A novel electrocardiogram arrhythmia classification method based on stacked sparse auto-encoders and softmax regression

• المؤلفون الرئيسيون: Yang, Jianli, Bai, Yang, Lin, Feng, Liu, Ming, Hou, Zengguang, Liu, Xiuling
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2020
• الموضوعات: Engineering::Computer science and engineering; Stacked Sparse Auto-encoders; ECG Arrhythmia Classification
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/139611
• المؤسسة: Nanyang Technological University

Arrhythmia classification is crucial in electrocardiogram (ECG) based automatic cardiovascular disease diagnosis, e.g., to help prevent stroke or sudden cardiac death. However, the complex individual differences in ECG morphology make it challenging in accurately categorizing arrhythmia heartbeats....