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

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 severi...

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Autores principales: Tsiouris, Kostas M., Gatsios, Dimitrios, Rigas, George, Miljkovic, Dragana, Koroušić Seljak, Barbara, Bohanec, Marko, Arredondo, Maria T., Antonini, Angelo, Konitsiotis, Spyros, Koutsouris, Dimitrios D., Fotiadis, Dimitrios I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Institution of Engineering and Technology 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5496467/
https://www.ncbi.nlm.nih.gov/pubmed/28706727
http://dx.doi.org/10.1049/htl.2017.0007
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author Tsiouris, Kostas M.
Gatsios, Dimitrios
Rigas, George
Miljkovic, Dragana
Koroušić Seljak, Barbara
Bohanec, Marko
Arredondo, Maria T.
Antonini, Angelo
Konitsiotis, Spyros
Koutsouris, Dimitrios D.
Fotiadis, Dimitrios I.
author_facet Tsiouris, Kostas M.
Gatsios, Dimitrios
Rigas, George
Miljkovic, Dragana
Koroušić Seljak, Barbara
Bohanec, Marko
Arredondo, Maria T.
Antonini, Angelo
Konitsiotis, Spyros
Koutsouris, Dimitrios D.
Fotiadis, Dimitrios I.
author_sort Tsiouris, Kostas M.
collection PubMed
description 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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spelling pubmed-54964672017-07-13 PD_Manager: an mHealth platform for Parkinson's disease patient management Tsiouris, Kostas M. Gatsios, Dimitrios Rigas, George Miljkovic, Dragana Koroušić Seljak, Barbara Bohanec, Marko Arredondo, Maria T. Antonini, Angelo Konitsiotis, Spyros Koutsouris, Dimitrios D. Fotiadis, Dimitrios I. Healthc Technol Lett Special Issue: Addressing Age-related Conditions: technologies for early detection 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. The Institution of Engineering and Technology 2017-05-23 /pmc/articles/PMC5496467/ /pubmed/28706727 http://dx.doi.org/10.1049/htl.2017.0007 Text en http://creativecommons.org/licenses/by/3.0/ This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
spellingShingle Special Issue: Addressing Age-related Conditions: technologies for early detection
Tsiouris, Kostas M.
Gatsios, Dimitrios
Rigas, George
Miljkovic, Dragana
Koroušić Seljak, Barbara
Bohanec, Marko
Arredondo, Maria T.
Antonini, Angelo
Konitsiotis, Spyros
Koutsouris, Dimitrios D.
Fotiadis, Dimitrios I.
PD_Manager: an mHealth platform for Parkinson's disease patient management
title PD_Manager: an mHealth platform for Parkinson's disease patient management
title_full PD_Manager: an mHealth platform for Parkinson's disease patient management
title_fullStr PD_Manager: an mHealth platform for Parkinson's disease patient management
title_full_unstemmed PD_Manager: an mHealth platform for Parkinson's disease patient management
title_short PD_Manager: an mHealth platform for Parkinson's disease patient management
title_sort pd_manager: an mhealth platform for parkinson's disease patient management
topic Special Issue: Addressing Age-related Conditions: technologies for early detection
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5496467/
https://www.ncbi.nlm.nih.gov/pubmed/28706727
http://dx.doi.org/10.1049/htl.2017.0007
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