{"type":"ScholarlyArticle","title":"ElderMTL: Multi-Task Affect Monitoring for Elderly Care","authors":[{"name":"Maria Razzhivina","slug":"maria-razzhivina","given":"Maria","family":"Razzhivina","affiliation":""},{"name":"Shahane Tigranyan","slug":"shahane-tigranyan","given":"Shahane","family":"Tigranyan","affiliation":""},{"name":"Aram Avetisyan","slug":"aram-avetisyan","given":"Aram","family":"Avetisyan","affiliation":""},{"name":"Ilya Makarov","slug":"ilya-makarov","given":"Ilya","family":"Makarov","affiliation":""},{"name":"Andrey Savchenko","slug":"andrey-savchenko","given":"Andrey","family":"Savchenko","affiliation":""}],"abstract":"We present ElderMTL, a multi-task affect monitoring system designed for elderly care settings. The system simultaneously estimates Facial Action Units (FAUs), Valence-Arousal (VA) signals, and categorical emotions (FER) from video, capturing multiple layers of affective information. To improve sensitivity to subtle affective cues common in older adults, our approach incorporates age-conditioned physiological modeling, including baseline muscle adjustments and a dynamic AU co-activation graph. This enables the system to adapt to age-related changes in facial expression patterns, providing more reliable and interpretable emotion assessments. In a live demonstration, we showcase ElderMTL processing video streams, visualizing AU activations, affective state predictions, and interpretable insights that highlight age-specific affective dynamics. This work demonstrates that physiologically grounded, multi-task affective monitoring can provide meaningful, real-world support for elderly care.","doi":"10.24963/ijcai.2026/988","url":"https://ijcai.org/proceedings/2026/988","pdf":"https://ijcai.org/proceedings/2026/0988.pdf","markdown":"https://ijcai.org/proceedings/2026/988.md","bibtex":"https://ijcai.org/proceedings/2026/bibtex/988","volume":{"slug":"2026","title":"Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2026","url":"https://ijcai.org/proceedings/2026/","year":2026,"location":"Bremen, Germany","dates":"15-21 August 2026","editors":"Diego Calvanese","isbn":"978-1-956792-09-6","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2026"},"section":"Demo Track","track":"Demo Track","number":988,"pages":{"first":8497,"last":8500},"keywords":["AI: Humans and AI","AI: Machine Learning","AI: Computer Vision"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}