@ARTICLE{ iet:/content/journals/10.1049/htl.2017.0007, author = {Kostas M. Tsiouris}, affiliation = { Unit of Medical Technology and Intelligent Information Systems, University of Ioannina, GR45110 Ioannina, Greece }, affiliation = { Biomedical Engineering Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, GR15773 Athens, Greece }, author = {Dimitrios Gatsios}, affiliation = { Unit of Medical Technology and Intelligent Information Systems, University of Ioannina, GR45110 Ioannina, Greece }, author = {George Rigas}, affiliation = { Unit of Medical Technology and Intelligent Information Systems, University of Ioannina, GR45110 Ioannina, Greece }, author = {Dragana Miljkovic}, affiliation = { Department of Knowledge Technologies, Jozef Stefan Institute, Jamova 39, SI1000 Ljubljana, Slovenia }, author = {Barbara Koroušić Seljak}, affiliation = { Computer Systems Department, Jozef Stefan Institute, Jamova 39, SI1000 Ljubljana, Slovenia }, author = {Marko Bohanec}, affiliation = { Department of Knowledge Technologies, Jozef Stefan Institute, Jamova 39, SI1000 Ljubljana, Slovenia }, author = {Maria T. Arredondo}, affiliation = { Life Supporting Technologies, Universidad Politécnica de Madrid, Avenida Complutense 30, ES28040 Madrid, Spain }, author = {Angelo Antonini}, affiliation = { Department for Parkinson's Disease, IRCCS San Camillo, Via Alberoni 70, IT30126 Venice, Italy }, author = {Spyros Konitsiotis}, affiliation = { Department of Neurology, Medical School, University of Ioannina, GR45110 Ioannina, Greece }, author = {Dimitrios D. Koutsouris}, affiliation = { Biomedical Engineering Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, GR15773 Athens, Greece }, author = {Dimitrios I. Fotiadis}, affiliation = { Unit of Medical Technology and Intelligent Information Systems, University of Ioannina, GR45110 Ioannina, Greece }, keywords = {mood;wrist sensors;skin temperature sensor;gyroscope;smartphone;decision support system;DSS;cloud infrastructure;accelerometers;mHealth platform;Parkinson's disease patient management;cognition;insole sensors;PD motor symptoms;optical heart rate sensor;nutrition;PD_Manager;nonmotor self-evaluation tests;mobile health platform;}, language = {English}, abstract = {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.}, title = {PD_Manager: an mHealth platform for Parkinson's disease patient management}, journal = {Healthcare Technology Letters}, issue = {3}, volume = {4}, year = {2017}, month = {June}, pages = {102-108(6)}, publisher ={Institution of Engineering and Technology}, copyright = {This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)}, url = {https://digital-library.theiet.org/;jsessionid=7vj7u0q8ifego.x-iet-live-01content/journals/10.1049/htl.2017.0007} }