Combination of multi-component and single-component based Electrocardiogram beat detection algorithms

The accuracy of the beat detector is very important for the overall system performance in computerised processing of the Electrocardiogram (ECG). In the present study we introduce the concept of multi-component based beat detection using Cross Correlation (CC) and Neural Networks (NN) techniques. In addition, a new beat detection algorithm is proposed. A database containing 2966 cardiac cycles was used to validate the approaches. Results have shown the ability of achieving a 7% improvement in detecting individual waveform components. Furthermore, the new approach was able to reduce the number of incorrectly detected waveform components by a factor higher than 15.