Wearable sensor-based objective assessment of motor symptoms in Parkinson’s disease
Abstract
Effective management and development of new treatment strategies of motor symptoms in Parkinson's disease (PD) largely depend on clinical rating instruments like the Unified PD rating scale (UPDRS) and the modified abnormal involuntary movement scale (mAIMS). Regarding inter-rater variability and continuous monitoring, clinical rating scales have various limitations. Patient-administered questionnaires such as the PD home diary to assess motor stages and fluctuations in late-stage PD are frequently used in clinical routine and as clinical trial endpoints, but diary/questionnaire are tiring, and recall bias impacts on data quality, particularly in patients with cognitive dysfunction or depression. Consequently, there is a strong need for continuous and objective monitoring of motor symptoms in PD for improving therapeutic regimen and for usage in clinical trials. Recent advances in battery technology, movement sensors such as gyroscopes, accelerometers and information technology boosted the field of objective measurement of movement in everyday life and medicine using wearable sensors allowing continuous (long-term) monitoring. This systematic review summarizes the current wearable sensor-based devices to objectively assess the various motor symptoms of PD.
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Common consumer technologies such as smartphones have the advantages of widespread availability, low cost, and high sensor quality.
“common consumer technologies such as smartphones have the advantages of widespread availability, low cost, and high sensor quality.”
From Evaluation of smartphone‐based testing to generate exploratory outcome measures in a phase 1 Parkinson's disease clinical trial (2018) · cites this paper as [8]
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References 57 · Cited by 164
- Authors
- Ossig, C., Antonini, A., Buhmann, C., Classen, J., Csoti, I., Falkenburger, B., Schwarz, M., Winkler, J., & Storch, A.
- Affiliations
- Charité – Universitätsmedizin Berlin (DE)
- IRCCS San Camillo Hospital (IT)
- University Medical Center Hamburg-Eppendorf (DE)
- Leipzig University (DE)
- RWTH Aachen University (DE)
- Klinikum Dortmund (DE)
- Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
- German Center for Neurodegenerative Diseases (DZNE) Dresden (DE)
- Corresponding author
- Storch, Alexander
- ORCID
- Venue
- Journal of Neural Transmission
- Published
- 2015-08-08
- Volume
- 123
- Issue
- 1
- Pages
- 57-64
- ISSN
- 0300-9564 (ISSN-L)
- 1435-1463
- OpenAlex
- W1070793310
- Cited by
- 164
- References
- 57
- Citations by year
- 2026: 6 · 2025: 21 · 2024: 22 · 2023: 12 · 2022: 13 · 2021: 18 · 2020: 23 · 2019: 15 · 2018: 15 · 2017: 13 · 2016: 6
- FWCI
- 2.29
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Journal of Neural Transmission (publishedVersion)
- PubMed (publishedVersion)
- DZNE Pub (submittedVersion)
- RWTH Publications (RWTH Aachen) (submittedVersion)
- Padua Research Archive (University of Padova) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Health Sciences › Medicine › Neurology › Parkinson's Disease Mechanisms and Treatments
- Health Sciences › Health Professions › Physical Therapy, Sports Therapy and Rehabilitation › Balance, Gait, and Falls Prevention
- Keywords
- Parkinson's disease, wearable sensors, motor symptoms, objective assessment, continuous monitoring, accelerometer, gyroscope, Unified Parkinson's Disease Rating Scale, abnormal involuntary movements, motor fluctuations, clinical trial endpoints, patient-reported outcome questionnaires
- MeSH terms
- Humans, Movement, Parkinson Disease, Surveys and Questionnaires, Severity of Illness Index, Monitoring, Ambulatory, PubMed
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