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학술지 Efficient Real-Time R and QRS Detection Method Using a Pair of Derivative Filters and Max Filter for Portable ECG Device
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저자
배태욱, 권기구
발행일
201910
출처
Applied Sciences, v.9 no.19, pp.1-20
ISSN
2076-3417
출판사
MDPI
DOI
https://dx.doi.org/10.3390/app9194128
협약과제
19ZD1100, 대경권 지역산업 기반 ICT융합기술 고도화 지원사업, 문기영
초록
Recently, with the active development of wearable electrocardiogram (ECG) devices such as smart-bands or portable ECG devices, efficient ECG signal processing technology that can be applied in real-time has been actively studied. However, a wearable ECG device is exposed to various noise situations, thereby reducing the reliability of the detected R point or QRS interval. In addition, as early warning techniques in healthcare systems have been studied, real-time ECG signal processing techniques have become very important in wearable ECG devices. In this paper, we propose an efficient real-time R and QRS detection method using two kinds of first-order derivative filters and a max filter to analyze ECG signals measured from wearable ECG devices in real-time. The proposed method detects the R point and QRS interval in units of a sliding window for real-time processing and combines the detected R points in each sliding window. Also, the reliability of the detected R points and RR intervals is examined through noise region analysis using the histogram characteristic of a sample point. The performance of the proposed method was verified by the MIT-BIH database (DB), CYBHi DB and real ECG data measured from the developed wearable ECG patch. The proposed method achieves Se = 99.80%, +P = 99.80%, and DER = 0.36% against MIT-BIH DB. In addition, the proposed method enables accurate R point detection and heart rate variability (HRV) analysis even with noisy ECG signals.
KSP 제안 키워드
Detection Method, ECG devices, ECG signal processing, First-order derivative, Healthcare Systems, Heart rate variability, MIT-BIH database, QRS Detection, RR interval, Real-Time processing, Region Analysis
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