Key result
Alternating optimization algorithm for S2 separation achieves 0.76 auROC for detecting pulmonary hypertension.
Why the study?
Does a novel alternating optimization algorithm improve the blind source separation of the second heart sound into aortic and pulmonary components and enable the detection of pulmonary hypertension?
Does a novel alternating optimization algorithm improve the blind source separation of the second heart sound into aortic and pulmonary components and enable the detection of pulmonary hypertension?
Answers are grounded in this paper and cite their sources.
A novel unsupervised alternating optimization algorithm successfully separates the second heart sound into aortic and pulmonary components, enabling non-invasive detection of pulmonary hypertension with an auROC of 0.76.
An algorithm for blind source separation (BSS) of the second heart sound (S2) into aortic and pulmonary components is proposed. It recovers aortic (A2) and pulmonary (P2) waveforms, as well as their relative delays, by solving an alternating optimization problem on the set of S2 sounds, without the use of auxiliary ECG or respiration phase measurement data. This unsupervised and data-driven approach assumes that the A2 and P2 components maintain the same waveform across heartbeats and that the relative delay between onset of the components varies according to respiration phase. The proposed approach is applied to synthetic heart sounds and to real-world heart sounds from 43 patients. It improves over two state-of-the-art BSS approaches by 10% normalized root mean-squared error in the reconstruction of aortic and pulmonary components using synthetic heart sounds, demonstrates robustness to noise, and recovery of splitting delays. The detection of pulmonary hypertension (PH) in a Brazilian population is demonstrated by training a classifier on three scalar features from the recovered A2 and P2 waveforms, and this yields an auROC of 0.76.
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Renna et al. (2024) studied Pulmonary Hypertension (n=43). Alternating optimization algorithm for S2 sound separation vs. State-of-the-art blind source separation approach (Tang et al.) was evaluated on Detection of pulmonary hypertension (auROC). The proposed alternating optimization algorithm for separating the second heart sound into aortic and pulmonary components achieved an auROC of 0.76 for detecting pulmonary hypertension.
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