Assessment of Hamilton-Tompkins Algorithm in a Noise Contaminated ECG Signal Environment
Saeka Rahman1, Mohammad Anwar Rahman2
1SaekaRahman, Artificial Intelligence Department, Catholic university in Belgium, leuven.
2Mohammad Anwar Rahman, Industrial Engineering Department, University of Southern Mississippi, Hattiesburg, MS, USA.
Manuscript received on August 11, 2013. | Revised Manuscript received on August 15, 2013. | Manuscript published on August 25, 2013. | PP: 82-86 | Volume-1, Issue-10, August 2013. | Retrieval Number: J04430811013/2013©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Accurate parameter detection is an integral part of the use of electrocardiograms (ECGs) in the healthcare system. Advances in technology have resulted in a considerable increase in the number of portable, battery-operated ECG instruments including in developing countries. A growing concern is that algorithms that diagnose ECG signals should be tested at different noise circumstances to verify the reliability and efficiency of signal interpretation. This study investigates the accuracy and reliability of the Hamilton-Tompkins (H-T) algorithm using simulated ECG signals generated by MATLAB. In the test process, randomly generated noises are added to simulated input signals to represent high-level noise contaminated surroundings. Simulation results show that the H-T algorithm accurately detected peaks every time it has been tested. The algorithm’s performance parameter diagnosis for the Q, R and S wave peak was 99.96%, 99.97% and 99.93% accuracy, respectively. Test results indicate the H-T algorithm is reliable in detecting accurate ECG signals even in aggravated noise surroundings.
Keywords: ECG, Hamilton-Tompkins algorithm, Noise, QRS complex.