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Authors: Peter Christ 1 ; Felix Werner 2 ; Ulrich Rückert 2 and Jörg Mielebacher 3

Affiliations: 1 Universität Bielefeld, Germany ; 2 Bielefeld University, Germany ; 3 Mielebacher Informatiksysteme, Germany

ISBN: 978-989-8565-36-5

Keyword(s): Human Identification, Accelerometer, Electrocardiograph (ECG), Wireless Body Sensor (WBS), Pattern Recognition.

Related Ontology Subjects/Areas/Topics: Applications ; Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Biometrics ; Biometrics and Pattern Recognition ; Computational Intelligence ; Data Manipulation ; Detection and Identification ; Devices ; Health Engineering and Technology Applications ; Health Information Systems ; Human-Computer Interaction ; Methodologies and Methods ; Multimedia ; Multimedia Signal Processing ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Telecommunications ; Theory and Methods ; Wearable Sensors and Systems

Abstract: In this paper we propose a biometric method for identifying humans during walking and jogging. We use acceleration and electrocardiographic measurements recorded with a wireless body sensor attached to a chest strap. Our method does not require a particular acquisition setup. Information on the gait style and on the physiology is combined to identify a human despite severe motion related artefacts in the electrocardiograph and variations in the gait patterns. We propose to identify humans using features extracted in time and frequency domain and a standard classifier. With the collected data of 22 subjects on a treadmill at velocities from 3 to 9 km/h we obtained an accuracy of 98.1 %. The sensitivity of the identification ranged between 94.6 to 99.5% for the different subjects and the specificity was higher than 99.7 %.

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Paper citation in several formats:
Christ, P.; Werner, F.; Rückert, U. and Mielebacher, J. (2013). Athlete Identification using Acceleration and Electrocardiographic Measurements Recorded with a Wireless Body Sensor.In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013) ISBN 978-989-8565-36-5, pages 11-19. DOI: 10.5220/0004190300110019

@conference{biosignals13,
author={Peter Christ. and Felix Werner. and Ulrich Rückert. and Jörg Mielebacher.},
title={Athlete Identification using Acceleration and Electrocardiographic Measurements Recorded with a Wireless Body Sensor},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013)},
year={2013},
pages={11-19},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004190300110019},
isbn={978-989-8565-36-5},
}

TY - CONF

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013)
TI - Athlete Identification using Acceleration and Electrocardiographic Measurements Recorded with a Wireless Body Sensor
SN - 978-989-8565-36-5
AU - Christ, P.
AU - Werner, F.
AU - Rückert, U.
AU - Mielebacher, J.
PY - 2013
SP - 11
EP - 19
DO - 10.5220/0004190300110019

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