A Comparison of Adaptive Neuro-Fuzzy Inference System and Real-time Filtering in Cancellation ECG Artifact From Surface EMGs

A Comparison of Adaptive Neuro-Fuzzy Inference System and Real-time Filtering in Cancellation ECG Artifact From Surface EMGs

Electromyogram (EMG) is used in different applications such as diagnosis and treatment of diseases. Recorded EMG signals from upper trunk muscles are contaminated byelectrocardiogram (ECG). Removal of the ECG artifact from surface EMG is not simple because their frequency content is muchoverlap. In this paper, we compare the results of adaptive Neuro fuzzy inference system (ANFIS) and real time filtering techniques. Finally performance of these methods is evaluated usingqualitative criteria, power spectrum density and coherence and Quantitative criteria signal to noise ratio, relative error and crosscorrelation. The result of signal to noise ratio, relative error and cross correlation for better results (ANN) is equal to 13.274, 0.03and %97respectively