A time-varying AR modeling of heart wall vibration
ICASSP '95 Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02
Neural network classification of homomorphic segmented heart sounds
Applied Soft Computing
Comparison of clustering algorithms for analog modulation classification
Expert Systems with Applications: An International Journal
Detection of valvular heart disorders using wavelet packet decomposition and support vector machine
Expert Systems with Applications: An International Journal
Selection of wavelet packet measures for insufficiency murmur identification
Expert Systems with Applications: An International Journal
Falling sheet envelope method for non-destructive testing time-dependent signals
Expert Systems with Applications: An International Journal
Automatic phonocardiograph signal analysis for detecting heart valve disorders
Expert Systems with Applications: An International Journal
Augmented phonocardiogram acquisition and analysis
FAC'11 Proceedings of the 6th international conference on Foundations of augmented cognition: directing the future of adaptive systems
Quality-driven wavelet based PCG signal coding for wireless cardiac patient monitoring
Proceedings of the 1st International Conference on Wireless Technologies for Humanitarian Relief
Development of a joint space width measurement method based on radiographic hand images
Computers in Biology and Medicine
Optimum heart sound signal selection based on the cyclostationary property
Computers in Biology and Medicine
Computers in Biology and Medicine
Phonocardiography signal segmentation for telemedicine environments
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advences in computational intelligence - Volume Part II
Hi-index | 12.06 |
This paper describes a comparative study of the envelope extraction algorithms for the cardiac sound signal segmentation. In order to extract the envelope curves based on the time elapses of the first and the second heart sounds of cardiac sound signals, three representative algorithms such as the normalized average Shannon energy, the envelope information of Hilbert transform, and the cardiac sound characteristic waveform (CSCW) are introduced. Performance comparison of the envelope extraction algorithms, and the advantages and disadvantages of the methods are examined by some parameters.