This study explored (1) the effect of applying an autocalibration algorithm on accelerometer data analyzed using different signal processing techniques and (2) how these techniques changed the signal composition. Using a dataset of preschoolers (n = 137; 4.31 ± 0.87 years; Actigraph accelerometers (100 Hz) on right hip 24 hours/7 days) the vector magnitude (VM) was calculated as a reference; highpass, bandpass and lowpass filters were applied and the "Euclidean Norm Minus One" (ENMO) was calculated. Amplitude probability distribution functions were created to compare the (1) uncalibrated versus calibrated data and, (2) amplitude distribution across the techniques. Results showed that the calibration correction significantly impacted ENMO, VM lowpass and VM data, but the impact on VM highpass and bandpass data was minimal. Comparing across the techniques, results showed the lowest outputs were derived according to ENMO, followed by the VM highpass/VM bandpass and the VM lowpass/VM which yielded very similar results.