Version 1
: Received: 3 September 2024 / Approved: 4 September 2024 / Online: 4 September 2024 (08:32:41 CEST)
How to cite:
Polvorinos-Fernández, C.; Sigcha, L.; Borzì, L.; Olmo, G.; Asensio, C.; López, J. M.; de Arcas, G.; Pavón, I. Evaluating Mobility in Parkinson’s Disease through Wearable Sensors: A Systematic Review of Digital Biomarkers. Preprints2024, 2024090310. https://doi.org/10.20944/preprints202409.0310.v1
Polvorinos-Fernández, C.; Sigcha, L.; Borzì, L.; Olmo, G.; Asensio, C.; López, J. M.; de Arcas, G.; Pavón, I. Evaluating Mobility in Parkinson’s Disease through Wearable Sensors: A Systematic Review of Digital Biomarkers. Preprints 2024, 2024090310. https://doi.org/10.20944/preprints202409.0310.v1
Polvorinos-Fernández, C.; Sigcha, L.; Borzì, L.; Olmo, G.; Asensio, C.; López, J. M.; de Arcas, G.; Pavón, I. Evaluating Mobility in Parkinson’s Disease through Wearable Sensors: A Systematic Review of Digital Biomarkers. Preprints2024, 2024090310. https://doi.org/10.20944/preprints202409.0310.v1
APA Style
Polvorinos-Fernández, C., Sigcha, L., Borzì, L., Olmo, G., Asensio, C., López, J. M., de Arcas, G., & Pavón, I. (2024). Evaluating Mobility in Parkinson’s Disease through Wearable Sensors: A Systematic Review of Digital Biomarkers. Preprints. https://doi.org/10.20944/preprints202409.0310.v1
Chicago/Turabian Style
Polvorinos-Fernández, C., Guillermo de Arcas and Ignacio Pavón. 2024 "Evaluating Mobility in Parkinson’s Disease through Wearable Sensors: A Systematic Review of Digital Biomarkers" Preprints. https://doi.org/10.20944/preprints202409.0310.v1
Abstract
Parkinson's disease (PD) is the second most common neurodegenerative disorder, entailing several motor-related symptoms that contribute to a reduced quality of life in affected subjects. Recent advances in wearable technologies and computing resources have shown great potential for the assessment of PD-related symptoms. However, the potential applications (e.g., early diagnosis, prognosis and monitoring) and key features of digital biomarkers for motor symptoms of PD (DB-MS-PD) have not been comprehensively studied. This study aims to provide a state-of-the-art review of current digital biomarker definitions for PD, focusing on the use of wearable devices. This review systematically examines research articles from 2012 to 2024, focusing on key features and recent technologies in PD research. A total of 22 studies were included and thoroughly analyzed. Results indicate that DB-MS-PD can accurately distinguish patients with PD (PwPD) from healthy controls (HC), assess disease severity or treatment response, and detect motor symptoms. Large sample sizes, proper validation, non-invasive devices, and ecological monitoring make DB-MS-PD promising for improving PD management. Challenges include sample and method heterogeneity and lack of public datasets. Future studies can leverage evidence of the current literature to provide more effective and ready-to-use digital tools for monitoring PD.
Keywords
Parkinson’s disease; digital biomarkers; motor symptoms; wearables; body-worn sensors; machine learning
Subject
Engineering, Bioengineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
