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Published on in Vol 8 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/72338, first published .
Using Wearable Sensors to Measure and Predict Personal Circadian Lighting Exposure in Nursing Home Residents: Model Development and Validation

Using Wearable Sensors to Measure and Predict Personal Circadian Lighting Exposure in Nursing Home Residents: Model Development and Validation

Using Wearable Sensors to Measure and Predict Personal Circadian Lighting Exposure in Nursing Home Residents: Model Development and Validation

Journals

  1. Wang Y, Zhang Y, Cheng S, Zhang Y, Zhang X. Towards a predictive paradigm for individual light exposure history: A trajectory-based modeling framework. Building and Environment 2026;294:114422 View
  2. Ribino P, Potenza G, Baglivo C, Bonomolo M. Intelligent lighting systems: Leveraging LSTM and time-series clustering for optimal PhotoSensor deployment. Journal of Building Engineering 2026;122:115761 View
  3. Beiglary S, Wang J. Real-time modeling of human behavior effects on circadian lighting exposure in nursing homes. Building and Environment 2026;298:114618 View
  4. Spitschan M, Zauner J. Light Exposure as a Modifiable Determinant of Mental Health. Current Psychiatry Reports 2026;28(1) View
  5. de Vries S, Mardaljevic J, van Duijnhoven J. Impact of wear position on dosimeter performance: measurement validity under simulated indoor illumination. npj Biological Timing and Sleep 2026;3(1) View