Title: Mechanomyogram signal detection and decomposition: conceptualisation and research design

Authors: Hisham Gamal Daoud; Hani Fikry Ragai

Addresses: Faculty of Engineering, Department of Electrical Communications and Electronics Systems, MSA University, 6th October City, 41511, Egypt ' Faculty of Engineering, Department of Electrical Communications and Electronics, Ain Shams University, Cairo, 11517, Egypt

Abstract: The primary purpose of the present study is to construct behavioural modelling of the detection and analysis of the Mechanomyogram (MMG) signal for different muscles using virtual muscle model. Mechanomyography is the superficial recording of low frequency vibrations detected over contracting muscles. In this study, a MEMS based accelerometer model is used. Three decomposition techniques which are Discrete Wavelet Transform, Principle Component Analysis and empirical mode decomposition are applied on the MMG for the purpose of feature extraction which could be used for the diagnosis process. A comparison between results of the different techniques as well as hybrid techniques is studied to reach the best one.

Keywords: MMG; mechanomyogram; accelerometers; signal decomposition; signal detection; behavioural modelling; virtual muscle models; mechanomyography; superficial recording; low frequency vibrations; contracting muscles; muscle contraction; MEMS; microelectromechanical systems; micro-electro-mechanical systems; accelerometer models; DWT; discrete wavelet transform; PCA; principal component analysis; empirical mode decomposition; feature extraction; diagnosis processes; hybrid techniques; healthcare technology; healthcare management.

DOI: 10.1504/IJHTM.2012.048972

International Journal of Healthcare Technology and Management, 2012 Vol.13 No.1/2/3, pp.32 - 44

Published online: 15 Nov 2014 *

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