Real-time gait analysis with accelerometer-based smart shoes

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.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.identifier.citation2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Seogwipo (KOR), pp. 148-148c
dc.titleReal-time gait analysis with accelerometer-based smart shoes
dc.typeProceedings Article
dc.type.csemresearchareasDigital Health