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

Healthcare Technology Letters

article

Kostas M. Tsiouris¹  Dimitrios Gatsios²  George Rigas²  Dragana Miljkovic³  Barbara Koroušić Seljak⁴  Marko Bohanec³  Maria T. Arredondo⁵  Angelo Antonini⁶  Spyros Konitsiotis⁷  Dimitrios D. Koutsouris¹  Dimitrios I. Fotiadis² 

[1] Biomedical Engineering Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens;Unit of Medical Technology and Intelligent Information Systems, University of Ioannina;Department of Knowledge Technologies, Jozef Stefan Institute;Computer Systems Department, Jozef Stefan Institute;Universidad Politécnica de Madrid;Department for Parkinson's Disease;Department of Neurology, Medical School, University of Ioannina

关键词: diseases;    mobile computing;    telemedicine;    patient monitoring;    smart phones;    cognition;    decision support systems;    accelerometers;    gyroscopes;    optical sensors;    bio-optics;    cardiology;    temperature sensors;    skin temperature sensor;    optical heart rate sensor;    gyroscope;    accelerometers;    DSS;    decision support system;    cloud infrastructure;    nutrition;    mood;    cognition;    nonmotor self-evaluation tests;    PD motor symptoms;    smartphone;    insole sensors;    wrist sensors;    Parkinson's disease patient management;    mobile health platform;    mHealth platform;    PD_Manager;   

DOI  :  10.1049/htl.2017.0007

学科分类：肠胃与肝脏病学

来源: Wiley

【 摘 要 】

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.

【 授权许可】

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