Journal
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
Volume 63, Issue 7, Pages 1377-1388Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TBME.2016.2549060
Keywords
Biomedical signal processing; electrocardiogram (ECG); electrocardiography; QRS; telemedicine
Categories
Funding
- Australian Research Council [LP0883728]
- Australian Research Council [LP0883728] Funding Source: Australian Research Council
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Objective: QRS detection algorithms are needed to analyze electrocardiogram (ECG) recordings generated in telehealth environments. However, the numerous published QRS detectors focus on clean clinical data. Here, a UNSW QRS detection algorithm is described that is suitable for clinical ECG and also poorer quality telehealth ECG. Methods: The UNSW algorithm generates a feature signal containing information about ECG amplitude and derivative, which is filtered according to its frequency content and an adaptive threshold is applied. The algorithm was tested on clinical and telehealth ECG and the QRS detection performance is compared to the Pan-Tompkins (PT) and Gutierrez-Rivas (GR) algorithm. Results: For the MIT-BIH Arrhythmia database (virtually artifact free, clinical ECG), the overall sensitivity (Se) and positive predictivity (+P) of the UNSW algorithm was >99%, which was comparable to PT and GR. When applied to the MIT-BIH noise stress test database (clinical ECG with added calibrated noise) after artifact masking, all three algorithms had overall Se >99%, and the UNSW algorithm had higher +P (98%, p < 0.05) than PT and GR. For 250 telehealth ECG records (unsupervised recordings; dry metal electrodes), the UNSW algorithm had 98% Se and 95% +P which was superior to PT (+P: p < 0.001) and GR (Se and +P: p < 0.001). Conclusion: This is the first study to describe a QRS detection algorithm for telehealth data and evaluate it on clinical and telehealth ECG with superior results to published algorithms. Significance: The UNSW algorithm could be used to manage increasing telehealth ECG analysis workloads.
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