New hybrid deep learning approach using bigru-bilstm and multilayered dilated cnn to detect arrhythmia

• Main Authors: Islam, Md Shofiqul, Islam, Md Nahidul, Noramiza, Hashim, Rashid, Mamunur, Bari, Bifta Sama, Al Farid, Fahmid
• Format: Article
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2022
• Subjects: QA75 Electronic computers. Computer science; QA76 Computer software; T Technology (General); TA Engineering (General). Civil engineering (General)
• Online Access: http://umpir.ump.edu.my/id/eprint/34932/1/New%20hybrid%20deep%20learning%20approach%20using%20bigru-bilstm%20and%20multilayered%20dilated%20cnn%20to%20detect%20arrhythmia.pdf; http://umpir.ump.edu.my/id/eprint/34932/; https://doi.org/10.1109/ACCESS.2022.3178710; https://doi.org/10.1109/ACCESS.2022.3178710

Deep learning methods have shown early progress in analyzing complicated ECG signals, especially in heartbeat classification and arrhythmia detection. However, there is still a long way to go in terms of health-related data analysis. This research provides a duel structured and bidirectional Recurre...