Deterministic Compressed Domain Analysis ofMulti-channel ECG Measurements
Abstract
Continuous and long term acquisition of multi-channel ECG measurements are significant for diagnostic purposes. Compressive sensing has been proposed in the literature for obtaining continuous ECG measurements as it provides advantages including a reduced number of measurements, reduced power consumption and bandwidth for transmission. Reconstruction of the compressed ECG measurements is then done to analyze the measurements for diagnostic purposes. However, reconstruction of ECG measurements is computationally expensive. Therefore, in this paper, ECG analysis is carried out in the compressed domain without resorting to reconstruction. Multi-channel ECG measurements from MIT-BIH Arrhythmia database is used to validate the compressed domain ECG analysis. ECG signals are compressed at various compression ratios (CR) using morphology preserving deterministic sensing matrix. Structural similarity measures are used to quantitatively demonstrate the fidelity of the compressed measurements. R-peaks are detected in the compressed domain from compressed ECG measurements. Detection performance metrics such as sensitivity, positive predictivity and detection rate decrease as CR increases.
Cite
@article{arxiv.2002.09851,
title = {Deterministic Compressed Domain Analysis ofMulti-channel ECG Measurements},
author = {Dipayan Mitra and Sreeraman Rajan},
journal= {arXiv preprint arXiv:2002.09851},
year = {2020}
}
Comments
6 pages, 2 figures, Submitted at IEEE MeMeA 2020