Assessment of Reliability of Hamilton-Tompkins Algorithm to ECG Parameter Detection

Accurate electrocardiogram (ECG) parameters detection is an integral part of modern computerized ECG monitoring system. A growing concern that algorithms that diagnose ECG signals should be tested at different noise circumstances to verify algorithms’ reliability and efficiency of signal interpretation. This study investigates the accuracy and reliability of Hamilton-Tompkins (H-T) algorithm using simulated ECG signals generated by MATLAB. In the test process, randomly generated noises are added to simulated input signal to represent high-level noise surroundings. The algorithm is tested with noise contaminated ECG signals. Simulation results show that H-T algorithm’s accuracy in detecting the peaks is 100%, i.e. detects signal patterns every time it has been tested. The algorithm’s performance parameters diagnosis for Q, R and S wave peak reaches to 99.96%, 99.97% and 99.93% accuracy, respectively. Test results indicate the H-T algorithm is reliable in detecting accurate ECG signals at the aggravated noise surroundings.