中国医疗设备2017，Vol.32Issue(5)：22-27,6.DOI:10.3969/j.issn.1674-1633.2017.05.006
基于SWT和ANN的无创连续血压测量方法研究
Noninvasive Continuous Blood Pressure Measurment Method Based on SWT and ANN
摘要
Abstract
In order to solve the problem of non-invasive continuous measurement of blood pressure in electronic sphygmomanometer, a non-invasive blood pressure measurement method based on stationary wavelet transform (SWT) algorithm and photoplethysmography were proposed. In the experiment, a total of 26900 pulse wave signals from the mimic database were analyzed and subsequently the pulse wave was decomposed by SWT. Furthermore, 10 characteristic parameters of the 5th layer high frequency reconstruction signal were extracted as the input of artificial neural networks (ANN). The blood pressure corresponding to the pulse wave was taken as the output of ANN to train the blood pressure model. The error analysis of the model was carried out. The results indicated that the error of the model met the standards of the American association for the advancement of medical instrumentation. Therefore, this method can be employed in noninvasive continuous measurement of blood pressure.关键词
血压/光电容积脉搏波/平稳小波变换/神经网络Key words
blood pressure/photoplethysmography/stationary wavelet transform/artificial neural networks分类
信息技术与安全科学引用本文复制引用
吴育东,钟舜聪,沈耀春..基于SWT和ANN的无创连续血压测量方法研究[J].中国医疗设备,2017,32(5):22-27,6.基金项目
国家自然科学基金资助项目(51675103) （51675103）
教育部高等学校博士学科点科研基金(博导类:20133514110008) （博导类:20133514110008）
国家卫生和计划生育委员会科研基金(WKJ-FJ-27) （WKJ-FJ-27）
福建省杰出青年基金(滚动资助计划,2014J07007). （滚动资助计划,2014J07007）
