Biomedical Research

In Electrocardiogram (ECG) the heart beat feature QRS is very important parameter for analysis. This feature is the basis for analysis in any heart beat classification automated diagnosis system. In this paper the method which we have used is by using the counter which is used in parallel. The first level is detection of heart beats in two steps which involved hashing. Then in our second level we designed profiler, which profiles the person regular and irregular ECG characteristic behaviour. Our proposed method depends on series of data which is of ECG instead of number of information contained in the ECG signal. Because of parallel processing the data storage unit requirement as well as the processing time is less. The dependent values in the proposed method changes according to the change in the ECG waveform. Such type of analysis method is very suitable for detection of heart disease (e.g., arrhythmia) purposes. Most significant application of such characteristic plotting is to generate an alert signal for irregular ECG behaviour of any person. Such automated system will be very useful for remote areas where human operator monitoring (Cardiologist) is not available and is extremely costly.

Author(s): Chinmay Chandrakar, Monisha Sharma
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