DWT based beat rate detection in ECG analysis

Electrocardiogram (ECG) classification systems have the potential to benefit from the inclusion of the automated measurement capabilities. The first stage in computerized processing of the ECG is beat detection. The accuracy of the beat detector is very important for the overall system performance hence there is a benefit in improving the accuracy. In present study we introduce the concept of Discrete Wavelet Transform which is suitable for the non stationary ECG signals as it has adequate scale values and shifting in time. As baseline Wander and different types of noise elimination are considered as classical problem in ECG analysis we present a wavelet based search algorithm in different scales for Denoising and subtractive procedure to isolate baseline wander from noisy ECG signal(to remove the noise). This algorithm is tested using the data record from MIT-BIH database and excellent results are obtained.

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