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Sensors 2017, 17(4), 827; doi:10.3390/s17040827

A Waist-Worn Inertial Measurement Unit for Long-Term Monitoring of Parkinson’s Disease Patients

1
Technical Research Centre for Dependency Care and Autonomous Living—CETPD, Universitat Politècnica de Catalunya—BarcelonaTech, Rambla de l’Exposició 59-69, Vilanova i la Geltrú, 08800 Barcelona, Spain
2
Unidad de Parkinson y Trastornos del Movimiento (UParkinson), Passeig Bonanova 26, 08022 Barcelona, Spain
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editors: Ioannis Kompatsiaris, Thanos G. Stavropoulos and Antonis Bikakis
Received: 16 November 2016 / Revised: 4 April 2017 / Accepted: 7 April 2017 / Published: 11 April 2017
(This article belongs to the Special Issue Sensors for Ambient Assisted Living, Ubiquitous and Mobile Health)
View Full-Text   |   Download PDF [4193 KB, uploaded 11 April 2017]   |  

Abstract

Inertial measurement units (IMUs) are devices used, among other fields, in health applications, since they are light, small and effective. More concretely, IMUs have been demonstrated to be useful in the monitoring of motor symptoms of Parkinson’s disease (PD). In this sense, most of previous works have attempted to assess PD symptoms in controlled environments or short tests. This paper presents the design of an IMU, called 9 × 3, that aims to assess PD symptoms, enabling the possibility to perform a map of patients’ symptoms at their homes during long periods. The device is able to acquire and store raw inertial data for artificial intelligence algorithmic training purposes. Furthermore, the presented IMU enables the real-time execution of the developed and embedded learning models. Results show the great flexibility of the 9 × 3, storing inertial information and algorithm outputs, sending messages to external devices and being able to detect freezing of gait and bradykinetic gait. Results obtained in 12 patients exhibit a sensitivity and specificity over 80%. Additionally, the system enables working 23 days (at waking hours) with a 1200 mAh battery and a sampling rate of 50 Hz, opening up the possibility to be used for other applications like wellbeing and sports. View Full-Text
Keywords: inertial measurement unit; Parkinson’s disease; monitoring; inertial data capture; algorithm inertial measurement unit; Parkinson’s disease; monitoring; inertial data capture; algorithm
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Rodríguez-Martín, D.; Pérez-López, C.; Samà, A.; Català, A.; Moreno Arostegui, J.M.; Cabestany, J.; Mestre, B.; Alcaine, S.; Prats, A.; Cruz Crespo, M.; Bayés, À. A Waist-Worn Inertial Measurement Unit for Long-Term Monitoring of Parkinson’s Disease Patients. Sensors 2017, 17, 827.

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