SynthesisJournal of neural transmission (Vienna, Austria : 1996)2019
Using wearables to assess bradykinesia and rigidity in patients with Parkinson's disease: a focused, narrative review of the literature.
Synthesis in Journal of neural transmission (Vienna, Austria : 1996), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
30 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Quantitative Measurement of Rigidity in Parkinson´s Disease: A Systematic Review.Sensors (Basel, Switzerland) · 2020Pooled it
- Quantitative Analysis of Axial Rigidity at Different Passive Movement Velocities in Parkinson's Disease: A Cross-Sectional Study.Journal of clinical medicine · 2026Article
- Electromyography (EMG) Signal Processing to Evaluate Low-Frequency Tremors.Sensors (Basel, Switzerland) · 2025Article
- Exploratory digital outcome measures of motor sign progression in Parkinson's disease patients treated with prasinezumab.NPJ digital medicine · 2025Article
- Digital gait biomarkers in Parkinson's disease: susceptibility/risk, progression, response to exercise, and prognosis.NPJ Parkinson's disease · 2025Review
- The future of Parkinson's care: a need to expand access.Frontiers in neurology · 2025Article
- Attributes, Methods, and Frameworks Used to Evaluate Wearables and Their Companion mHealth Apps: Scoping Review.JMIR mHealth and uHealth · 2024Article
- Sensor-Based Quantification of MDS-UPDRS III Subitems in Parkinson's Disease Using Machine Learning.Sensors (Basel, Switzerland) · 2024Article
- Time-resolved quantification of fine hand movements as a proxy for evaluating bradykinesia-induced motor dysfunction.Scientific reports · 2024Article
- Objective clinical registration of tremor, bradykinesia, and rigidity during awake stereotactic neurosurgery: a scoping review.Neurosurgical review · 2024Article
- Kinematic Effects of Combined Subthalamic and Dorsolateral Nigral Deep Brain Stimulation in Parkinson's Disease.Journal of Parkinson's disease · 2024Article
- Future Directions for Developing Non-dopaminergic Strategies for the Treatment of Parkinson's Disease.Current neuropharmacology · 2024Review
- A First Methodological Development and Validation of ReTap: An Open-Source UPDRS Finger Tapping Assessment Tool Based on Accelerometer-Data.Sensors (Basel, Switzerland) · 2023Article
- Clinical Evaluation in Parkinson's Disease: Is the Golden Standard Shiny Enough?Sensors (Basel, Switzerland) · 2023Article
- Wrist Rigidity Evaluation in Parkinson's Disease: A Scoping Review.Healthcare (Basel, Switzerland) · 2022Article
- Non-Contact Hand Movement Analysis for Optimal Configuration of Smart Sensors to Capture Parkinson's Disease Hand Tremor.Sensors (Basel, Switzerland) · 2022Article
- Intraoperative Quantification of MDS-UPDRS Tremor Measurements Using 3D Accelerometry: A Pilot Study.Journal of clinical medicine · 2022Article
- Digital Phenotyping in Clinical Neurology.Seminars in neurology · 2022Article
- Quantitative Digitography Measures Motor Symptoms and Disease Progression in Parkinson's Disease.Journal of Parkinson's disease · 2022Article
- The Disease Modification Conundrum in Parkinson's Disease: Failures and Hopes.Frontiers in aging neuroscience · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The potential of using wearable technologies for the objective assessment of motor symptoms in Parkinson's disease (PD) has gained prominence recently. Nonetheless, compared to tremor and gait impairment, less emphasis has been placed on the quantification of bradykinesia and rigidity. This review aimed to consolidate the existing research on objective measurement of bradykinesia and rigidity in PD through the use of wearables, focusing on the continuous monitoring of these two symptoms in free-living environments. A search of PubMed was conducted through a combination of keyword and MeSH searches. We also searched the IEEE, Google Scholar, Embase, and Scopus databases to ensure thorough results and to minimize the chances of missing relevant studies. Papers published after the year 2000 with sample sizes greater than five were included. Studies were assessed for quality and information was extracted regarding the devices used and their location on the body, the setting and duration of the study, the "gold standard" used as a reference for validation, the metrics used, and the results of each paper. Thirty-one and eight studies met the search criteria and evaluated bradykinesia and rigidity, respectively. Several studies reported strong associations between wearable-based measures and the gold-standard references for bradykinesia, and, to a lesser extent, rigidity. Only a few, pilot studies investigated the measurement of bradykinesia and rigidity in the home and free-living settings. While the current results are promising for the future of wearables, additional work is needed on their validation and adaptation in ecological, free-living settings. Doing so has the potential to improve the assessment and treatment of motor fluctuations and symptoms of PD more generally through real-time objective monitoring of bradykinesia and rigidity.
Indexed as
Identifiers
31115669What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.