Abstract
Electrocardiogram (ECG) is widely used in the hospital emergency rooms for detecting vital signs, such as heart rate variability and respiratory rate. However, the quality of the ECGs is inconsistent. ECG signals lose information because of noise resulting from motion artifacts. To obtain an accurate information from ECG, signal quality indexing (SQI) is used where acceptable thresholds are set in order to select or eliminate the signals for the subsequent information extraction process. A good evaluation of SQI depends on the R-peak detection quality. Nevertheless, most R-peak detectors in the literature are prone to noise. This paper assessed and compared five peak detectors from different resources. The two best peak detectors were further tested using MIT-BIH arrhythmia database and then used for SQI evaluation. These peak detectors robustly detected the R-peak for signals that include noise. Finally, the overall SQI of three patient datasets, namely, Fantasia, CapnoBase, and MIMIC-II, was conducted by providing the interquartile range (IQR) and median SQI of the signals as the outputs. The evaluation results revealed that the R-peak detectors developed by Clifford and Behar showed accuracies of 98% and 97%, respectively. By introducing SQI and choosing only high-quality ECG signals, more accurate vital sign information will be achieved.
Highlights
Electrocardiogram (ECG) reflects the electrical activity of the heart and contains vast diagnostic information that can guide clinical decision making [1]
From the perspective of signal processing, the R-peak is an important aspect of heart rate variability (HRV) measurement, respiration rate (RR) extraction, and signal quality indexing (SQI) evaluation
The two best detectors were used to gauge its accuracy by searching for the R-peak of the MIT-BIH arrhythmia dataset prior to its use in the SQI process
Summary
Electrocardiogram (ECG) reflects the electrical activity of the heart and contains vast diagnostic information that can guide clinical decision making [1]. A signal quality index (SQI) algorithm is used to evaluate the overall signal quality of ECG [11] For this purpose, the R-peak detector must be capable of robustly detecting the correct R-peak even in a highnoise ECG. From the perspective of signal processing, the R-peak is an important aspect of heart rate variability (HRV) measurement, respiration rate (RR) extraction, and signal quality indexing (SQI) evaluation. The waveform database contains the raw signals monitored from the patient, such as ECG, photoplethysmogram, and RR. The continuous ECG, respiration, and blood pressure signals were digitized at 250 Hz. Each heartbeat was annotated using an automated arrhythmia detection algorithm, and each beat annotation was verified by visual inspection. Two peak detectors that exhibited the best result for R-peak detection were selected to run SQI for the three patient datasets, namely MIMIC-II, Capnobase, and Fantasia
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Bulletin of Electrical Engineering and Informatics
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
