Adaptive ECG interval extraction

Temesghen Tekeste; Nourhan Bayasi; Hani Saleh; Ahsan Khandoker; Baker Mohammad; Mahmoud Al-Qutayri; Mohammed Ismail

doi:10.1109/ISCAS.2015.7168804

Adaptive ECG interval extraction

Temesghen Tekeste, Nourhan Bayasi, Hani Saleh, Ahsan Khandoker, Baker Mohammad, Mahmoud Al-Qutayri, Mohammed Ismail

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

8 Scopus citations

Abstract

ECG intervals such as QRS, QT and PR provide significant information and are widely used as clinical parameters for diagnosing cardiac diseases. This paper presents a novel QRS detection technique based on Curve Length Transform (CLT) and a refined delineation of P-wave and T-wave using Discrete Wavelet Transform (DWT). The proposed technique was verified using the PhysioNet database. The QRS detection achieved a sensitivity of 98.59% and a positive predictivity of 97.86%. The QRS duration, QT interval and PR interval had a mean error of -1.56± 28.8ms, -5.39± 42.4ms and 0.86± 40.3ms respectively. The proposed algorithm is computationally efficient and is simpler to implement in hardware, hence, will lead to a faster execution time, smaller design area and consequently low power consumption.

Original language	British English
Title of host publication	2015 IEEE International Symposium on Circuits and Systems, ISCAS 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	998-1001
Number of pages	4
ISBN (Electronic)	9781479983919
DOIs	https://doi.org/10.1109/ISCAS.2015.7168804
State	Published - 27 Jul 2015
Event	IEEE International Symposium on Circuits and Systems, ISCAS 2015 - Lisbon, Portugal Duration: 24 May 2015 → 27 May 2015

Publication series

Name	Proceedings - IEEE International Symposium on Circuits and Systems
Volume	2015-July
ISSN (Print)	0271-4310

Conference

Conference	IEEE International Symposium on Circuits and Systems, ISCAS 2015
Country/Territory	Portugal
City	Lisbon
Period	24/05/15 → 27/05/15

Keywords

Curve length Transform
Discrete Wavelet Transform
ECG interval
P wave
QRS complex
T wave

Access to Document

10.1109/ISCAS.2015.7168804

Cite this

Tekeste, T., Bayasi, N., Saleh, H., Khandoker, A., Mohammad, B., Al-Qutayri, M., & Ismail, M. (2015). Adaptive ECG interval extraction. In 2015 IEEE International Symposium on Circuits and Systems, ISCAS 2015 (pp. 998-1001). Article 7168804 (Proceedings - IEEE International Symposium on Circuits and Systems; Vol. 2015-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISCAS.2015.7168804

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title = "Adaptive ECG interval extraction",

abstract = "ECG intervals such as QRS, QT and PR provide significant information and are widely used as clinical parameters for diagnosing cardiac diseases. This paper presents a novel QRS detection technique based on Curve Length Transform (CLT) and a refined delineation of P-wave and T-wave using Discrete Wavelet Transform (DWT). The proposed technique was verified using the PhysioNet database. The QRS detection achieved a sensitivity of 98.59% and a positive predictivity of 97.86%. The QRS duration, QT interval and PR interval had a mean error of -1.56± 28.8ms, -5.39± 42.4ms and 0.86± 40.3ms respectively. The proposed algorithm is computationally efficient and is simpler to implement in hardware, hence, will lead to a faster execution time, smaller design area and consequently low power consumption.",

keywords = "Curve length Transform, Discrete Wavelet Transform, ECG interval, P wave, QRS complex, T wave",

author = "Temesghen Tekeste and Nourhan Bayasi and Hani Saleh and Ahsan Khandoker and Baker Mohammad and Mahmoud Al-Qutayri and Mohammed Ismail",

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doi = "10.1109/ISCAS.2015.7168804",

language = "British English",

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Tekeste, T, Bayasi, N, Saleh, H , Khandoker, A , Mohammad, B , Al-Qutayri, M & Ismail, M 2015, Adaptive ECG interval extraction. in 2015 IEEE International Symposium on Circuits and Systems, ISCAS 2015., 7168804, Proceedings - IEEE International Symposium on Circuits and Systems, vol. 2015-July, Institute of Electrical and Electronics Engineers Inc., pp. 998-1001, IEEE International Symposium on Circuits and Systems, ISCAS 2015, Lisbon, Portugal, 24/05/15. https://doi.org/10.1109/ISCAS.2015.7168804

Adaptive ECG interval extraction. / Tekeste, Temesghen; Bayasi, Nourhan; Saleh, Hani et al.
2015 IEEE International Symposium on Circuits and Systems, ISCAS 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 998-1001 7168804 (Proceedings - IEEE International Symposium on Circuits and Systems; Vol. 2015-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Adaptive ECG interval extraction

AU - Tekeste, Temesghen

AU - Bayasi, Nourhan

AU - Saleh, Hani

AU - Khandoker, Ahsan

AU - Mohammad, Baker

AU - Al-Qutayri, Mahmoud

AU - Ismail, Mohammed

PY - 2015/7/27

Y1 - 2015/7/27

N2 - ECG intervals such as QRS, QT and PR provide significant information and are widely used as clinical parameters for diagnosing cardiac diseases. This paper presents a novel QRS detection technique based on Curve Length Transform (CLT) and a refined delineation of P-wave and T-wave using Discrete Wavelet Transform (DWT). The proposed technique was verified using the PhysioNet database. The QRS detection achieved a sensitivity of 98.59% and a positive predictivity of 97.86%. The QRS duration, QT interval and PR interval had a mean error of -1.56± 28.8ms, -5.39± 42.4ms and 0.86± 40.3ms respectively. The proposed algorithm is computationally efficient and is simpler to implement in hardware, hence, will lead to a faster execution time, smaller design area and consequently low power consumption.

AB - ECG intervals such as QRS, QT and PR provide significant information and are widely used as clinical parameters for diagnosing cardiac diseases. This paper presents a novel QRS detection technique based on Curve Length Transform (CLT) and a refined delineation of P-wave and T-wave using Discrete Wavelet Transform (DWT). The proposed technique was verified using the PhysioNet database. The QRS detection achieved a sensitivity of 98.59% and a positive predictivity of 97.86%. The QRS duration, QT interval and PR interval had a mean error of -1.56± 28.8ms, -5.39± 42.4ms and 0.86± 40.3ms respectively. The proposed algorithm is computationally efficient and is simpler to implement in hardware, hence, will lead to a faster execution time, smaller design area and consequently low power consumption.

KW - Curve length Transform

KW - Discrete Wavelet Transform

KW - ECG interval

KW - P wave

KW - QRS complex

KW - T wave

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T3 - Proceedings - IEEE International Symposium on Circuits and Systems

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Y2 - 24 May 2015 through 27 May 2015

ER -

Adaptive ECG interval extraction

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