December 10, 2024
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Review

Evaluating Motor Symptoms in Parkinson's Disease Through Wearable Sensors: A Systematic Review of Digital Biomarkers

Publicated to: Applied Sciences-Basel. 14 (22): 10189- - 2024-11-01 14(22), DOI: 10.3390/app142210189

Authors:

Polvorinos-Fernández, C; Sigcha, L; Borzì, L; Olmo, G; Asensio, C; López, JM; de Arcas, G; Pavón, I
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Affiliations

Politecn Torino, Dept Control & Comp Engn, I-10129 Turin, Italy - Author
Univ Limerick, Data Driven Comp Engn Res Ctr D2iCE, Dept Phys Educ & Sport Sci PESS, Limerick V94T9PX, Ireland - Author
Univ Limerick, Hlth Res Inst HRI, Limerick V94T9PX, Ireland - Author
Univ Politecn Madrid, Dept Audiovisual Engn & Commun, Instrumentat & Appl Acoust Res Grp I2A2, ETS Ingn & Sistemas Telecomunicac, Madrid 28031, Spain - Author
Univ Politecn Madrid, Dept Mech Engn, Instrumentat & Appl Acoust Res Grp I2A2, ETS Ingn Ind, Madrid 28006, Spain - Author
Univ Politecn Madrid, Dept Phys Elect Elect Engn & Appl Phys, Instrumentat & Appl Acoust Res Grp I2A2, ETS Ingn & Sistemas Telecomunica, Madrid 28031, Spain - Author
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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.
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Keywords

'currentBody-worn sensorsDefinitionsDeviceDiagnosisDigital biomarkerDigital biomarkersFerroelectric ramKey featureMachine learninMachine learningMachine-learningMotor symptomMotor symptomsNeurodegenerative diseasesNeurodegenerative disordersNoninvasive medical proceduresParkinson's diseaseParkinson’s diseasePatient monitoringProgressionSystematic reviewTechnologyWearableWearable computersWearables

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Applied Sciences-Basel due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2024 there are still no calculated indicators, but in 2023, it was in position 50/179, thus managing to position itself as a Q2 (Segundo Cuartil), in the category Engineering, Multidisciplinary. Notably, the journal is positioned en el Cuartil Q2 para la agencia Scopus (SJR) en la categoría Engineering (Miscellaneous).

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-25:

  • Google Scholar: 8
  • WoS: 6
  • Scopus: 5
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-25:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 38.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 34 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 5.
  • The number of mentions on the social network X (formerly Twitter): 6 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/89109/

As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

  • Views: 167
  • Downloads: 174
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Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Italy; United Kingdom.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (POLVORINOS FERNANDEZ, CARLOS) and Last Author (PAVON GARCIA, IGNACIO).

the author responsible for correspondence tasks has been PAVON GARCIA, IGNACIO.

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Awards linked to the item

This research has been possible thanks to the financing of the project BIOCLITE PID2021-123708OB-I00, funded by MCIN/AEI/10.13039/501100011033/FEDER, EU.
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