A model-free technique based on computer vision and sEMG for classification in Parkinson's disease by using computer-assisted handwriting analysis
A model-free technique based on computer vision and sEMG for classification in Parkinson's disease by using computer-assisted handwriting analysis
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DOI：
10.1016/j.patrec.2018.04.006
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发表时间：
2019-04
期刊：
影响因子：
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通讯作者：
Claudio Loconsole;Giacomo Donato Cascarano;Antonio Brunetti;Gianpaolo Francesco Trotta;Giacomo Losavio;Vitoantonio Bevilacqua;E. Sciascio
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文献类型：
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作者：
Claudio Loconsole;Giacomo Donato Cascarano;Antonio Brunetti;Gianpaolo Francesco Trotta;Giacomo Losavio;Vitoantonio Bevilacqua;E. Sciascio
患有帕金森病的患者的特征在于异常的手写活动，因为他们在运动协调方面有困难并且认知能力下降。在本文中，我们提出了一种无模型的技术，用于区分帕金森氏病患者从健康受试者通过使用手写分析工具，基于计算机视觉和表面肌电图（sEMG）信号处理技术和人工智能为基础的分类器。使用所提出的技术对健康和帕金森病患者进行了实验测试，以解决一些具体的研究科学问题，这些问题涉及最具代表性的特征，最佳书写模式，ANN最佳拓扑结构和SVM方法之间的最佳基于AI的分类方法，以及结果的准确性和可重复性。最后，报告并讨论了所获得的结果，以推断书写模式、分类方法以及肌肉活动在手写分析应用于神经退行性疾病研究中的作用的一些重要性质。
Patients suffering from Parkinson’s disease are characterized by an abnormal handwriting activity since they have difficulties in motor coordination and a decline in cognition. In this paper, we propose a model-free technique for differentiating Parkinson’s disease patients from healthy subjects by using a handwriting analysis tool based on computer vision and surface ElectroMyoGraphy (sEMG) signal-processing techniques and an Artificial Intelligence-based classifier. Experimental tests have been conducted with both healthy and Parkinson’s Disease patients using the proposed technique to address some specific research scientific questions regarding most representative features, best writing patterns, best AI-based classification approach between ANN optimal topology and SVM approaches in terms of both accuracy and repeatability of the results. Finally, the obtained results are reported and discussed to infer some important properties on writing patterns, classification approaches and the role of muscular activities on the handwriting analysis applied to neurodegenerative disease research.