Electroencephalogram (EEG) can record spontaneous, rhythmic, and non‑rhythmic electrical activity in brain cell populations, and is an important means of evaluating cognitive, arousal, and conscious activity. Compared to traditional EEG linear analysis methods, EEG nonlinear dynamic analysis theory has more advantages in analyzing central brain network disorders in patients with cognitive impairments. Alzheimer's disease (AD) is a degenerative disease of the central nervous system characterized by progressive cognitive impairment and is also the most common cause of senile dementia. This article analyzes the current application status of EEG in the diagnosis, evaluation, and prediction of AD from a linear and nonlinear perspective, aiming to explore the application prospects of EEG in evaluating cognitive impairment related diseases and improve the prognosis of cognitive impairment patients.