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  • 标题:Mankind Lifesaving from Cardiac Arrhythmia through Heart Beat Classification based on SMBO Technique
  • 本地全文:下载
  • 作者:K. Koteswara Rao ; B. Prasad Kumar ; V Srinivasa Rao
  • 期刊名称:International Journal of Computer Science and Network Security
  • 印刷版ISSN:1738-7906
  • 出版年度:2020
  • 卷号:20
  • 期号:11
  • 页码:182-187
  • DOI:10.22937/IJCSNS.2020.20.11.22
  • 出版社:International Journal of Computer Science and Network Security
  • 摘要:Unlike cardiovascular disease, which describes problems with the blood vessels and circulatory system as well as the heart, heart disease refers to issues and deformities in the heart itself. According to the Centers for Disease Control (CDC), heart disease is the leading cause of death in the United Kingdom, United States, Canada, and Australia. One in every four deaths in the U.S. Trusted Source occurs as a result of heart disease. Even though several methods are introduced to perform the heart beat classification by using the ECG signals, but classifying the heart beat by analyzing the cardiac arrhythmia is still a challenging task. Hence, an effective RNN-based SM-BS optimization algorithm is introduced in this work, which is the combination of the SMO and the BS algorithm. As the SMO and BSA are integrated together, the features from both the optimization will be utilized in the proposed work. As SMO uses the intelligent behavior and BSA mimics the foraging behavior, flight behavior, and vigilance behavior. Both these algorithms are effectively used to optimize the problem. Hence, this can be fused with the RNN to perform the beat classification in the proposed work.
  • 关键词:BSA; ECG; RNN; SMO; Abbreviations: BSA(Bird Swarm Algorithm); ECG (Electrocardiogram); RNN(Recurrent Neural Network); SMO(Spider Monkey Optimization)
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