Recognition of Mental Workload Levels using Diagnosis of ECG Signals

Author(s):

Dharani R , CCET, Oddanchatram, Dindigul,Tamilnadu.; Muhil vinoliya M, CCET, Oddanchatram, Dindigul,Tamilnadu.; Thulasi devi S, CCET, Oddanchatram, Dindigul,Tamilnadu.; Vinothini S, CCET, Oddanchatram, Dindigul,Tamilnadu.; SathisKumar R, CCET, Oddanchatram, Dindigul,Tamilnadu.

Keywords:

signal recognition, directional Filtering, ANFIS classifier

Abstract:

ECG signal shows the electrical activity of the hearts. These signals are non-stationary; they display a fractal like self-similarity. It is one of the most important physiological parameter, which is being extensively used for knowing the state of cardiac patients. They may contain indicators of heart disease, or even warnings about impending diseases. The indicators may be present at all times or may occur at random. Soft-Computing approach is an important tool in which two or more successive ECG recordings are compared in order to find disorders in cardiac. This project presents the method to analyze ECG signal extract features and classification according to different arrhythmias.

Other Details:

Manuscript Id	:	IJSTEV2I10066
Published in	:	Volume : 2, Issue : 10
Publication Date	:	01/05/2016
Page(s)	:	277-281

Download Article