Suicidal Tendency and Depression Diagnosing Medical Agent Using fNIRS and VFT

Functional Near-Infrared Spectroscopy (fNIRS) is a technique for measuring blood flow in the brain, specifically focusing on changes in the frontal lobe. It has found valuable applications in psychiatry, particularly in diagnostic processes. This study explores the potential of fNIRS data and verbal fluency test (VFT) data, both collected during fNIRS measurements, as tools for diagnosing the severity of major depressive disorder, a significant mental health condition. Beyond merely detecting depression, our research introduces a medical support agent model to identify signs of suicidal tendencies in individuals with severe depression. By integrating data collection, preprocessing techniques, feature extraction, and multimodal classification methods for fNIRS and VFT data, our study suggests these artificial intelligence-based medical agents could enhance diagnostic accuracy and provide valuable support in clinical judgments.