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Sensors 2014, 14(4), 6229-6246; doi:10.3390/s140406229

A Wearable System for Gait Training in Subjects with Parkinson’s Disease

Biomedical Engineering Unit, DEI, University of Bologna, 40136 Bologna, Italy
Micrel Lab, DEI, University of Bologna, 40136 Bologna, Italy
Neuromotor Research Group, Department of Rehabilitation Sciences, KU Leuven, 3001 Leuven, Belgium
DA Unit, ICT Center, Fondazione Bruno Kessler, 38123 Trento, Italy
This paper is dedicated, by all the authors, to Matteo Lanzi, who gave an initial fundamental contribution to the work. It is also dedicated to his family.
These authors equally contributed to the study.
Author to whom correspondence should be addressed.
Received: 8 January 2014 / Revised: 20 March 2014 / Accepted: 24 March 2014 / Published: 28 March 2014
(This article belongs to the Special Issue Wearable Gait Sensors)
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In this paper, a system for gait training and rehabilitation for Parkinson’s disease (PD) patients in a daily life setting is presented. It is based on a wearable architecture aimed at the provision of real-time auditory feedback. Recent studies have, in fact, shown that PD patients can receive benefit from a motor therapy based on auditory cueing and feedback, as happens in traditional rehabilitation contexts with verbal instructions given by clinical operators. To this extent, a system based on a wireless body sensor network and a smartphone has been developed. The system enables real-time extraction of gait spatio-temporal features and their comparison with a patient’s reference walking parameters captured in the lab under clinical operator supervision. Feedback is returned to the user in form of vocal messages, encouraging the user to keep her/his walking behavior or to correct it. This paper describes the overall concept, the proposed usage scenario and the parameters estimated for the gait analysis. It also presents, in detail, the hardware-software architecture of the system and the evaluation of system reliability by testing it on a few subjects. View Full-Text
Keywords: wearable; body area networks; motor disorders; rehabilitation; Parkinson’s disease; audio-feedback; gait analysis wearable; body area networks; motor disorders; rehabilitation; Parkinson’s disease; audio-feedback; gait analysis

This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Casamassima, F.; Ferrari, A.; Milosevic, B.; Ginis, P.; Farella, E.; Rocchi, L. A Wearable System for Gait Training in Subjects with Parkinson’s Disease. Sensors 2014, 14, 6229-6246.

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