@article{ref1,
title="Real-time gait analysis with accelerometer-based smart shoes",
journal="Conference proceedings - IEEE engineering in medicine and biology society",
year="2017",
author="Delgado-Gonzalo, R. and Hubbard, J. and Renevey, Ph and Lemkaddem, A. and Vellinga, Q. and Ashby, D. and Willardson, J. and Bertschi, M.",
volume="2017",
number="",
pages="148-148c",
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.<p /> <p>Language: en</p>",
language="en",
issn="1557-170X",
doi="10.1109/EMBC.2017.8036783",
url="http://dx.doi.org/10.1109/EMBC.2017.8036783"
}