Acceso abierto

Preliminary study in the analysis of the severity of cardiac pathologies using the higher-order spectra on the heart-beats signals


Cite

1. World Health Organization.Cardiovascular diseases. https://www.who.int/westernpacific/health-topics/cardiovascular-diseases. Search in Google Scholar

2. Debbal SM. Computerized Heart Sounds Analysis. In: Discrete Wavelet Transforms: Biomedical Applications. IntechOpen, 2011. https://doi.org/10.5772/2370010.5772/23700 Search in Google Scholar

3. Li X, Zhong L, Luo L, et al. Synchronization control of pulsatile ventricular assist devices by combination usage of different physiological signals. Comput Assist Surg. 2019;24:105-112. https://doi.org/10.1080/24699322.2018.156008910.1080/24699322.2018.156008930760103 Search in Google Scholar

4. Ahmad MS, Mir J, Ullah MO, et al. An efficient heart murmur recognition and cardiovascular disorders classification system. Australas Phys Eng Sci Med. 2019;42:733-743. https://doi.org/10.1007/s13246-019-00778-x10.1007/s13246-019-00778-x31313129 Search in Google Scholar

5. Meziani F, Debbal SM, Atbi A. Analysis of phonocardiogram signals using wavelet transform. J Med Eng Technol. 2012;36:283-302. https://doi.org/10.3109/03091902.2012.68483010.3109/03091902.2012.68483022738192 Search in Google Scholar

6. Acharya UR, Sudarshan VK, Koh JEW, et al. Application of higher-order spectra for the characterization of Coronary artery disease using electrocardiogram signals. Biomed Signal Process Control. 2017;31:31-43. https://doi.org/10.1016/j.bspc.2016.07.00310.1016/j.bspc.2016.07.003 Search in Google Scholar

7. Mahmoodian N, Schaufler A, Pashazadeh A, et al. Proximal detection of guide wire perforation using feature extraction from bispectral audio signal analysis combined with machine learning. Comput Biol Med. 2019;107:10–17. https://doi.org/10.1016/j.compbiomed.2019.02.00110.1016/j.compbiomed.2019.02.00130769168 Search in Google Scholar

8. Vejdannik M, Sadr A. Automatic Microstructural Characterization and Classification Using Higher-Order Spectra on Ultrasound Signals. J Nondestruct Eval. 2016;35:16. https://doi.org/10.1007/s10921-015-0332-610.1007/s10921-015-0332-6 Search in Google Scholar

9. Bou Assi E, Gagliano L, Rihana S, et al. Bispectrum Features and Multilayer Perceptron Classifier to Enhance Seizure Prediction. Sci Rep. 2018;8:15491. https://doi.org/10.1038/s41598-018-33969-910.1038/s41598-018-33969-9619559430341370 Search in Google Scholar

10. Martis RJ, Acharya UR, Adeli H. Current methods in electrocardiogram characterization. Comput Biol Med. 2014;48:133-149. https://doi.org/10.1016/j.compbiomed.2014.02.01210.1016/j.compbiomed.2014.02.01224681634 Search in Google Scholar

11. Nikias CL, Mendel JM. Signal processing with higher-order spectra. IEEE Signal Process Mag. 1993;10(3):10-37. https://doi.org/10.1109/79.22132410.1109/79.221324 Search in Google Scholar

12. Du X, Dua S, Acharya RU, Chua CK. Classification of Epilepsy Using High-Order Spectra Features and Principle Component Analysis. J Med Syst. 2012;36:1731-1743. https://doi.org/10.1007/s10916-010-9633-610.1007/s10916-010-9633-621222222 Search in Google Scholar

13. Nasrolahzadeh M, Mohammadpoory Z, Haddadnia J. Higher-order spectral analysis of spontaneous speech signals in Alzheimer’s disease. Cogn Neurodyn. 2018;12:583-596. https://doi.org/10.1007/s11571-018-9499-810.1007/s11571-018-9499-8623332930483366 Search in Google Scholar

14. Mishra M, Pratiher S, Banerjee S, Mukherjee A. Grading heart sounds through variational mode decomposition and higher order spectral features. In: 2018 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) 1–5 (IEEE, 2018). https://doi.org/10.1109/I2MTC.2018.840962010.1109/I2MTC.2018.8409620 Search in Google Scholar

15. Mookiah MRK, Acharya UR, Lim CM, et al. Data mining technique for automated diagnosis of glaucoma using higher order spectra and wavelet energy features. Knowl-Based Syst. 2012;33:73-82. https://doi.org/10.1016/j.knosys.2012.02.01010.1016/j.knosys.2012.02.010 Search in Google Scholar

16. Zhou SM, Gan JQ, Sepulveda F. Classifying mental tasks based on features of higher-order statistics from EEG signals in brain– computer interface. Inf Sci.2008;178:1629-1640. https://doi.org/10.1016/j.ins.2007.11.01210.1016/j.ins.2007.11.012 Search in Google Scholar

17. Du X, Dua S, Acharya RU, Chua CK. Classification of Epilepsy Using High-Order Spectra Features and Principle Component Analysis. J Med Syst. 2012;36:1731-1743. https://doi.org/10.1007/s10916-010-9633-610.1007/s10916-010-9633-6 Search in Google Scholar

18. Yugesh CK, Hariharan M, Yuvaraj R, et al. Bispectral features and mean shift clustering for stress and emotion recognition from natural speech. Comput Electr Eng. 2017;62:676-691. https://doi.org/10.1016/j.compeleceng.2017.01.02410.1016/j.compeleceng.2017.01.024 Search in Google Scholar

19. Ahmad TJ, Ali H, Khan SA. Classification of Phonocardiogram using an Adaptive Fuzzy Inference System. Proc. Int. Conf. Image Process. Comput Vis Pattern Recognit. Proceedings of the 2009 International Conference on Image Processing, Computer Vision, & Pattern Recognition, IPCV 2009, July 13-16, 2009, Las Vegas, Nevada, USA. Search in Google Scholar

20. Meziani F, Debbal SM, Atbi A. Analysis of the pathological severity degree of aortic stenosis (AS) and mitral stenosis (MS) using the discrete wavelet transform (DWT). J Med Eng Technol. 2013;37:61-74. https://doi.org/10.3109/03091902.2012.73305810.3109/03091902.2012.73305823173773 Search in Google Scholar

21. Swami A, Mendel JM, Nikias CL. (1998). Higher-order spectral analysis toolbox. The Mathworks Inc, 3, 22-26. Search in Google Scholar

22. eGeneral Medical Inc. USA. eGeneralMedical.com. http://www.egeneralmedical.com/listohearmur.html Accessed 20 Apr 2018. Search in Google Scholar

23. http://www.cardiosource.com/heartsounds. Accessed 20 Apr 2018. Search in Google Scholar

eISSN:
1898-0309
Idioma:
Inglés
Calendario de la edición:
4 veces al año
Temas de la revista:
Medicine, Biomedical Engineering, Physics, Technical and Applied Physics, Medical Physics