Abstract
The extracted features from the QRS complex in the electrocardiogram (ECG) signal are considered mainly in the heart rate evaluation and cardiac disease diagnosis. In this paper, high speed approach named 'Rising Falling Transition Method (RFTM)' is proposed to detect the characteristics of QRS complex in single lead ECG signal. The proposed approach applies single straight forward algorithm with two stages. The first stage takes the advantage of the transition from rising to falling edge inside each QRS complex as a base to determine the time locations of the vertices in a triangle that composes from the Q-wave end, R-wave peak, and S-wave onset. The second stage determines the time location of Q-wave onset and S-wave end (J-point) using a linear scan along short period which starts from Q-wave end and S-wave onset towards the target end points at Q-wave onset and S-wave end, respectively. The detector approach is able to detect QRS complex of different morphologies (wide/small interval, high/low amplitude, and negative polarities). The detection performance of the proposed approach is evaluated on a single channel of some annotated records from the QT database which collected from seven ECG categories and 48 annotated records from MIT-BIH database. Simulation results show that the average detection rates of sensitivity (Se) and specificity (Sp) are 99.84% and 99.94%, respectively for MIT-BIH Arrhythmia database. The validation results prove the reliability and accuracy of proposed RFTM approach.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2013 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2013 |
| Pages | 391-396 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - Dec 1 2013 |
| Event | 2013 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2013 - Penang, Malaysia Duration: Nov 29 2013 → Dec 1 2013 |
Other
| Other | 2013 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2013 |
|---|---|
| Country | Malaysia |
| City | Penang |
| Period | 11/29/13 → 12/1/13 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
Cite this
}
High speed approach for detecting QRS complex characteristics in single lead electrocardiogram signal. / Salih, Sameer K.; Aljunid, S. A.; Aljunid, Syed M.; Maskon, Oteh; Yahya, Abid.
Proceedings - 2013 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2013. 2013. p. 391-396 6719996.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - High speed approach for detecting QRS complex characteristics in single lead electrocardiogram signal
AU - Salih, Sameer K.
AU - Aljunid, S. A.
AU - Aljunid, Syed M.
AU - Maskon, Oteh
AU - Yahya, Abid
PY - 2013/12/1
Y1 - 2013/12/1
N2 - The extracted features from the QRS complex in the electrocardiogram (ECG) signal are considered mainly in the heart rate evaluation and cardiac disease diagnosis. In this paper, high speed approach named 'Rising Falling Transition Method (RFTM)' is proposed to detect the characteristics of QRS complex in single lead ECG signal. The proposed approach applies single straight forward algorithm with two stages. The first stage takes the advantage of the transition from rising to falling edge inside each QRS complex as a base to determine the time locations of the vertices in a triangle that composes from the Q-wave end, R-wave peak, and S-wave onset. The second stage determines the time location of Q-wave onset and S-wave end (J-point) using a linear scan along short period which starts from Q-wave end and S-wave onset towards the target end points at Q-wave onset and S-wave end, respectively. The detector approach is able to detect QRS complex of different morphologies (wide/small interval, high/low amplitude, and negative polarities). The detection performance of the proposed approach is evaluated on a single channel of some annotated records from the QT database which collected from seven ECG categories and 48 annotated records from MIT-BIH database. Simulation results show that the average detection rates of sensitivity (Se) and specificity (Sp) are 99.84% and 99.94%, respectively for MIT-BIH Arrhythmia database. The validation results prove the reliability and accuracy of proposed RFTM approach.
AB - The extracted features from the QRS complex in the electrocardiogram (ECG) signal are considered mainly in the heart rate evaluation and cardiac disease diagnosis. In this paper, high speed approach named 'Rising Falling Transition Method (RFTM)' is proposed to detect the characteristics of QRS complex in single lead ECG signal. The proposed approach applies single straight forward algorithm with two stages. The first stage takes the advantage of the transition from rising to falling edge inside each QRS complex as a base to determine the time locations of the vertices in a triangle that composes from the Q-wave end, R-wave peak, and S-wave onset. The second stage determines the time location of Q-wave onset and S-wave end (J-point) using a linear scan along short period which starts from Q-wave end and S-wave onset towards the target end points at Q-wave onset and S-wave end, respectively. The detector approach is able to detect QRS complex of different morphologies (wide/small interval, high/low amplitude, and negative polarities). The detection performance of the proposed approach is evaluated on a single channel of some annotated records from the QT database which collected from seven ECG categories and 48 annotated records from MIT-BIH database. Simulation results show that the average detection rates of sensitivity (Se) and specificity (Sp) are 99.84% and 99.94%, respectively for MIT-BIH Arrhythmia database. The validation results prove the reliability and accuracy of proposed RFTM approach.
UR - http://www.scopus.com/inward/record.url?scp=84894212027&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84894212027&partnerID=8YFLogxK
U2 - 10.1109/ICCSCE.2013.6719996
DO - 10.1109/ICCSCE.2013.6719996
M3 - Conference contribution
SN - 9781479915088
SP - 391
EP - 396
BT - Proceedings - 2013 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2013
ER -