AUTOMATIC DETECTION OF ARRHYTHMIA IN ECG SIGNAL USING DISCRETE COSINE TRANSFORM


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ABSTRACT

The Electrocardiogram (ECG) is the bioelectrical activity of the signal of the heart which represents the cyclic rhythm of contraction and relaxation of the heart muscles.
An arrhythmia is an irregularity with the speed or rhythm of the heartbeat. During an arrhythmia, the heart can beat too fast, too slow, or with an irregular rhythm.
The P,Q,R,S and T waves of the ECG signal contains all important features, the features of these waves are used to classify different types of arrhythmia.
Discrete cosine transform (DCT) expresses a sequence of finitely many data points in terms of a sum of cosine functions oscillating at different frequencies and it is purely real.
DCTs are important to numerous applications in science and engineering, from lossy compression of audio (e.g. MP3) and images. (e.g. JPEG).

Introduction to Signals & Systems

Signals:-
A signal is a time varying physical phenomenon that can convey information. Like human voice, electrocardiogram, sinusoidal, videos etc.
There are different types of signals such as
Analog or Continuous signals
Digital /Discrete signals

DISCRETE COSINE TRANSFORM

A discrete cosine transform (DCT) expresses a sequence of finitely many data points in terms of a sum of cosine functions oscillating at different frequencies.
DCTs are important to numerous applications in science and engineering,and compression of audio and images components to spectral methods for the numerical solution of partial differential equations, functions oscillating at different frequencies.

PROPERTIES OF DCT

Decorrelation-The principle advantage of image transformation is the removal of redundancy between neighboring pixels. This leads to uncorrelated transform coefficients which can be encoded independently.
Energy Compaction - DCT exhibits excellent energy compaction for highly correlated images. The uncorrelated image has its energy spread out, whereas the energy of the correlated image is packed into the low frequency region.