Lightweight AI Reverse-Stimulation Emotional Regulation System (LAIRSERS): A Practical Approach to Realize “Emotion Suppression”

Abstract

The Lightweight AI Reverse-Stimulation Emotional Regulation System (LAIRSERS) presents a novel, privacy-focused approach to managing extreme emotional states such as rage, anxiety, and overexcitement. Built on a localized, lightweight AI framework, LAIRSERS eliminates the need for cloud processing, ensuring user autonomy and data security. The system leverages electrocardiography (EKG) analysis to monitor emotional fluctuations and applies reverse-stimulation techniques to regulate emotional responses in real-time. The presentation introduces the latest progress of LAIRSERS, exploring how self-adaptive AI models optimized for microcontrollers enable ultra-low power consumption and seamless integration into wearable devices. The innovative energy self-sustaining system also aims to minimize user intervention while maintaining continuous functionality. LAIRSERS also emphasizes a fashion-forward, modular design, moving beyond conventional fitness bands to offer customizable, stylish wearable solutions. By bridging AI, physiological monitoring, and human-computer interaction principles, LAIRSERS provides a low-effort, high-impact intervention for stress management and emotional well-being. This talk highlights its potential applications in mental health, high-pressure environments, and cognitive performance enhancement, offering a practical, adaptive, and privacy-first solution to emotional regulation.

Bio

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Dr. Shaoyuan Wu has an interdisciplinary background spanning science, law, policy, and history. Currently pursuing his third master's degree through Georgia Tech's OMSCS program, he aims to expand his research scope in AI and human-computer interaction. He led the LAIRSERS project, integrating lightweight AI and physiological monitoring to develop a practical, adaptive, and privacy-first emotional regulation system.