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Authors: Gernot Kvas 1 and Rosemarie Velik 2

Affiliations: 1 Otto Bock Healthcare Products GmbH, Austria ; 2 Institute of Computer Technology, Vienna Technical University, Austria

ISBN: 978-989-8111-65-4

Keyword(s): Electromyogram, Pattern Recognition, Genetic Algorithm.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Data Manipulation ; Evolutionary Systems ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Soft Computing

Abstract: State of the art self powered prostheses make use of the surface myoelectric signal for motor control. With increasing height of the amputation, control by residual muscles becomes less intuitive and physiologic. Targeted muscle reinnervation (TMR), a surgery technique to increase the number of control sites available in combination with multichannel surface electromyography allows for improved prosthesis control. This paper presents a genetic algorithm that determines a channel subset with high classification accuracy out of a given number of channels recorded from the reinnervated area of a patient.

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Paper citation in several formats:
Kvas G.; Velik R. and (2009). SUBSET SELECTION OF MYOELECTRIC CHANNELS - A Genetic Algorithm for Subset Selection of Myoelectric Channels for Patients Following TMR Surgery.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 222-226. DOI: 10.5220/0001433602220226

@conference{biosignals09,
author={Gernot Kvas and Rosemarie Velik},
title={SUBSET SELECTION OF MYOELECTRIC CHANNELS - A Genetic Algorithm for Subset Selection of Myoelectric Channels for Patients Following TMR Surgery},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2009)},
year={2009},
pages={222-226},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001433602220226},
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 - SUBSET SELECTION OF MYOELECTRIC CHANNELS - A Genetic Algorithm for Subset Selection of Myoelectric Channels for Patients Following TMR Surgery
SN - 978-989-8111-65-4
AU - Kvas, G.
AU - Velik, R.
PY - 2009
SP - 222
EP - 226
DO - 10.5220/0001433602220226

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