%0 Conference Paper %1 6521192 %A Barma, Shovan %A Kuan, Ta-Wen %A Wu, Jaw-Shyang %A Tseng, Shih-Pang %A Wang, Jhing-Fa %B 2013 1st International Conference on Orange Technologies (ICOT) %D 2013 %K audio ecg machine-learning pcg tiny-hearts %P 201-204 %R 10.1109/ICOT.2013.6521192 %T A review on heart sound modeling: Fluid dynamics and signal processing perspective %U https://ieeexplore.ieee.org/abstract/document/6521192 %X Heart sounds are generated by the several mechanical movements, such as the heart valve leaflets, the blood flow in vessels etc., that can provide the useful information to understand the cardiovascular system in details. Auscultation (PCG) is a non-invasive, low cost and easily repeatable technique to observe the entire system behavior at a glance. Several works have been investigated to model the sounds from different aspects, including the signal processing, the fluid mechanic and the equivalent electrical analogy. However, all the works gave the limitations. Most of the signal processing literatures that are addressed the heuristic decision-based approach; on the other hand, the fluid mechanic-based works discussed the behavior of overall or particular part of the cardiovascular system. Besides, the acoustic signals from heart can be modeled with the help of behavior through the source generation. In this study, several modeling works of heart sound are inspected and categorized according to the literatures, thereafter the advantages and the limitations are discussed. An overall research direction will be conducted to combine the fluid mechanic, the acoustics and the signal processing in the study.

@inproceedings{6521192, abstract = {Heart sounds are generated by the several mechanical movements, such as the heart valve leaflets, the blood flow in vessels etc., that can provide the useful information to understand the cardiovascular system in details. Auscultation (PCG) is a non-invasive, low cost and easily repeatable technique to observe the entire system behavior at a glance. Several works have been investigated to model the sounds from different aspects, including the signal processing, the fluid mechanic and the equivalent electrical analogy. However, all the works gave the limitations. Most of the signal processing literatures that are addressed the heuristic decision-based approach; on the other hand, the fluid mechanic-based works discussed the behavior of overall or particular part of the cardiovascular system. Besides, the acoustic signals from heart can be modeled with the help of behavior through the source generation. In this study, several modeling works of heart sound are inspected and categorized according to the literatures, thereafter the advantages and the limitations are discussed. An overall research direction will be conducted to combine the fluid mechanic, the acoustics and the signal processing in the study.}, added-at = {2021-07-28T06:46:52.000+0200}, author = {Barma, Shovan and Kuan, Ta-Wen and Wu, Jaw-Shyang and Tseng, Shih-Pang and Wang, Jhing-Fa}, biburl = {https://www.bibsonomy.org/bibtex/25969d36287444484c812916e05525617/gameovercite}, booktitle = {2013 1st International Conference on Orange Technologies (ICOT)}, description = {A review on heart sound modeling: Fluid dynamics and signal processing perspective | IEEE Conference Publication | IEEE Xplore}, doi = {10.1109/ICOT.2013.6521192}, interhash = {c7d74a78a07ae4ba98547603a5dda39f}, intrahash = {5969d36287444484c812916e05525617}, keywords = {audio ecg machine-learning pcg tiny-hearts}, month = {March}, pages = {201-204}, timestamp = {2021-07-28T06:46:52.000+0200}, title = {A review on heart sound modeling: Fluid dynamics and signal processing perspective}, url = {https://ieeexplore.ieee.org/abstract/document/6521192}, year = 2013 }