Dynamic Gait Monitoring Mobile Platform

Robin Amsters, Ali Bin Junaid, Nick Damen, Jeroen Van de Laer, Benjamin Filtjens, Bart Vanrumste, Peter Slaets

Abstract

Human gait is an important indicator of health. Existing gait analysis systems are either expensive, intrusive, or require structured environments such as a clinic or a laboratory. In this research, a low-cost, non-obtrusive, dynamic gait monitoring platform is presented. By utilizing a mobile robot equipped with a Kinect sensor, comprehensive gait information can be extracted. The mobile platform tracks the skeletal joint movements while following the person. The acquired skeletal joint data is filtered to improve detection. Gait parameters such as step length, cadence and gait cycle time are extracted by processing the filtered data. The proposed approach was validated by using a VICON motion capture system. Results show that the proposed system is able to accurately detect gait parameters but requires a calibration procedure. Even though the camera is moving while tracking, the performance is on par with existing works. Step times can be detected with an average accuracy of around 10 milliseconds. Step length can be detected with an average accuracy of a few centimeters.

Download


Paper Citation


in Harvard Style

Amsters R., Bin Junaid A., Damen N., Van de Laer J., Filtjens B., Vanrumste B. and Slaets P. (2018). Dynamic Gait Monitoring Mobile Platform.In Proceedings of the 4th International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE, ISBN 978-989-758-299-8, pages 49-61. DOI: 10.5220/0006733200490061


in Bibtex Style

@conference{ict4awe18,
author={Robin Amsters and Ali Bin Junaid and Nick Damen and Jeroen Van de Laer and Benjamin Filtjens and Bart Vanrumste and Peter Slaets},
title={Dynamic Gait Monitoring Mobile Platform},
booktitle={Proceedings of the 4th International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE,},
year={2018},
pages={49-61},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006733200490061},
isbn={978-989-758-299-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 4th International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE,
TI - Dynamic Gait Monitoring Mobile Platform
SN - 978-989-758-299-8
AU - Amsters R.
AU - Bin Junaid A.
AU - Damen N.
AU - Van de Laer J.
AU - Filtjens B.
AU - Vanrumste B.
AU - Slaets P.
PY - 2018
SP - 49
EP - 61
DO - 10.5220/0006733200490061