Reliability of Emotion Analysis from Human Facial Expressions Using Multi-task Cascaded Convolutional Neural Networks

• Published in: The Journal of Medical Investigation Vol. 72; no. 1.2; pp. 93 - 101
• Main Authors: Blaquera, Allan Paulo L., Tanioka, Tetsuya, Ito, Hirokazu, Bollos, Leah Anne Christine, Soriano, Gil P., Tanioka, Ryuichi, Akiyama, Toshiya, Osaka, Kyoko, Umehara, Hidehiro
• Format: Journal Article
• Language: English
• Published: Japan The University of Tokushima Faculty of Medicine 2025
• Subjects: Adult; Convolutional Neural Networks; Emotions; Facial Expression; Facial expression analysis; Female; Humans; Inter-rater reliability; Male; Multi-task Cascaded Convolutional Neural Networks; Neural Networks, Computer; Reproducibility of Results; Robotics; Young Adult; Inter-rater reliability; Multi-task Cascaded Convolutional Neural Networks; Facial expression analysis; Robotics

Life support robots in care settings must be able to read a person’s emotions from facial expressions to achieve empathic communication. This study aims to determine the degree of agreement between Multi-task Cascaded Convolutional Neural Networks (MTCNN) results and human subjective emotion analysi...