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.

翻译：可穿戴设备日益支持压力检测，而大语言模型则实现了对话式心理健康支持。然而，如何设计出能将可穿戴设备触发的压力事件与生成式对话有效结合的交互系统仍未充分探索，尤其是从设计视角出发。我们提出了EmBot，一个功能型移动应用，它结合了可穿戴设备触发的压力检测与大语言模型支持的对话系统，用于日常压力管理。我们以EmBot为设计探针，对15位心理健康专家进行了半结构化访谈，以考察他们的观点，并揭示由可穿戴设备触发的对话式支持所引发的早期设计张力与考量，从而为未来此类系统在日常生活压力管理与心理健康支持方面的设计提供参考。