Citation

Delgado-Gonzalo R, Hubbard J, Renevey P, Lemkaddem A, Vellinga Q, Ashby D, Willardson J, Bertschi M. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2017; 2017: 148-148c.

Copyright

(Copyright © 2017, IEEE (Institute of Electrical and Electronics Engineers))

DOI

10.1109/EMBC.2017.8036783

PMID

29059831

Abstract

In this paper, we present the evaluation of a new smart shoe capable of performing gait analysis in real time. The system is exclusively based on accelerometers which minimizes the power consumption. The estimated parameters are activity class (rest/walk/run), step cadence, ground contact time, foot impact (zone, strength, and balance), forward distance, and speed. The different parameters have been validated with a customized database of 26 subjects on a treadmill and video data labeled manually. Key measures for running analysis such as the cadence is retrieved with a maximum error of 2%, and the ground contact time with an average error of 3.25%. The classification of the foot impact zone achieves a precision between 72% and 91% depending of the running style. The presented algorithm has been licensed to ICON Health & Fitness Inc. for their line of wearables under the brand iFit.

Language: en