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An ipRGC-influenced/Non-Visual Spectral Occupant Model for lighting design, Part 2: Photobiological model

J Alstan Jakubiec1,2, A Alight1

  • 1John H. Daniels Faculty of Architecture, Landscape and Design, University of Toronto, Toronto, ON, Canada.

Lighting Research & Technology (London, England : 2001)
|March 19, 2026
PubMed
Summary
This summary is machine-generated.

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An ipRGC-influenced/Non-Visual Spectral Occupant Model (iNSOM) for lighting design, Part 1: Light simulation method.

Lighting research & technology (London, England : 2001)·2026
See all related articles

This study introduces the iNSOM model for assessing non-visual lighting effects. It predicts occupant responses like circadian dynamics and alertness, offering a new way to evaluate lighting design for health.

Area of Science:

  • Lighting science
  • Photobiology
  • Human-centered design

Background:

  • Non-visual lighting effects are crucial for human health and well-being.
  • Existing metrics may not fully capture the impact of light on intrinsically photosensitive retinal ganglion cells (ipRGCs).
  • A need exists for advanced models to assess lighting's photobiological impact.

Purpose of the Study:

  • To pilot a novel method, the ipRGC-influenced/Non-Visual Spectral Occupant Model (iNSOM), for assessing non-visual lighting effects.
  • To develop metrics for predicting circadian dynamics, alertness, and melatonin levels based on light exposure.
  • To evaluate lighting designs using quantitative outputs and spatial visualizations of ipRGC-influenced effects.

Main Methods:

  • Annual full-spectrum lighting calculations using the iNSOM model.

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  • Derivation of seasonal and time-of-day metrics from established photobiological models.
  • Application of the model to a hospital ward under various lighting scenarios and sleep quality conditions.
  • Comparative analysis with existing ipRGC-influenced lighting metrics and standards.
  • Main Results:

    • iNSOM provides quantitative metrics and spatial visualizations for evaluating lighting design based on ipRGC-influenced effects.
    • The model demonstrates differences between predicted alertness/health metrics and existing saturation-based metrics.
    • The study highlights variations in ipRGC-influenced metrics across different operational scenarios and sleep quality types.

    Conclusions:

    • The iNSOM model offers a comprehensive approach to assessing non-visual lighting effects.
    • iNSOM's outputs can inform lighting design for improved occupant health and well-being.
    • The developed metrics provide a nuanced understanding of light's impact on circadian and cognitive functions.