A simple realtime algorithm for automatic external defibrillator

Somaye Abedini Khadar, Narges Tabatabaey-Mashadi, Gheshlaghi Mojtaba Daliri

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

Automatic External Defibrillator is a device that automatically diagnoses the heart rhythm which requires an electric shock. In general the signal processing unit of an AED aims to immediately identify the occurrence of ventricular fibrillation and ventricular tachycardia in a patient's electrocardiograph signal. In this research, a quick and high-precision method is presented that identifies peaks and heart rate arrhythmias of the cardiac signals that do not include QRS complex. Initially, asystole and presence of extra noise are recognized in a preprocessing step. Furthermore, two support vector machine classifiers have been used in a hierarchical way to separate Ventricular Fibrillation, Ventricular Tachycardia and normal signals. As a result, a real-time algorithm is developed that matches American Heart Association standard with an accuracy of 98.6%. Finally the Raspberry pi board is used as a hardware platform to embed the proposed algorithm into an AED system. The results show that the implemented system can detect shock-required rhythms in 0.56 s; and the method may be used in an actual signal processing unit of an AED.

Original languageEnglish
Pages (from-to)277-284
Number of pages8
JournalBiomedical Signal Processing and Control
Volume51
Early online date15 Mar 2019
DOIs
Publication statusPublished - May 2019

Keywords

  • Adaptive threshold
  • Automatic external defibrillators
  • Embedded system
  • Hierarchical
  • Python
  • Raspberry pi
  • Real time
  • Support vector machine
  • Ventricular fibrillation
  • Ventricular tachycardia

ASJC Scopus subject areas

  • Signal Processing
  • Health Informatics

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