Open Access Medical Books



Edited by Joseph Mizrahi .

224 pages .
Open Access . 

The electrical activity of the muscles, as measured by means of electromyography (EMG), is a major expression of muscle contraction. Since the contracting skeletal muscles are greatly responsible for loading of the bones and joints, information about the muscle EMG is important to gain knowledge about musculo-skeletal biomechanics.
Myoelectric signals can also demonstrate the development of loading imbalance and asymmetry, which in turn relate to physical disability. In smooth muscles, EMG may be used to indicate function of internal organs. EMG may thus be used clinically for the diagnosis of neuromuscular problems and for assessing biomechanical and motor control deficits and other functional disorders. It may also be used as a control signal for interfacing with orthotic and/or prosthetic devices or other rehabilitation assists.
Apart from muscular activity, EMG may also be used to indicate and quantify the development of muscle fatigue.
EMG signals from whole muscles are generally stochastic in nature, thus requiring reference to methods of signal analysis in order to be characterized ad classified and to obtain quantitative information about muscle activity both in the time and the frequency domains. Exceptionally, EMG signals may exhibit a deterministic pattern when all the muscle fibers contract simultaneously. This takes place when the muscle's activation is being induced by means of electrical stimulation from a source external to the central nervous system. A synchronous compound muscle action potential (CMAP) then replaces the natural, somewhat random-like, signal produced by the asynchronous firing of the different motor units. Rather simple methods of signal processing are sufficient for characterizing the synchronous CMAP.
The EMG signal is usually accompanied by mechanical signals emerging from the contracting and vibrating muscles. Although these signals are measurable by means of microphones (acoustic myography, AMG) or accelerometers (mechano myography, MMG) the EMG is still the major and dominant source serving to monitor muscle activity.
This is so because EMG signals are more reliable and reproducible compared to the AMG and MMG signals.
This book aims at providing an updated overview of the recent developments in electromyography from diverse aspects and various applications in clinical and experimental research. It consists of ten chapters arranged in four sections. The first section deals with EMG signals from skeletal muscles and their significance in assessing biomechanical and physiologic function and in applications in neuro-musculo-skeletal rehabilitation. The second section addresses methodologies for the treatment of the signal itself: noise removal and pattern recognition for the activation of artificial limbs.
The third section deals with utilizing the EMG signals for inferring on the mechanical action of muscle, such as force, e.g., pinching force in humans or sucking pressure in the cibarial pump during feeding of the hematophagous hemiptera insect. The fourth and last section deals with the clinical role of electromyograms in studying the pelvic floor muscle function.

Prof. Joseph Mizrahi
Department of Biomedical Engineering
Technion Israel Institute of Technology, Haifa,


Part 1 of the textbook : Skeletal Muscles, Biomechanics and Rehabilitation .

  1 The Role of Electromyograms in 
Resolving Musculoskeletal Interactions in Able-Bodied and Disabled Human Individuals 3 J. Mizrahi

  2 Electromyography Assessment of Muscle 
Recruitment Strategies During High-Intensity Exercise 25 François Billaut

  3 Classification of Upper Limb 
Motions from Around-Shoulder Muscle Activities 41 Hirokazu Soma, Yuse Horiuchi, Jose Gonzalez and Wenwei Yu

  4 Walking and Jogging: Quantification of 
Muscle Activity of the Lower Extremities 55 Begoña Gavilanes-Miranda, Juan J. Goiriena De Gandarias and Gonzalo A. Garcia

Part 2 of the textbook : EMG Processing and Noise Reduction .

  5 EMG Signal Noise Removal Using Neural Netwoks 77 
Vijay R. Mankar

  6 Electromyography Pattern-Recognition-Based Control 
of Powered Multifunctional Upper-Limb Prostheses 99 Guanglin Li

Part 3 of the textbook : Force Estimation .

  7 Pinching Effort Evaluation 
Based on Tendon Force Estimation 119 Atsutoshi Ikeda, Yuichi Kurita and Tsukasa Ogasawara

Chapter 8 Electromyogram of the Cibarial Pump and 
the Feeding Process in Hematophagous Hemiptera 137 Ricardo N Araujo, Nelder F Gontijo, Alessandra A Guarneri, Alberto F Gontijo, Adriana C Soares and Marcos H Pereira

Part 4 of the textbook : Pelvic Floor Muscle Function from Electromyograms .

  9 Anal Sphincter Electromyogram for 
Dysfunction of Lower Urinary Tract and Pelvic Floor 161 Chuangyu Qu, Dangfeng Xu, Cunzhou Wang, Jie Chen, Lei Yin and Xingang Cui

  10 Electromyography of Pelvic Floor Muscles in Rats 189 
Yolanda Cruz Gómez, Hai-Hong Jiang, Paul Zaszczurynski, Raúl Juárez, César Pastelin and Margot S. Damaser .

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Published by: younes younes - Thursday, February 21, 2013


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