基于时域空间特征的腕部脉冲信号分析

D. Rangaprakash, D. Dutt
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引用次数: 11

摘要

腕部脉搏信号包含了一个人的健康状况的更重要的信息,脉冲信号诊断在东方医学中已经应用了很长时间。在本文中,我们使用信号处理技术从腕部脉搏信号中提取信息。为此,我们在不同的病例中无创地获取了腕位桡动脉脉搏信号。利用空间特征分析了腕部脉冲波形。在运动前和运动后记录了几个受试者的手腕脉搏信号。结果表明,空间特征在两种情况下均表现出统计学意义上的显著变化,因此它们可以有效地区分运动引起的变化。采用支持向量机分类器进行组间分类,分类准确率达到99.71%。因此,本文证明了空间特征在研究不同记录条件下获得的手腕脉冲信号中的实用性。模型区分在两种不同记录条件下发生的变化的能力可以潜在地用于医疗保健应用程序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of wrist pulse signals using spatial features in time domain
Wrist pulse signal contains more important information about the health status of a person and pulse signal diagnosis has been employed in oriental medicine since very long time. In this paper we have used signal processing techniques to extract information from wrist pulse signals. For this purpose we have acquired radial artery pulse signals at wrist position noninvasively for different cases of interest. The wrist pulse waveforms have been analyzed using spatial features. Results have been obtained for the case of wrist pulse signals recorded for several subjects before exercise and after exercise. It is shown that the spatial features show statistically significant changes for the two cases and hence they are effective in distinguishing the changes taking place due to exercise. Support vector machine classifier is used to classify between the groups, and a high classification accuracy of 99.71% is achieved. Thus this paper demonstrates the utility of the spatial features in studying wrist pulse signals obtained under various recording conditions. The ability of the model to distinguish changes occurring under two different recording conditions can be potentially used for healthcare applications.
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