RageSense: Leveraging Acoustic Sensing and LLM-Based Intervention for Emotion Regulation in Mobile Gaming

Apr 13, 2026·

Cong Liu

Ruihao Zheng

Junbin Ren

Kaiyi Guo

Qian Zhang

Dong She

Yuting Bai

Zhanpeng Jin

Yang Gao

Cite ACM DL

RageSense uses near-ultrasonic facial sensing and game context to generate personalized emotion-regulation interventions.

Figure 1 from the paper.

Abstract

RageSense investigates emotion regulation in mobile gaming by combining acoustic sensing with LLM-based intervention. The project focuses on detecting rage-related affective states during gameplay and delivering context-aware support that can help users reflect, recover, and continue interacting in healthier ways. This work contributes to affective computing and human-centered AI by connecting passive mobile sensing with adaptive, language-driven intervention strategies.

Type

Conference paper

Publication

Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI 2026)

Last updated on Apr 13, 2026

CHI Affective Computing Acoustic Sensing Mobile Gaming Large Language Models

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