PD_Manager: an mHealth platform for Parkinson's disease patient management

Kostas M. Tsiouris; Dimitrios Gatsios; George Rigas; Dragana Miljkovic; Barbara Koroušić Seljak; Marko Bohanec; Maria T. Arredondo; Angelo Antonini; Spyros Konitsiotis; Dimitrios D. Koutsouris; Dimitrios I. Fotiadis

PD_Manager: an mHealth platform for Parkinson's disease patient management

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Author(s): Kostas M. Tsiouris ^{1, 2} ; Dimitrios Gatsios ¹ ; George Rigas ¹ ; Dragana Miljkovic ³ ; Barbara Koroušić Seljak ⁴ ; Marko Bohanec ³ ; Maria T. Arredondo ⁵ ; Angelo Antonini ⁶ ; Spyros Konitsiotis ⁷ ; Dimitrios D. Koutsouris ² ; Dimitrios I. Fotiadis ¹
- Affiliations: 1: Unit of Medical Technology and Intelligent Information Systems, University of Ioannina, GR45110 Ioannina, Greece ;
  2: Biomedical Engineering Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, GR15773 Athens, Greece ;
  3: Department of Knowledge Technologies, Jozef Stefan Institute, Jamova 39, SI1000 Ljubljana, Slovenia ;
  4: Computer Systems Department, Jozef Stefan Institute, Jamova 39, SI1000 Ljubljana, Slovenia ;
  5: Life Supporting Technologies, Universidad Politécnica de Madrid, Avenida Complutense 30, ES28040 Madrid, Spain ;
  6: Department for Parkinson's Disease, IRCCS San Camillo, Via Alberoni 70, IT30126 Venice, Italy ;
  7: Department of Neurology, Medical School, University of Ioannina, GR45110 Ioannina, Greece
Source: Volume 4, Issue 3, June 2017, p. 102 – 108
DOI: 10.1049/htl.2017.0007 , Online ISSN 2053-3713

This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)

Received 13/01/2017, Accepted 03/04/2017, Revised 27/03/2017, Published 23/05/2017

PD_Manager is a mobile health platform designed to cover most of the aspects regarding the management of Parkinson's disease (PD) in a holistic approach. Patients are unobtrusively monitored using commercial wrist and insole sensors paired with a smartphone, to automatically estimate the severity of most of the PD motor symptoms. Besides motor symptoms monitoring, the patient's mobile application also provides various non-motor self-evaluation tests for assessing cognition, mood and nutrition to motivate them in becoming more active in managing their disease. All data from the mobile application and the sensors is transferred to a cloud infrastructure to allow easy access for clinicians and further processing. Clinicians can access this information using a separate mobile application that is specifically designed for their respective needs to provide faster and more accurate assessment of PD symptoms that facilitate patient evaluation. Machine learning techniques are used to estimate symptoms and disease progression trends to further enhance the provided information. The platform is also complemented with a decision support system (DSS) that notifies clinicians for the detection of new symptoms or the worsening of existing ones. As patient's symptoms are progressing, the DSS can also provide specific suggestions regarding appropriate medication changes.

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