Alzheimer Disease is one of the most common & tremendously growing neurological diseases in the world. Several biomarkers tools exist for diagnosis & disease progression in Alzheimer disease which can be assumed as key issues for clinical applications. Electroencephalogram signals (EEG) yields out powerful and relatively cheap tool of diagnosis of different neurological disease. The need in this case is to improve the diagnostic accuracy of the EEG signals. In this proposed work, a new methodology for diagnosis of Alzheimer disease using EEG signals is proposed; thereby increasing the diagnostic accuracy of the EEG signals & diagnosis. Several features of EEG Signals such as Spectral features, Coherence features & EEG Spectro-temporal modulation energy based features are discussed in detail. From the above discussed features available in the EEG signal, it is concluded that EEG can play an important role in diagnosis of Dementia & Alzheimer Disease.