Wrist Pulse Signal Classification for Health Diagnosis

摘要：

Ancient Indian and Chinese medicine both use noninvasive wrist pulse signals for health diagnosis of patients. In this paper, data obtained from a number of patients have been used to categorize the types of pulse signals that are found in both normal and abnormal health conditions. Features were extracted from the pulse signals using both frequency and wavelet transformations and these were then ranked according to their classification power for multiclass classifier design. Linear and quadratic pulse classifiers are proposed with raw features as well as subset of ranked features. Linear classifier has found to be giving highest classification accuracy of 73.82％ using 4 ranked features.

关键词： Wrist Pulse Segment Discrete Wavelet Transform Linear Classifier Weighted Ranking Quadratic Classifier

作者: Bhaskar Thakker Anoop Lai Vyas Omar Farooq David Mulvaney Sekharjit Datta

作者单位: Instrument Design Development Centre Indian Institute of Technology Delhi New Delhi, India Dept. of Electronics Engineering ZH College of Engineering and Technology Aligarh Muslim University Department of Electronic and Electrical Engineering Loughborough University United Kingdom

会议类型: 国际会议

会议名称: 2011 4th International Conference on Biomedical Engineering and Informatics(第四届生物医学工程与信息学国际会议 BMEI 2011)

会议地点: 上海

会议语种:英文

页码: 1811-1817

在线出版日期: 2011-10-15（万方平台首次上网日期，不代表论文的发表时间）