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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.04314 |
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| _version_ | 1866915960444682240 |
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| author | Zhou, Boyang Dana, Zara |
| author_facet | Zhou, Boyang Dana, Zara |
| contents | People often recognize what triggered their stress only after the moment has passed. In therapy, this can become a recurring problem: clients are asked to remember what happened between sessions, but the details that matter (where they were, what they saw and heard, what was happening around them) are easy to lose. We introduce HeartbeatCam, a wearable sensing system that gathers contextual information during moments of elevated stress. It uses a consumer smartwatch stress signal to trigger capture from an open-source AR glasses camera, recording a sparse image-audio clip that can later be reviewed and annotated. The system adopts an actionable sensing approach to mental healthcare, using physiological signals along with contextual capture to support collaborative interpretation of stress-triggering moments with mental health professionals. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_04314 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | HeartbeatCam: Self-Triggered Photo Elicitation of Stress Events Using Wearable Sensing Zhou, Boyang Dana, Zara Human-Computer Interaction People often recognize what triggered their stress only after the moment has passed. In therapy, this can become a recurring problem: clients are asked to remember what happened between sessions, but the details that matter (where they were, what they saw and heard, what was happening around them) are easy to lose. We introduce HeartbeatCam, a wearable sensing system that gathers contextual information during moments of elevated stress. It uses a consumer smartwatch stress signal to trigger capture from an open-source AR glasses camera, recording a sparse image-audio clip that can later be reviewed and annotated. The system adopts an actionable sensing approach to mental healthcare, using physiological signals along with contextual capture to support collaborative interpretation of stress-triggering moments with mental health professionals. |
| title | HeartbeatCam: Self-Triggered Photo Elicitation of Stress Events Using Wearable Sensing |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2604.04314 |