ETRI-Knowledge Sharing Plaform

KOREAN
논문 검색
Type SCI
Year ~ Keyword

Detail

Journal Article Efficient Real-Time R and QRS Detection Method Using a Pair of Derivative Filters and Max Filter for Portable ECG Device
Cited 21 time in scopus Download 142 time Share share facebook twitter linkedin kakaostory
Authors
Tae Wuk Bae, Kee Koo Kwon
Issue Date
2019-10
Citation
Applied Sciences, v.9, no.19, pp.1-20
ISSN
2076-3417
Publisher
MDPI
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.3390/app9194128
Abstract
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 Keywords
Detection Method, ECG device, ECG signal processing, Early Warning, First-Order derivative, Healthcare System, MIT-BIH database, QRS Detection, RR interval, Real-Time processing, Region Analysis
This work is distributed under the term of Creative Commons License (CCL)
(CC BY)
CC BY