Classification of ECG anomaly with dynamically-biased LSTM for continuous cardiac monitoring

• Main Authors: Hu, Jinhai, Goh, Wang Ling, Gao, Yuan
• 其他作者: School of Electrical and Electronic Engineering
• 格式: Conference or Workshop Item
• 語言: English
• 出版: 2024
• 主題: Engineering; Long short-term memory; ECG classification; DB-LSTM
• 在線閱讀: https://hdl.handle.net/10356/179112; https://ieeexplore.ieee.org/abstract/document/10181690

This paper presents an electrocardiogram (ECG) signal classification model based on dynamically-biased Long Short-Term Memory (DB-LSTM) network. Compared to conventional LSTM networks, DB-LSTM introduces a set of parameters C which save the previous time-step cell gate states of the unit cell. Hence...