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dc.contributor.authorDelgado-Gonzalo, Ricard
dc.contributor.authorHubbard, Jeremy
dc.contributor.authorRenevey, Philippe
dc.contributor.authorLemkaddem, Alia
dc.contributor.authorVellinga, Quinn
dc.contributor.authorAshby, Darren
dc.contributor.authorWillardson, Jared
dc.contributor.authorBertschi, Mattia
dc.identifier.citation2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Seogwipo (KOR), pp. 148-148c
dc.description.abstractIn 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.
dc.titleReal-time gait analysis with accelerometer-based smart shoes
dc.typeProceedings Article
dc.type.csemresearchareasDigital Health

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