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Clinician versus machine: Reliability and responsiveness of motor endpoints in Parkinson's disease
Open accessAbstract
Background Enhancing the reliability and responsiveness of motor assessments required to demonstrate therapeutic efficacy is a priority for Parkinson's disease (PD) clinical trials. The objective of this study is to determine the reliability and responsiveness of a portable kinematic system for quantifying PD motor deficits as compared to clinical ratings.Methods Eighteen PD patients with subthalamic nucleus deep-brain stimulation (DBS) performed three tasks for evaluating resting tremor, postural tremor, and finger-tapping speed, amplitude, and rhythm while wearing a wireless motion-sensor unit (Kinesia) on the more-affected index finger. These tasks were repeated three times with DBS turned off and at each of 10 different stimulation amplitudes chosen to yield small changes in treatment response. Each task performance was video-recorded for subsequent clinician rating in blinded, randomized order. Test-retest reliability was calculated as intraclass correlation (ICC) and sensitivity was calculated as minimal detectable change (MDC) for each DBS amplitude.Results ICCs for Kinesia were significantly higher than those for clinician ratings of finger-tapping speed (p < 0.0001), amplitude (p < 0.0001), and rhythm (p < 0.05), but were not significantly different for evaluations of resting or postural tremor. Similarly, Kinesia scores yielded a lower MDC as compared with clinician scores across all finger-tapping subscores (p < 0.0001), but did not differ significantly for resting and postural tremor.Conclusions The Kinesia portable kinematic system can provide greater test-retest reliability and sensitivity to change than conventional clinical ratings for measuring bradykinesia, hypokinesia, and dysrhythmia in PD patients.
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“This clinical assessment is subject to bias from placebo effects, anxiety, or the opposite “white coat syndrome,” where patients apply an extra effort, resulting in a performance that does not fully reflect patients' abilities (107, 108).”
From A Review on Wearable Technologies for Tremor Suppression (2021) · cites this paper as [108]
Experimental — accuracy not yet measuredIn the citing paper
“In PD, wearables were used to detect and quantify cardinal motor symptoms including bradykinesia [19], tremor [20, 21], and postural sway [22, 23] as well as medication-evoked adverse symptoms such as dyskinesia [24–27] and motor fluctuations [28, 29].”
From Wearable sensors for clinical applications in epilepsy, Parkinson’s disease, and stroke: A mixed-methods systematic review (2018) · cites this paper as [21]
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Metadata
- Authors
- Heldman, D. A., Espay, A. J., LeWitt, P. A., & Giuffrida, J. P.
- Affiliations
- Great Lakes NeuroTechnologies (United States) (US)
- University of Cincinnati (US)
- Wayne State University (US)
- Corresponding author
- Heldman, Dustin A.
- Venue
- Parkinsonism & Related Disorders
- Publisher
- Elsevier BV
- Published
- 2014-06
- Volume
- 20
- Issue
- 6
- Pages
- 590-595
- ISSN
- 1353-8020 (ISSN-L)
- PMC
- PMC4028404
- OpenAlex
- W2020188512
- Cited by
- 156
- References
- 44
- Citations by year
- 2026: 7 · 2025: 7 · 2024: 14 · 2023: 13 · 2022: 13 · 2021: 16 · 2020: 11 · 2019: 18 · 2018: 18 · 2017: 10 · 2016: 21 · 2015: 7 · 2014: 1
- FWCI
- 8.43
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Parkinsonism & Related Disorders (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (1r43ns074627-01a1)
- National Institute of Mental Health (K23MH092735)
- National Institute of Neurological Disorders and Stroke (1R43NS074627-01A1, R44NS065554, R43 NS074627, R43NS081902)
- Topics
- Health Sciences › Medicine › Clinical Neurology › Deep Brain Stimulation and Movement Disorders
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Health Sciences › Medicine › Clinical Neurology › Parkinson's Disease Mechanisms and Treatments
- Keywords
- Parkinson's disease, motor function assessment
- MeSH terms
- Adult, Aged, Biomechanical Phenomena, Double-Blind Method, Female, Humans, Male, Middle Aged, Parkinson Disease, Psychomotor Disorders, Severity of Illness Index, Tremor, Video Recording, Reproducibility of Results, Hypokinesia, Subthalamic Nucleus, Deep Brain Stimulation
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