Paper Information

Title: 

QRS DETECTION AND RECOGNITION OF ECG SIGNALS

Type: PAPER
Author(s): MANSOORI E.*
 
 *COMPUTER SCIENCE & ENGINEERING DEPARTMENT, SHIRAZ UNIVERSITY
 
Name of Seminar: IRANIAN CONFERENCE ON BIOMEDICAL ENGINEERING
Type of Seminar:  CONFERENCE
Sponsor:  ANJOMANE MOHANDESI PEZESHKI IRAN
Date:  2004Volume 11
 
 
Abstract: 

THE QRS DETECTION AND FEATURE EXTRACTION OF ECG SIGNALS CAN BE USED AS AN EXPERT SYSTEM IN HEART ARRHYTHMIA DIAGNOSIS. AN ALGORITHM THAT DETECTS QRS COMPLEXES AND CLASSIFIES ECG SIGNALS CAN UNDERTAKE THE TASK OF DETECTING HEART ABNORMALITIES. IN THIS PAPER, A REAL-TIME ALGORITHM FOR ECG SIGNAL PROCESSING HAS BEEN SUGGESTED AND UTILIZED.
IN THE FIRST PHASE, THE OCCURRENCE OF QRS COMPLEXES IS RECOGNIZED AND WHILE COUNTING THEM, THEY ARE STORED FOR THE NEXT PHASE. THE DETECTION ALGORITHM USES THE AMPLITUDE, DURATION, SLOPES OF QRS COMPLEXES FOR EXAMINING THEIR OCCURRENCE, AND AUTOMATICALLY ADJUSTS THE REQUIRED THRESHOLDS. SIGNAL CLASSIFICATION HAS BEEN EXAMINED FROM THREE ASPECTS: NEURAL NETWORK, STATISTICAL AND FUZZY METHODS.
THE RESULTS OF IMPLEMENTATION SHOW THE CAPABILITY OF THE ALGORITHMS PRESENTED FOR QRS COMPLEX DETECTION AND ECG SIGNAL CLASSIFICATION. BY COMPARING THE CLASSIFICATION METHODS, IT IS CLEAR THAT FOR REAL-TIME APPLICATIONS THE STATISTICAL AND FUZZY METHODS ARE MORE SUITABLE.

 
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