Evaluation method for measuring the statistical parameters of existing heartbeat classification method of ECG signal

Vol.2  No.1

Year : 2014

Issue : Jan-Mar

Title : Evaluation method for measuring the statistical parameters of existing heartbeat classification method of ECG signal

Author Name : mansi varshney, Chinmay Chandrakar , Monisha Sharma

Synopsis :

Diagnosis of diseases using ECG signal required, classification of beat, which is the main criteria for arrhythmia detection. But accuracy of the detected beat plays an important role in the diagnosis of the disease using ECG signal. This paper describes an evaluation method which is used to analyze the ECG signal and help in diagnosis of cardiac arrhythmia diseases. The evaluation method is used in classification of the beats of ECG signal. Generally there are two types of beats present in human heartbeat – normal beats (NORM) and abnormal beats (LBBB, RBBB, APC, and VPC). For diagnosis, these parameters are first determined. These values can be classified with the help of any existing methodology. This paper aims to check the accuracy of the beat (normal and abnormal beat). Statistical parameters are used for calculating accuracy. Statistical parameters are nothing but the parameter which is used to check the accuracy of the detected beat. The proposed method in this paper evaluates statistical parameters namely Sensitivity (Se), Specificity (Sp), Positive Predictive Values (PPV,) and Negative Predictive Values (NPV) and compares it with the ideal values. The proposed method can be used to detect the accuracy of any existing heartbeat classification methods.

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