期刊
FRONTIERS IN NEUROLOGY
卷 11, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fneur.2020.610614
关键词
Parkinson's disease; hypokinesia; movement disorder; technology; computer assisted diagnosis
资金
- Capital Region of Denmark
- Research Fund for Health Promotion
- Capital Region of Denmark, Mental Health Services Research Fund
- Lundbeck Foundation
The developed Motorgame was able to detect common motor symptoms in Parkinson's disease in a statistically significant and clinically meaningful way, with the strongest effects observed in the right hand, showing promise for further testing in larger samples.
Background: Current assessments of motor symptoms in Parkinson's disease are often limited to clinical rating scales. Objectives: To develop a computer application using the Microsoft Kinect sensor to assess performance-related bradykinesia. Methods: The developed application (Motorgame) was tested in patients with Parkinson's disease and healthy controls. Participants were assessed with the Movement Disorder Society Unified Parkinson's disease Rating Scale (MDS-UPDRS) and standardized clinical side effect rating scales, i.e., UKU Side Effect Rating Scale and Simpson-Angus Scale. Additionally, tests of information processing (Symbol Coding Task) and motor speed (Token Motor Task), together with a questionnaire, were applied. Results: Thirty patients with Parkinson's disease and 33 healthy controls were assessed. In the patient group, there was a statistically significant (p < 0.05) association between prolonged time of motor performance in the Motorgame and upper body rigidity and bradykinesia (MDS-UPDRS) with the strongest effects in the right hand (p < 0.001). In the entire group, prolonged time of motor performance was significantly associated with higher Simson-Angus scale rigidity score and higher UKU hypokinesia scores (p < 0.05). A shortened time of motor performance was significantly associated with higher scores on information processing (p < 0.05). Time of motor performance was not significantly associated with Token Motor Task, duration of illness, or hours of daily physical activity. The Motorgame was well-accepted. Conclusions: In the present feasibility study the Motorgame was able to detect common motor symptoms in Parkinson's disease in a statistically significant and clinically meaningful way, making it applicable for further testing in larger samples.
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