An Automatic Gait Analysis Pipeline for Wearable Sensors: A Pilot Study in Parkinson’s Disease

The use of wearable sensors allows continuous recordings of physical activity from participants in free-living or at-home clinical studies. The large amount of data collected demands automatic analysis pipelines to extract gait parameters that can be used as clinical endpoints. We introduce a deep l...

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Principais autores:	Luis R. Peraza, Kirsi M. Kinnunen, Roisin McNaney, Ian J. Craddock, Alan L. Whone, Catherine Morgan, Richard Joules, Robin Wolz
格式:	Artigo
語言:	Inglês
出版:	MDPI AG 2021-12-01
叢編:	Sensors
主題:	accelerometry deep learning free living step length initial contact toe-off
在線閱讀:	https://www.mdpi.com/1424-8220/21/24/8286
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