Despite the high performance of existing state-of-the-art deep learning models for depression detection using electroencephalography (EEG). they incur a heavy computational burden. In this paper. we propose an efficient model consisting of a cascade of an encoder. https://spencertifieders.shop/product-category/power-supply-enclosures/