Key result
Adapted ICA and PCA improve ECG-derived respiration accuracy over standard KPCA.
Why the study?
A growing trend toward ambulatory measurements outside laboratory environments encourages developing indirect measurement methods such as ECG-derived respiration, and existing decomposition techniques require further performance improvements.
Demonstrates improved respiratory signal extraction from single-channel electrocardiograms using adapted component analysis, indicating enhanced potential for ambulatory patient monitoring.
Respiration is an important signal in early diagnostics, prediction, and treatment of several diseases. Moreover, a growing trend toward ambulatory measurements outside laboratory environments encourages developing indirect measurement methods such as ECG derived respiration (EDR). Recently, decomposition techniques like principal component analysis (PCA), and its nonlinear version, kernel PCA (KPCA), have been used to derive a surrogate respiration signal from single-channel ECG. In this paper, we propose an adapted independent component analysis (AICA) algorithm to obtain EDR signal, and extend the normal linear PCA technique based on the best principal component (PC) selection (APCA, adapted PCA) to improve its performance further. We also demonstrate that the usage of smoothing spline resampling and bandpass-filtering improve the performance of all EDR methods. Compared with other recent EDR methods using correlation coefficient and magnitude squared coherence, the proposed AICA and APCA yield a statistically significant improvement with correlations 0.84, 0.82, 0.76 and coherences 0.90, 0.91, 0.85 between reference respiration and AICA, APCA and KPCA, respectively.
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Tiinanen et al. (2015) studied this question. Adapted independent component analysis (AICA) and adapted principal component analysis (APCA) for ECG-derived respiration vs. Kernel PCA (KPCA) and other recent EDR methods was evaluated on Correlation coefficient and magnitude squared coherence with reference respiration. Adapted ICA and PCA for ECG-derived respiration improved reference respiration correlation (0.84 and 0.82 vs 0.76 for KPCA) and coherence (0.90 and 0.91 vs 0.85).
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