文章基本信息

标题：Classification of Subjects with Parkinson’s Disease using Finger Tapping Dataset ⁎
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作者：Víctor Asanza ; Nadia N. Sánchez-Pozo ; Leandro L. Lorente-Leyva 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2021
卷号：54
期号：15
页码：376-381
DOI：10.1016/j.ifacol.2021.10.285
语种：English
出版社：Elsevier
摘要：AbstractParkinson’s disease is the second most common neurodegenerative disorder and affects more than 7 million people globally. In this work, we classify subjects with Parkinson’s disease using data from finger-tapping on a keyboard. We use a free database by Physionet with more than 9 million records, preprocessed to delete atypical data. In the feature extraction stage, we obtained 48 features. We use Google Colaboratory to train, validate, and test nine supervised learning algorithms that detect the disease. As a result, we achieve a degree of accuracy higher than 98%.
关键词：KeywordsParkinson’s diseaseClassificationMachine LearningFinger Tapping