A Real Time QRS Detection Algorithm Based on ET and PD Controlled Threshold Strategy
As one of the important components of electrocardiogram (ECG) signals, QRS signal represents the basic characteristics of ECG signals. The detection of QRS waves is also an essential step for ECG signal analysis. In order to further meet the clinical needs for the accuracy and real-time detection of...
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| Format: | Article |
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MDPI AG
2020-07-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/20/14/4003 |
| _version_ | 1797562055633403904 |
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| author | Aiyun Chen Yidan Zhang Mengxin Zhang Wenhan Liu Sheng Chang Hao Wang Jin He Qijun Huang |
| author_facet | Aiyun Chen Yidan Zhang Mengxin Zhang Wenhan Liu Sheng Chang Hao Wang Jin He Qijun Huang |
| author_sort | Aiyun Chen |
| collection | DOAJ |
| description | As one of the important components of electrocardiogram (ECG) signals, QRS signal represents the basic characteristics of ECG signals. The detection of QRS waves is also an essential step for ECG signal analysis. In order to further meet the clinical needs for the accuracy and real-time detection of QRS waves, a simple, fast, reliable, and hardware-friendly algorithm for real-time QRS detection is proposed. The exponential transform (ET) and proportional-derivative (PD) control-based adaptive threshold are designed to detect QRS-complex. The proposed ET can effectively narrow the magnitude difference of QRS peaks, and the PD control-based method can adaptively adjust the current threshold for QRS detection according to thresholds of previous two windows and predefined minimal threshold. The ECG signals from MIT-BIH databases are used to evaluate the performance of the proposed algorithm. The overall sensitivity, positive predictivity, and accuracy for QRS detection are 99.90%, 99.92%, and 99.82%, respectively. It is also implemented on Altera Cyclone V 5CSEMA5F31C6 Field Programmable Gate Array (FPGA). The time consumed for a 30-min ECG record is approximately 1.3 s. It indicates that the proposed algorithm can be used for wearable heart rate monitoring and automatic ECG analysis. |
| first_indexed | 2024-03-10T18:23:10Z |
| format | Article |
| id | doaj.art-d685b682a5fb42ee9ac44a3cc912f120 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T18:23:10Z |
| publishDate | 2020-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-d685b682a5fb42ee9ac44a3cc912f1202023-11-20T07:12:55ZengMDPI AGSensors1424-82202020-07-012014400310.3390/s20144003A Real Time QRS Detection Algorithm Based on ET and PD Controlled Threshold StrategyAiyun Chen0Yidan Zhang1Mengxin Zhang2Wenhan Liu3Sheng Chang4Hao Wang5Jin He6Qijun Huang7School of Physics and Technology, Wuhan University, Wuhan 430072, ChinaSchool of Physics and Technology, Wuhan University, Wuhan 430072, ChinaSchool of Physics and Technology, Wuhan University, Wuhan 430072, ChinaSchool of Physics and Technology, Wuhan University, Wuhan 430072, ChinaSchool of Physics and Technology, Wuhan University, Wuhan 430072, ChinaSchool of Physics and Technology, Wuhan University, Wuhan 430072, ChinaSchool of Physics and Technology, Wuhan University, Wuhan 430072, ChinaSchool of Physics and Technology, Wuhan University, Wuhan 430072, ChinaAs one of the important components of electrocardiogram (ECG) signals, QRS signal represents the basic characteristics of ECG signals. The detection of QRS waves is also an essential step for ECG signal analysis. In order to further meet the clinical needs for the accuracy and real-time detection of QRS waves, a simple, fast, reliable, and hardware-friendly algorithm for real-time QRS detection is proposed. The exponential transform (ET) and proportional-derivative (PD) control-based adaptive threshold are designed to detect QRS-complex. The proposed ET can effectively narrow the magnitude difference of QRS peaks, and the PD control-based method can adaptively adjust the current threshold for QRS detection according to thresholds of previous two windows and predefined minimal threshold. The ECG signals from MIT-BIH databases are used to evaluate the performance of the proposed algorithm. The overall sensitivity, positive predictivity, and accuracy for QRS detection are 99.90%, 99.92%, and 99.82%, respectively. It is also implemented on Altera Cyclone V 5CSEMA5F31C6 Field Programmable Gate Array (FPGA). The time consumed for a 30-min ECG record is approximately 1.3 s. It indicates that the proposed algorithm can be used for wearable heart rate monitoring and automatic ECG analysis.https://www.mdpi.com/1424-8220/20/14/4003electrocardiogram (ECG)exponential transform (ET)PD-controlQRS detectionreal-time |
| spellingShingle | Aiyun Chen Yidan Zhang Mengxin Zhang Wenhan Liu Sheng Chang Hao Wang Jin He Qijun Huang A Real Time QRS Detection Algorithm Based on ET and PD Controlled Threshold Strategy Sensors electrocardiogram (ECG) exponential transform (ET) PD-control QRS detection real-time |
| title | A Real Time QRS Detection Algorithm Based on ET and PD Controlled Threshold Strategy |
| title_full | A Real Time QRS Detection Algorithm Based on ET and PD Controlled Threshold Strategy |
| title_fullStr | A Real Time QRS Detection Algorithm Based on ET and PD Controlled Threshold Strategy |
| title_full_unstemmed | A Real Time QRS Detection Algorithm Based on ET and PD Controlled Threshold Strategy |
| title_short | A Real Time QRS Detection Algorithm Based on ET and PD Controlled Threshold Strategy |
| title_sort | real time qrs detection algorithm based on et and pd controlled threshold strategy |
| topic | electrocardiogram (ECG) exponential transform (ET) PD-control QRS detection real-time |
| url | https://www.mdpi.com/1424-8220/20/14/4003 |
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