On ECG reconstruction using weighted-compressive sensing

Healthcare Technology Letters

article

Dornoosh Zonoobi¹  Ashraf A. Kassim¹ 

[1] Department of Electrical and Computer Engineering, National University of Singapore

关键词: electrocardiography;    medical signal processing;    signal reconstruction;    probability;    discrete wavelet transforms;    compressed sensing;    miniaturised wearable ECG monitoring devices;    discrete wavelet transform-based method;    probability model;    ECG signals;    weighted-compressive sensing;    electrocardiograph signal reconstruction;   

DOI  :  10.1049/htl.2013.0038

学科分类：肠胃与肝脏病学

来源: Wiley

【 摘 要 】

The potential of the new weighted-compressive sensing approach for efficient reconstruction of electrocardiograph (ECG) signals is investigated. This is motivated by the observation that ECG signals are hugely sparse in the frequency domain and the sparsity changes slowly over time. The underlying idea of this approach is to extract an estimated probability model for the signal of interest, and then use this model to guide the reconstruction process. The authors show that the weighted-compressive sensing approach is able to achieve reconstruction performance comparable with the current state-of-the-art discrete wavelet transform-based method, but with substantially less computational cost to enable it to be considered for use in the next generation of miniaturised wearable ECG monitoring devices.

【 授权许可】

CC BY|CC BY-ND|CC BY-NC|CC BY-NC-ND