ECG Signals Classification Model Based on Frequency domain Features Coupled with Least Square Support Vector Machine (LSSVM)

Paper


Azeez, Rand Ameen, Alkhafaji, Sarmad K. D., Diykh, Mohammed and Abdulla, Shahab. 2022. "ECG Signals Classification Model Based on Frequency domain Features Coupled with Least Square Support Vector Machine (LSSVM)." Agma, Traina, Wang, Hua, Zhang, Yong, Siuly, Siuly, Zhou, Rui and Chen, Lui (ed.) 11th International Conference on Health Information Science (HIS 2022). Biarritz, France 28 - 30 Oct 2022 Switzerland. https://doi.org/10.1007/978-3-031-20627-6_28
Paper/Presentation Title

ECG Signals Classification Model Based on Frequency domain
Features Coupled with Least Square Support Vector Machine (LSSVM)

Presentation TypePaper
AuthorsAzeez, Rand Ameen (Author), Alkhafaji, Sarmad K. D. (Author), Diykh, Mohammed (Author) and Abdulla, Shahab (Author)
EditorsAgma, Traina, Wang, Hua, Zhang, Yong, Siuly, Siuly, Zhou, Rui and Chen, Lui
Journal or Proceedings TitleProceedings of the 11th International Conference on Health Information Science (HIS 2022)
Journal Citation13705, pp. 303-312
Number of Pages10
Year2022
Place of PublicationSwitzerland
ISBN9783031206269
9783031206276
Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-031-20627-6_28
Web Address (URL) of Paperhttps://link.springer.com/chapter/10.1007/978-3-031-20627-6_28
Web Address (URL) of Conference Proceedingshttps://link.springer.com/book/10.1007/978-3-031-20627-6
Conference/Event11th International Conference on Health Information Science (HIS 2022)
Event Details
11th International Conference on Health Information Science (HIS 2022)
Parent
International Conference on Health Information Science (HIS)
Event Date
28 to end of 30 Oct 2022
Event Location
Biarritz, France
Abstract

The electrocardiogram (ECG) is used to inspect the electrical activity of the heart through which experts can detect heart disorders. Mainly medical experts manually examine ECG patterns; however, manual inspection of ECG signals takes significant amount of time and effort as well as is prone to errors. As a result, researchers have started to design automatic models for ECG patterns classification. In this paper, we propose a novel ECG signals classification model that utilises frequency characteristics of ECG signals coupled with a least-squares support vector machine (LS-SVM). An Optimization Triple Half Band Filter Bank (OTHFB) is used to decompose ECG signals into 6 bands delta δδ, theta θθ, alpha αα, beta1 β1β1, beta2 β2β2, and gamma γγ. Then nine statistical features named {max, min, mean, mode, std, variance, skewness, rang, median} are extracted from each band and sent to the LS-SVM. The obtained results showed that the extracted features from the bands alpha αα, beta1 β1,β1, beta2 β2β2, gamma γγ gave a high classification accuracy compared bands delta δδ, theta θθ. The results showed that the proposed model achieved a high accuracy compared with the previous studies. An accuracy of 96% was obtained by the proposed model.

KeywordsECG, OTFB, statistical features, LSSVM
ANZSRC Field of Research 2020329999. Other biomedical and clinical sciences not elsewhere classified
Public Notes

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SeriesLecture Notes in Computer Science
Byline AffiliationsMinistry of Education, Iraqi
University of Thi-Qar, Iraq
USQ College
Institution of OriginUniversity of Southern Queensland
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Abdulla, Shahab A. and Wen, Peng. 2012. "The effects of time-delay on feedback control of depth of anesthesia." Zhang, Yuan-Ting, Naghavi, Morteza, Bonato, Paolo and Carmen, C. Y. Poon (ed.) 2012 IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics (BHI 2012). Hong Kong and Shenzhen, China 02 - 07 Jan 2012 Hong Kong, China. https://doi.org/10.1109/BHI.2012.6211747
Depth of anaesthesia control investigation using robust deadbeat control technique
Abdulla, Shahab and Wen, Peng. 2012. "Depth of anaesthesia control investigation using robust deadbeat control technique." Tetsuo, Kobayashi, Tetsuo, Touge, Hisao, Tachibana and Jinglong, Wu (ed.) 2012 International Conference on Complex Medical Engineering (ICME 2012). Kobe, Japan 01 - 04 Jul 2012 Piscataway, NJ. United States. https://doi.org/10.1109/ICCME.2012.6275636
Depth of anaesthesia control techniques and human body models
Abdulla, Shahab Anna. 2012. Depth of anaesthesia control techniques and human body models. PhD Thesis Doctor of Philosophy. University of Southern Queensland.
Convection drying process modeling and simulation study based on tomato
Shahab, Anna, Wen, Peng and Richard, George. 2009. "Convection drying process modeling and simulation study based on tomato." Giannoccaro, Nicola Ivan and Klingajay, Mongkorn (ed.) International Conference on Robotics, Informatics, Intelligence Control System Technology (RIIT 2009). Bangkok, Thailand 11 - 14 Dec 2009 Bangkok, Thailand.
Fruit drying process: analysis, modeling and simulation
Abdulla, Shahab, Wen, Paul, Landers, Richard and Yousif, B. F.. 2011. "Fruit drying process: analysis, modeling and simulation." Scientific Research and Essays. 6 (23), pp. 4915-4924.
Robust internal model control for depth of anaesthesia
Abdulla, Shahab Anna and Wen, Peng. 2011. "Robust internal model control for depth of anaesthesia." International Journal of Mechatronics and Automation. 1 (1), pp. 1-8. https://doi.org/10.1504/IJMA.2011.039150
The design and investigation of model based internal model control for the regulation of hypnosis
Abdulla, Shahab, Wen, Peng and Xiang, Wei. 2010. "The design and investigation of model based internal model control for the regulation of hypnosis." Kuo, Way, Tsui, Lap Chee and Sung, Jao Yiu (ed.) IEEE/NANOMED 2010: Promoting Good Health with Nanotechnology. Hong Kong, China 05 - 09 Dec 2010 Hong Kong. https://doi.org/10.1109/NANOMED.2010.5749833
Depth of anesthesia control using internal model control techniques
Anna, Shahab and Wen, Peng. 2010. "Depth of anesthesia control using internal model control techniques." Li, Yan, Yang, Jiajia, Wen, Peng and Wu, Jinglong (ed.) 2010 IEEE/ICME International Conference on Complex Medical Engineering (ICME 2010). Gold Coast, Australia 13 - 15 Jul 2010 Piscataway, NJ. United States. https://doi.org/10.1109/ICCME.2010.5558825