Title :
An Ultra-Low Power QRS Complex Detection Algorithm Based on Down-Sampling Wavelet Transform
Author :
Yao Zou ; Jun Han ; Xinqian Weng ; Xiaoyang Zeng
Author_Institution :
State Key Lab. of ASIC & Syst., Fudan Univ., Shanghai, China
Abstract :
Low-power design has become a key technology for battery-power biomedical devices in Wireless Body Area Network. In order to meet the requirement of low-power dissipation for electrocardiogram related applications, a down-sampling QRS complex detection algorithm is proposed. Based on Wavelet Transform (WT), this letter characterizes the energy distribution of QRS complex corresponding to the frequency band of WT. Then this letter details for the first time the process of down-sampled filter design, and presents the time and frequency response of the filter. The algorithm is evaluated in fixed point on MIT-BIH and QT database. Compared with other existing results, our work reduces the power dissipation by 23%, 61%, and 72% for 1 ×, 2 ×, and 3 × down-sampling rate, respectively, while maintaining almost constant detection performance.
Keywords :
body area networks; electrocardiography; filters; frequency response; radio networks; wavelet transforms; WT; battery-power biomedical devices; down-sampled filter design; down-sampling wavelet transform; electrocardiogram; energy distribution; frequency response; low-power design; low-power dissipation; time response; ultra-low power QRS complex detection algorithm; wavelet transform; wireless body area network; Detection algorithms; Electrocardiography; Frequency response; Power dissipation; Signal processing algorithms; Wavelet transforms; Down-sampling; QRS complex detection; energy distribution; filter design; wavelet transform;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2013.2254475