脉搏(音乐)
计算机科学
信号处理
人工智能
特征(语言学)
信号(编程语言)
领域(数学)
特征提取
模式识别(心理学)
医学
语音识别
数学
电信
雷达
语言学
探测器
哲学
程序设计语言
纯数学
作者
Zhichao Zhang,Yuan Zhang,Lina Yao,Houbing Song,Anton Kos
标识
DOI:10.1016/j.jbi.2018.01.009
摘要
Pulse diagnosis is an efficient method in traditional Chinese medicine for detecting the health status of a person in a non-invasive and convenient way. Jin's pulse diagnosis (JPD) is a very efficient recent development that is gradually recognized and well validated by the medical community in recent years. However, no acceptable results have been achieved for lung cancer recognition in the field of biomedical signal processing using JPD. More so, there is no standard JPD pulse feature defined with respect to pulse signals. Our work is designed mainly for care giving service conveniently at home to the people having lung cancer by proposing a novel wrist pulse signal processing method, having an insight from JPD. We developed an iterative slide window (ISW) algorithm to segment the de-noised signal into single periods. We analyzed the characteristics of the segmented pulse waveform and for the first time summarized 26 features to classify the pulse waveforms of healthy individuals and lung cancer patients using a cubic support vector machine (CSVM). The result achieved by the proposed method is found to be 78.13% accurate.
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