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  • 标题:Detection of signs of Parkinson’s disease using dynamical features via an indirect pointing device ⁎
  • 本地全文:下载
  • 作者:Rosane Ushirobira ; Denis Efimov ; Géry Casiez
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2020
  • 卷号:53
  • 期号:2
  • 页码:16347-16352
  • DOI:10.1016/j.ifacol.2020.12.664
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractIn this paper, we study the problem of detecting early signs of Parkinson’s disease during an indirect human-computer interaction via a computer mouse activated by a user. The experimental setup provides a signal determined by the screen pointer position. An appropriate choice of segments in the cursor position raw data provides a filtered signal from which a number of quantifiable criteria can be obtained. These dynamical features are derived based on control theory methods. Thanks to these indicators, a subsequent analysis allows the detection of users with tremor. Real-life data from patients with Parkinson’s and healthy controls are used to illustrate our detection method.
  • 关键词:KeywordsQuantification of physiological parameters for diagnosistreatment assessmentDevelopments in measurementsignal processingControl of physiologicalclinical variables
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