Bio-Sensors & their Working Principle
Application of Bio-Sensors in the field of Electrical
EMG
ECG
EEG
Implementation target for Robotic Arm
Conclusion
Electromyography (EMG) measures the electrical activity in muscles in response to nerve stimulation. EMG is used to detect abnormalities in the neuromuscular system. The EMG process involves placing electrodes on the skin or inserting needles into muscles to pick up tiny electrical signals from contracting muscle fibers. The signals are amplified and processed before being visually displayed and analyzed. EMG can be diagnostic to study muscle and nerve diseases or kinesiological to examine muscle activity. It provides information about motor unit structure and function.
This document provides an overview of electromyography (EMG) including:
- EMG measures the electrical activity of active muscle fibers using electrodes placed close to muscles. Rectified EMG signals indicate muscle activity.
- Applications of EMG include assessing muscle function, neuromuscular diseases, and prosthetics.
- Factors that impact EMG signal quality include signal-to-noise ratio, filtering, and minimizing noise contamination and signal distortion.
- Different types of EMG electrodes exist including fine-wire, needle, and surface electrodes, each with their own advantages and disadvantages for measuring muscle activity.
The document discusses electroencephalography (EEG), which measures the electrical activity of the brain using electrodes placed on the scalp. It describes brain anatomy, including the cerebrum, cerebellum, and brainstem. It also discusses the 10-20 international system for electrode placement on the scalp and the different types of brain waves that can be measured by EEG, including alpha, beta, theta, delta, and gamma waves. The document provides an overview of how EEG is used to record and analyze brain activity for applications such as epilepsy diagnosis, monitoring anesthesia and brain injury.
This document discusses electromyography (EMG), which is the study of electrical activity in muscles. It describes how EMG is recorded using different types of electrodes, including surface electrodes to record signals on the skin surface and needle electrodes that can detect deeper muscle potentials. The EMG recording system involves electrodes to pick up signals, amplification, and output to devices like speakers or tape recorders. EMG has applications in studying neuromuscular functions and diseases. Measurement of conduction velocity in motor nerves can help locate nerve lesions by stimulating nerves and measuring latency between stimulation and muscle action potentials.
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.
Sensing and processing of Bio metric signals for Low cost Bio Robotic systemsDEVANAND P PRABHU
This document discusses sensing and processing of bio-metric signals for use in low cost bio-robotic systems. It describes how bio-metrics work using input sensors, a processing unit, and an output interface. Bio-robotic systems are needed to replace humans in hazardous conditions and perform high precision tasks. Prosthetics are discussed as a type of bio-robotic system that can replace injured body parts either passively or actively using sensors. Electromyography and electroencephalography are described as sensing technologies that can be used in prosthetics. The document concludes that electromyography offers an effective low-cost solution for prosthetics, though customization is needed and signal strength depends on variable user factors.
PRESENTATION LAB DSP.Analysis & classification of EMG signal - DSP LABNurhasanah Shafei
The document discusses analyzing and classifying EMG signals from different patients. It presents the objectives of identifying signal characteristics, analyzing power spectra to define parameters for patient identification, and implementing a rule-based classifier. The methodology block diagram shows receiving EMG signals from two patients and identifying the signal source. Key steps are identifying signal characteristics, generating power spectra using FFT, extracting parameters, and using these as classifier inputs to differentiate patients. Results figures show input signals, power spectra, and the system verifying classification of signals from two patients.
The document discusses electromyography (EMG), which is used to record and study the electrical activity of muscles. EMG uses surface or needle electrodes to measure bioelectric potentials from muscles. The measured signals are amplified and displayed. EMG can detect nerve lesions, muscle conditions, and reflex responses. However, the EMG signals can be affected by various artefacts like power line interference, electrocardiogram signals, movement, DC offset, and muscle crosstalk.
Electromyography (EMG) measures the electrical activity in muscles in response to nerve stimulation. EMG is used to detect abnormalities in the neuromuscular system. The EMG process involves placing electrodes on the skin or inserting needles into muscles to pick up tiny electrical signals from contracting muscle fibers. The signals are amplified and processed before being visually displayed and analyzed. EMG can be diagnostic to study muscle and nerve diseases or kinesiological to examine muscle activity. It provides information about motor unit structure and function.
This document provides an overview of electromyography (EMG) including:
- EMG measures the electrical activity of active muscle fibers using electrodes placed close to muscles. Rectified EMG signals indicate muscle activity.
- Applications of EMG include assessing muscle function, neuromuscular diseases, and prosthetics.
- Factors that impact EMG signal quality include signal-to-noise ratio, filtering, and minimizing noise contamination and signal distortion.
- Different types of EMG electrodes exist including fine-wire, needle, and surface electrodes, each with their own advantages and disadvantages for measuring muscle activity.
The document discusses electroencephalography (EEG), which measures the electrical activity of the brain using electrodes placed on the scalp. It describes brain anatomy, including the cerebrum, cerebellum, and brainstem. It also discusses the 10-20 international system for electrode placement on the scalp and the different types of brain waves that can be measured by EEG, including alpha, beta, theta, delta, and gamma waves. The document provides an overview of how EEG is used to record and analyze brain activity for applications such as epilepsy diagnosis, monitoring anesthesia and brain injury.
This document discusses electromyography (EMG), which is the study of electrical activity in muscles. It describes how EMG is recorded using different types of electrodes, including surface electrodes to record signals on the skin surface and needle electrodes that can detect deeper muscle potentials. The EMG recording system involves electrodes to pick up signals, amplification, and output to devices like speakers or tape recorders. EMG has applications in studying neuromuscular functions and diseases. Measurement of conduction velocity in motor nerves can help locate nerve lesions by stimulating nerves and measuring latency between stimulation and muscle action potentials.
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.
Sensing and processing of Bio metric signals for Low cost Bio Robotic systemsDEVANAND P PRABHU
This document discusses sensing and processing of bio-metric signals for use in low cost bio-robotic systems. It describes how bio-metrics work using input sensors, a processing unit, and an output interface. Bio-robotic systems are needed to replace humans in hazardous conditions and perform high precision tasks. Prosthetics are discussed as a type of bio-robotic system that can replace injured body parts either passively or actively using sensors. Electromyography and electroencephalography are described as sensing technologies that can be used in prosthetics. The document concludes that electromyography offers an effective low-cost solution for prosthetics, though customization is needed and signal strength depends on variable user factors.
PRESENTATION LAB DSP.Analysis & classification of EMG signal - DSP LABNurhasanah Shafei
The document discusses analyzing and classifying EMG signals from different patients. It presents the objectives of identifying signal characteristics, analyzing power spectra to define parameters for patient identification, and implementing a rule-based classifier. The methodology block diagram shows receiving EMG signals from two patients and identifying the signal source. Key steps are identifying signal characteristics, generating power spectra using FFT, extracting parameters, and using these as classifier inputs to differentiate patients. Results figures show input signals, power spectra, and the system verifying classification of signals from two patients.
The document discusses electromyography (EMG), which is used to record and study the electrical activity of muscles. EMG uses surface or needle electrodes to measure bioelectric potentials from muscles. The measured signals are amplified and displayed. EMG can detect nerve lesions, muscle conditions, and reflex responses. However, the EMG signals can be affected by various artefacts like power line interference, electrocardiogram signals, movement, DC offset, and muscle crosstalk.
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.
The document provides an overview of commonly used biomedical signals for monitoring physiological processes and detecting pathological conditions. It discusses several key signals including the electrocardiogram (ECG), electroencephalogram (EEG), electromyogram (EMG), electroretinogram (ERG), electrooculogram (EOG) and event-related potentials (ERPs). For each signal, it describes what physiological process is being measured, how the signal is recorded, its typical amplitude and bandwidth, main sources of interference and common applications. The document emphasizes that biomedical signals reflect the electrical, chemical and mechanical activities of cells, tissues and organs, and can provide important diagnostic information when analyzed.
Electromyography (EMG) is a diagnostic procedure to assess the health of muscles and the nerve cells that control them (motor neurons). EMG results can reveal nerve dysfunction, muscle dysfunction or problems with nerve-to-muscle signal transmission.
Senior Project Student's Presentation on Design of EMG Signal Recording SystemMd Kafiul Islam
This document summarizes a student project to design and implement an affordable EMG signal recorder to control a prosthetic arm. The system uses EMG electrodes to detect muscle signals, filters and amplifies the signals, analyzes them using MATLAB, and uses the output to control a robotic prosthetic arm. The system achieves an average accuracy of 83% across 5 test subjects. It costs around 10,000 BDT to build, making it much more affordable than commercial prosthetics. Future work could involve 3D printing a prosthetic hand and allowing individual finger movement control.
Electromyography (EMG) measures the electrical activity of muscles through intramuscular or surface electrodes. EMG signals can help characterize neurological and muscular diseases. Neuropathies produce longer, higher amplitude muscle action potentials with increased polyphasicity. Myopathies decrease action potential duration and area-to-amplitude ratio. EMG biofeedback uses electrode feedback to control muscle activation and is used to assess muscle imbalance.
This document provides an overview of electromyography (EMG) including:
1. EMG measures the bioelectric potentials of muscle activity through either inserted fine-wire or needle electrodes, or skin surface electrodes.
2. Different types of electrodes have advantages and disadvantages related to sensitivity, ability to access deep muscles, risk of cross-talk, and ease of use.
3. Factors like signal-to-noise ratio and minimal signal distortion are important to maximize the quality of EMG signals.
An EEG is a test that detects electrical activity in the brain using electrodes placed on the scalp. It is used to diagnose brain conditions like epilepsy and Alzheimer's disease. During an EEG, electrodes pick up electrical signals produced by the brain and transmit them to an amplifier. The amplified signals are then processed and displayed. Common wave patterns seen on EEGs include alpha, beta, theta, and delta waves which are classified by their frequency and amplitude. EEGs are generally safe and painless but can potentially cause seizures in patients with seizure disorders.
This document provides an overview of electromyography (EMG) including what it is, how it works, the types of electrodes used, and applications. EMG is a technique that evaluates and records the electrical activity of muscles using an electromyograph instrument. There are two main types of EMG electrodes: surface electrodes that measure potential from the skin surface using various attachment methods, and inserted electrodes like needle and fine wire types that are placed into muscles. EMG signals can be analyzed to detect medical issues or analyze human and animal movement biomechanics.
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.
The document outlines various topics related to biomedical instrumentation including biometrics, physiological systems of the human body like cardiovascular and respiratory systems, the kidney, bioelectric potentials, biopotential electrodes, and transducers for ECG, EEG, and EMG. It also provides details on the characteristics of biomedical instrumentation systems and describes concepts like bioelectric potential, action potential, and the recording setup for ECG, EEG, and EMG.
Electromyography (EMG) is an electrodiagnostic medicine technique for evaluating and recording the electrical activity produced by skeletal muscles. EMG is performed using an instrument called an electromyograph to produce a record called an electromyogram
Bhaskar Health News and Medical Education is leading source for trustworthy health, medical, science and technology news and information. Providing world health information Medical Education.
Bhaskar Health News and Medical Education is dedicated to medical students, physiotherapists, doctors, nurses, paramedics, physician associates, dentists, pharmacists, midwives and other healthcare professionals.
We're committed to being your source for expert health guidance. Bhaskar Health and Medical Education.
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@drrohitbhaskar @bhaskarhealth
#DrRohitBhaskar #BhaskarHealth
#Health #Medical #News #Physiotherapy
1. Electromyography (EMG) is a technique for evaluating and recording muscle activation signals using an electromyograph. EMG detects the electrical potentials generated by muscle cells during contraction and relaxation.
2. There are two main types of EMG electrodes - inserted needle electrodes and surface electrodes. Needle electrodes are more sensitive but require medical expertise, while surface electrodes are quick and easy to apply but only record superficial muscles.
3. EMG can be used to diagnose disorders of nerves, neuromuscular junctions, and muscles. It involves cleaning the electrode site, placing electrodes on the muscle, and recording electrical activity both at rest and during voluntary contractions.
This document provides an overview of electrodiagnostic testing, including nerve conduction studies (NCS) and electromyography (EMG). It discusses what each test evaluates, how they are performed, and key terms. NCS evaluate nerves by applying electrical stimuli and measuring nerve response. EMG evaluates muscles by inserting a needle electrode to measure intrinsic electrical activity. Both tests provide information about nerves and the muscles they innervate. The document also reviews reasons electrodiagnostic testing is useful, including establishing diagnoses, localizing lesions, determining treatment, and assessing prognosis. It emphasizes the importance of compassionate, skilled performance of the tests to minimize patient discomfort.
This slide has been prepared in detaied manner and will help you.
The topics covered are:-
1- introduction
2.circuit diagram and its explaination
3.working
4. features
5.advantages / disadvantages
6. the top vendors
Definition of Biofeedback and what is its Importance ? - The Physio ClubThephysioclub .
The term biofeedback refer to the procedure by which information about a physiological function is fed back to the individual by means of an auditory or visual signal. Biofeedback Importance .
Dr. Samuel Theagene is a diplomate of the American Board of Physical Medicine and Rehabilitation. An experienced doctor who works in pain management, Samuel M. Theagene, M.D., delivers interventional spine treatments aided by modern techniques like electromyography.
Intraoperative electromyography (EMG) provides useful diagnostic and prognostic information during spine and peripheral nerve surgeries. The basic techniques include free-running EMG, stimulus-triggered EMG, and intraoperative nerve conduction studies. These techniques can be used to monitor nerve roots during spine surgeries, the facial nerve during cerebellopontine angle surgeries, and peripheral nerves during brachial plexus exploration and repair.
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.
This document provides an overview of electromyography (EMG). It defines EMG as the study of motor unit activity through the recording and analysis of myoelectric signals. EMG allows direct examination of muscle performance and function. It describes the motor unit and how EMG detects the motor unit action potential. Different types of electrodes used for EMG are discussed, including surface, fine-wire, and needle electrodes. The document outlines how EMG signals are captured and factors that can influence the myoelectric signal recording.
The document discusses electroencephalography (EEG) and summarizes an experiment on EEG waveforms. Key points:
1. An EEG measures electrical activity in the brain using electrodes placed on the scalp. It can detect abnormalities and monitor brain states.
2. The experiment stimulated EEG patterns on a subject under different conditions like eyes open/closed, blinking, movement, talking and sleep.
3. The EEG recordings showed different waveform patterns and brain activations depending on the subject's activity level and state. This demonstrated how EEG can interpret brain activity in real-time.
Diagnostic medical equipment is used in hospitals and clinics to diagnose patients' conditions. This includes laboratory equipment like cell blood counters, arterial blood gas analyzers, spectrophotometers, and microscopes. It also includes devices like electrocardiographs, electroencephalographs, electromyographs, patient monitors, pulse oximeters, pH meters, and thermometers. These devices help evaluate patients internally, detect any abnormalities, and allow doctors to precisely analyze organ function.
EMG can detect changes that occur in muscles during fatigue and contraction. Measurements were taken from the human adductor pollicis muscle and showed that force and contractile speed decreased during fatigue. EMG signals also changed, with motor unit action potentials increasing in duration and amplitude. This suggests that fatigue causes motor units to recruit more muscle fibers to maintain force levels during contractions. EMG is useful for evaluating muscle fatigue and understanding how the motor system adapts during physical exertion.
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.
The document provides an overview of commonly used biomedical signals for monitoring physiological processes and detecting pathological conditions. It discusses several key signals including the electrocardiogram (ECG), electroencephalogram (EEG), electromyogram (EMG), electroretinogram (ERG), electrooculogram (EOG) and event-related potentials (ERPs). For each signal, it describes what physiological process is being measured, how the signal is recorded, its typical amplitude and bandwidth, main sources of interference and common applications. The document emphasizes that biomedical signals reflect the electrical, chemical and mechanical activities of cells, tissues and organs, and can provide important diagnostic information when analyzed.
Electromyography (EMG) is a diagnostic procedure to assess the health of muscles and the nerve cells that control them (motor neurons). EMG results can reveal nerve dysfunction, muscle dysfunction or problems with nerve-to-muscle signal transmission.
Senior Project Student's Presentation on Design of EMG Signal Recording SystemMd Kafiul Islam
This document summarizes a student project to design and implement an affordable EMG signal recorder to control a prosthetic arm. The system uses EMG electrodes to detect muscle signals, filters and amplifies the signals, analyzes them using MATLAB, and uses the output to control a robotic prosthetic arm. The system achieves an average accuracy of 83% across 5 test subjects. It costs around 10,000 BDT to build, making it much more affordable than commercial prosthetics. Future work could involve 3D printing a prosthetic hand and allowing individual finger movement control.
Electromyography (EMG) measures the electrical activity of muscles through intramuscular or surface electrodes. EMG signals can help characterize neurological and muscular diseases. Neuropathies produce longer, higher amplitude muscle action potentials with increased polyphasicity. Myopathies decrease action potential duration and area-to-amplitude ratio. EMG biofeedback uses electrode feedback to control muscle activation and is used to assess muscle imbalance.
This document provides an overview of electromyography (EMG) including:
1. EMG measures the bioelectric potentials of muscle activity through either inserted fine-wire or needle electrodes, or skin surface electrodes.
2. Different types of electrodes have advantages and disadvantages related to sensitivity, ability to access deep muscles, risk of cross-talk, and ease of use.
3. Factors like signal-to-noise ratio and minimal signal distortion are important to maximize the quality of EMG signals.
An EEG is a test that detects electrical activity in the brain using electrodes placed on the scalp. It is used to diagnose brain conditions like epilepsy and Alzheimer's disease. During an EEG, electrodes pick up electrical signals produced by the brain and transmit them to an amplifier. The amplified signals are then processed and displayed. Common wave patterns seen on EEGs include alpha, beta, theta, and delta waves which are classified by their frequency and amplitude. EEGs are generally safe and painless but can potentially cause seizures in patients with seizure disorders.
This document provides an overview of electromyography (EMG) including what it is, how it works, the types of electrodes used, and applications. EMG is a technique that evaluates and records the electrical activity of muscles using an electromyograph instrument. There are two main types of EMG electrodes: surface electrodes that measure potential from the skin surface using various attachment methods, and inserted electrodes like needle and fine wire types that are placed into muscles. EMG signals can be analyzed to detect medical issues or analyze human and animal movement biomechanics.
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.
The document outlines various topics related to biomedical instrumentation including biometrics, physiological systems of the human body like cardiovascular and respiratory systems, the kidney, bioelectric potentials, biopotential electrodes, and transducers for ECG, EEG, and EMG. It also provides details on the characteristics of biomedical instrumentation systems and describes concepts like bioelectric potential, action potential, and the recording setup for ECG, EEG, and EMG.
Electromyography (EMG) is an electrodiagnostic medicine technique for evaluating and recording the electrical activity produced by skeletal muscles. EMG is performed using an instrument called an electromyograph to produce a record called an electromyogram
Bhaskar Health News and Medical Education is leading source for trustworthy health, medical, science and technology news and information. Providing world health information Medical Education.
Bhaskar Health News and Medical Education is dedicated to medical students, physiotherapists, doctors, nurses, paramedics, physician associates, dentists, pharmacists, midwives and other healthcare professionals.
We're committed to being your source for expert health guidance. Bhaskar Health and Medical Education.
Source : https://www.bhaskarhealth.com
Health Shop: https://www.bhaskarhealth.org
@drrohitbhaskar @bhaskarhealth
#DrRohitBhaskar #BhaskarHealth
#Health #Medical #News #Physiotherapy
1. Electromyography (EMG) is a technique for evaluating and recording muscle activation signals using an electromyograph. EMG detects the electrical potentials generated by muscle cells during contraction and relaxation.
2. There are two main types of EMG electrodes - inserted needle electrodes and surface electrodes. Needle electrodes are more sensitive but require medical expertise, while surface electrodes are quick and easy to apply but only record superficial muscles.
3. EMG can be used to diagnose disorders of nerves, neuromuscular junctions, and muscles. It involves cleaning the electrode site, placing electrodes on the muscle, and recording electrical activity both at rest and during voluntary contractions.
This document provides an overview of electrodiagnostic testing, including nerve conduction studies (NCS) and electromyography (EMG). It discusses what each test evaluates, how they are performed, and key terms. NCS evaluate nerves by applying electrical stimuli and measuring nerve response. EMG evaluates muscles by inserting a needle electrode to measure intrinsic electrical activity. Both tests provide information about nerves and the muscles they innervate. The document also reviews reasons electrodiagnostic testing is useful, including establishing diagnoses, localizing lesions, determining treatment, and assessing prognosis. It emphasizes the importance of compassionate, skilled performance of the tests to minimize patient discomfort.
This slide has been prepared in detaied manner and will help you.
The topics covered are:-
1- introduction
2.circuit diagram and its explaination
3.working
4. features
5.advantages / disadvantages
6. the top vendors
Definition of Biofeedback and what is its Importance ? - The Physio ClubThephysioclub .
The term biofeedback refer to the procedure by which information about a physiological function is fed back to the individual by means of an auditory or visual signal. Biofeedback Importance .
Dr. Samuel Theagene is a diplomate of the American Board of Physical Medicine and Rehabilitation. An experienced doctor who works in pain management, Samuel M. Theagene, M.D., delivers interventional spine treatments aided by modern techniques like electromyography.
Intraoperative electromyography (EMG) provides useful diagnostic and prognostic information during spine and peripheral nerve surgeries. The basic techniques include free-running EMG, stimulus-triggered EMG, and intraoperative nerve conduction studies. These techniques can be used to monitor nerve roots during spine surgeries, the facial nerve during cerebellopontine angle surgeries, and peripheral nerves during brachial plexus exploration and repair.
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.
This document provides an overview of electromyography (EMG). It defines EMG as the study of motor unit activity through the recording and analysis of myoelectric signals. EMG allows direct examination of muscle performance and function. It describes the motor unit and how EMG detects the motor unit action potential. Different types of electrodes used for EMG are discussed, including surface, fine-wire, and needle electrodes. The document outlines how EMG signals are captured and factors that can influence the myoelectric signal recording.
The document discusses electroencephalography (EEG) and summarizes an experiment on EEG waveforms. Key points:
1. An EEG measures electrical activity in the brain using electrodes placed on the scalp. It can detect abnormalities and monitor brain states.
2. The experiment stimulated EEG patterns on a subject under different conditions like eyes open/closed, blinking, movement, talking and sleep.
3. The EEG recordings showed different waveform patterns and brain activations depending on the subject's activity level and state. This demonstrated how EEG can interpret brain activity in real-time.
Diagnostic medical equipment is used in hospitals and clinics to diagnose patients' conditions. This includes laboratory equipment like cell blood counters, arterial blood gas analyzers, spectrophotometers, and microscopes. It also includes devices like electrocardiographs, electroencephalographs, electromyographs, patient monitors, pulse oximeters, pH meters, and thermometers. These devices help evaluate patients internally, detect any abnormalities, and allow doctors to precisely analyze organ function.
EMG can detect changes that occur in muscles during fatigue and contraction. Measurements were taken from the human adductor pollicis muscle and showed that force and contractile speed decreased during fatigue. EMG signals also changed, with motor unit action potentials increasing in duration and amplitude. This suggests that fatigue causes motor units to recruit more muscle fibers to maintain force levels during contractions. EMG is useful for evaluating muscle fatigue and understanding how the motor system adapts during physical exertion.
The document discusses electrodiagnostic tests like electromyography (EMG), nerve conduction velocity (NCV) tests, and evoked potentials (EP) which are used to study the nervous system. EMG involves inserting needle electrodes into muscles to record electrical activity, NCV tests how quickly electrical signals move through nerves, and EP stimulates nerves or parts of the body to measure response in the brain. Together these tests can provide information about nerve and muscle injuries, diseases, and help guide treatment.
Acrylic Prosthetic Limb Using EMG signalAnveshChinta1
The topic deals with the development of a prosthetic limb made of the acrylic sheet using electromyography signals for the people who lost a part of their limb due to circulation problems from atherosclerosis or diabetes, traumatic injuries occurring due to traffic accidents and military combat, cancer or birth
effects. Electromyography (EMG) is a technique for evaluating and recording the electrical activity produced by skeletal muscles. An electromyography (EMG) detects the electrical potential generated by muscle cells when these cells are electrically or neurologically activated. Measured EMG potentials range between 2 millivolts to 4 millivolts depending on the muscle under observation. The two surface electrodes are attached to the healthy limb and sense the muscle contraction when a movement is made. This output is given to the arduino
microcontroller, this controller is programmed that, it acquires the angle and transformation link obtained due to the locomotion of normal limb.
The output signals are given to the servo motor
through servo driver and then to the prosthetic
limb. The methodology adapted here provides
locomotive action for the prosthetic limb. The
major advantage of the proposed system is that usage of acrylic sheets reduces the weight of the
prosthetic limb to a greater extent. This cost-effective acrylic prosthetic limb avoids any
irritation or side effects to the one who carries it.
This study aimed to non-invasively detect electromyography (EMG) activity of deep thumb muscles using surface electrodes. Researchers placed electrodes on the forearms of 15 participants and recorded EMG signals while participants performed thumb movements. Independent component analysis was used to separate EMG signals from superficial and deep muscles. Predicted EMG waveforms for each deep muscle were correlated with independent components, and the highest correlated component was considered to represent that muscle's activity. Overall high correlations were found between predicted and recorded waveforms. Accuracy, sensitivity and specificity measures between predicted and recorded waveforms were also statistically significant when using a threshold activation level, demonstrating the first non-invasive detection of EMG activity from deep thumb muscles.
This document discusses different types of medical electronics testing. It describes electroencephalography (EEG) which measures electrical activity in the brain using electrodes placed on the scalp. It also describes electromyography (EMG) which records electrical activity of muscles to determine contraction using surface or needle electrodes. Finally, it explains how conduction velocity in motor nerves is measured by stimulating two points on a nerve and calculating velocity based on distance and latency of response. Applications mentioned include electrophysiological testing, clinical neurophysiology, neurology, psychiatry, and sports biomechanics.
The document discusses biosignals, which are variables that can be measured from the human body to provide health information. It defines active biosignals that use internal energy sources like bioelectric signals (ECG, EEG), and passive biosignals that use external energy sources. It describes instruments used to measure biosignals like electrodes, amplifiers, and recorders. Specific biosignals discussed include ECG, EEG, and temperature signals. Challenges like electrode contact potentials and signal artifacts are also covered.
Biofeedback is a technique that uses sensors to measure physiological processes and provide feedback to help patients learn to control these processes. It works on the principle of motor learning by providing knowledge of performance or results. Various biofeedback modalities measure muscle activity, skin temperature, brain waves, heart function and more. Electromyography biofeedback uses electrodes to measure muscle electrical activity and is effective for conditions like muscle re-education, chronic back pain, and spasticity control. Precautions include ensuring patient ability and motivation to participate.
Feature Extraction Techniques and Classification Algorithms for EEG Signals t...Editor IJCATR
This document reviews techniques for extracting features and classifying EEG signals to detect human stress levels. It discusses EEG signals and how they can provide information about mental states. It also reviews common feature extraction methods like DCT and DWT that can preprocess EEG data by transforming it from the time to frequency domain. Classification algorithms like KNN, LDA, and Naive Bayes that can classify EEG data are also examined. The document proposes a system to use a Neurosky Mindwave EEG headset to record raw EEG signals, preprocess them with DWT, and classify stress levels using a combination of classifiers.
This document summarizes brainwave technology and its applications. It discusses how electroencephalography (EEG) is used to record the electrical activity of the brain in the form of brainwaves, which are measured in Hertz. It then provides examples of how brainwave technology can be applied, including to control a robot. The document outlines the process by which a brainwave-controlled robot would work, involving an EEG brainwave sensor to analyze signals and transmit them to control a robot based on analyzed brainwave patterns.
EEG measures the electrical activity of the brain through electrodes placed on the scalp. It can detect different wave patterns associated with different brain states. Evoked potentials involve stimulating a sensory pathway and measuring the electrical response along the pathway. This allows localization of lesions. Somatosensory evoked potentials involve stimulating a peripheral nerve like the median nerve and measuring the response along the pathway to detect spinal cord or brain injuries. Auditory evoked potentials involve measuring the brainstem response to a click stimulus to detect acoustic neuromas or other posterior fossa lesions. Both evoked potentials and EMG monitoring are used during surgery to detect injuries.
Biomedical Signal Processing / Biomedical Signals/ Bio-signals/ Bio-signals C...Mehak Azeem
These amazing and highly informative slides presented to the IEEE Signal Processing Society of IEEE MESCE Student Branch. These slides aim to provide basic knowledge about biosignals, their classification, examples and their working.
For more information, please contact:
[mehakazeem@ieee.org]
This document provides information about electromyography (EMG). EMG is a test that evaluates the health and function of muscles and the nerve cells that control them. It involves inserting a needle electrode into a muscle to record electrical activity from muscle fibers and nerves. Abnormal spontaneous electrical activities in muscles can indicate neurological or muscular disorders. EMG is useful for diagnosing conditions like amyotrophic lateral sclerosis, myasthenia gravis, and muscular dystrophy. It provides information about the location and severity of nerve or muscle damage.
This document provides an overview of biomedical instruments including electroencephalography (EEG), electrocardiography (ECG), and electromyography (EMG). It discusses the purpose and applications of each, and includes block diagrams of the components and systems. EEG measures electrical activity in the brain and is used to diagnose epilepsy and other brain disorders. ECG measures the heart's electrical activity through electrodes on the skin and is used to diagnose heart conditions. EMG measures muscle electrical activity and is used to diagnose neuromuscular diseases.
1. The document discusses the somatosensory and skeletal motor nerve axes of the nervous system and how they relate to muscle stretch reflexes and nerve conduction.
2. It provides details on the muscle stretch reflex pathway and how sensory signals from muscle spindles are transmitted to the spinal cord to elicit reflexive muscle contractions in response to changes in muscle length.
3. The document describes experiments measuring nerve conduction velocity along the ulnar nerve and the equipment, electrode placements, stimulation procedures, and data analysis methods used.
1. This document discusses neuron activation signals in the brain and how they relate to EEG measurements and blood oxygen levels. It describes how EEG maps different frequency bands to cognitive states and activities. It also discusses how external brain-computer interfaces can be used for medical applications by recording EEG signals or stimulating neurons.
2. The document speculates that remote wireless devices could potentially scan and map EEG signals without electrodes, enabling covert abuse. It suggests such devices could target brain regions to induce artificial sensations like tinnitus. However, the speculation about covert abuse technology is presented without evidence.
3. The document raises ethical concerns about potential misuse of brain mapping and stimulation technologies but presents speculative claims about covert abuse devices without clear supporting
The document discusses electromyography (EMG), which measures the electrical potential generated by muscle cells when they contract. It describes how EMG is produced by motor units consisting of motor neurons and muscle fibers. EMG signals can be measured on the skin's surface or intramuscularly using needle electrodes, and they provide information about muscle activation levels, recruitment patterns, and biomechanics. EMG is used clinically to diagnose neuromuscular diseases and assess pain conditions, and technologically to control prosthetics and interface with electronic devices through gesture recognition.
This document discusses two main applications of EEG waves: diagnosis of sleep disorders and brain-computer interfaces (BCIs). For sleep disorder diagnosis, EEG signals are analyzed to stage sleep and identify abnormalities. Statistical methods classify sleep stages over time. BCIs translate brain signals into commands, using visual evoked potentials from stimuli flickering at different frequencies to identify intended commands. Key issues discussed include reducing electrode numbers and optimizing frequency feature extraction from EEG signals to improve BCI accuracy and usability.
Bio-sensing principle
Types of Bio-Sensing:
EMG (Electromyogram)
EEG (Electroencephalogram)
ECG (Electrocardiogram)
Various Stages for EMG
Simulation of EMG Sensor
Video of prototype fabricated
The document describes the design of a water purifier called Atlantis. It has several sections including pebbles/gravel, coarse sand, fine sand, a ceramic layer, charcoal, and cloth. Water passes through these layers which help remove impurities like algae, physical particles of various sizes, smells, and chemicals. The purified water exits with a total dissolved solids (TDS) level of 300 compared to the incoming water's 3000 TDS level. Maintenance is required every 6 months by two people and involves replacing or cleaning the various filter layers.
Project Implementation
Real-Time Data Analysis of fabricated hardware & conclusions
Proposed Implementation using the concepts of IoT
Challenges faced in Smart Farming with perspective of India
Further Scope for Innovation from Electrical Engineer’s POV
Block diagram of Robot functioning.
Hardware required to make robot.
Programming of image processing in MATLAB. (simulation)
Implementation of control circuit in ARDUINO. (simulation)
Development of “TAURUS: v1.0”: a farmbot.
Hardware for dual axis Camera focus system. (video)
Programming in the software: Processing.
Feature Extraction for a Object: Pixel Detection & Motion Detection
Conclusion
Digital Image Processing using MatLAB with Arduino Shivang Rana
What is a digital image?
How is processing done with a digital image?
Classification of image
Block diagram of DIP
Quality Workforce Algorithm for Fruit Sorter
Block Diagram of Face Detection
Block Diagram of Comparing to Two Images
The document discusses various topics related to personality, including fundamentals of personality, measuring personality, and determinants of personality like heredity and environment. It describes several methods of measuring personality, such as clinical methods, psychometric methods, experimental methods, projective methods, personality inventories, and interview methods. It also discusses personality traits like self-esteem, locus of control, self-efficacy, self-monitoring, and emotional intelligence. The document contains a case study and takes examples to illustrate different concepts related to personality.
Energy Efficient Clustering: Wireless Sensor NetworkShivang Rana
- Clustering algorithms aim to organize wireless sensor nodes into clusters to optimize energy efficiency and enable scalability. Clustering involves selecting certain sensor nodes as cluster heads that aggregate data from member nodes and transmit to the base station.
- The document discusses several clustering objectives like load balancing, fault tolerance, reducing energy consumption and latency. It also introduces some popular clustering routing protocols like LEACH, PEGASIS and TEEN.
- LEACH is one of the most widely used clustering algorithms that selects cluster heads randomly and rotates this role to balance energy usage among nodes and prolong network lifetime. It forms clusters based on received signal strength.
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceIndexBug
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on integration of Salesforce with Bonterra Impact Management.
Interested in deploying an integration with Salesforce for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
3. Index
• Bio-Sensors & their Working Principle
• Application of Bio-Sensors in field of Electrical
• EMG
• ECG
• EEG
• Implementation target for Robotic Arm
• Conclusion
4. Introduction
What are Biosensors?
• It is an analytical device which is used for the detection of analyte which combines
biological component with electrical signals.
• It detects the presence and concentration of specific substances in test solution.
6. Electromyography (EMG) sensor
● Detects muscle activation using electric potential
● Used in medical field for curing neuromuscular disorders for the study of kinesiology
● Surface EMG sensors assess muscle function by recording muscle activity using suitable
electrodes above the skin.
● Intramuscular sensors use monopolar needle approach wherein a fine wire is inserted in the
muscle and the surface electrode is used as a reference.
EMG(V)
7.
8. Electrocardiogram Sensor (ECG)
• Used to monitor electrical and muscular functions of heart.
• It records electrical pulses generated by heart muscle depolarization which propagate in pulsating electrical
waves to the skin.
• Signal is filtered and amplified for further analysis.
9. Cardiac parameters of interest
1. Heart Rate (HR): it reflects the complete heart beat from its generation to the beginning
of the next beat expressed in Beats Per Minute (bpm).
2. Inter-Beat Interval (IBI): time interval between the individual beats of the heart,
generally expressed in milliseconds (ms).
3. Heart Rate Variability (HRV): it expresses the variation of IBI from beat to beat. HRV
varies widely at times of stress, emotions etc.
10. Electroencephalogram (EEG)
- Potential : due to postsynaptic current
- Used for diagnosis of neurological disorder or tumour
- 25 scalp electrodes system (10-20 montage system):
23 active, 1 ref, 1 ground : Cerebral Cortex
- Two types of potential : 10-100 mV
1) Between Active Electrodes
2) Between Active & Ref Electrodes
- Evoked Potentials :V, A, S, M types
14. Focus for Review: 2
• Acquiring Myo-Ware Sensor: EMG
• Interfacing with Arduino
• Signal processing of EMG in Matlab
• Implementation of controlling motor with EMG sensor