Quantification of Parkinsonian Bradykinesia Based on Axis-Angle Representation and SVM Multiclass Classification Method

Accurate evaluation of bradykinesia plays a crucial role in the diagnosis and therapy effect of Parkinson's disease. However, the subjective assessment shows low consistency among different evaluators, and the objective sensor-based methods cannot accurately distinguish patients with different...

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Veröffentlicht in:	IEEE access 2018-01, Vol.6, p.26895-26903
Hauptverfasser:	Zhirong Lin, Yongsheng Xiong, Guoen Cai, Houde Dai, Xuke Xia, Yandan Tan, Lueth, Tim C.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Classification Diseases Evaluation Feature extraction Gyroscopes Kalman filters Parkinson's disease Parkinsonian bradykinesia quantification Reliability analysis Representations sensor fusion Statistical analysis Subjective assessment support vector machine (SVM) Support vector machines Task analysis Three-dimensional displays wearable device
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