Differentiation between ischemic and heart rate related events using the continuous wavelet transform

  1. Carolina Fernández Biscay
  2. Pedro David Arini
  3. Anderson Iván Rincón Soler
  4. María Paula Bonomini
Libro:
From Bioinspired Systems and Biomedical Applications to Machine Learning: 8th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2019, Almería, Spain, June 3–7, 2019, Proceedings, Part II
  1. José Manuel Ferrández Vicente (dir. congr.)
  2. José Ramón Álvarez-Sánchez (dir. congr.)
  3. Félix de la Paz López (dir. congr.)
  4. Javier Toledo Moreo (dir. congr.)
  5. Hojjat Adeli (coord.)

Editorial: Springer Suiza

ISBN: 978-3-030-19651-6

Año de publicación: 2019

Páginas: 352-360

Tipo: Capítulo de Libro

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Resumen

Cardiovascular diseases are one of the main causes of deathin the world, as a result much efforts have been made to detect early ischemia. Traditionally changes produced in the ST or STT segments of the heartbeat were analyzed. The main difficulty relies on alterations produced in the ST or STT segment because of non ischemic events, such as changes in the heart rate, the ventricular conduction or the cardiac electrical axis. The aim of this work is to differentiate between ischemic and heart rate related events using the information provided by the continuous wavelet transform of the electrocardiogram. To evaluate the performance of the classifier, the Long Term ST Database was used, withischemic and non ischemic differentiated events annotated by specialists. The analysis was performed over 77 events (52 ischemic and 25 heart rate related), obtaining a sensitivity and positive predictivity of 86.64% for both indicators.

Fuente de los datos: Dialnet