Deep Learning-Based Data-Point Precise R-Peak Detection in Single-Lead Electrocardiograms

Autor: M D, Oudkerk Pool, B D, de Vos, M M, Winter, I, Isgum
Přispěvatelé: Radiology and Nuclear Medicine, Biomedical Engineering and Physics, ACS - Atherosclerosis & ischemic syndromes, Amsterdam Neuroscience - Brain Imaging, ACS - Heart failure & arrhythmias, IvI Research (FNWI)
Rok vydání: 2021
Předmět:
Zdroj: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2021, 718-721. Institute of Electrical and Electronics Engineers Inc.
43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society: pre-conference workshops & social events: Saturday, October 30, 2021, conference dates: Monday, November 1-Friday, November 5, 2021, 718-721
STARTPAGE=718;ENDPAGE=721;TITLE=43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society
ISSN: 2694-0604
DOI: 10.1109/embc46164.2021.9630062
Popis: Low-cost wearables with capability to record electrocardiograms (ECG) are becoming increasingly available. These wearables typically acquire single-lead ECGs that are mainly used for screening of cardiac arrhythmias such as atrial fibrillation. Most arrhythmias are characteruzed by changes in the RR-interval, hence automatic methods to diagnose arrythmia may utilize R-peak detection. Existing R-peak detection methods are fairly accurate but have limited precision. To enable data-point precise detection of R-peaks, we propose a method that uses a fully convolutional dilated neural network. The network is trained and evaluated with manually annotated R-peaks in a heterogeneous set of ECGs that contain a wide range of cardiac rhythms and acquisition noise. 700 randomly chosen ECGs from the PhysioNet/CinC challenge 2017 were used for training (n=500), validation (n=100) and testing (n=100). The network achieves a precision of 0.910, recall of 0.926, and an F1-score of 0.918 on the test set. Our data-point precise R-peak detector may be important step towards fully automatic cardiac arrhythmia detection.Clinical relevance- This method enables data-point precise detection of R-peaks that provides a basis for detection and characterization of arrhythmias.
Databáze: OpenAIRE
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