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Authors: Abbas K. Abbas 1 and Rasha Bassam 2

Affiliations: 1 RWTH Aachen University, Germany ; 2 Aachen University of Applied Sciences, Germany

ISBN: 978-989-8111-65-4

Keyword(s): EMG clustering, Motor Unit Action Potentials (MUAPs), Independent Component Analysis (ICA), EMG Entropy, ROC analysis.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Biomedical Engineering ; Biomedical Signal Processing ; Computer Vision, Visualization and Computer Graphics ; Medical Image Detection, Acquisition, Analysis and Processing

Abstract: Adaptive independent component analysis is interactive method for processing and classifying EMG signals pattern through short steps of ICA algorithms. In this work the efficiency and presentation of EMG signal decomposition and classification with adaptive ICA algorithm was investigated and presented. Single and multiple fibers motor unit action potentials (MUAP) patterns were tested and identified. Applying a fixed point modified ICA method, instead of much decomposition and pattern clustering algorithm localization of the action-potential source in the vicinity of specific neuromuscular diseases was achieved. ICA has its flex-ibility for robustly classify and identify the MUAP’s signal stochastic sources with a linear way and localizing the blind source for bioelectric potential. The utilization of adaptive ICA as an embedded clustering algorithm for separating a blind signal source will assist in construction an automated EMG signal diagnosis system with aid of new computerized real time signal processing technique. From the proposed system a stable and robust EMG classifying system based on multiple MUAP’s intensity were developed and tested through a standardization of clinical EMG signal acquisition and processing. (More)

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Paper citation in several formats:
K. Abbas A.; Bassam R. and (2009). AUTOMATED EMG-SIGNAL PATTERN CLUSTERING BASED ON ICA DECOMPOSITION .In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2009) ISBN 978-989-8111-65-4, pages 305-310. DOI: 10.5220/0001544503050310

@conference{biosignals09,
author={Abbas {K. Abbas} and Rasha Bassam},
title={AUTOMATED EMG-SIGNAL PATTERN CLUSTERING BASED ON ICA DECOMPOSITION },
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2009)},
year={2009},
pages={305-310},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001544503050310},
isbn={978-989-8111-65-4},
}

TY - CONF

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2009)
TI - AUTOMATED EMG-SIGNAL PATTERN CLUSTERING BASED ON ICA DECOMPOSITION
SN - 978-989-8111-65-4
AU - K. Abbas, A.
AU - Bassam, R.
PY - 2009
SP - 305
EP - 310
DO - 10.5220/0001544503050310

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