kingers Posted May 11 Report Share Posted May 11 Brain Computer Interfaces, Neural Engineering, NeuroRobotics Published 3/2025 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 4h 31m | Size: 1.94 GBFundamentals of Neural Recording, Neural Stimulation, and Closed-Loop Brain-Computer Interfaces for Robotic Applications What you'll learn Learning objectives are listed categorically as software/hardware expertise, quantitative skills, critical thinking, biology knowledge, and scientific literacy Software: filter noisy biological signals Software: extract features from neuromuscular waveforms Software: decode information from neural and electromyographic recordings Software: implement an artificial neural network in MATLAB for real-time control Software: control a robotic hand in real-time using biological recordings Software: implement real-time bioinspired haptic feedback Software: develop real-time functional electrical stimulation for assistive and rehabilitative tech Hardware: describe how to implement various electrophysiology techniques (e.g., space clamp, voltage clamp) and what they are used for Hardware: describe the principles of safe and effective neurostimulation Hardware: sketch various stimulation waveforms Hardware: describe chemical reactions for electrically exciting neurons Hardware: explain the pros and cons of various materials as neurostimulation electrodes Hardware: record electromyographic signals from the surface of the body Quantitative: model neurons as electrical circuits Quantitative: quantify ion and voltage changes during action potentials Quantitative: quantify spatiotemporal changes in electrical activity throughout neurons Quantitative: perform a safety analysis of neurostimulation Quantitative: measure how changes in neuron morphology (e.g., length, diameter) impact spatiotemporal changes in electrical activity Quantitative: measure how changes in neuron electrical properties (e.g., capacitance, resistance) impact spatiotemporal changes in electrical activity Critical Thinking: explain the characteristics of good training data for neural engineering applications Critical Thinking: describe how artificial neural networks relate to biological neural networks Critical Thinking: explain how artificial neural networks work in the context of neural engineering Critical Thinking: evaluate the performance of a motor-decode algorithm Critical Thinking: interpret physiological responses to neurostimulation Critical Thinking: debug common neurostimulation errors Critical Thinking: debug common electrophysiology errors Critical Thinking: develop novel neuromodulation applications Critical Thinking: critically evaluate brain-computer interface technology Biology: list several applications of neural engineering Biology: identify potential diseases suitable for next-generation neuromodulation applications Biology: draw and explain how biological neural networks transmit information and perform complex tasks Biology: describe the molecular basis of action potentials Biology: summarize the pathway from motor intent to physical movement Biology: explain the neural code for motor actions Biology: sketch various neuromuscular waveforms Biology: describe how biological neural networks encode sensory information Biology: use basic biological principles to guide the development of artificial intelligence Scientific Literacy: summarize the state of the neural engineering field Scientific Literacy: identify future research challenges in the field of neural engineering Scientific Literacy: cite relevant neural engineering manuscripts Scientific Literacy: write 4-page conference proceedings in IEEE format Scientific Literacy: use a reference manager Scientific Literacy: performance basic statistical analyses Requirements There are no requirements for this course. This course contains OPTIONAL labs that benefit from a background in programming. However, since these labs are optional, programming experience is not required. Description This course will cover tools and applications in the field of Neural Engineering with an emphasis on real-time robotic applications. Neural Engineering is an interdisciplinary field that overlaps with many other areas including neuroanatomy, electrophysiology, circuit theory, electrochemistry, bioelectric field theory, biomedical instrumentation, biomaterials, computational neuroscience, computer science, robotics, human-computer interaction, and neuromuscular rehabilitation. This course is designed around the central idea that Neural Engineering is the study of transferring electromagnetic information into or out of the nervous system. With this framework, the course is divided into three broad segments: neurorecording, neurostimulation and closed-loop neuromodulation. The neurorecording segment includes: invasive and non-invasive recording techniques, signal processing, neural feature extraction, biological and artificial neural networks, and real-time control of robotic devices using neurorecordings. The neurostimulation segment includes: invasive and non-invasive stimulation techniques, signal generation, physiological responses, safety analysis, and real-time stimulation for haptic feedback and for reanimating paralyzed limbs. The closed-loop neuromodulation segment features hands-on student-led projects and a review of various neurotech companies. Example applications include bionic arms controlled by thought that restore a natural sense of touch, or neural-links that can decode a person's thoughts to reanimate a paralyzed limb.The course provides students with fundamental articles from the field and dozens of quizzes for students to assess their understanding and reinforce key concepts. Optional hands-on research projects are also available. Who this course is for Individuals interested in working in the field of brain-computer interfaces, neural engineering, or neurorobotics Students and individuals interested in learning about the upcoming field of brain-computer interfaces Teachers interested in adding curriculum to their institution in the field of neural engineering & neurorobotics Investors interested in understanding basic concepts necessary to confidentially invest in neurotech companies such as Elon Musk's Neuralink Homepage https://www.udemy.com/course/neurorobotics/AusFilehttps://ausfile.com/2a4y8mhy0b2o/yxusj.Brain.Computer.Interfaces.Neural.Engineering.NeuroRobotics.part1.rarhttps://ausfile.com/mccqp8z5dc82/yxusj.Brain.Computer.Interfaces.Neural.Engineering.NeuroRobotics.part2.rarhttps://ausfile.com/2vrjajr1a656/yxusj.Brain.Computer.Interfaces.Neural.Engineering.NeuroRobotics.part3.rarRapidGatorhttps://rapidgator.net/file/d68da27196b7c0a31237942928ccf4fe/yxusj.Brain.Computer.Interfaces.Neural.Engineering.NeuroRobotics.part1.rarhttps://rapidgator.net/file/3daa435d6eb730f3f138c72ada9a0321/yxusj.Brain.Computer.Interfaces.Neural.Engineering.NeuroRobotics.part2.rarhttps://rapidgator.net/file/5106227dbab9f46a60bdaab5cbe6bf0e/yxusj.Brain.Computer.Interfaces.Neural.Engineering.NeuroRobotics.part3.rarTurboBithttps://turbobit.net/419jyuhyx4he/yxusj.Brain.Computer.Interfaces.Neural.Engineering.NeuroRobotics.part1.rar.htmlhttps://turbobit.net/quuzh8p3l36p/yxusj.Brain.Computer.Interfaces.Neural.Engineering.NeuroRobotics.part2.rar.htmlhttps://turbobit.net/4q4k0m2nh627/yxusj.Brain.Computer.Interfaces.Neural.Engineering.NeuroRobotics.part3.rar.html Link to comment Share on other sites More sharing options...
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