The proposed down-sampling wavelet transform algorithm significantly reduces power dissipation for QRS detection in wearable ECG devices without compromising performance.
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May enable longer wearable ECG monitoring; leaves open prospective clinical validation of the down-sampling algorithm.
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.
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Zou et al. (2013) studied this question.
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