The reliability of Electroencephalography (EEG) measurements in human neurophysiology can be used to determine reliable measures when detecting changes in brain electrical activity, nevertheless, attempts have been made to directly address the problem of automatically assessing the reliability of independent components (ICs) across subjects from longitudinal studies. Therefore, the aim of this study is to report the reliability of relative band powers drawn from a longitudinal resting EEG study. Data was collected from extracted from a two-year four-session resting-EEG longitudinal study conditioned for 43 healthy subjects by an automated pipeline that leverages state of the art EEG signal-processing approaches involving ICA, wavelet-ICA, and normalization by a recording-specific constant. The Intraclass Correlation Coefficient (ICC) was used as a measure of reliability. Similarly, to assess the association between age and relative performance. The results of the ICC for EEG data acquisition and preprocessing process showed high significant reliability, where an average ICC of 0.91 ± 0.04 was obtained for neural-related Independent Components (ICs) and 0.92 ± 0.03 for ROIs (p-value < 5% for all data). These results suggest that relative power measured from EEGs preprocessed with the automated pipeline is a replicable metric across sessions, and, consequently, is useful for the study of relative power changes caused by the progression of neurodegenerative pathologies such as Alzheimer's disease.