Real-time gait analysis with accelerometer-based smart shoes

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Delgado-Gonzalo, Ricard
Hubbard, Jeremy
Renevey, Philippe
Lemkaddem, Alia
Vellinga, Quinn
Ashby, Darren
Willardson, Jared
Bertschi, Mattia
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.
Publication Reference
2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Seogwipo (KOR), pp. 148-148c