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Abstract
Cardiac auscultation is a method used to listen heart sound. Condition of the heart can be predicted with cardiac auscultation because heart generates a specific rhythm of sound and any changes in the rhythm of the heart sound may be due to abnormalities of heart. Auscultation is an easy way to diagnose heart abnormalities; however, it needs training and years of physician’s experience to diagnose heart and identify any heart abnormalities. With years of experience, it is still difficult to analyze heart sound. The ability to automatically identify abnormalities or at least support physician decision is relevant to ease the reach of medical diagnosis using mobile or Digi-scope. This paper presents a novel approach for segmentation of S1 and S2 heart sounds by using some of the heart sounds temporal and spectral features. Our method differentiates between S1 and S2 heart sounds and also improves the results as compared to the three finalists.
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Authors and Affiliations
Department of Computer Engineering, College of Electrical and Mechanical Engineering, National University of Science and Technology, Islamabad, Pakistan
Shah Khalid, Ali Hassan, Sana Ullah & Farhan Riaz
- Shah Khalid
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- Ali Hassan
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- Sana Ullah
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- Farhan Riaz
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Correspondence toShah Khalid.
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Faculty of Science and Engineering, Saga University, Saga, Japan
Kohei Arai
The Science and Information (SAI) Organization, Bradford, UK
Supriya Kapoor
The Science and Information (SAI) Organization, Bradford, UK
Rahul Bhatia
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Khalid, S., Hassan, A., Ullah, S., Riaz, F. (2019). Segmentation of Heart Sound by Clustering Using Spectral and Temporal Features. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Systems and Applications. IntelliSys 2018. Advances in Intelligent Systems and Computing, vol 868. Springer, Cham. https://doi.org/10.1007/978-3-030-01054-6_24
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