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Applications, Challenges, and Advancements in Electromyography Signal Processing [Kõva köide]

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"This book 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"--Provided by publisher.

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.
Preface xv
Section 1 EMG Basics and Motor Unit Action Potentials
Chapter 1 Neural Control of Muscle
1(27)
Parveen Bawa
Kelvin E. Jones
Chapter 2 New Advances in Single Fiber Electromyography
28(30)
Javier Rodriguez-Falces
Chapter 3 Detection and Conditioning of EMG
58(37)
Imran Goker
Chapter 4 An Introduction to EMG Signal Processing Using MatLab and Microsoft Excel
95(19)
Daniel Robbins
Section 2 EMG Signal Modeling and Signal Processing
Chapter 5 Modeling the Human Elbow Joint Dynamics from Surface Electromyography
114(15)
Andres Felipe Ruiz-Olaya
Chapter 6 Arm Swing during Human Gait Studied by EMG of Upper Limb Muscles
129(32)
Johann P. Kuhtz-Buschbeck
Antonia Frendel
Bo Jing
Chapter 7 Using in Vivo Subject-Specific Musculotendon Parameters to Investigate Voluntary Movement Changes after Stroke: An EMG-Driven Model of Elbow Joint
161(20)
Hujing Hu
Chapter 8 Study and Interpretation of Neuromuscular Patterns in Golf
181(22)
Sergio Marta
Joao Rocha Vaz
Luis Silva
Maria Antonio Castro
Pedro Pezarat Correia
Section 3 EMG: Endurance, Stability, and Muscle Activities
Chapter 9 Assessing Joint Stability from Eigenvalues Obtained from Multi-Channel EMG: A Spine Example
203(16)
Dianne M. Ikeda
Stuart M. McGill
Chapter 10 Endurance Time Prediction using Electromyography
219(15)
Sebastien Boyas
Arnaud Guevel
Chapter 11 EMG Activation Pattern during Voluntary Bending and Donning Safety Shoes
234(23)
P. K. Nag
Varsha Chorsiya
Anjali Nag
Chapter 12 Tongue Movement Estimation Based on Suprahyoid Muscle Activity
257(18)
Makoto Sasaki
Section 4 EMG for Prosthetic and HCI Applications
Chapter 13 Design of Myocontrolled Neuroprosthesis: Tricks and Pitfalls
275(29)
Emilia Ambrosini
Simona Ferrante
Alessandro Pedrocchi
Chapter 14 Design and Development of EMG Conditioning System and Hand Gesture Recognition Based on Principal Component Analysis Feature Reduction Technique
304(17)
P. Geethanjali
Chapter 15 The Relationship between Anthropometric Variables and Features of Electromyography Signal for Human-Computer Interface
321(33)
Angkoon Phinyomark
Franck Quaine
Yann Laurillau
Compilation of References 354(42)
About the Contributors 396(6)
Index 402
Ganesh R. Naik University of Technology Sydney (UTS), Australia