Problem
Research questions and friction points this paper is trying to address.
earable system
stress-adaptive meditation
physiological sensing
personalized intervention
closed-loop adaptation
EarStreAM: A Closed-Loop Earable System for Personalized Stress-Adaptive Meditation
🤖 AI Summary
研究提出EarStreAM系统，通过耳内生理信号监测与个性化实时干预结合的方法，实现适应性冥想以缓解压力。
📝 Abstract
We present EarStreAM, a closed-loop earable system for stress-adaptive meditation that integrates in-ear physiological sensing with personalized, real-time intervention. Leveraging OpenEarable 2.0's multimodal sensing, EarStreAM continuously monitors physiological signals and detects elevated stress from heart rate and heart rate variability. Upon detection, the system initiates a personalized guided meditation generated by an LLM and adapted in real time to the user's stress state. The demo offers a hands-on experience of stress-adaptive meditation in two modes: a biosignal-adaptive meditation with optional stress induction to illustrate closed-loop adaptation, and a meditation-only mode focusing on EarStreAM's generative personalization capabilities. The demo highlights how in-ear sensing, closed-loop adaptation, and personalized generative meditation can be integrated into an earable system for real-time stress support in demanding office work contexts.
Innovation
Methods, ideas, or system contributions that make the work stand out.
closed-loop adaptation
in-ear sensing
personalized generative meditation
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