Visual and non-visual properties of filters manipulating short-wavelength light

Abstract

Optical filters and tints manipulating short-wavelength light (so-called “blue-blocking” or “blue-attenuating”) are used as a remedy for a range of ocular, retinal, neurological and psychiatric disorders. In many cases, the only available quantification of the optical effects of a given optical filter is the spectral transmittance, which specifies the amount of light transmitted as a function of wavelength. Here, we propose a novel physiologically relevant and retinally referenced framework for quantifying the visual and non-visual effects of these filters, incorporating the attenuation of luminance (luminance factor), the attenuation of melanopsin activation (melanopsin factor), the shift in colour, and the reduction of the colour gamut (gamut factor). We examined a novel data base of optical transmittance filters (n=120) which were digitally extracted from a variety of sources and find a large diversity in the alteration of visual and non-visual properties. We suggest that future studies and examinations of the physiological effects of optical filters quantify the visual and non-visual effects of the filters beyond the spectral transmittance, which will eventually aid in developing a mechanistic understanding of how different filters affect physiology.

Modeling melanopsin‐mediated effects of light on circadian phase, melatonin suppression, and subjective sleepiness

“…29,[57][58][59][60] It further enables design of interventions based on the spectrum, intensity, and timing of light as opposed to the old model where only light with limited spectra could be considered. The new model can now also be applied to predict nonvisual responses to light of different sources when using filters including blue-blocking lenses, or sunglasses, 61,62 as well as for individuals of different ages, as age affects prereceptoral filtering of light. 12,63 Another important consideration is that the model parameters are calibrated for group average, and thus, all model predictions are made for either a group average or a "standard" individual.…”