Exploring Expert Perspectives on Wearable-Triggered LLM Conversational Support for Daily Stress Management

TL;DR

This paper introduces EmBot, a mobile app integrating wearable stress detection with LLM-based chat support, and explores mental health experts' perspectives to inform future design of stress management systems.

Contribution

It presents EmBot as a novel prototype and provides insights from experts on designing wearable-triggered conversational mental health support.

Findings

Experts identified key design tensions and considerations.

The study highlights the importance of user-centered design in stress support systems.

Early design insights can guide future development of wearable-triggered mental health tools.

Abstract

Wearable devices increasingly support stress detection, while LLMs enable conversational mental health support. However, designing systems that meaningfully connect wearable-triggered stress events with generative dialogue remains underexplored, particularly from a design perspective. We present EmBot, a functional mobile application that combines wearable-triggered stress detection with LLM-based conversational support for daily stress management. We used EmBot as a design probe in semi-structured interviews with 15 mental health experts to examine their perspectives and surface early design tensions and considerations that arise from wearable-triggered conversational support, informing the future design of such systems for daily stress management and mental health support.