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A New Paradigm in Parkinson's Disease Evaluation With Wearable Medical Devices: A Review of STAT-ON(TM)

In the past decade, the use of wearable medical devices has been a great breakthrough in clinical practice, trials, and research. In the Parkinson's disease field, clinical evaluation is time limited, and healthcare professionals need to rely on retrospective data collected through patients...

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Autores principales: Rodríguez-Martín, Daniel, Cabestany, Joan, Pérez-López, Carlos, Pie, Marti, Calvet, Joan, Samà, Albert, Capra, Chiara, Català, Andreu, Rodríguez-Molinero, Alejandro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9202426/
https://www.ncbi.nlm.nih.gov/pubmed/35720090
http://dx.doi.org/10.3389/fneur.2022.912343
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author Rodríguez-Martín, Daniel
Cabestany, Joan
Pérez-López, Carlos
Pie, Marti
Calvet, Joan
Samà, Albert
Capra, Chiara
Català, Andreu
Rodríguez-Molinero, Alejandro
author_facet Rodríguez-Martín, Daniel
Cabestany, Joan
Pérez-López, Carlos
Pie, Marti
Calvet, Joan
Samà, Albert
Capra, Chiara
Català, Andreu
Rodríguez-Molinero, Alejandro
author_sort Rodríguez-Martín, Daniel
collection PubMed
description In the past decade, the use of wearable medical devices has been a great breakthrough in clinical practice, trials, and research. In the Parkinson's disease field, clinical evaluation is time limited, and healthcare professionals need to rely on retrospective data collected through patients' self-filled diaries and administered questionnaires. As this often leads to inaccurate evaluations, a more objective system for symptom monitoring in a patient's daily life is claimed. In this regard, the use of wearable medical devices is crucial. This study aims at presenting a review on STAT-ON(TM), a wearable medical device Class IIa, which provides objective information on the distribution and severity of PD motor symptoms in home environments. The sensor analyzes inertial signals, with a set of validated machine learning algorithms running in real time. The device was developed for 12 years, and this review aims at gathering all the results achieved within this time frame. First, a compendium of the complete journey of STAT-ON(TM) since 2009 is presented, encompassing different studies and developments in funded European and Spanish national projects. Subsequently, the methodology of database construction and machine learning algorithms design and development is described. Finally, clinical validation and external studies of STAT-ON(TM) are presented.
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spelling pubmed-92024262022-06-17 A New Paradigm in Parkinson's Disease Evaluation With Wearable Medical Devices: A Review of STAT-ON(TM) Rodríguez-Martín, Daniel Cabestany, Joan Pérez-López, Carlos Pie, Marti Calvet, Joan Samà, Albert Capra, Chiara Català, Andreu Rodríguez-Molinero, Alejandro Front Neurol Neurology In the past decade, the use of wearable medical devices has been a great breakthrough in clinical practice, trials, and research. In the Parkinson's disease field, clinical evaluation is time limited, and healthcare professionals need to rely on retrospective data collected through patients' self-filled diaries and administered questionnaires. As this often leads to inaccurate evaluations, a more objective system for symptom monitoring in a patient's daily life is claimed. In this regard, the use of wearable medical devices is crucial. This study aims at presenting a review on STAT-ON(TM), a wearable medical device Class IIa, which provides objective information on the distribution and severity of PD motor symptoms in home environments. The sensor analyzes inertial signals, with a set of validated machine learning algorithms running in real time. The device was developed for 12 years, and this review aims at gathering all the results achieved within this time frame. First, a compendium of the complete journey of STAT-ON(TM) since 2009 is presented, encompassing different studies and developments in funded European and Spanish national projects. Subsequently, the methodology of database construction and machine learning algorithms design and development is described. Finally, clinical validation and external studies of STAT-ON(TM) are presented. Frontiers Media S.A. 2022-06-02 /pmc/articles/PMC9202426/ /pubmed/35720090 http://dx.doi.org/10.3389/fneur.2022.912343 Text en Copyright © 2022 Rodríguez-Martín, Cabestany, Pérez-López, Pie, Calvet, Samà, Capra, Català and Rodríguez-Molinero. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neurology
Rodríguez-Martín, Daniel
Cabestany, Joan
Pérez-López, Carlos
Pie, Marti
Calvet, Joan
Samà, Albert
Capra, Chiara
Català, Andreu
Rodríguez-Molinero, Alejandro
A New Paradigm in Parkinson's Disease Evaluation With Wearable Medical Devices: A Review of STAT-ON(TM)
title A New Paradigm in Parkinson's Disease Evaluation With Wearable Medical Devices: A Review of STAT-ON(TM)
title_full A New Paradigm in Parkinson's Disease Evaluation With Wearable Medical Devices: A Review of STAT-ON(TM)
title_fullStr A New Paradigm in Parkinson's Disease Evaluation With Wearable Medical Devices: A Review of STAT-ON(TM)
title_full_unstemmed A New Paradigm in Parkinson's Disease Evaluation With Wearable Medical Devices: A Review of STAT-ON(TM)
title_short A New Paradigm in Parkinson's Disease Evaluation With Wearable Medical Devices: A Review of STAT-ON(TM)
title_sort new paradigm in parkinson's disease evaluation with wearable medical devices: a review of stat-on(tm)
topic Neurology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9202426/
https://www.ncbi.nlm.nih.gov/pubmed/35720090
http://dx.doi.org/10.3389/fneur.2022.912343
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