부산대학교 도서관

There is a lack of automated tools that utilize artificial intelligence to monitor mental health. The mental status examination (MSE) is an important tool used by mental health providers for assessing mental health. Currently, MSEs are conducted by licensed professionals, which is a barrier for patients in low income and remote areas. We propose an AI-based personal online mental status examination (aiMSE), the first interactive MSE platform. Users can use aiMSE to self-administer MSEs at home through a web browser, using only a camera and microphone. aiMSE uses multimodal image, speech, and natural language processing algorithms to detect signs of abnormalities in mental functioning and recommend them for further examination by a mental health specialist. We conducted a 14-person study, which supports the feasibility of detecting a wide range of signs commonly found in patients with changes in mental or cognitive capacity.