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Light Spot-Based Assay for Analysis of Drosophila Larval Phototaxis
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RayWatch: Hemispherical Diffusion on Wrist UV Sensor for Indoor-Outdoor Sensing.

Harrison Dong1,2, Glenn Fernandes1,2, Christopher Romano1,2

  • 1Department of Computer Science, Northwestern University, Evanston, IL, USA.

... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks
|July 16, 2026
PubMed
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A new UV-monitoring watch uses a special dome and machine learning to accurately detect outdoor sun exposure. This technology aims to provide timely protection cues, reducing melanoma risk.

Area of Science:

  • Biomedical Engineering
  • Wearable Technology
  • Photodetection

Background:

  • Excessive ultraviolet (UV) radiation exposure is a primary cause of melanoma.
  • Current wrist-worn UV monitors lack accuracy due to variations in sensor angle and wrist orientation.
  • Timely, context-aware UV protection alerts are crucial for at-risk individuals.

Purpose of the Study:

  • To develop a novel wrist-worn device for accurate UV context sensing.
  • To improve the reliability of UV monitoring by stabilizing sensor angular response.
  • To enable personalized interventions for reducing cumulative UV exposure.

Main Methods:

  • Developed a wrist-watch device with a UV photodiode under a hemispherical polytetrafluoroethylene (PTFE) dome.
  • Collected over 93,000 indoor/outdoor data points from 10 participants wearing the device during daily activities.

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Last Updated: Jul 17, 2026

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  • Implemented an on-device logistic-regression classifier using UVA, UVB, and inertial sensor data.
  • Main Results:

    • The PTFE-dome watch achieved 94% accuracy and a 0.95 F1 score in distinguishing indoor/outdoor contexts.
    • This performance significantly outperformed a flat-window sensor (71% accuracy, F1=0.72) and a cylindrical-PTFE enclosure (84% accuracy, F1=0.85).
    • Leave-one-participant-out cross-validation confirmed the system's robust performance.

    Conclusions:

    • The developed PTFE-dome watch provides reliable on-wrist UV context sensing.
    • On-device machine learning enhances the accuracy of UV exposure monitoring.
    • This technology offers a pathway for unobtrusive interventions to mitigate UV-related health risks.