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Supervised threshold-based heart sound classification algorithm
Physiological Measurement, 2018Deep classification networks have been one of the predominant methods for classifying heart sound recordings. To satisfy their demand for sample size, the most commonly used method for data augmentation is that which divides each heart sound instance into a number of segments, with each segment labelled as the same category as its origin and used as a ...
Wei, Han +3 more
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Phonocardiogram signals classification into normal heart sounds and heart murmur sounds
2016 11th International Conference on Intelligent Systems: Theories and Applications (SITA), 2016Heart disease is the biggest killer in the world, it is a serious public health problem facing the world today. This problem has not only attracted the attention of doctors and cardiologists, but also that of signal processing specialists who seek to effectively detect this disease by treating cardiac signals.
Fatima Chakir +3 more
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Heart Sounds Classification Using Hybrid CNN Architecture
5th International Students Science Congress, 2021In this paper, we propose a hybrid model for diagnosing heart conditions by analyzing heart sounds and signals. The Hybrid CNN (Convolutional Neural Network) model is trained to classify distinguishable pathological heart sounds into three classes; normal, murmur, and extrasystole.
Mohammed Mansur Abubakar, Taner Tuncer
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Abnormal heart sound classification using phonocardiography signals
Smart Health, 2021Abstract An intelligent support system is needed to assist in the identification of abnormalities of a human heart. The integration of signal processing with machine learning techniques is a new research trend in the studies of heart sound analysis.
M.G.M. Milani +3 more
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Unsupervised classification of heart sound recordings
2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 2013An unsupervised framework for classifying heart sound data is proposed in this paper. Our goal is to cluster unknown heart sound recordings, such that each cluster contains sound recordings belonging to the same heart diseases or normal heart beat category.
Wei-Ho Tsai, Sung-How Su, Cin-Hao Ma
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Multimodal classification of heart sounds attributes
2014 Pan American Health Care Exchanges (PAHCE), 2014Pollution and associated negative impacts on human health is one of the major concerns of the World Health Organization and healthcare providers. Current interests focus on particles suspended in air known as PM 10 which significantly contribute to increased prevalence of heart disease.
P. Mayorga +3 more
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Segmentation and classification of heart sounds
Canadian Conference on Electrical and Computer Engineering, 2005., 2006An algorithm for segmentation of heart sounds (HSs) into a single cardiac cycle (Sl-Systole-S2-Diastole) using homomorphic filtering and k-means clustering and a three way classification of heart sounds into normal (N), systolic murmur (S), and diastolic murmur (D), based on neural networks is developed.
C.N. Gupta +4 more
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Multi-label classification of heart sound signals
2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI), 2021In recent years, with the development of heart sound classification technology, it has played an important role in the detection of congenital heart disease. However, in the traditional heart sound classification tasks, they are all two classification tasks.
Li Zhiming, Miao Sheng
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Heart sound localization in chest sound using temporal fuzzy c-means classification
2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012Most of heart sound cancellation algorithms to improve the quality of lung sound use information about heart sound locations. Therefore, a reliable estimation of heart sound localizations within chest sound is a key issue to enhance the performance of heart sound cancellation algorithms.
ÖZBEK, İbrahim Yücel, SHAMSİ, HAMED
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Cluster analysis and classification of heart sounds
Biomedical Signal Processing and Control, 2009Acoustic heart signals, generated by the mechanical processes of the cardiac cycle, carry significant information about the underlying functioning of the cardiovascular system. We describe a computational analysis framework for identifying distinct morphologies of heart sounds and classifying them into physiological states.
Guy Amit, Noam Gavriely, Nathan Intrator
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