Delirium is a common disorder encountered in psychiatric clinical practice, particularly prevalent among elderly patients in hospitals, associated with poor outcome. Early detection and intervention are crucial, yet often overlooked, leading to inadequate treatment. While delirium screening tools like the Confusion Assessment Method (CAM) are generally considered to have high sensitivity and specificity, their sensitivity significantly decreases in busy clinical settings. On the other hand, delirium has long been known to be detectable by EEG, with characteristic findings of low‐frequency waves known as diffuse slowing seen from all electrodes. However, specialized knowledge is required for electrode placement and interpretation, and the equipment itself is large, making it difficult to use as a screening tool. The authors developed their own algorithm, ”bispectral EEG (BSEEG) ,” focusing on distinctive features of delirium and using brain waves obtained from a limited number of electrodes to detect delirium and predict its outcomes. This paper introduces an overview of previous research, its development, and recent findings.