Non-invasive Blood Glucose Estimation using Near-Infrared Spectroscopy based on SVR

摘要：

　　There is a nonlinear relation between the blood glucose and photoplethysmography(PPG)signal.In order to estimate the blood glucose from the photoplethysmography signal,this paper presents a non-invasive blood glucose estimation using Near-Infrared spectroscopy based on the Support Vector Regression(SVR).The wavelet transform algorithm is used to remove baseline drift and smooth signals.22 parameters,including features obtained from PPG signal and some physiological and environmental parameters,are the input parameters of Support Vector Regression model.The comparison between estimated and reference values shows better accuracy than the multiple linear regression analysis method,partial least squares method.

关键词： Blood Glucose Estimation PPG SVR Feature extraction NIR

作者: Yue Zhang Ziliang Wang

作者单位: Laboratory of Embedded Systems and Technology Graduate School at Shenzhen,Tsinghua University Shenzhen,China

会议类型: 国际会议

会议名称: 2017 IEEE 3rd Information Technology and Mechatronics Engineering Conference(ITOEC2017)(2017 IEEE 第3届信息技术与机电一体化工程国际学术会议)

会议地点: 重庆

会议语种:英文

页码: 594-598

在线出版日期: 2017-10-03（万方平台首次上网日期，不代表论文的发表时间）