Applications, Challenges, and Advancements in Electromyography Signal Processing

Applications, Challenges, and Advancements in Electromyography Signal Processing

Indexed In: SCOPUS
Release Date: May, 2014|Copyright: © 2014 |Pages: 404
DOI: 10.4018/978-1-4666-6090-8
ISBN13: 9781466660908|ISBN10: 1466660902|EISBN13: 9781466660915
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Description & Coverage
Description:

Electromyography (EMG) is a procedure for assessing and recording the electrical activity produced by skeletal muscles. Since the contracting skeletal muscles are greatly responsible for loading the bones and joints, information about the muscle EMG is important to gain knowledge about muscular-skeletal biomechanics.

Applications, Challenges, and Advancements in Electromyography Signal Processing provides an updated overview of signal processing applications and recent developments in EMG from a number of diverse aspects and various applications in clinical and experimental research. Presenting new results, concepts, and further developments in the field of EMG signal processing, this publication is an ideal resource for graduate and post-graduate students, academicians, engineers, and scientists in the fields of signal processing and biomedical engineering.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Applications in Electromyography (EMG)
  • Electromyography Signal Processing
  • Gesture Recognition
  • Joint Biometrics
  • Motion Analysis
  • Muscle Fatigue
  • Source Localization
Reviews & Statements

This collection brings together 15 chapters on recent developments in electromyography (EMG) and applications in clinical and experimental research. Engineers, sport scientists, and other researchers from Europe, Asia, Canada, and Colombia cover the basics of EMG and motor unit action potentials (MUAPs), including the neural control of muscle contraction, the anatomical, physiological, and technical aspects of recording single fiber action potentials, monitoring the electrical activity of skeletal muscles, and the fundamentals of biological signal analysis and processing, followed by discussion of EMG signal modeling and processing, including the biomechanic modeling of elbow joint dynamics, arm swing during gait for upper limb muscles, using ultrasonography to measure the musculotendon parameters of elbow muscles, and neuromuscular patterns in golf.

– ProtoView Book Abstracts (formerly Book News, Inc.)
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Editor/Author Biographies
Ganesh R. Naik received B.E. degree in Electronics and Communication Engineering from the University of Mysore, India, in 1997. He received his M.E. degree in Communication and Information Engineering from Griffith University, Brisbane, Australia, in 2002, and the PhD degree in the area of Electronics Engineering, specialised in Biomedical Engineering and Signal processing from RMIT University, Melbourne, Australia, in 2009. He is currently Chancellor's Post Doctoral Research Fellow at Faculty of Engineering and Information Technology (FEIT), UTS. As an early career researcher, he has edited 9 books, authored more than 80 papers in peer reviewed journals, conferences, and book chapters over the last five years. His research interests include EMG signal processing, Pattern recognition, Blind Source Separation (BSS) techniques, Biomedical signal processing, Human Computer Interface (HCI) and Audio signal processing. Currently he serves as an associate editor for two Springer journals (Circuits, Systems, and Signal Processing and Australasian Physical & Engineering Sciences in Medicine). He is also a reviewer and member of editorial board in several reputed journals. He is a recipient of the Baden–Württemberg Scholarship from the University of Berufsakademie, Stuttgart, Germany (2006–2007). In 2010, Dr. Naik is awarded with ISSI overseas fellowship from skilled Institute Victoria, Australia.
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