Learning Hand Kinematics for Parkinson's Disease Assessment Using a Multimodal Sensor Glove
Abstract: Hand dysfunctions in Parkinson's disease include rigidity, muscle weakness, and tremor, which can severely affect the patient's daily life. Herein, a multimodal sensor glove is developed for quantifying the severity of Parkinson's disease symptoms in patients’ hands while assessing the hands’ multifunctionality. Toward signal processing, various algorithms are used to quantify and analyze each signal: Exponentially Weighted Average algorithm and Kalman filter are used to filter out noise, normalization to process bending signals, K‐Means Cluster Analysis to classify muscle strength grades, and Back Propagation Neural Network to identify and classify tremor signals with an accuracy of 95.83%. Given the compelling features, the flexibility, muscle strength, and stability assessed by the glove and the clinical observations are proved to be highly consistent with Kappa values of 0.833, 0.867, and 0.937, respectively. The intraclass correlation coefficients obtained by reliability evaluation experiments for the three assessments are greater than 0.9, indicating that the system is reliable. The glove can be applied to assist in formulating targeted rehabilitation treatments and improve hand recovery efficiency.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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Learning Hand Kinematics for Parkinson's Disease Assessment Using a Multimodal Sensor Glove ; day:07 ; month:05 ; year:2023 ; extent:10
Advanced science ; (07.05.2023) (gesamt 10)
- Creator
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Li, Yu
Yin, Junyi
Liu, Shuoyan
Xue, Bing
Shokoohi, Cyrus
Ge, Gang
Hu, Menglei
Li, Tenghuan
Tao, Xue
Rao, Zhi
Meng, Fanye
Shi, Hongfeng
Ji, Xiaoqiang
Servati, Peyman
Xiao, Xiao
Chen, Jun
- DOI
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10.1002/advs.202206982
- URN
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urn:nbn:de:101:1-2023050815101731631508
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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14.08.2025, 11:00 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Li, Yu
- Yin, Junyi
- Liu, Shuoyan
- Xue, Bing
- Shokoohi, Cyrus
- Ge, Gang
- Hu, Menglei
- Li, Tenghuan
- Tao, Xue
- Rao, Zhi
- Meng, Fanye
- Shi, Hongfeng
- Ji, Xiaoqiang
- Servati, Peyman
- Xiao, Xiao
- Chen, Jun
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