System Design Approach for Heartbeat Detection and Classification of Individuals Irrespective of their Physical Condition

In an electrocardiogram (ECG), the heartbeat feature QRS is an important parameter for analysis in any heartbeat classification automated diagnosis system. In this communication the method which we have proposed is by using the counter which is used in parallel. The first level is detection of heartbeats, which uses hashing of ECG features. In the second level, the profiler profiles a person's regular and irregular ECG characteristic behaviour. The proposed method works on data related with ECG, instead of particular features of ECG. Because of parallel processing, data storage unit requirements and the processing time are less. The dependent values in the proposed method vary according to the changes in the ECG waveform. Such type of analysis is suitable for detection of heart disease. The most significant application of such characteristic plotting is to generate an alert signal for irregular ECG behaviour in a person. Such automated system will be useful in remote areas where a cardiologist may not be easily available.