Logistic Regression-HSMM-Based Heart Sound Segmentation

By David B. Springer, Lionel Tarassenko, G. Clifford. IEEE Transactions on Biomedical Engineering, 2016

517 citations recorded by the source corpus.

Subfields: Cardiology and Cardiovascular Medicine, Pulmonary and Respiratory Medicine, Signal Processing

View Paper: https://www.semanticscholar.org/paper/bce9112f4b9eab404ab2d230fbed2f3933681c39

How researchers see this paper

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In Signal Processing

1. Sridha Sridharan
2. Clinton Fookes

Citations in the corpus

• Deep Learning for Medical Anomaly Detection – A Survey (2020, methodology): “Similar to [88] the raw audio recordings were segmented to heart states using the algorithm of [90].”
• Real-time FDM machine condition monitoring and diagnosis based on acoustic emission and hidden semi-Markov model (2017, background): “Therefore HSMM is helpful to model signal segments and make inference for unobservable state based on observable sensor signals in the noisy environment [28,36].”