An Automatic Subject-Adaptable Heartbeat Classifier Based on Multiview Learning

• Published in: IEEE journal of biomedical and health informatics Vol. 20; no. 6; pp. 1485 - 1492
• Main Authors: Can Ye, Vijaya Kumar, B. V. K., Tavares Coimbra, Miguel
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.11.2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptation models; Algorithms; Arrhythmia; Arrhythmias, Cardiac - physiopathology; Automatic subject adaptation; Classification; Databases, Factual; ECG heartbeat classification; Echocardiography; Electrocardiography; Electrocardiography - methods; Heart beat; Heart Rate - physiology; Humans; Indexing; Machine Learning; Model testing; multiview learning; Pattern analysis; Pattern matching; Pattern Recognition, Automated - methods; Signal Processing, Computer-Assisted; similar training data selection; Statistics; Training; Ventricle

In this paper, a novel subject-adaptable heartbeat classification model is presented, in order to address the significant interperson variations in ECG signals. A multiview learning approach is proposed to automate subject adaptation using a small amount of unlabeled personal data, without requiring...