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Volume 17
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Article

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

by
Daniel Rodríguez-Martín
1,*,†,
Carlos Pérez-López
1,†,
Albert Samà
1,
Andreu Català
1,
Joan Manuel Moreno Arostegui
1,
Joan Cabestany
1,
Berta Mestre
2,
Sheila Alcaine
2,
Anna Prats
2,
María De la Cruz Crespo
2 and
Àngels Bayés
2
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
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Sensors 2017, 17(4), 827; https://doi.org/10.3390/s17040827
Submission 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)
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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.
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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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.D.l.; et al. A Waist-Worn Inertial Measurement Unit for Long-Term Monitoring of Parkinson’s Disease Patients. Sensors 2017, 17, 827. https://doi.org/10.3390/s17040827

AMA Style

Rodríguez-Martín D, Pérez-López C, Samà A, Català A, Moreno Arostegui JM, Cabestany J, Mestre B, Alcaine S, Prats A, Cruz Crespo MDl, et al. A Waist-Worn Inertial Measurement Unit for Long-Term Monitoring of Parkinson’s Disease Patients. Sensors. 2017; 17(4):827. https://doi.org/10.3390/s17040827

Chicago/Turabian Style

Rodríguez-Martín, Daniel, Carlos Pérez-López, Albert Samà, Andreu Català, Joan Manuel Moreno Arostegui, Joan Cabestany, Berta Mestre, Sheila Alcaine, Anna Prats, María De la Cruz Crespo, and et al. 2017. "A Waist-Worn Inertial Measurement Unit for Long-Term Monitoring of Parkinson’s Disease Patients" Sensors 17, no. 4: 827. https://doi.org/10.3390/s17040827

APA 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. D. l., & Bayés, À. (2017). A Waist-Worn Inertial Measurement Unit for Long-Term Monitoring of Parkinson’s Disease Patients. Sensors, 17(4), 827. https://doi.org/10.3390/s17040827

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