Melanopic Limits of Metamer Spectral Optimisation in Multi-Channel Smart Lighting Systems

Modern indoor lighting faces the challenge of finding an appropriate balance between energy consumption, legal requirements, visual performance, and the circadian effectiveness of a spectrum. Multi-channel LED luminaires have the option of keeping image-forming metrics steady while varying the melanopic radiance through metamer spectra for non-visual purposes. Here, we propose the theoretical concept of an automated smart lighting system that is designed to satisfy the user’s visual preference through neural networks while triggering the non-visual pathway via metamers. To quantify the melanopic limits of metamers at a steady chromaticity point, we have used 561 chromaticity coordinates along the Planckian locus (2700 K to 7443 K, ±Duv 0 to 0.048) as optimisation targets and generated the spectra by using a 6-channel, 8-channel, and 11-channel LED combination at three different luminance levels. We have found that in a best-case scenario, the melanopic radiance can be varied up to 65% while keeping the chromaticity coordinates constant (Δu′v′≤7.05×10−5) by using metamer spectra. The highest melanopic metamer contrast can be reached near the Planckian locus between 3292 and 4717 K within a Duv range of −0.009 to 0.006. Additionally, we publish over 1.2 million optimised spectra generated by multichannel LED luminaires as an open-source dataset along with this work.

Deep learning-based pupil model predicts time and spectral dependent light responses

Although research has made significant findings in the neurophysiological process behind the pupillary light reflex, the temporal prediction of the pupil diameter triggered by polychromatic or chromatic stimulus spectra is still not possible. State of the art pupil models rested in estimating a static diameter at the equilibrium-state for spectra along the Planckian locus. Neither the temporal receptor-weighting nor the spectral-dependent adaptation behaviour of the afferent pupil control path is mapped in such functions. Here we propose a deep learning-driven concept of a pupil model, which reconstructs the pupil’s time course either from photometric and colourimetric or receptor-based stimulus quantities. By merging feed-forward neural networks with a biomechanical differential equation, we predict the temporal pupil light response with a mean absolute error below 0.1 mm from polychromatic (2007 $$\pm$$ ± 1 K, 4983 $$\pm$$ ± 3 K, 10,138 $$\pm$$ ± 22 K) and chromatic spectra (450 nm, 530 nm, 610 nm, 660 nm) at 100.01 ± 0.25 cd/m2. This non-parametric and self-learning concept could open the door to a generalized description of the pupil behaviour.

Vision and Hyper-Responsiveness in Migraine

We investigated contrast processing in relation to visual comfort from coloured light in individuals with migraine. In Experiment 1, 24 individuals who experienced migraine with aura (MA), 15 migraine without aura (MO), and 23 healthy controls, identified which of four patterns, one in each quadrant, had the greatest contrast. Although there were no significant differences between groups, contrast discrimination was superior in the visual field affected by aura in all eight participants in whom the aura was consistently lateralised. In Experiment 2, 20 participants without aura and 20 controls selected comfortable light with a chromaticity close to the daylight (Planckian) locus, whilst 20 individuals with aura chose more strongly saturated colours, mostly distant from the locus. In Experiment 3, nine participants with consistently unilateral aura undertook the contrast discrimination task wearing (a) lenses that provided a comfortable colour of light and (b) grey lenses of similar transmission. With grey lenses, seven of the nine individuals with unilateral aura showed a superior performance in the affected field, as before. With lenses providing a comfortable colour, however, the performance was relatively poor for the nine individuals with unilateral aura, but not for the 10 controls. This was the case in both visual fields. The cortical hyper-responsiveness with which migraine is associated may improve the perception of contrast. The perception is poorer (and more normal) with ophthalmic lenses having a comfortable colour.

A white–cyan-red LED system for low correlated colour temperature lighting

A white LED complemented by cyan and red LEDs is a good candidate for achieving high colour rendering at low correlated colour temperatures. This is usually very difficult with commercially available white LEDs. In addition, the system is able to replace incandescent lighting in many applications; for example, the lighting for museum display cases. To investigate and optimize the colour and light distribution properties, both spectral and geometrical modelling are used. Mapping of the possible combinations of LEDs is used to locate the optimal solutions within the colour gamut, with emphasis on chromaticity and colour rendering indices. A geometric optical model is used to design and optimize the homogeneity of the colour and light intensity distribution as a function of angle. The resulting system produces diffused homogeneous white light with a tunable correlated colour temperature from 2000 K to 2400 K. Within this range the white light is characterized by a high general colour rendering index (Ra > 90), special colour rendering indices for saturated red objects (R9 > 85), and low chromaticity distance (Duv) from the Planckian locus (Duv < 2 × 10−3).