Arhamia Estimation Method

ARRHYTHMIA DETECTION USING FEATURE FUSION

Shamya C Smitha PB M.Tech Student ,Department of AECS Assistant Professor,Department of AECS Thejus Engineering College Thejus Engineering College Thrissur Thrissur

ABSTRACT:

Automatic diagnosis of ECG is required for timely and accurate diagnosis of heart diseases. In this project, a global ECG beat classification approach is proposed. Rather than conventional time interval or morphology features, transformed features like discrete cosine transform (DCT), discrete wavelet transform (DWT) and fused

Arrhythmia is one of such cardiac diseases. Arrhythmia occur due to the interruption in the regular rhythm of the heart beat. Fast and accurate diagnosis of such diseases is extremely important for saving the life of patients. Electrocardiogram (ECG) is widely used to monitor heart function. At present, an expert cardiologist analyzes short-duration ECG plots to detect the presence of abnormalities. Since certain kinds of heartbeat arrhythmias occur sporadically over an extended period, long term monitoring of patient is required. In such cases, automated classification of heartbeats is vital as manual examinations are tedious. In intensive cardiac care unit (ICCU) or operation room immediate analysis of abnormal heart beat is crucial for taking swift action. It is difficult for human beings to observe continuously and analyze the abnormal beats. In many cases, portable Holter monitor is used to record electrical activity of heart for 24 to 48 hours. Computer-aided ECG analysis and quantification in such cases would be of immense aid to the clinicians to handle these