The alpha band (8–13 Hz) is widely used as a personalized stimulation frequency in neuromodulation techniques, such as transcranial electrical or magnetic stimulation, targeting the prefrontal cortex. A critical step in these interventions is the identification of individualized stimulation frequencies, which are typically derived from endogenous alpha rhythms observed during resting-state brain activity. However, several aspects of this approach remain unresolved. To address these gaps, we collected resting-state EEG data under both eyes-open (EO) and eyes-closed (EC) conditions from 67 healthy individuals, along with 238 sessions of longitudinal recordings (scheduled monthly) from 21 individuals (averaging 11.3 sessions per participant over up to 16 months; mean duration: 10.3 months). Using multiple estimation methods, we systematically examined the frequency characteristics of the alpha band. Our analyses revealed that alpha peak estimation was unstable under EO conditions but robust under EC conditions. Furthermore, in participants with a prominent alpha peak, the frequencies estimated across different methods were highly consistent. Finally, we confirmed that both the frequency and power of alpha oscillations remain remarkably stable over extended periods. These findings provide crucial insights for optimizing personalized stimulation frequencies in neuromodulation and may contribute to the development of more targeted and effective interventions aimed at enhancing cognitive function.