the
assumption that activity, which is present in both muscles of a muscle-pair can be considered
to be a result of reciprocal cross-talk. This does not have to be the case, as the significant
differences in SV between new and old electrodes in the corrugator/mentalis muscle-pair
indicate. Furthermore, the used method cannot account for cross-talk that stems from other
not-recorded muscles. This myoelectric signal may be picked up by a less selective electrode
pair and not by the selective electrode pair, thereby adding to the MAVperc (or delta) of the
non-selective electrode pair. This may result in a higher SV for the non-selective electrode
pair, for instance if a nearby non-recorded muscle is coactivated.
It could be argued that the results may be (partly) explained by accounting for inter-subject
variability. A pilot-analysis, however, revealed that the results of the analysis at subject-level
did not differ from the presented results.
48. Improving the selectivity of surface EMG recordings
48
Conclusions
The two electrode types yield different EMG signals (hypothesis I). A reduced bipolar
spacing results in a decrease of the overall amplitude of the EMG signal (hypothesis I and II).
This study revealed no general increase in selectivity by means of a reduced bipolar spacing
(contrary to hypothesis III). However, Van Boxtel et al. (1984) pointed out that volume
conduction is a complicating factor, which affects the validity of integrated EMG measures.
The SV is such an integrated measure and although its simplicity may seem appealing, it
presumably lacks the detail required for a reliable analysis of the extent of cross-talk in EMG
records. Therefore, the SV by itself does not seem to be a valid measure for determining the
selectivity of an EMG recording. Future analysis should focus on frequency analysis and
multimuscle cross-correlation. Both may provide more direct measures of selectivity than
integrated measures.
49. Improving the selectivity of surface EMG recordings
49
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54. Improving the selectivity of surface EMG recordings
Acknowledgements
I am indebted to the following people for their contributions to this paper:
Ton Aalbers
Bert Bastiaansen
John van den Beesen
Ton van Boxtel
Franc Donkers
Charles Rambelje
54
55. Improving the selectivity of surface EMG recordings
55
Appendix
Secondary goal and stimulus selection
Distinct affective states are presumed to be reflected by different facial expressions. The
secondary goal of this experiment is to determine which facial muscles are activated during
distinct affective states. This research question will be addressed in a later stage. To be able to
answer this question, it is necessary to determine the experienced affective state as accurately
as possible and to measure facial muscle activity reliably. Previous attempts are assumed to
be unreliable due to cross-talk (A. van Boxtel, personal communication, June 2000). The
experienced affective state is ascertained by asking the subjects to judge the pictures by
means of six different five-point scales ranging from “not at all” to “very strongly” (Hoekstra,
1986). Each scale centers round one affective state: happy, sad, anger, surprise, disgust and
fear. Although this classification is not intended to be omnifarious, these six affective states
are thought to be universal (e.g. Ekman & Friesen, 1978).
Since the experienced affective state would ideally be as archetypical (i.e. uncontaminated) as
possible, the pictures need to be selected with care. Hence, a picture that would elicit a
combination of affective states would lead to inconclusive results: the relationship between a
distinct affective state and the recorded muscle activity would remain unclear.
In order to create a dataset of pictures that were associated with only one affective state a pilot
study was performed. 24 Subjects rated 144 pictures from the IAPS dataset (Lang et al., 1999)
on the six scales described above. 48 pictures were selected: 7 slides of each category and 6
neutral slides. The following criteria were used to select suitable pictures:
1) level of differentiation:
a) the mean score of a picture on one category should be higher than the score
on the other 5 categories and this difference should be statistically significant;
b) when the difference between the categories is not significant the picture with
the least number of insignificant differences was chosen;
2) highest value:
c) if several pictures met criterium a, the picture with the highest value on the
category was chosen;
56. 56
Improving the selectivity of surface EMG recordings
This procedure yielded 42 pictures. 6 Neutral stimuli were selected by choosing the pictures
with the lowest overall values. The following 48 pictures were shown in the physiological
study (*.bmp):
1300
3062
7150
1302
3063
7175
1313
3150
7211
1321
3168
7238
1463
3230
7325
1721
4599
7380
1750
4613
7705
1930
4621
8040
1931
5510
9102
2205
5760
9220
2550
6230
9320
2575
6243
9560
2700
6260
9561
2800
7025
9570
3000
7050
9800
3060
7080
9810