Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:135-138. doi: 10.1109/EMBC46164.2021.9630574.

Automatic segmentation for neonatal phonocardiogram.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

Sergi Gomez-Quintana, Ihor Shelevytsky, Victoriya Shelevytska, Emanuel Popovici, Andriy Temko

PMID: 34891256 DOI: 10.1109/EMBC46164.2021.9630574

Abstract

This work addresses the automatic segmentation of neonatal phonocardiogram (PCG) to be used in the artificial intelligence-assisted diagnosis of abnormal heart sounds. The proposed novel algorithm has a single free parameter - the maximum heart rate. The algorithm is compared with the baseline algorithm, which was developed for adult PCG segmentation. When evaluated on a large clinical dataset of neonatal PCG with a total duration of over 7h, an F1 score of 0.94 is achieved. The main features relevant for the segmentation of neonatal PCG are identified and discussed. The algorithm is able to increase the number of cardiac cycles by a factor of 5 compared to manual segmentation, potentially allowing to improve the performance of heart abnormality detection algorithms.

Publication Types

• Journal Article
• Research Support, Non-U.S. Gov't