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Journal Article
Efficient Real-Time R and QRS Detection Method Using a Pair of Derivative Filters and Max Filter for Portable ECG Device
- 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
- 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)
