The document compares the human brain to a computer CPU. It notes that while the brain and CPU both process information, their construction and methods of information storage and processing differ. The brain is self-organizing and can correct errors, while computers require external maintenance. The document also discusses neural signal transmission and brain imaging techniques like EEG. It describes how robotic prosthetics and other engineering solutions assist with conditions like Parkinson's disease.
The mind-to-movement system that allows a quadriplegic man to control a computer using only his thoughts is a scientific milestone. It was reached, in large part, through the brain gate system. This system has become a boon to the paralyzed. The Brain Gate System is based on Cyber kinetics platform technology to sense, transmit, analyze and apply the language of neurons. The principle of operation behind the Brain Gate System is that with intact brain function, brain signals are generated even though they are not sent to the arms, hands and legs.The signals are interpreted and translated into cursor movements, offering the user an alternate Brain Gate pathway to control a computer with thought,just as individuals who have the ability to move their hands use a mouse. The 'Brain Gate' contains tiny spikes that will extend down about one millimetre into the brain after being implanted beneath the skull,monitoring the activity from a small group of neurons.It will now be possible for a patient with spinal cord injury to produce brain signals that relay the intention of moving the paralyzed limbs,as signals to an implanted sensor,which is then output as electronic impulses. These impulses enable the user to operate mechanical devices with the help of a computer cursor. Matthew Nagle,a 25-year-old Massachusetts man with a severe spinal cord injury,has been paralyzed from the neck down since 2001.After taking part in a clinical trial of this system,he has opened e-mail,switched TV channels,turned on lights
This slide is about the basic theories of Neurotechnology.
It shows
1. An overview of this area
- Market value, etc
2. Basic knowledge
- Types of neurotechnologies
- Basics of neuroscience
- software engineering.
3. Use cases with neurotechnologies.
This document summarizes brain implants, which connect directly to the brain to electrically stimulate, block, or record neural signals. It discusses the history of brain implants dating back to 1870 experiments stimulating a dog's brain. Modern brain implants are used for various purposes like treating depression, seizures, epilepsy, Parkinson's, and restoring functions like hearing, vision, and motion. While brain implants provide advantages like aiding research and restoring functions, they also involve risks like surgery complications and limitations in technology. The document concludes that brain implants may enhance capabilities but are not a permanent solution and will expire at the end of a person's life.
Brain Computer Interface for User Recognition And Smart Home ControlIJTET Journal
This project discussed about a brain controlled biometric based on Brain–computer interfaces (BCI). BCIs are systems that can bypass conventional channels of communication (i.e., muscles and thoughts) to provide direct communication and control between the human brain and physical devices by translating different patterns of brain activity into commands in real time. With these commands a biometric technology can be controlled. The intention of the project work is to develop a user recognition machine that can assist the work independent on others. Here, we are analyzing the brain wave signals. Human brain consists of millions of interconnected neurons. The patterns of interaction between these neurons are represented as thoughts and emotional states. According to the human thoughts, this pattern will be changing which in turn produce different electrical waves. A muscle contraction will also generate a unique electrical signal. All these electrical waves will be sensed by the brain wave sensor and it will convert the data into packets and transmit through Bluetooth medium. Level analyzer unit (LAU) will receive the brain wave raw data and it will extract and process the signal using Mat lab platform. Then the control commands will be transmitted to the robotic module to process. With this entire system, we can operate the home application according to the human thoughts and it can be turned by blink muscle contraction.
Brain-computer interfaces (BCIs) acquire brain signals, analyze them, and translate them into commands to control devices. BCIs do not use normal motor pathways. The goal is to restore function for people with disabilities. Early BCIs demonstrated spelling and device control using EEG and single neuron signals. Current BCIs can control cursors, robotic arms, wheelchairs using EEG, ECoG, and intracortical signals. Future advances depend on improved signal acquisition, validation of BCIs for real-world use, and improved reliability approaching natural function.
Neurobionics and robotic neurorehabilitationsNeurologyKota
This document discusses neurobionics, robotic neurorehabilitation, and applications of neurobionics. It summarizes key areas including: (1) neurobionics aims to integrate electronics with the nervous system to repair or substitute impaired functions, (2) robotic neurorehabilitation uses robots to assist in rehabilitation processes, and (3) applications of neurobionics include motor interfaces like robotic arms, sensory interfaces like cochlear implants, and treating conditions like epilepsy and Parkinson's disease.
Neuroprosthetics are devices that detect and translate neural activity into commands for computers and prosthetics. They have the potential to help people with motor impairments by allowing thought-controlled prosthetic limbs or devices. Current neuroprosthetics include brain-computer interfaces that can control prosthetic arms or cursors on screens. Future neuroprosthetics may allow for fully functioning prosthetic limbs controlled by neural signals as well as treatments for conditions like paralysis, ALS, and multiple sclerosis. Research is ongoing to improve device function, biocompatibility, and restoration of natural motor control.
This document describes a brain-controlled robot system using EEG signals. The system uses EEG electrodes placed on the scalp to measure brain wave activity. Different patterns of brain waves can be translated into commands to control a mobile robot in real time. The goal is to develop a robot that can assist disabled people and allow them to move independently without physical movement. The system works by analyzing EEG signals through techniques like fast Fourier transforms to separate different brain wave frequencies associated with different mental states and intentions. This allows the user to think of commands to direct the robot's movement. The system aims to improve quality of life for people with disabilities.
The mind-to-movement system that allows a quadriplegic man to control a computer using only his thoughts is a scientific milestone. It was reached, in large part, through the brain gate system. This system has become a boon to the paralyzed. The Brain Gate System is based on Cyber kinetics platform technology to sense, transmit, analyze and apply the language of neurons. The principle of operation behind the Brain Gate System is that with intact brain function, brain signals are generated even though they are not sent to the arms, hands and legs.The signals are interpreted and translated into cursor movements, offering the user an alternate Brain Gate pathway to control a computer with thought,just as individuals who have the ability to move their hands use a mouse. The 'Brain Gate' contains tiny spikes that will extend down about one millimetre into the brain after being implanted beneath the skull,monitoring the activity from a small group of neurons.It will now be possible for a patient with spinal cord injury to produce brain signals that relay the intention of moving the paralyzed limbs,as signals to an implanted sensor,which is then output as electronic impulses. These impulses enable the user to operate mechanical devices with the help of a computer cursor. Matthew Nagle,a 25-year-old Massachusetts man with a severe spinal cord injury,has been paralyzed from the neck down since 2001.After taking part in a clinical trial of this system,he has opened e-mail,switched TV channels,turned on lights
This slide is about the basic theories of Neurotechnology.
It shows
1. An overview of this area
- Market value, etc
2. Basic knowledge
- Types of neurotechnologies
- Basics of neuroscience
- software engineering.
3. Use cases with neurotechnologies.
This document summarizes brain implants, which connect directly to the brain to electrically stimulate, block, or record neural signals. It discusses the history of brain implants dating back to 1870 experiments stimulating a dog's brain. Modern brain implants are used for various purposes like treating depression, seizures, epilepsy, Parkinson's, and restoring functions like hearing, vision, and motion. While brain implants provide advantages like aiding research and restoring functions, they also involve risks like surgery complications and limitations in technology. The document concludes that brain implants may enhance capabilities but are not a permanent solution and will expire at the end of a person's life.
Brain Computer Interface for User Recognition And Smart Home ControlIJTET Journal
This project discussed about a brain controlled biometric based on Brain–computer interfaces (BCI). BCIs are systems that can bypass conventional channels of communication (i.e., muscles and thoughts) to provide direct communication and control between the human brain and physical devices by translating different patterns of brain activity into commands in real time. With these commands a biometric technology can be controlled. The intention of the project work is to develop a user recognition machine that can assist the work independent on others. Here, we are analyzing the brain wave signals. Human brain consists of millions of interconnected neurons. The patterns of interaction between these neurons are represented as thoughts and emotional states. According to the human thoughts, this pattern will be changing which in turn produce different electrical waves. A muscle contraction will also generate a unique electrical signal. All these electrical waves will be sensed by the brain wave sensor and it will convert the data into packets and transmit through Bluetooth medium. Level analyzer unit (LAU) will receive the brain wave raw data and it will extract and process the signal using Mat lab platform. Then the control commands will be transmitted to the robotic module to process. With this entire system, we can operate the home application according to the human thoughts and it can be turned by blink muscle contraction.
Brain-computer interfaces (BCIs) acquire brain signals, analyze them, and translate them into commands to control devices. BCIs do not use normal motor pathways. The goal is to restore function for people with disabilities. Early BCIs demonstrated spelling and device control using EEG and single neuron signals. Current BCIs can control cursors, robotic arms, wheelchairs using EEG, ECoG, and intracortical signals. Future advances depend on improved signal acquisition, validation of BCIs for real-world use, and improved reliability approaching natural function.
Neurobionics and robotic neurorehabilitationsNeurologyKota
This document discusses neurobionics, robotic neurorehabilitation, and applications of neurobionics. It summarizes key areas including: (1) neurobionics aims to integrate electronics with the nervous system to repair or substitute impaired functions, (2) robotic neurorehabilitation uses robots to assist in rehabilitation processes, and (3) applications of neurobionics include motor interfaces like robotic arms, sensory interfaces like cochlear implants, and treating conditions like epilepsy and Parkinson's disease.
Neuroprosthetics are devices that detect and translate neural activity into commands for computers and prosthetics. They have the potential to help people with motor impairments by allowing thought-controlled prosthetic limbs or devices. Current neuroprosthetics include brain-computer interfaces that can control prosthetic arms or cursors on screens. Future neuroprosthetics may allow for fully functioning prosthetic limbs controlled by neural signals as well as treatments for conditions like paralysis, ALS, and multiple sclerosis. Research is ongoing to improve device function, biocompatibility, and restoration of natural motor control.
This document describes a brain-controlled robot system using EEG signals. The system uses EEG electrodes placed on the scalp to measure brain wave activity. Different patterns of brain waves can be translated into commands to control a mobile robot in real time. The goal is to develop a robot that can assist disabled people and allow them to move independently without physical movement. The system works by analyzing EEG signals through techniques like fast Fourier transforms to separate different brain wave frequencies associated with different mental states and intentions. This allows the user to think of commands to direct the robot's movement. The system aims to improve quality of life for people with disabilities.
The document summarizes a seminar report on Brain Gates. It describes how Brain Gates were developed by Cyberkinetics in 2003 to help people with disabilities control devices using only their brain activity. The Brain Gate system consists of a sensor implanted in the motor cortex that detects brain signals, which are then translated by a computer into cursor movements or control of other devices. Currently two patients have been implanted with Brain Gates, which use 100 electrodes to monitor brain activity related to intended limb movements and allow control of a computer cursor.
This presentation shows the detail knowledge about EEG. It contains slides with animation. You can build your own concept to explain the slide.
Best view in 16:9 ratio.
The Brain Gate system allows paralyzed individuals to control external devices like computers and prosthetics using only their brain activity. Tiny sensors are implanted in the brain to detect neural signals, which are then translated into commands to move a computer cursor or robotic limb. In clinical trials, one patient with a spinal cord injury was able to open emails, control his TV, and move a prosthetic hand just by thinking. This system provides an alternative pathway for communication and control for those who have lost physical function due to injury or disease.
The document discusses BrainGate technology, which involves implanting a neuroprosthetic device into the brain that can detect brain signals and convert them into computer commands. It describes how BrainGate was developed in 2003 and involves implanting an electrode array on the motor cortex. The underlying principle is that intact brain function generates neural signals even if they can't be sent to the limbs. It explains how the device works by sending brain activity data through wires to a computer for processing and allows paralyzed individuals to control external devices with their thoughts.
BCI provides direct communication between the brain and external devices. It extracts electro-physical signals from the brain and processes them to generate control signals. This allows devices to be controlled by thought alone and has applications in assisting those with disabilities or improving performance. Key challenges include interpreting complex neural signals originating from billions of neurons and developing biocompatible probes and neural interfaces.
One-day system authentication could be widely achieved through brainwaves. One doesn’t need to remember that 8 or more character long strange password. Simply thinking of certain things, such as a person face, or a rotating displayed cube, or line of song would be enough to unlock a device. Electro-encephalography (EEC) sensors are behind the technique. That is where electrical activity in certain parts of the brain is recorded. These sensors are used to generate the graphical lines on charts created from wired electrodes placed on the scalp, as seen in hospitals and TV shows. They are used in hospital to diagnose epilepsy, among other things. In this case, though, one wouldn’t need to be fitted with wired electrodes —or even a headset, which is used already in some current non-muscular EEC computer controls. An ear bud will collect the signals (mental gesture) and perform secure authentication. This research could provide hands-free and wireless interaction, authentication, and user experience, all in the form-factor of a typical ear bud.
The document discusses brain-machine interfaces (BMI). It begins with an introduction to BMI, explaining that it allows communication between the brain and machines by collecting, interpreting, and outputting commands based on brain signals. It then provides details on brain structure and function, how EEG is used to detect electrical signals in the brain, applications of BMI like restoring motor function, and current BMI projects. It concludes that BMI is an advancing technology with potential therapeutic benefits and high technological impact.
The document discusses the Blue Brain project, which aims to create a virtual human brain through supercomputer-based digital reconstruction and simulation. It seeks to upload the complete information from a human brain into a computer in order to preserve knowledge and intelligence even after death. The project involves creating software to integrate building and simulating digital brain models, as well as systematically searching for basic brain principles and behaviors. A comparison is provided between natural human brains and simulated virtual brains in terms of input, interpretation, output, memory, and processing.
This document provides an overview of several human organ systems and how they can be analyzed from an engineering perspective. It discusses the brain and how it functions similarly to a CPU system, processing information via electrical signals. It also discusses the eye and how it functions similarly to a camera system, with components like a lens, retina, and photoreceptors that allow images to be focused and sensed. Additionally, it discusses the heart and how it functions as a pump system, with electrical signaling and applications of devices like pacemakers.
The document provides information about the BrainGate system, which is a neuroprosthetic device that allows users to control external devices like computers with their brain activity. It consists of a sensor implanted on the motor cortex of the brain that detects electrical signals associated with movement planning. These signals are transmitted to a computer system via a connector on the skull. The computer analyzes the brain signals and translates them into commands to control a computer cursor or other devices. This provides a "BrainGate pathway" for users who have lost limb function to control devices with their thoughts. The system was developed by Cyberkinetics to help paralyzed individuals and represents an early application of brain-computer interface technology.
Neuroprosthetics involves using brain signals acquired from neurons for various purposes like restoring movement in paralyzed patients. Nanotechnology like nano multi-electrode arrays can be used to receive and transmit brain signals more effectively by increasing electrode conduction and reducing incorrect connections with neurons. Neuroprosthetics has applications in both in vivo and in vitro contexts and can help improve functions like movement, speech, and understanding of drug effects on animal behavior and emotions.
This document discusses Brain-Computer Interfaces (BCI) which allow direct communication between the brain and external devices. It focuses on the BrainGate technology, which involves implanting a small chip in the motor cortex to detect brain signals and translate them to control computers or prosthetics. The BrainGate system has been tested on humans to allow paralyzed patients to control devices and interact digitally just by thinking.
Brain Computer Interface (BCI) aims at providing an alternate means of communication and control to people with severe cognitive or sensory-motor disabilities. These systems are based on the single trial recognition of different mental states or tasks from the brain activity. This paper discusses the major components involved in developing a Brain Computer Interface system which includes the modality to obtain brain signals and its related processing methods.
Brain gate technology allows people to control external devices like computers and robotic limbs using only their brain signals. It involves implanting a microchip in the motor cortex of the brain that detects neural activity and transmits it via wires to a computer for translation into device commands. While promising for restoring function to paralyzed individuals, it requires invasive brain surgery and users must undergo training to learn how to produce distinct brain patterns to control different devices. Current research focuses on developing smaller, wireless versions of the technology.
IRJET- Precision of Lead-Point with Support Vector Machine based Microelectro...IRJET Journal
This document discusses using microelectrode recordings (MER) with support vector machine learning to study the function of subthalamic nucleus (STN) neurons in the human brain during deep brain stimulation for Parkinson's disease. The study aims to improve the signal-to-noise ratio of MER signals and precisely identify the location of the STN to ensure safety and efficacy of deep brain stimulation chip implantation. MER is found to confirm the presence of abnormal STN neurons and clear positioning of the microchip electrode in the target area. Access to functional data from neurons deep in the brain using MER may help further elucidate cryptic aspects of brain function.
The document discusses Brain Gate, which is an electrode chip that can be implanted in the brain to allow communication between brain signals and external devices. It works by detecting electrical signals from the brain during imagined movements and transmitting them to decoding software. The goal is to provide paralyzed patients with computer and device control through thought alone. Early successful tests were conducted with monkeys and then humans. While promising, challenges remain around improving information transfer rates, adaptation, and reducing costs.
Brain Computer Interface (BCI) - seminar PPTSHAMJITH KM
This document discusses brain computer interfaces (BCI). It begins by providing background on early pioneers in the field like Hans Berger in the 1920s-1950s. It then discusses some key BCI developments from the 1990s to present day, including devices that allow paralyzed individuals to control prosthetics or computers using brain signals. The document outlines the basic hardware and principles of how BCIs work by interpreting brain signals to control external devices. It discusses potential applications like internet browsing, gaming, or prosthetic limb control. The benefits and disadvantages of BCIs are noted, and the future possibilities of using BCIs to enhance human abilities are explored.
This document discusses brain-machine interfaces (BMI). A BMI establishes a communication link between the brain and external devices. Signals from the brain are detected via implants and transformed to control signals. There are invasive, partially invasive and non-invasive BMI approaches. A typical BMI system includes implant devices to detect brain signals, signal processing to analyze the signals, an external device to be controlled, and feedback. Potential applications include assisting people with disabilities and developing prosthetics. However, BMIs also face challenges regarding signal detection and processing.
This document summarizes a research paper on controlling a mobile robot using brain waves (EEG) detected by an electrode cap worn by the user. It discusses how EEG signals are analyzed to extract features related to different mental tasks. Machine learning classifiers are then used to translate the EEG features into commands to control the robot in real-time. The goal is to develop a system that can assist disabled people by controlling devices independently using only their brain activity.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
The document summarizes a seminar report on Brain Gates. It describes how Brain Gates were developed by Cyberkinetics in 2003 to help people with disabilities control devices using only their brain activity. The Brain Gate system consists of a sensor implanted in the motor cortex that detects brain signals, which are then translated by a computer into cursor movements or control of other devices. Currently two patients have been implanted with Brain Gates, which use 100 electrodes to monitor brain activity related to intended limb movements and allow control of a computer cursor.
This presentation shows the detail knowledge about EEG. It contains slides with animation. You can build your own concept to explain the slide.
Best view in 16:9 ratio.
The Brain Gate system allows paralyzed individuals to control external devices like computers and prosthetics using only their brain activity. Tiny sensors are implanted in the brain to detect neural signals, which are then translated into commands to move a computer cursor or robotic limb. In clinical trials, one patient with a spinal cord injury was able to open emails, control his TV, and move a prosthetic hand just by thinking. This system provides an alternative pathway for communication and control for those who have lost physical function due to injury or disease.
The document discusses BrainGate technology, which involves implanting a neuroprosthetic device into the brain that can detect brain signals and convert them into computer commands. It describes how BrainGate was developed in 2003 and involves implanting an electrode array on the motor cortex. The underlying principle is that intact brain function generates neural signals even if they can't be sent to the limbs. It explains how the device works by sending brain activity data through wires to a computer for processing and allows paralyzed individuals to control external devices with their thoughts.
BCI provides direct communication between the brain and external devices. It extracts electro-physical signals from the brain and processes them to generate control signals. This allows devices to be controlled by thought alone and has applications in assisting those with disabilities or improving performance. Key challenges include interpreting complex neural signals originating from billions of neurons and developing biocompatible probes and neural interfaces.
One-day system authentication could be widely achieved through brainwaves. One doesn’t need to remember that 8 or more character long strange password. Simply thinking of certain things, such as a person face, or a rotating displayed cube, or line of song would be enough to unlock a device. Electro-encephalography (EEC) sensors are behind the technique. That is where electrical activity in certain parts of the brain is recorded. These sensors are used to generate the graphical lines on charts created from wired electrodes placed on the scalp, as seen in hospitals and TV shows. They are used in hospital to diagnose epilepsy, among other things. In this case, though, one wouldn’t need to be fitted with wired electrodes —or even a headset, which is used already in some current non-muscular EEC computer controls. An ear bud will collect the signals (mental gesture) and perform secure authentication. This research could provide hands-free and wireless interaction, authentication, and user experience, all in the form-factor of a typical ear bud.
The document discusses brain-machine interfaces (BMI). It begins with an introduction to BMI, explaining that it allows communication between the brain and machines by collecting, interpreting, and outputting commands based on brain signals. It then provides details on brain structure and function, how EEG is used to detect electrical signals in the brain, applications of BMI like restoring motor function, and current BMI projects. It concludes that BMI is an advancing technology with potential therapeutic benefits and high technological impact.
The document discusses the Blue Brain project, which aims to create a virtual human brain through supercomputer-based digital reconstruction and simulation. It seeks to upload the complete information from a human brain into a computer in order to preserve knowledge and intelligence even after death. The project involves creating software to integrate building and simulating digital brain models, as well as systematically searching for basic brain principles and behaviors. A comparison is provided between natural human brains and simulated virtual brains in terms of input, interpretation, output, memory, and processing.
This document provides an overview of several human organ systems and how they can be analyzed from an engineering perspective. It discusses the brain and how it functions similarly to a CPU system, processing information via electrical signals. It also discusses the eye and how it functions similarly to a camera system, with components like a lens, retina, and photoreceptors that allow images to be focused and sensed. Additionally, it discusses the heart and how it functions as a pump system, with electrical signaling and applications of devices like pacemakers.
The document provides information about the BrainGate system, which is a neuroprosthetic device that allows users to control external devices like computers with their brain activity. It consists of a sensor implanted on the motor cortex of the brain that detects electrical signals associated with movement planning. These signals are transmitted to a computer system via a connector on the skull. The computer analyzes the brain signals and translates them into commands to control a computer cursor or other devices. This provides a "BrainGate pathway" for users who have lost limb function to control devices with their thoughts. The system was developed by Cyberkinetics to help paralyzed individuals and represents an early application of brain-computer interface technology.
Neuroprosthetics involves using brain signals acquired from neurons for various purposes like restoring movement in paralyzed patients. Nanotechnology like nano multi-electrode arrays can be used to receive and transmit brain signals more effectively by increasing electrode conduction and reducing incorrect connections with neurons. Neuroprosthetics has applications in both in vivo and in vitro contexts and can help improve functions like movement, speech, and understanding of drug effects on animal behavior and emotions.
This document discusses Brain-Computer Interfaces (BCI) which allow direct communication between the brain and external devices. It focuses on the BrainGate technology, which involves implanting a small chip in the motor cortex to detect brain signals and translate them to control computers or prosthetics. The BrainGate system has been tested on humans to allow paralyzed patients to control devices and interact digitally just by thinking.
Brain Computer Interface (BCI) aims at providing an alternate means of communication and control to people with severe cognitive or sensory-motor disabilities. These systems are based on the single trial recognition of different mental states or tasks from the brain activity. This paper discusses the major components involved in developing a Brain Computer Interface system which includes the modality to obtain brain signals and its related processing methods.
Brain gate technology allows people to control external devices like computers and robotic limbs using only their brain signals. It involves implanting a microchip in the motor cortex of the brain that detects neural activity and transmits it via wires to a computer for translation into device commands. While promising for restoring function to paralyzed individuals, it requires invasive brain surgery and users must undergo training to learn how to produce distinct brain patterns to control different devices. Current research focuses on developing smaller, wireless versions of the technology.
IRJET- Precision of Lead-Point with Support Vector Machine based Microelectro...IRJET Journal
This document discusses using microelectrode recordings (MER) with support vector machine learning to study the function of subthalamic nucleus (STN) neurons in the human brain during deep brain stimulation for Parkinson's disease. The study aims to improve the signal-to-noise ratio of MER signals and precisely identify the location of the STN to ensure safety and efficacy of deep brain stimulation chip implantation. MER is found to confirm the presence of abnormal STN neurons and clear positioning of the microchip electrode in the target area. Access to functional data from neurons deep in the brain using MER may help further elucidate cryptic aspects of brain function.
The document discusses Brain Gate, which is an electrode chip that can be implanted in the brain to allow communication between brain signals and external devices. It works by detecting electrical signals from the brain during imagined movements and transmitting them to decoding software. The goal is to provide paralyzed patients with computer and device control through thought alone. Early successful tests were conducted with monkeys and then humans. While promising, challenges remain around improving information transfer rates, adaptation, and reducing costs.
Brain Computer Interface (BCI) - seminar PPTSHAMJITH KM
This document discusses brain computer interfaces (BCI). It begins by providing background on early pioneers in the field like Hans Berger in the 1920s-1950s. It then discusses some key BCI developments from the 1990s to present day, including devices that allow paralyzed individuals to control prosthetics or computers using brain signals. The document outlines the basic hardware and principles of how BCIs work by interpreting brain signals to control external devices. It discusses potential applications like internet browsing, gaming, or prosthetic limb control. The benefits and disadvantages of BCIs are noted, and the future possibilities of using BCIs to enhance human abilities are explored.
This document discusses brain-machine interfaces (BMI). A BMI establishes a communication link between the brain and external devices. Signals from the brain are detected via implants and transformed to control signals. There are invasive, partially invasive and non-invasive BMI approaches. A typical BMI system includes implant devices to detect brain signals, signal processing to analyze the signals, an external device to be controlled, and feedback. Potential applications include assisting people with disabilities and developing prosthetics. However, BMIs also face challenges regarding signal detection and processing.
This document summarizes a research paper on controlling a mobile robot using brain waves (EEG) detected by an electrode cap worn by the user. It discusses how EEG signals are analyzed to extract features related to different mental tasks. Machine learning classifiers are then used to translate the EEG features into commands to control the robot in real-time. The goal is to develop a system that can assist disabled people by controlling devices independently using only their brain activity.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSIJNSA Journal
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
Slides from talk presenting:
Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, Serbia
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
3. 3
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
2.1 Brain as a CPU System
Brain is highly sophisticated & complex information processing system, similar to a CPU.
Both Brain & CPU receive & process inputs, store information & perform calculations to
produce outputs.
Way of storing & processing of information in both of them are different.
4. 4
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Comparison Chart
Basis for Comparison Brain Computer
Construction Neurons & synapses ICs, transistors, diodes,
capacitors, transistors, etc.
Memory growth Increases each time by
connecting synaptic links
Increases by adding more
memory chips
Backup systems Built-in backup system Backup system is constructed
Manually
Memory power 100 teraflops (100 trillion
calculations/seconds)
100 million megabytes
Memory density 107 circuits/cm3 1014 bits/cm3
Energy consumption 12 watts Gigawatts
Information storage Stored in electrochemical &
electric impulses.
Stored in numeric & symbolic
form (binary bits).
5. 5
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Comparison Chart continued
Basis for Comparison Brain Computer
Size and weight Volume = 1500 cm3 &
weight ≈ 3.3 pounds.
Variable weight and size form
few grams to tons.
Transmission of
information
Uses chemicals to fire the
action potential in the neurons.
Communication is achieved
through electrical coded
signals.
Information processing
power
Low High
Input/output equipment Sensory organs Keyboards, mouse, web
cameras, etc.
Structural organization Self-organized Pre-programmed structure
Parallelism Massive Limited
Reliability and damageability
Properties
Brain is self-organizing, self
maintaining
and reliable.
Computers perform a
monotonous job and can't
correct itself.
7. 7
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Prefrontal Cortex functions as similar to ALU.
Higher-level cognitive functions such as decision making & problem solving are identified by prefrontal
cortex.
Information is stored in memory units of CPU.
Human brain has several regions dedicated to memory storage, including the hippocampus & amygdala.
8. 8
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
CNS (Central Nervous System ) and PNS (Peripheral Nervous System)
9. 9
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Central Nervous System
• Consists of brain & spinal cord
• Receives, processes & integrates
sensory information and transmit
commands to the rest of the body.
• Brain acts as the command center,
receives & processes sensory inputs
and generates motor outputs.
• Spinal cord acts as a relay center,
transmitting information between the
brain and peripheral nerves.
Peripheral Nervous
System
• Located outside the brain and spinal
cord
• Transmits sensory information from
the periphery of the body (such as the
skin, muscles & organs) to the CNS,
and transmits commands from the
CNS to the periphery.
• PNS can be further divided into the
somatic nervous system (Voluntary
movements) and the autonomic
nervous system (Involuntary i.e
heart rate, digestion, respiration)
10. 10
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Signal Transmission
Occurs through the firing of nerve cells or neurons
known as Synaptic transmission.
Information transferred through Dendrites by
generating electric impulse down to Axons & Synaptic
terminals.
Postsynaptic neurons & the balance of
neurotransmitter levels can influence brain
function, including mood, learning & memory.
Influenced by various forms of synaptic plasticity,
including Long-term Potentiation (LTP) and
Long-term Depression (LTD).
12. 12
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
EEG (Electro Encephalo Graphy)
Non-invasive method for measuring the electrical activity of the brain.
Records the electrical signals generated by the brain‘s neurons as they communicate with each other.
Signals are recorded through electrodes placed on the scalp and the resulting EEG pattern provides
information about the synchronized electrical activity of large population of neurons
13. 13
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
EEG Applications
Diagnosis of Epilepsy (Abnornal activity in brain)
Sleep Studies (Sleep Pattern)
Brain-Computer Interfaces (BCI) {Prosthetics Limbs}
Research on Brain Function (Reading, Problem-Solving)
Diagnosis of Brain Disorders (Dementia,Parkinson’s Dis., Traumatic brain injury)
Anesthesia Monitoring (During Surgery- Safe and Comfortable state)
Monitoring Brain Activity during Coma (Level of brain function)
15. 15
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Robotic Arms for Prosthetics
Advanced prosthetic devices use robotics technology
to restore functionality of individuals with upper limb
amputations.
Consists of motors, actuators & sensors to mimic
the movements of a human arm & hand, allowing the
wearer to perform tasks such as reaching, grasping &
manipulating objects.
Direct control through muscle signals (myoelectric
control) or brain-machine interfaces, which use
electrodes implanted in the brain or placed on the
scalp to detect and interpret brain activity.
16. 16
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Robotic Arm Prosthetic Direct Control through Muscle Signals (Myoelectric Control)
Electrical signals generated by the wearer's remaining muscles control the movement of the prosthetic.
Electrodes placed on the skin over the remaining muscle are used to detect & interpret the electrical signals
generated by the muscle contractions.
Advantage of being directly controlled by the user, allowing for a more intuitive & natural interaction with
the prosthetic.
High level of control & precision, as the electrical signals are unique to each individual perform a wide range of
movements.
17. 17
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Myoelectric control systems can be complex and may require extensive rehabilitation and
training to use effectively.
Maintenance needed to ensure proper function.
Additionally, the system may not be suitable for individuals with muscle weakness or other
conditions that affect the ability to generate strong electrical signals.
18. 18
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Robotic Arm Prosthetic by Brain-Machine Interfaces (BMI)
19. 19
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Robotic Arm Prosthetic by Brain-Machine Interfaces (BMI) cont.
A technology that allows user to control a robotic
arm prosthetic directly with their brain activity.
Electrodes are placed on the scalp to detect user's
brain signals.
When the user thinks about moving the prosthetic
arm,
Brain activity is detected & signals are sent to a
control unit, which uses algorithms to interpret the
signals & control the movement of the prosthetic.
User can control the movement of the prosthetic in
real-time by thinking about the desired movement.
20. 20
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Robotic Arm Prosthetic by Brain-Machine Interfaces (BMI) cont.
Advantage of providing a direct & intuitive connection between
the user's brain & the prosthetic.
High level of control and precision.
Sensory feedback to the user, to experience the sensation of
touch.
BMIs can be complex & invasive systems, require surgical
implantation & ongoing maintenance to ensure proper function.
Unsuitable for individuals with conditions that affect brain
activity or unable to generate strong enough brain signals to
control the prosthetic effectively.
Ongoing research & development is aimed at improving the
performance & accessibility of BMIs, as well as increasing their
ease of use and reliability.
21. 21
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Engineering Solutions for Parkinson’s Disease
Neurodegenerative disorder that affects movement & motor
function.
Several engineering solutions aimed at improving the quality of life.
Deep Brain Stimulation (DBS): involves the implantation of
electrodes into specific regions of the brain to deliver electrical
stimulation which help to relieve tremors, stiffness & difficulty with
movement.
Exoskeletons: wearable devices that provide support & assistance
for individuals with mobility issues to improve balance, reduce
tremors & increase overall mobility.
Telerehabilitation: telecommunication technology to provide
physical therapy & rehabilitation services to individuals.
22. 22
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Smartwatch Applications: monitor symptoms of Parkinson's disease, such as tremors & provide
reminders and prompts for medication & exercise.
Virtual Reality: Rehabilitation and therapy for individuals with Parkinson's disease, providing
interactive and engaging environments for patients to practice movements, improve
coordination and balance.
Technologies are not a cure for Parkinson's disease and should be used in conjunction with other
forms of treatment and care.
23. 23
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Artificial Brain
Known as an Artificial General Intelligence (AGI) or a
synthetic brain.
Hypothetical machine with cognitive abilities similar to
those of a human brain
Machine that can learn, reason & solve problems in the
same way that humans do.
Technical, ethical & philosophical challenges need to be
addressed.
Artificial Intelligence (AI) systems are designed to
perform specific tasks such as image recognition, speech
recognition or decision making.
Exciting and rapidly advancing field of research that has the
potential to change the world in many ways
25. 25
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
• Both the eye and a camera capture light and convert it into an image.
Main components of the eye
•Cornea: Transparent outer layer of the eye functions like a camera lens,
bending light to focus it onto the retina.
•Iris: Diaphragm in a camera, controlling the amount of light that enters
the eye.
•Pupil: Aperture in a camera, adjusting the size to control the amount of
light entering the eye.
•Retina: Camera film or sensor, capturing the light and converting it into
electrical signals that are sent to the brain.
•Optic Nerve: Cable connecting the camera to a computer, transmitting
the electrical signals from the retina to the brain.
27. 27
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
In both the eye and a camera, the captured light is transformed into an
image by the lens and the light-sensitive component.
The eye processes the image further, allowing for visual perception,
while a camera stores the image for later use.
Eye is much more complex than a camera and has several additional
functions, such as adjusting for different levels of light and adjusting focus,
that are not found in a camera.
Ability to perceive depth and color, as well as adjust to movements and
provide a continuous, real-time image to the brain.
28. 28
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Architecture of Rod and Cone Cells
Rod Cells
•Photoreceptor cells in the retina of the eye
that are responsible for detecting light and
transmitting signals to the brain for the
perception of vision, especially in low
light conditions.
•Contain a protein called rhodopsin that
absorbs light and triggers a chain of events
leading to the activation of neural signals.
• Rods are more sensitive to light than
cone cells but do not distinguish color as
well.
29. 29
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Cone Cells
•Photoreceptor cells in the retina of the eye that are responsible for color
vision and visual acuity (sharpness of vision).
•Three types of cone cells, each containing a different photopigment
sensitive to different wavelengths of light (red, green, and blue), which
allow for the perception of color.
•Cones are less sensitive to light than rod cells but provide better visual
acuity and color discrimination.
•They are concentrated in the fovea, the central part of the retina
responsible for detailed and sharp vision.
30. 30
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Architecture
• Rod and cone cells have a similar basic
structure, but there are some differences that are
crucial for their different functions.
• Both types of cells have a photoreceptor outer
segment that contains the photopigment
(rhodopsin in rods and photopigments in cones)
that absorbs light and triggers a change in
membrane potential.
• Inner segment contains the cell's organelles,
including the nucleus and mitochondria.
31. 31
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Major difference between rod and cone cells is their
shape.
Rod cells are elongated and cylindrical, while cone
cells are shorter and more conical in shape.
This difference in shape affects the distribution of
photopigments and the number of synaptic contacts
with bipolar and ganglion cells, which transmit the
signals to the brain.
Rod cells have a single long outer segment, while
cone cells have several shorter segments.
Rod cells make synapses with one bipolar cell, while
cone cells synapse with one of several bipolar cells
32. 32
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Optical Corrections
• Devices or techniques used to improve or correct vision problems caused
by a refractive error in the eye.
• Refractive errors occur when light entering the eye is not properly
focused on the retina, leading to blurred vision. There are several types of
refractive errors,
1) Myopia (nearsightedness): Light is focused in front of the retina,
making distant objects appear blurry.
2) Hyperopia (farsightedness): Light is focused behind the retina, making
near objects appear blurry.
3) Astigmatism: Light is not focused evenly on the retina, leading to
blurred or distorted vision.
33. 33
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Most common optical corrections include:
• Eyeglasses: Glasses with corrective lenses can be used to refocus light onto the
retina, improving vision.
• Contact lenses: Corrective lenses in the form of contacts sit directly on the cornea
and work similarly to eyeglasses.
• Refractive surgery: Surgicals LASIK (Laser-Assisted In Situ Keratomileusis) and
PRK (Photorefractive keratectomy), can reshape the cornea to correct refractive
errors.
Optical corrections can greatly improve visual acuity and quality of life for people
with refractive errors. However, it is important to have regular eye exams to
determine the appropriate correction and monitor eye health.
34. 34
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Cataract
• Clouding of the lens of the eye that
affects vision.
•The lens, located behind the iris and
pupil, normally allows light to pass
through to the retina and produces
clear, sharp images.
• However, as we age or due to other
factors, the proteins in the lens can
clump together and cause the lens to
become opaque, leading to vision
problems.
35. 35
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
• Symptoms of a cataract include blurred or hazy vision, increased sensitivity to
glare and bright lights, faded or yellowed colors, and double vision in one eye.
• Cataracts can also cause frequent changes in prescription for eyeglasses or
contacts.
• Cataract surgery is a common and safe procedure to remove the cloudy lens
and replace it with an artificial lens.
• Most people experience improved vision within a few days after the procedure.
• Regular eye exams can help detect cataracts early and prevent vision loss.
36. 36
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Lens Materials
Most common lens materials (Each with its own unique properties and benefits)
• Polymethyl methacrylate (PMMA): Plastic that has been used for many years in
artificial lenses. It is a durable and affordable material, but does not have the ability
to flex and adjust focus like the natural lens.
• Silicone: Soft, flexible material that is resistant to cracking and breaking.
• Acrylic: Acrylic is a lightweight, clear material that is similar in properties to
PMMA. It is often used in foldable (intraocular lenses) IOLs, which can be inserted
through a smaller incision.
• Hydrophobic acrylic: Acrylic material that has a special surface treatment that
helps to reduce glare and halos around lights.
• Hydrophilic acrylic: Acrylic material that is designed to be more compatible with
the natural fluid in the eye, reducing the risk of vision-threatening complications.
Choice of lens material - patient's individual needs, the surgeon's preference, and the
potential risks and benefits of each material.
37. 37
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Bionic Eye or Artificial Eye
• Also known as a retinal implant, is a type of prosthetic device
that is surgically implanted into the eye to help restore vision to
people who have lost their sight due to certain conditions such
as retinitis pigmentosa or age-related macular degeneration.
• Consists of a camera, a processor, and an electrode array that
is attached to the retina.
• Camera captures images and sends signals to the processor,
which then transmits electrical stimulation to the electrodes in
the retina to stimulate the remaining healthy cells and restore
vision.
•The restored vision is not perfect, but it can help people with
vision loss to perform daily tasks more easily and safely.
39. 39
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
• Capturing images with a small camera and transmitting the information to a processing
unit that is attached to the eye.
• Processing unit then converts the visual information into electrical signals and sends
them to an electrode array that is surgically implanted onto the retina.
• Electrodes stimulate the remaining healthy cells in the retina, which then sends signals
to the brain to create the perception of vision.
•The restored vision is not perfect, but it can help people with vision loss to perform daily
tasks more easily and safely.
• Some bionic eyes only restore basic visual shapes and patterns, while others can provide
more detailed vision.
• Powered by a battery that is typically implanted behind the ear.
40. 40
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Materials Used in Bionic Eye
• Silicon or other semiconducting materials for the camera & electrode array.
• Biocompatible materials for the casing of the device and the electrode array,
such as titanium or titanium alloys, to minimize the risk of infection and rejection
by the body.
• Conductive materials, such as platinum, iridium, or gold, for the electrodes in
the array to provide efficient electrical stimulation to the retina.
• Polymers, such as silicone or polyimide, for insulation and protection of the
electrodes and other components.
• Optical materials, such as glass or acrylic, for the lens of the camera.
• Biocompatible and flexible materials for the electrical connections between the
camera and the processing unit and between the processing unit and the electrode
array.
•Advanced computer algorithms and machine learning techniques are also used to
improve the accuracy and reliability of the bionic eye technology.
43. 43
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Four chambers: Right atrium, Left atrium, Right ventricle, Left
ventricle.
Blood enters the right atrium from the body and is pumped into the right
ventricle, which then pumps the blood to the lungs for oxygenation.
Oxygenated blood returns to the heart and enters the left atrium, which
pumps the blood into the left ventricle. The left ventricle then pumps the
oxygenated blood out to the rest of the body.
Between each chamber, there are one-way valves that ensure the blood
flows in the correct direction and prevent backflow.
Surrounded by the pericardium, a sac that contains a small amount of
fluid and helps to protect and lubricate the heart as it beats.
44. 44
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
The Heart Beat
Heart's pumping action is
controlled by a complex
network of electrical and
chemical signals, which
generate the rhythm of the
heartbeat.
45. 45
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
•An electrical stimulus is generated in a special part of the heart muscle called
the sinus node (SA node).
• Small mass of special tissue in the right upper chamber of the heart (right
atrium).
• In an adult, the sinus node sends out a regular electrical pulse 60 to 100
times per minute.
• Electrical pulse travels down through the conduction pathways and causes
the heart's lower chambers (ventricles) to contract and pump out blood.
• The right and left atria are stimulated first and contract to push blood from
the atria into the ventricles.
• The ventricles then contract to push blood out into the blood vessels of the
body.
46. 46
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Electrical Signalling – ECG Monitoring and Heart Related Issues
47. 47
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Heart's pumping action is controlled by electrical signaling, which
generates the rhythm of the heartbeat.
Electrical signaling can be monitored using an electrocardiogram
(ECG), which records the electrical activity of the heart and provides
important information about the heart's function.
An ECG measures the electrical signals produced by the heart as it
beats and generates a trace or waveform that reflects the electrical
activity of the heart.
This trace can be used to diagnose heart conditions and monitor the
heart's function.
48. 48
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Some common heart-related issues that can be diagnosed or monitored
using an ECG include:
Arrhythmias: Abnormalities in the heart's rhythm or rate can
be detected using an ECG.
Heart disease: Changes in the heart's electrical activity can
indicate the presence of heart disease, such as coronary artery
disease or heart attacks.
Heart attack: Detecting changes in the heart's electrical
activity that indicate a lack of blood flow to the heart.
Overall, the ECG is a useful tool for diagnosing and monitoring heart-
related issues and helps to provide important information about the heart's
function and health.
49. 49
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Reasons for Blockages of Blood Vessels
(A)damage (dead heart muscle)
caused by a heart attack,
(B) shows the coronary artery with
plaque buildup and a blood clot.
50. 50
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Blockages in blood vessels, also known as arterial blockages or atherosclerosis, can occur for
several reasons:
High cholesterol levels: Excessive amounts of low-density lipoprotein (LDL) cholesterol
in the blood can lead to the formation of plaque in the blood vessels, which can narrow or
block them.
High blood pressure: Over time, high blood pressure can cause damage to the blood
vessels, leading to the formation of plaque and blockages.
Smoking: Smoking can damage the inner walls of blood vessels and promote the buildup
of plaque, leading to blockages.
Diabetes: People with uncontrolled diabetes are at a higher risk of developing blockages in
their blood vessels, due to damage to the blood vessels from high levels of glucose.
Age: As people age, the blood vessels can become stiff and less flexible, increasing the
risk of blockages.
Genetics: Some people may be predisposed to developing blockages in their blood vessels
due to genetic factors.
Poor diet: A diet high in saturated fats, trans fats, and cholesterol can increase the risk of
developing blockages in the blood vessels.
51. 51
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Design of Stents
Stents are small, metal mesh devices that are used to treat blockages in
blood vessels.
Typically used in procedures such as angioplasty, where a balloon catheter
is used to open up a blocked blood vessel and a stent is placed to keep it open.
52. 52
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Design of stents can vary depending on the type of stent and the specific medical condition
it is used to treat.
Shape: Cylindrical, helical, and spiraled, to match the shape of the blood vessel and
provide adequate support.
Material: Stainless steel, cobalt- chromium, and nitinol (a type of metal that is flexible
and can return to its original shape after being expanded).
Coating: Coated with different materials to prevent blood clots from forming and reduce
the risk of restenosis (recurrent blockage of the blood vessel).
Expansion mechanism: Designed to expand in different ways, such as by balloon
inflation or self-expansion, depending on the type of stent and the specific medical
condition it is used to treat.
Overall, the design of stents plays an important role in their effectiveness and safety. Stents
must be designed to provide adequate support to the blood vessel, prevent restenosis, and
minimize the risk of complications such as blood clots.
53. 53
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
Pace Makers
Small device that is surgically
implanted in the chest to regulate the
heartbeat.
It is used to treat heart rhythm
disorders, such as bradycardia (a slow
heartbeat) or arrhythmias (abnormal
heart rhythms), by delivering electrical
impulses to the heart to regulate its
rhythm.
54. 54
Prof.P.L.Puthani, Dept. of . Mech. Engg BLDEA’s V.P.Dr. P.G.Halakatti
The basic design of a pacemaker consists of:
Generator: Main component of the pacemaker and contains a battery
and electronic circuitry to generate and control the electrical impulses.
Leads: Thin wires that connect the generator to the heart and carry
the electrical impulses from the generator to the heart.
Electrodes: The electrodes are located at the end of the leads and are
used to deliver the electrical impulses to the heart.
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Single-chamber pacemaker: A single-chamber pacemaker
delivers electrical impulses to either the right atrium or the right
ventricle of the heart to regulate its rhythm.
Dual-chamber pacemaker: A dual-chamber pacemaker delivers
electrical impulses to both the right atrium and the right ventricle of
the heart to regulate its rhythm.
Biventricular pacemaker: A biventricular pacemaker delivers
electrical impulses to both ventricles of the heart to coordinate their
contractions and improve heart function in people with heart failure.
57. Uses of high-quality materials and specialized manufacturing processes to ensure
their safety and reliability.
Materials used in the construction of pacemakers include:
• Medical-grade plastics: Polycarbonate, are used to construct the exterior of
the device and to provide insulation and protection for the internal
components.
• Metals: Stainless steel and titanium, are used in the construction of the leads
and electrodes to ensure their durability and long-lasting performance.
• Electronic components: Microprocessors, batteries, and capacitors, are used
to control the delivery of the electrical impulses and to provide power to the
device.
• Adhesives: Cyanoacrylate and epoxy, are used to secure the components of
the device and to provide insulation and protection for the internal
components. 57
Construction of a Pacemaker
58. Medical device that delivers an
electric shock to the heart to
restore its normal rhythm in cases
of cardiac arrest or other life-
threatening heart rhythm
disorders.
Defibrillators can be external
(placed on the chest) or internal
(implanted within the body).
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Defibrillators
59. The basic design of a defibrillator consists of:
– Power source: The power source, typically a battery,
provides energy to deliver the electric shock to the heart.
– Electrodes: The electrodes are placed on the chest and
deliver the electric shock to the heart.
– Circuitry: The circuitry in the defibrillator controls the
delivery of the electric shock, including the timing,
strength, and duration of the shock.
– Display: A display on the defibrillator provides information
about the heart rhythm, battery life, and other relevant
information.
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60. Automated External Defibrillators (AEDs)
• External defibrillators, also known as AEDs, are designed for use by
laypeople and are commonly found in public places such as airports,
shopping centers, and schools. They are relatively simple in design
and typically have voice prompts and visual cues to guide the user
through the process of delivering the electric shock.
Implantable Cardioverter Defibrillators (ICDs),
• Internal defibrillators, also known as ICDs, are surgically implanted
within the body and are used to treat people with a high risk of sudden
cardiac arrest. They are typically more complex in design, including
features such as continuous monitoring of the heart rhythm, and
automatic delivery of shocks when necessary.
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61. Materials Used in the construction of defibrillators include:
• Medical-grade plastics: Polycarbonate, are used to construct the exterior
of the device and to provide insulation and protection for the internal
components.
• Metals: Stainless steel and titanium, are used in the construction of the
leads and electrodes to ensure their durability and long-lasting
performance.
• Electronic components: Microprocessors, batteries, capacitors, and
high-voltage transformers, are used to control the delivery of the
electrical impulses and to provide power to the device.
• Adhesives: Cyanoacrylate and epoxy, are used to secure the
components of the device and to provide insulation and protection for
the internal components.
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62. Artificial Heart
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Device that is designed to replace
the functions of a damaged or failing
heart.
Temporary measure to support a
patient while they are waiting for a
heart transplant, or as a permanent
solution for people who are not eligible
for a heart transplant.
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Two main types of artificial hearts:
Total artificial heart is a self-contained device that completely
replaces the functions of the natural heart. It is used as a bridge to
transplant, meaning it provides temporary support to a patient while
they are waiting for a heart transplant.
Heart assist devices, Devices that are surgically implanted into the
heart and work alongside the natural heart to support its functions.
While these devices are still in the early stages of development, they have
the potential to greatly improve the survival and well-being of people
with heart disease.