5 research outputs found
Unsupervised ensembling of multiple software sensors: a new approach for electrocardiogram-derived respiration using one or two channels
While several electrocardiogram-derived respiratory (EDR) algorithms have
been proposed to extract breathing activity from a single-channel ECG signal,
conclusively identifying a superior technique is challenging. We propose
viewing each EDR algorithm as a {\em software sensor} that records the
breathing activity from the ECG signal, and ensembling those software sensors
to achieve a higher quality EDR signal. We refer to the output of the proposed
ensembling algorithm as the {\em ensembled EDR}. We test the algorithm on a
large scale database of 116 whole-night polysomnograms and compare the
ensembled EDR signal with four respiratory signals recorded from four different
hardware sensors. The proposed algorithm consistently improves upon other
algorithms, and we envision its clinical value and its application in future
healthcare