Suppr超能文献

手部震颤时间序列的特征。

Characteristics of hand tremor time series.

作者信息

Timmer J, Gantert C, Deuschl G, Honerkamp J

机构信息

Fakultät für Physik, Albert-Ludwigs-Universität, Freiburg, Germany.

出版信息

Biol Cybern. 1993;70(1):75-80. doi: 10.1007/BF00202568.

Abstract

Tremor is classified into physiological, essential, and parkinsonian tremor by means of clinical criteria. The aim of our work was to extract quantitative features from the measurements of the acceleration of human postural hand tremor. Different mathematical methods were adopted and modified in order to separate these three types of tremor. Best discrimination between physiological and pathological tremors has been achieved by methods distinguishing nonlinear from linear behavior. On the other hand, methods separating different forms of nonlinear behavior have been found to be superior in discriminating parkinsonian and essential tremor. By these methods physiological and pathological tremors can be separated with an error rate below 20% and essential and parkinsonian tremor with an error rate below 10%. This may help to classify tremor time series by objective mathematical criteria and may increase the understanding of the pathophysiological differences underlying these kinds of tremor.

摘要

通过临床标准,震颤可分为生理性震颤、特发性震颤和帕金森氏震颤。我们这项工作的目的是从人体姿势性手部震颤加速度的测量中提取定量特征。采用并修改了不同的数学方法以区分这三种类型的震颤。通过区分非线性行为和线性行为的方法,已实现了生理性震颤与病理性震颤之间的最佳区分。另一方面,已发现区分不同形式非线性行为的方法在区分帕金森氏震颤和特发性震颤方面更具优势。通过这些方法,生理性震颤与病理性震颤的分离错误率可低于20%,特发性震颤与帕金森氏震颤的分离错误率可低于10%。这可能有助于根据客观的数学标准对震颤时间序列进行分类,并可能加深对这些类型震颤背后病理生理差异的理解。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验