Development of Long QT Syndrome Detection Using SciPy

  • Moses Himawan Student
  • Muammar Sadrawi Indonesian International Institute for Life Sciences
Keywords: Arrhythmia, ECG, LQTS, CVD


Long QT syndrome (LQTS) is a type of arrhythmia that manifests itself as the elongation of the QT interval. LQTS is caused due to different disorders in the sodium and potassium channels which results in reduced activity of the cardiac muscle. To diagnose LQTS, an algorithm is used to detect the elongated QT interval through detection of the peaks using Python. The current build of the algorithm is able to detect different ECG graphs for their QT interval with relative accuracy however is not capable of detecting the different components if the graph has too much noise or if they have irregular wavelengths due to other cardiovascular disease (CVD).


Download data is not yet available.


2015 ESC Guidelines for the management of patients with ventricular arrhythmias and the prevention of sudden cardiac death. (2015). Europace, euv319.

About PhysioNet. (n.d.). PhysioNet. Retrieved July 22, 2022, from

Ashley, E., & Niebauer, J. (2003). Cardiology Explained (Remedica Explained) (1st ed.). Remedica Publishing.

Beers, L., van Adrichem, L. P., Himmelreich, J. C. L., Karregat, E. P. M., de Jong, J. S. S. G., Postema, P. G., de Groot, J. R., Lucassen, W. A. M., & Harskamp, R. E. (2021). Manual QT interval measurement with a smartphone-operated single-lead ECG versus 12-lead ECG: a within-patient diagnostic validation study in primary care. BMJ Open, 11(11), e055072.

Bellenir, K. (2000). Heart Diseases and Disorders Sourcebook: Basic Consumer Health Information About Heart Attacks, Angina, Rhythm Disorders, Heart Failure, Valve Disorders, and More (Health Reference Series) (2nd ed.). Omnigraphics Inc
Cardiovascular diseases. (2019, June 11). Https://Www.Who.Int/Health-Topics/Cardiovascular-Diseases#tab=tab_1.

EMAy Portable ECG. (n.d.). Tokopedia.

Feather, A., Randall, D., & Waterhouse, M. (2020). Kumar and Clark’s Clinical Medicine E-Book (10th ed.). Elsevier.

Goldenberg, I., Zareba, W., & Moss, A. J. (2008). Long QT Syndrome. Current Problems in Cardiology, 33(11), 629–694.

Llobera, M. (2001). Building Past Landscape Perception With GIS: Understanding Topographic Prominence. Journal of Archaeological Science, 28(9), 1005–1014.

Nakano, Y., & Shimizu, W. (2015). Genetics of long-QT syndrome. Journal of Human Genetics, 61(1), 51–55.

Obeyesekere, M. N., Leong-Sit, P., Massel, D., Manlucu, J., Modi, S., Krahn, A. D., Skanes, A. C., Yee, R., Gula, L. J., & Klein, G. J. (2012). Risk of Arrhythmia and Sudden Death in Patients With Asymptomatic Preexcitation. Circulation, 125(19), 2308–2315.

Pearman, C. (2018, October 6). QT Interval [Graph].

Sarang. (2018, April 13). ECG graph [Vector image]. Wikipedia.

Tiwari, A. K. (2021). Automatic Detection of Q-T interval in ECG using MATLAB Tool. Automatic Detection of Q-T Interval in ECG Using MATLAB Tool.

Topol, E., Clinic, C., & Eisner, M. D. (2000). Cleveland Clinic Heart Book: The Definitive Guide for the Entire Family from the Nation’s Leading Heart Center (1st ed.). Hyperion.

Trappe, H. J. (2018). EKG-Befunde: Tipps und Tricks zur richtigen Diagnose. Herz, 43(2), 177–194.

Tse, G. (2016). Mechanisms of cardiac arrhythmias. Journal of Arrhythmia, 32(2), 75–81.

Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., van der Walt, S. J., Brett, M., Wilson, J., Millman, K. J., Mayorov, N., Nelson, A. R. J., Jones, E., Kern, R., Larson, E., . . . Vázquez-Baeza, Y. (2020). SciPy 1.0: fundamental algorithms for scientific computing in Python. Nature Methods, 17(3), 261–272.

Waks, J. W., & Josephson, M. E. (2014). Mechanisms of Atrial Fibrillation – Reentry, Rotors and Reality. Arrhythmia & Electrophysiology Review, 3(2), 90.

Woodrow, P. (1998). An introduction to the reading of electrocardiograms. British Journal of Nursing, 7(3), 135–142.
How to Cite
Himawan, M., & Sadrawi, M. (2023). Development of Long QT Syndrome Detection Using SciPy. Indonesian Journal of Life Sciences, 5(02), 1-8.
Information Technology in Life Sciences