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Multidimensional abnormal gait analysis and biomarker identification for patients with spinocerebellar ataxia type 3 using an Azure Kinect-based motion capture system.

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Title: Multidimensional abnormal gait analysis and biomarker identification for patients with spinocerebellar ataxia type 3 using an Azure Kinect-based motion capture system.
Authors: Cui, Mao-Lin1,2 (AUTHOR), Pan, Li-Ying1,3 (AUTHOR), Lin, Wei2 (AUTHOR), Huang, Zhuo-Ying2 (AUTHOR), Ye, Bei-Ning2 (AUTHOR), Li, Chu-Yi2 (AUTHOR), Ye, Ying-Xin2 (AUTHOR), Lin, Han2 (AUTHOR), Lin, Ming-Ting2,4,5 (AUTHOR), Wang, Ning1,2,4,5 (AUTHOR) ningwang@fjmu.edu.cn, Gan, Shi-Rui1,2,4,5 (AUTHOR) ganshirui@fjmu.edu.cn, Ma, Yun-Ru1,6 (AUTHOR) y.ma@fjmu.edu.cn
Source: Gait & Posture. Jan2026, Vol. 123, pN.PAG-N.PAG.
Database: SPORTDiscus with Full Text
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Header DbId: s3h
DbLabel: SPORTDiscus with Full Text
An: 189336821
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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        Value: 10.1016/j.gaitpost.2025.110019
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      – Text: English
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      – TitleFull: Multidimensional abnormal gait analysis and biomarker identification for patients with spinocerebellar ataxia type 3 using an Azure Kinect-based motion capture system.
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            NameFull: Cui, Mao-Lin
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            – D: 01
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              Text: Jan2026
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              Y: 2026
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