  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.
