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Sensors 2014, 14(11), 21329-21357; doi:10.3390/s141121329

PERFORM: A System for Monitoring, Assessment and Management of Patients with Parkinson’s Disease

1
Unit of Medical Technology and Intelligent Information Systems, Dept. of Materials Science and Engineering, University of Ioannina, P.O. Box 1186, GR 45110 Ioannina, Greece
2
Dept. of Informatics and Telecommunication Engineering, University of Western Macedonia, GR 50100 Kozani, Greece
3
Dept. of Neurology, Medical School, University of Ioannina, GR 45110 Ioannina, Greece
4
ANCO S.A. Research and Development Division, 44, Syngrou Avenues, Athens 11742, Greece
5
Life Supporting Technologies, Universidad Politécnica de Madrid, Madrid 28040, Spain
6
Campus de Excelencia Internacional Campus Moncloa, Universidad Complutense de Madrid - Universidad Politecnica de Madrid, Madrid 28040, Spain
*
Author to whom correspondence should be addressed.
Received: 22 July 2014 / Revised: 25 September 2014 / Accepted: 20 October 2014 / Published: 11 November 2014
(This article belongs to the Collection Sensors for Globalized Healthy Living and Wellbeing)
View Full-Text   |   Download PDF [4765 KB, uploaded 11 November 2014]   |  

Abstract

In this paper, we describe the PERFORM system for the continuous remote monitoring and management of Parkinson’s disease (PD) patients. The PERFORM system is an intelligent closed-loop system that seamlessly integrates a wide range of wearable sensors constantly monitoring several motor signals of the PD patients. Data acquired are pre-processed by advanced knowledge processing methods, integrated by fusion algorithms to allow health professionals to remotely monitor the overall status of the patients, adjust medication schedules and personalize treatment. The information collected by the sensors (accelerometers and gyroscopes) is processed by several classifiers. As a result, it is possible to evaluate and quantify the PD motor symptoms related to end of dose deterioration (tremor, bradykinesia, freezing of gait (FoG)) as well as those related to over-dose concentration (Levodopa-induced dyskinesia (LID)). Based on this information, together with information derived from tests performed with a virtual reality glove and information about the medication and food intake, a patient specific profile can be built. In addition, the patient specific profile with his evaluation during the last week and last month, is compared to understand whether his status is stable, improving or worsening. Based on that, the system analyses whether a medication change is needed—always under medical supervision—and in this case, information about the medication change proposal is sent to the patient. The performance of the system has been evaluated in real life conditions, the accuracy and acceptability of the system by the PD patients and healthcare professionals has been tested, and a comparison with the standard routine clinical evaluation done by the PD patients’ physician has been carried out. The PERFORM system is used by the PD patients and in a simple and safe non-invasive way for long-term record of their motor status, thus offering to the clinician a precise, long-term and objective view of patient’s motor status and drug/food intake. Thus, with the PERFORM system the clinician can remotely receive precise information for the PD patient’s status on previous days and define the optimal therapeutical treatment. View Full-Text
Keywords: Parkinson’s disease (PD); motor symptoms; remote monitoring; wearable devices Parkinson’s disease (PD); motor symptoms; remote monitoring; wearable devices
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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

Tzallas, A.T.; Tsipouras, M.G.; Rigas, G.; Tsalikakis, D.G.; Karvounis, E.C.; Chondrogiorgi, M.; Psomadellis, F.; Cancela, J.; Pastorino, M.; Waldmeyer, M.T.A.; Konitsiotis, S.; Fotiadis, D.I. PERFORM: A System for Monitoring, Assessment and Management of Patients with Parkinson’s Disease. Sensors 2014, 14, 21329-21357.

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