Proceedings

ElderMTL: Multi-Task Affect Monitoring for Elderly Care

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Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence. Demo Track. Pages 8497-8500.

https://doi.org/10.24963/ijcai.2026/988

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.

Maria Razzhivina, Shahane Tigranyan, Aram Avetisyan, Ilya Makarov, and Andrey Savchenko. 2026. ElderMTL: Multi-Task Affect Monitoring for Elderly Care. In Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-26. IJCAI, 8497–8500. https://doi.org/10.24963/ijcai.2026/988
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