Captivates: A Smart Eyeglass Platform for Across-Context Physiological Measurement
Patrick Chwalek, David B. Ramsay, Joseph A. Paradiso
摘要
We present Captivates, an open-source smartglasses system designed for long-term, in-the-wild psychophysiological monitoring at scale. Captivates integrate many underutilized physiological sensors in a streamlined package, including temple and nose temperature measurement, blink detection, head motion tracking, activity classification, 3D localization, and head pose estimation. Captivates were designed with an emphasis on: (1) manufacturing and scalability, so we can easily support large scale user studies for ourselves and offer the platform as a generalized tool for ambulatory psychophysiology research; (2) robustness and battery life, so long-term studies result in trustworthy data individual's entire day in natural environments without supervision or recharge; and (3) aesthetics and comfort, so people can wear them in their normal daily contexts without self-consciousness or changes in behavior. Captivates are intended to enable large scale data collection without altering user behavior. We validate that our sensors capture useful data robustly for a small set of beta testers. We also show that our additional effort on aesthetics was imperative to meet our goals; namely, earlier versions of our prototype make people uncomfortable to interact naturally in public, and our additional design and miniaturization effort has made a significant impact in preserving natural behavior. There is tremendous promise in translating psychophysiological laboratory techniques into real-world insight. Captivates serve as an open-source bridge to this end. Paired with an accurate underlying model, Captivates will be able to quantify the long-term psychological impact of our design decisions and provide real-time feedback for technologists interested in actuating a cognitively adaptive, user-aligned future.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了最后一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper2
- Cognitive Load Inference Using Physiological Markers in Virtual RealityJishang Wei, Erika Siegel, Prahalathan Sundaramoorthy, Antônio Gomes 等IEEE VR 2025 · 被引用 13 次
- UbiHR: Resource-efficient Long-range Heart Rate Sensing on Ubiquitous DevicesHaoyu Bian, Bin Guo, Sicong Liu, Yasan Ding 等UbiComp 2025 · 被引用 6 次
相关 Paper
- EyeEcho: Continuous and Low-power Facial Expression Tracking on GlassesKe Li, Ruidong Zhang, Siyuan Chen, Boao Chen 等CHI 2024 · 被引用 27 次
- In Focus, Out of Privacy: The Wearer's Perspective on the Privacy Dilemma of Camera GlassesDivyanshu Bhardwaj, Alexander Ponticello, Shreya Tomar, Adrian Dabrowski 等CHI 2024 · 被引用 31 次
- OSMO: Open-vocabulary Self-eMOtion TrackingMohamed Abdelfattah, Bugra Tekin, Fadime Sener, Necati Cihan Camgoz 等CVPR 2026
- Thermal Earring: Low-power Wireless Earring for Longitudinal Earlobe Temperature SensingQiuyue (Shirley) Xue, Yujia Liu, Joseph Breda, Mastafa Springston 等UbiComp 2024 · 被引用 9 次
- HabitSense: A Privacy-Aware, AI-Enhanced Multimodal Wearable Platform for mHealth ApplicationsGlenn Fernandes, Jiayi Zheng, Mahdi Pedram, Christopher Romano 等UbiComp 2024 · 被引用 19 次
