A Study to Explore the Altered State of Consciousness Using Brain–Computer Interface (BCI)

Affective computing, a category of artificial intelligence, encompasses functions such as detecting, processing, interpreting, and simulating human emotions. The development of non-invasive, portable human sensor technologies, the interest of academics from a number of fields are becoming interested in areas like emotion detection and brain–computer interfaces (BCI). Human emotions may be recognized using a number of psychological signals, including behavior (gesture/posture), and body language, speech, and physiological signs. However, it is ineffective since people can cover their genuine feelings either intentionally or subconsciously (a practice known as social masking). More precise and objective emotion identification can be achieved using physiological signals. Patients with Disorder of Consciousness (DOC), such as in coma, vegetative state, minimally conscious state, and generally have motor dysfunctions and are unable to accurately express their feelings when in a growing minimally conscious condition. In order to help patients with DOC, they used BCI technology for emotion identification. Our study justifies the same model can be used for different mental states and diseases that can be used for the DOC. The BCI system may be the most effective method for identifying patients with DOC are experiencing emotional emotions.