ACCELEROMETER BASED GAIT ANALYSIS - Multi Variate Assessment of Fall Risk with FD-NEAT

Bart Jansen, Maxine Tan, Ivan Bautmans, Bart Van Keymolen, Tony Mets, Rudi Deklerck

2011

Abstract

This paper describes an accelerometer based gait analysis system for the assessment of fall risk. The assessment is based on 22 different features calculated from the signal. The different features are combined using machine learning algorithms in order to decide whether the subject has an increased fall risk. Results from Naive Bayes, Neural Networks, Locally Weighted Learning, Support Vector Machines and C4.5 are reported and compared. It is argued that the neural networks provide low accuracy results because of the high dimensionality of the feature space compared to the available data. It is shown that FD-NEAT (a method from neuro evolution which simultaneously learns the network topology, the network weights and the relevant features) outperforms the other methods in the given classification task. The system is evaluated on a database consisting of 40 elderly with known fall risk and 40 healthy elderly controls.

Paper Citation

in Harvard Style

Jansen B., Tan M., Bautmans I., Van Keymolen B., Mets T. and Deklerck R. (2011). ACCELEROMETER BASED GAIT ANALYSIS - Multi Variate Assessment of Fall Risk with FD-NEAT . In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2011) ISBN 978-989-8425-35-5, pages 138-143. DOI: 10.5220/0003132701380143

in Bibtex Style

@conference{biosignals11,
author={Bart Jansen and Maxine Tan and Ivan Bautmans and Bart Van Keymolen and Tony Mets and Rudi Deklerck},
title={ACCELEROMETER BASED GAIT ANALYSIS - Multi Variate Assessment of Fall Risk with FD-NEAT},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2011)},
year={2011},
pages={138-143},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003132701380143},
isbn={978-989-8425-35-5},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2011)
TI - ACCELEROMETER BASED GAIT ANALYSIS - Multi Variate Assessment of Fall Risk with FD-NEAT
SN - 978-989-8425-35-5
AU - Jansen B.
AU - Tan M.
AU - Bautmans I.
AU - Van Keymolen B.
AU - Mets T.
AU - Deklerck R.
PY - 2011
SP - 138
EP - 143
DO - 10.5220/0003132701380143