A Machine Learning Framework for Gait Classification Using Inertial Sensors

Open AccessThis article is freely available re-usable Sensors 2016, 16(1), 134; doi:10.3390/s16010134 (registering DOI) Article 1 The BioRobotics Institute, Scuola Superiore Sant’Anna, Pisa 56127, Italy 2 Information Engineering Unit, POLCOMING Department, University of Sassari, Sassari 07100, Italy * Author to whom correspondence should be addressed. Received: 7 December 2015 / Revised: 16 January 2016 / Accepted: 18 January 2016 / Published: 21 January 2016 No Machine learning methods have been widely used for gait assessment through the estimation of spatio-temporal parameters. As a further step, the objective of this work is to propose and validate a general probabilistic modeling approach for the classification of different pathological gaits. Specifically, the presented methodology was tested on gait data recorded on two pathological populations (Huntington’s disease and post-stroke subjects) and healthy elderly controls…


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