The purpose of this study was to determine the effect of the ECG artifact on low-level trunk muscle activation amplitudes and assess the effectiveness of two methods used to remove the ECG. Simulations were performed and percent error in root mean square (RMS) amplitudes were calculated from uncontaminated and contaminated EMG signals at various ECG to EMG ratios. Two methods were used to remove the ECG: (1) filtering by adaptive sampling (FAS) and (2) Butterworth high pass filter at 30 Hz (BW-30 Hz HPF). The percent error was also calculated between the ECG removed and the uncontaminated EMG RMS amplitudes. Next, the BW-30 Hz HPF method was used to remove the ECG from 3-bilateral external oblique (EO) muscle sites collected from 30 healthy subjects performing a one handed lift and replace task. Two separate ANOVA models assessed the effects of ECG on the statistical interpretation of EO recruitment strategies. One model included EMG data that contained the ECG and the other model included EMG data after the ECG was removed. Large percent errors were observed when the ECG was not removed. These errors increased with larger ECG to EMG ratios. Both removal methods reduced the errors to below 10%, but the BW-30 Hz HPF method was more time efficient in removing the ECG artifact. Different statistical findings were observed among the muscle sites for the ECG contaminated model compared to the ECG removed model, which resulted in different conclusions concerning neuromuscular control.