Abstract
In automatic electrocardiogram (ECG) signal analysis, the QRS onset must be identified prior to QT interval or QRS duration measurements. These measurements are decisive ECG parameters for diagnosing cardiac abnormalities among cardiologists. Hence, the efficiency of the developed automatic algorithm to detect the QRS onset is essential to obtain an accurate result of the ECG parameters. In this report, an algorithm to detect the QRS onset based on secant line slope formula is proposed. The preprocessing and wave delineation process were implemented in MATLAB using modified Pan-Tompkins algorithm (an established adaptive threshold method). The window of the preceding Q-wave was determined before calculating the slope of secant line along the descending slope for QRS onset detection. The performance of the proposed algorithm was evaluated using 25 subjects from Pusat Perubatan Universiti Kebangsaan Malaysia (PPUKM) and volunteered participants under the approval of Research and Ethics Committee, PPUKM (Code of ethics approval: FF-2013-313). All data were acquired using biosignal amplifier (g.USBamp by g.tec, Austria) with 2 minutes duration of recording and sampled at 512 Hz. The efficiency of the proposed algorithm has obtained a sensitivity of 99.67%, positive predictivity of 99.39%, and accuracy of 99.07%. The result shows stable performance and insensitivity of the proposed algorithm towards ECG wave morphology changes.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2019 IEEE 15th International Colloquium on Signal Processing and its Applications, CSPA 2019 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 132-136 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781538675632 |
| DOIs | |
| Publication status | Published - 22 Apr 2019 |
| Event | 15th IEEE International Colloquium on Signal Processing and its Applications, CSPA 2019 - Penang, Malaysia Duration: 8 Mar 2019 → 9 Mar 2019 |
Publication series
| Name | Proceedings - 2019 IEEE 15th International Colloquium on Signal Processing and its Applications, CSPA 2019 |
|---|
Conference
| Conference | 15th IEEE International Colloquium on Signal Processing and its Applications, CSPA 2019 |
|---|---|
| Country | Malaysia |
| City | Penang |
| Period | 8/3/19 → 9/3/19 |
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Keywords
- Automatic ECG detection
- Pan-Tompkins algorithm
- QRS onset
- Secant line slope
ASJC Scopus subject areas
- Signal Processing
Cite this
Automatic QRS Onset Detection of ECG Signal using Secant Line Slope Formula. / Jumahat, Shaliza; Kok Beng, Gan; Misran, Norbahiah; Islam, Mohammad Tariqul; Mahri, Nurhafizah.
Proceedings - 2019 IEEE 15th International Colloquium on Signal Processing and its Applications, CSPA 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 132-136 8695982 (Proceedings - 2019 IEEE 15th International Colloquium on Signal Processing and its Applications, CSPA 2019).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Automatic QRS Onset Detection of ECG Signal using Secant Line Slope Formula
AU - Jumahat, Shaliza
AU - Kok Beng, Gan
AU - Misran, Norbahiah
AU - Islam, Mohammad Tariqul
AU - Mahri, Nurhafizah
PY - 2019/4/22
Y1 - 2019/4/22
N2 - In automatic electrocardiogram (ECG) signal analysis, the QRS onset must be identified prior to QT interval or QRS duration measurements. These measurements are decisive ECG parameters for diagnosing cardiac abnormalities among cardiologists. Hence, the efficiency of the developed automatic algorithm to detect the QRS onset is essential to obtain an accurate result of the ECG parameters. In this report, an algorithm to detect the QRS onset based on secant line slope formula is proposed. The preprocessing and wave delineation process were implemented in MATLAB using modified Pan-Tompkins algorithm (an established adaptive threshold method). The window of the preceding Q-wave was determined before calculating the slope of secant line along the descending slope for QRS onset detection. The performance of the proposed algorithm was evaluated using 25 subjects from Pusat Perubatan Universiti Kebangsaan Malaysia (PPUKM) and volunteered participants under the approval of Research and Ethics Committee, PPUKM (Code of ethics approval: FF-2013-313). All data were acquired using biosignal amplifier (g.USBamp by g.tec, Austria) with 2 minutes duration of recording and sampled at 512 Hz. The efficiency of the proposed algorithm has obtained a sensitivity of 99.67%, positive predictivity of 99.39%, and accuracy of 99.07%. The result shows stable performance and insensitivity of the proposed algorithm towards ECG wave morphology changes.
AB - In automatic electrocardiogram (ECG) signal analysis, the QRS onset must be identified prior to QT interval or QRS duration measurements. These measurements are decisive ECG parameters for diagnosing cardiac abnormalities among cardiologists. Hence, the efficiency of the developed automatic algorithm to detect the QRS onset is essential to obtain an accurate result of the ECG parameters. In this report, an algorithm to detect the QRS onset based on secant line slope formula is proposed. The preprocessing and wave delineation process were implemented in MATLAB using modified Pan-Tompkins algorithm (an established adaptive threshold method). The window of the preceding Q-wave was determined before calculating the slope of secant line along the descending slope for QRS onset detection. The performance of the proposed algorithm was evaluated using 25 subjects from Pusat Perubatan Universiti Kebangsaan Malaysia (PPUKM) and volunteered participants under the approval of Research and Ethics Committee, PPUKM (Code of ethics approval: FF-2013-313). All data were acquired using biosignal amplifier (g.USBamp by g.tec, Austria) with 2 minutes duration of recording and sampled at 512 Hz. The efficiency of the proposed algorithm has obtained a sensitivity of 99.67%, positive predictivity of 99.39%, and accuracy of 99.07%. The result shows stable performance and insensitivity of the proposed algorithm towards ECG wave morphology changes.
KW - Automatic ECG detection
KW - Pan-Tompkins algorithm
KW - QRS onset
KW - Secant line slope
UR - http://www.scopus.com/inward/record.url?scp=85065483213&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85065483213&partnerID=8YFLogxK
U2 - 10.1109/CSPA.2019.8695982
DO - 10.1109/CSPA.2019.8695982
M3 - Conference contribution
AN - SCOPUS:85065483213
T3 - Proceedings - 2019 IEEE 15th International Colloquium on Signal Processing and its Applications, CSPA 2019
SP - 132
EP - 136
BT - Proceedings - 2019 IEEE 15th International Colloquium on Signal Processing and its Applications, CSPA 2019
PB - Institute of Electrical and Electronics Engineers Inc.
ER -