Abstract:
This study proposes a personal healthcare system to monitor, identify ectopic heartbeats, and provide services to patients with heart diseases. The proposed system includ...Show MoreMetadata
Abstract:
This study proposes a personal healthcare system to monitor, identify ectopic heartbeats, and provide services to patients with heart diseases. The proposed system includes three subsystems: (1) an electrocardiography (ECG) signal acquisition device to acquire ECG signals accurately; (2) an Android-based smartphone to display the actual ECG waveform and upload the signal to the Web platform for analysis of cardiac disorder events; and (3) a Web platform for feature selection and arrhythmia classification with the support vector machine algorithm. The classification algorithm can identify three types of heartbeats, namely, normal, atrial premature beat, and premature ventricular contraction. The average sensitivity, specificity, and accuracy of the classification algorithm over the training set are 98.5%, 96.7%, and 97.7%, respectively.
Date of Conference: 28-30 September 2020
Date Added to IEEE Xplore: 23 November 2020
ISBN Information: