Evidence for human-centric in-vehicle lighting: part 3-Illumination preferences based on subjective ratings, eye-tracking behavior, and EEG features.

Within this third part of our mini-series, searching for the best and worst automotive in-vehicle lighting settings, we aim to extend our previous finding about white light illumination preferences by adding local cortical area activity as one key indicator. Frontal electrical potential asymmetry, measured using an electroencephalogram (EEG), is a highly correlated index for identifying positive and negative emotional behavior, primarily in the alpha band. It is rarely understood to what extent this observation can be applied to the evaluation of subjective preference or dislike based on luminaire variations in hue, chroma, and lightness. Within a controlled laboratory study, we investigated eight study participants who answered this question after they were shown highly immersive 360° image renderings. By so doing, we first subjectively defined, based on four different external driving scenes varying in location and time settings, the best and worst luminaire settings by changing six unlabeled luminaire sliders. Emotional feedback was collected based on semantic differentials and an emotion wheel. Furthermore, we recorded 120 Hz gaze data to identify the most important in-vehicle area of interest during the luminaire adaptation process. In the second study session, we recorded EEG data during a binocular observation task of repeated images arbitrarily paired by previously defined best and worst lighting settings and separated between all four driving scenes. Results from gaze data showed that the central vehicle windows with the left-side orientated colorful in-vehicle fruit table were both significantly longer fixed than other image areas. Furthermore, the previously identified cortical EEG feature describing the maximum power spectral density could successfully separate positive and negative luminaire settings based only on cortical activity. Within the four driving scenes, two external monotonous scenes followed trendlines defined by highly emotionally correlated images. More interesting external scenes contradicted this trend, suggesting an external emotional bias stronger than the emotional changes created by luminaires. Therefore, we successfully extended our model to define the best and worst in-vehicle lighting with cortical features by touching the field of neuroaesthetics.

Brightness perception under photopic conditions: experiments and modeling with contributions of S-cone and ipRGC.

In 1924, the CIE published and standardized the photopic luminous efficiency function. Based on the standardized curve, luminous flux in lumens, luminance in cd/m[Formula: see text], and illuminance in lux are determined by an integral of the curve and the incident light spectra in photometers and are considered physical brightness. However, human brightness perception is not only weighted by this simple determination, but is a more complicated combination of all L-cones, M-cones, S-cones, rods and later ipRGCs, which was partly described by the equivalent brightness of Fotios et al. with the correction factor [Formula: see text]. Recently, new research has demonstrated the role of ipRGCs in human light perception. However, it is still unclear how these signal components of the human visual system are involved in the overall human brightness perception. In this work, human brightness perception under photopic conditions was investigated by visual experiments with 28 subjects under 25 different light spectra. In this way, the contributions of the signal components can be investigated. An optimization process was then performed on the resulting database. The results show that not only the [Formula: see text] component, but also the S-cones and ipRGC play a role, although it is smaller. Thus, the visually scaled brightness model based on the database optimization was constructed using not only illuminance but also S-cones and ipRGC with [Formula: see text] of 0.9554 and RMSE of 4.7802. These results are much better than the brightness model after Fotios et al. using only S-cones ([Formula: see text] = 0.8161, RMSE = 9.7123) and the traditional model without S-cones and ipRGC ([Formula: see text] = 0.8121, RMSE = 9.8171).

Numerical correlation between non-visual metrics and brightness metrics-implications for the evaluation of indoor white lighting systems in the photopic range.

From the beginning of the [Formula: see text] century until today, the demand for lighting systems includes not only visual parameters (brightness, contrast perception, color quality), but also non-visual parameters. It is necessary to define the new non-visual parameters for the realization of the new concept of Human Centric Lighting (HCL) or Integrative Lighting. As a contribution to this approach, many international research groups have tried to quantify the non-visual parameters such as Circadian Stimulus by Rea et. al. in USA ([Formula: see text], [Formula: see text]), Melanopic Equivalent Daylight ([Formula: see text]) illuminance, mEDI of the CIE S 026/E:2018 or the latest formula by Giménez et al., for the nocturnal melatonin suppression. Therefore, it is necessary to analyze the correlation between these non-visual metrics and brightness metrics such as the equivalent luminance of Fotios et al., or the latest brightness model of TU Darmstadt so that scientists, lighting engineers and lighting system users can correctly apply them in their work. In this context, this paper attempts to investigate and analyze these correlations between the three metric groups based on the database of 884 light sources of different light source technologies and daylight spectra. The obtained results show that the latest Circadian Stimulus model of Rea et. al. [Formula: see text] with the improvement of Circadian Light [Formula: see text] ([Formula: see text]) has solved the disadvantage of [Formula: see text], especially for the interrupted point between warm and cold white (about [Formula: see text]) or the junction between negative and positive signal of the opponent channel ([Formula: see text]). Moreover, these three metrics of the three research groups contain a high correlation coefficient, so that one metric can be transformed by linear functions to the other two parameters.

Reconstruction of spectral irradiance in a real application with a multi-channel spectral sensor using convolutional neural networks.

Lighting is not only a key mediator for the perception of the architectural space but also plays a crucial role regarding the long-term well-being of its human occupants. Future lighting solutions must therefore be capable of monitoring lighting parameters to allow for a dynamic compensation of temporal changes from the optimal or intended conditions. Although mostly based on synthetic data, previous studies adopting small, low-cost, multi-band color sensors for this kind of parameter estimation have reported some promising preliminary results. Building up on these findings, the present work introduces a new methodology for estimating the absolute spectral irradiances of real-world lighting scenarios from the responses of a 10-channel spectral sensor by using a convolutional neural network approach. The lighting scenarios considered here are based on a tunable white floor lamp system set up at three different indoor locations and comprise combinations of LED, fluorescent, tungsten, and daylight lighting conditions. For white light mixtures of the various spectral components, the proposed reconstruction methodology yields estimates of the spectral power distribution with an average root-mean-square error of 1.6%, an average Δu'v' of less than 0.001, and an average illuminance accuracy of 2.7%. Sensor metamerism is discussed as a limiting factor for the achievable spectral reconstruction accuracy with certain light mixtures.

Determination and Measurement of Melanopic Equivalent Daylight (D65) Illuminance (mEDI) in the Context of Smart and Integrative Lighting.

In the context of intelligent and integrative lighting, in addition to the need for color quality and brightness, the non-visual effect is essential. This refers to the retinal ganglion cells (ipRGCs) and their function, which were first proposed in 1927. The melanopsin action spectrum has been published in CIE S 026/E: 2018 with the corresponding melanopic equivalent daylight (D65) illuminance (mEDI), melanopic daylight (D65) efficacy ratio (mDER), and four other parameters. Due to the importance of mEDI and mDER, this work synthesizes a simple computational model of mDER as the main research objective, based on a database of 4214 practical spectral power distributions (SPDs) of daylight, conventional, LED, and mixed light sources. In addition to the high correlation coefficient R2 of 0.96795 and the 97% confidence offset of 0.0067802, the feasibility of the mDER model in intelligent and integrated lighting applications has been extensively tested and validated. The uncertainty between the mEDI calculated directly from the spectra and that obtained by processing the RGB sensor and applying the mDER model reached ± 3.3% after matrix transformation and illuminance processing combined with the successful mDER calculation model. This result opens the potential for low-cost RGB sensors for applications in intelligent and integrative lighting systems to optimize and compensate for the non-visual effective parameter mEDI using daylight and artificial light in indoor spaces. The goal of the research on RGB sensors and the corresponding processing method are also presented and their feasibility is methodically demonstrated. A comprehensive investigation with a huge amount of color sensor sensitivities is necessary in a future work of other research.

Evidence for human-centric in-vehicle lighting: Part 2-Modeling illumination based on color-opponents.

Illumination preference models are usually defined in a static scenery, rating common-colored objects by a single scale or semantic differentials. Recently, it was reported that two to three illumination characteristics are necessary to define a high correlation in a bright office-like environment. However, white-light illumination preferences for vehicle-occupants in a dynamic semi- to full automated modern driving context are missing. Here we conducted a global free access online survey using VR engines to create 360° sRGB static in-vehicle sceneries. A total of 164 participants from China and Europe answered three levels in our self-hosted questionnaire by using mobile access devices. First, the absolute perceptional difference should be defined by a variation of CCT for 3,000, 4,500, and 6,000 K or combinations, and light distribution, either in a spot- or spatial way. Second, psychological light attributes should be associated with the same illumination and scenery settings. Finally, we created four driving environments with varying external levels of interest and time of the day. We identified three key results: (1) Four illumination groups could be classified by applying nMDS. (2) Combinations of mixed CCTs and spatial light distributions outperformed compared single light settings (p < 0.05), suggesting that also during daylight conditions artificial light supplements are necessary. (3) By an image transformation in the IPT and CAM16 color appearance space, comparing external and in-vehicle scenery, individual illumination working areas for each driving scenery could be identified, especially in the dimension of chroma-, partially following the Hunt-Effect, and lightness contrast, which synchronizes the internal and external brightness level. We classified our results as a starting point, which we intend to prove in a follow-up-controlled laboratory study with real object arrangements. Also, by applying novel methods to display high fidelity 360° rendered images on mobile access devices, our approach can be used in the future interdisciplinary research since high computational mobile devices with advanced equipped sensory systems are the new standard of our daily life.

Study protocol for measuring the impact of (quasi-)monochromatic light on post-awakening cortisol secretion under controlled laboratory conditions.

Cortisol secretion has a fundamental role in human circadian regulation. The cortisol awakening response (CAR) can be observed as a daily recurring sharp increase in cortisol concentration within the first hour after awakening and is influenced by environmental light conditions. The current work provides the study protocol for an ongoing research project that is intended to explore the spectral dependencies and to discuss measures of emotional state and cognitive functioning potentially related to the CAR. Based on a controlled within-subjects sleep laboratory study, the impact of a two-hour, (quasi-)monochromatic, post-awakening light exposure of different peak wavelength (applied from 6:00 to 8:00 am) on resulting CAR levels should be investigated in a systematic manner to eventually derive a corresponding spectral sensitivity model. As a secondary outcome, it should be explored whether a potentially light-enhanced cortisol secretion might also impact different measures of sleepiness, mood, and vigilance for certain wavelengths. The study protocol described in the present work discusses the various protocol steps using pilot data collected for two different wavelength settings (i.e., short-wavelength blue-light at λmax = 476 nm and long-wavelength red-light at λmax = 649 nm) experienced by a group of four healthy male adults at an average ± SD age of 25.25 ± 3.59 years.

Extending the color discrimination metric with consideration of illuminance level.

Color discrimination is a crucial dimension for the visual assessment of white light sources. In this Letter, we took full advantage of data comparability among Farnsworth-Munsell 100 Hue (FM-100) color vision tests and modified our recent proposed color discrimination metric [Opt. Lett.45, 6062 (2020)10.1364/OL.400422] to make it effective in quantifying the color discrimination capability of lighting under multiple illuminance levels. The updated metric was developed based on a meta-analysis of 100 sets of combined visual data derived from three groups of visual studies containing 29 FM-100 trials and its superiority was comprehensively validated by 140 sets of combined data from five groups of studies with 42 FM-100 trials.

Optimising metameric spectra for integrative lighting to modulate the circadian system without affecting visual appearance.

Smart integrative lighting systems aim to support human health and wellbeing by capitalising on the light-induced effects on circadian rhythms, sleep, and cognitive functions, while optimising the light's visual aspects like colour fidelity, visual comfort, visual preference, and visibility. Metameric spectral tuning could be an instrument to solve potential conflicts between the visual preferences of users with respect to illuminance and chromaticity and the circadian consequences of the light exposure, as metamers can selectively modulate melanopsin-based photoreception without affecting visual properties such as chromaticity or illuminance. This work uses a 6-, 8- and 11-channel LED luminaire with fixed illuminance of 250 lx to systematically investigate the metameric tuning range in melanopic equivalent daylight illuminance (EDI) and melanopic daylight efficacy ratio (melanopic DER) for 561 chromaticity coordinates as optimisation targets (2700 K to 7443 K ± Duv 0 to 0.048), while applying colour fidelity index Rf criteria from the TM-30-20 Annex E recommendations (i.e. Rf [Formula: see text] 85, Rf,h1 [Formula: see text] 85). Our results reveal that the melanopic tuning range increases with rising CCT to a maximum tuning range in melanopic DER of 0.24 (CCT: 6702 K, Duv: 0.003), 0.29 (CCT: 7443 K, Duv: 0) and 0.30 (CCT: 6702, Duv: 0.006), depending on the luminaire's channel number of 6, 8 or 11, respectively. This allows to vary the melanopic EDI from 212.5-227.5 lx up to 275-300 lx without changes in the photopic illuminance (250 lx) or chromaticity ([Formula: see text] [Formula: see text] 0.0014). The highest metameric melanopic Michelson contrast for the 6-, 8- and 11-channel luminaire is 0.16, 0.18 and 0.18, which is accomplished at a CCT of 3017 K (Duv: - 0.018), 3456 K (Duv: 0.009) and 3456 K (Duv: 0.009), respectively. By optimising ~ 490,000 multi-channel LED spectra, we identified chromaticity regions in the CIExy colour space that are of particular interest to control the melanopic efficacy with metameric spectral tuning.

Quantifying observer metamerism of LED spectra which chromatically mimic natural daylight.

When LEDs are used to mimic daylight, a side-by-side comparison of the chromaticity difference between the LED spectrum and natural daylight will be perceived differently by individual observers. The magnitude of this effect depends on the LED light's spectral power distribution and can be assessed by using individual observer functions. To minimize the computational effort, an observer metamerism index can be utilized. Here, we compare three methods from the literature to define an observer metamerism index by carrying out a correlation analysis, in which reference spectra of the whole daylight range (1600 K to 88000 K) are used together with an empirical study. The recommended metric is based on a principal component analysis of 1000 individual observers' color matching functions to define a deviate observer. Using the proposed metamerism index significantly simplifies the calculation of the observer metamerism evaluation. Thus, this metric can be applied in spectral optimization pipelines, which are embedded in smart and adaptive multi-primary LED luminaires.

Memory colors and the assessment of color quality in lighting applications.

Due to their potential use as an internal reference, memory colors may provide an excellent approach for the color rendition evaluation of white light sources in terms of predicting visual appreciation. Because of certain limitations in the design of existing memory-related color quality measures, a new metric based on the outcome of a series of recently conducted memory color appearance rating experiments is proposed in this work. In order to validate its predictive performance, a meta-correlation analysis on a comprehensive set of preference rating data collected from literature is performed. Results indicate that the new metric proposal outperforms established color quality measures and is capable of correctly predicting the rank order of light sources in different lighting scenarios. The future inclusion of this new metric into a comprehensive lighting quality model may serve as a valuable tool for the lighting designer to create optimally lit environments for humans that do not only support the visual task fulfillment but also increase the users' well-being and emotional comfort by rendering the perceived space in such a way that it complies with the people's inherent memory references.

PupilEXT: Flexible Open-Source Platform for High-Resolution Pupillometry in Vision Research.

The human pupil behavior has gained increased attention due to the discovery of the intrinsically photosensitive retinal ganglion cells and the afferent pupil control path's role as a biomarker for cognitive processes. Diameter changes in the range of 10-2 mm are of interest, requiring reliable and characterized measurement equipment to accurately detect neurocognitive effects on the pupil. Mostly commercial solutions are used as measurement devices in pupillometry which is associated with high investments. Moreover, commercial systems rely on closed software, restricting conclusions about the used pupil-tracking algorithms. Here, we developed an open-source pupillometry platform consisting of hardware and software competitive with high-end commercial stereo eye-tracking systems. Our goal was to make a professional remote pupil measurement pipeline for laboratory conditions accessible for everyone. This work's core outcome is an integrated cross-platform (macOS, Windows and Linux) pupillometry software called PupilEXT, featuring a user-friendly graphical interface covering the relevant requirements of professional pupil response research. We offer a selection of six state-of-the-art open-source pupil detection algorithms (Starburst, Swirski, ExCuSe, ElSe, PuRe and PuReST) to perform the pupil measurement. A developed 120-fps pupillometry demo system was able to achieve a calibration accuracy of 0.003 mm and an averaged temporal pupil measurement detection accuracy of 0.0059 mm in stereo mode. The PupilEXT software has extended features in pupil detection, measurement validation, image acquisition, data acquisition, offline pupil measurement, camera calibration, stereo vision, data visualization and system independence, all combined in a single open-source interface, available at https://github.com/openPupil/Open-PupilEXT.

The Sternberg Paradigm: Correcting Encoding Latencies in Visual and Auditory Test Designs.

The Sternberg task is a widely used tool for assessing the working memory performance in vision and cognitive science. It is possible to apply a visual or auditory variant of the Sternberg task to query the memory load. However, previous studies have shown that the subjects' corresponding reaction times differ dependent on the used variant. In this work, we present an experimental approach that is intended to correct the reaction time differences observed between auditory and visual item presentation. We found that the subjects' reaction time offset is related to the encoding speed of a single probe item. After correcting for these individual encoding latencies, differences in the results of both the auditory and visual Sternberg task become non-significant, p=0.252. Thus, an equal task difficulty can be concluded for both variants of item presentation.

Tackling Heterogeneous Color Registration: Binning Color Sensors.

Intelligent systems for interior lighting strive to balance economical, ecological, and health-related needs. For this purpose, they rely on sensors to assess and respond to the current room conditions. With an augmented demand for more dedicated control, the number of sensors used in parallel increases considerably. In this context, the present work focuses on optical sensors with three spectral channels used to capture color-related information of the illumination conditions such as their chromaticities and correlated color temperatures. One major drawback of these devices, in particular with regard to intelligent lighting control, is that even same-type color sensors show production related differences in their color registration. Standard methods for color correction are either impractical for large-scale production or they result in large colorimetric errors. Therefore, this article shows the feasibility of a novel sensor binning approach using the sensor responses to a single white light source for cluster assignment. A cluster specific color correction is shown to significantly reduce the registered color differences for a selection of test stimuli to values in the range of 0.003-0.008 Δu'v', which enables the wide use of such sensors in practice and, at the same time, requires minimal additional effort in sensor commissioning.

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 [Formula: see text] 1 K, 4983 [Formula: see text] 3 K, 10,138 [Formula: see text] 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.

Prediction accuracy of L- and M-cone based human pupil light models.

Multi-channel LED luminaires offer a powerful tool to vary retinal receptor signals while keeping visual parameters such as color or brightness perception constant. This technology could provide new fields of application in indoor lighting since the spectrum can be enhanced individually to the users' favor or task. One possible application would be to optimize a light spectrum by using the pupil diameter as a parameter to increase the visual acuity. A spectral- and time-dependent pupil model is the key requirement for this aim. We benchmarked in our work selected L- and M-cone based pupil models to find the estimation error in predicting the pupil diameter for chromatic and polychromatic spectra at 100 cd/m2. We report an increased estimation error up to 1.21 mm for 450 nm at 60-300 s exposure time. At short exposure times, the pupil diameter was approximately independent of the used spectrum, allowing to use the luminance for a pupil model. Polychromatic spectra along the Planckian locus showed at 60-300 s exposure time, a prediction error within a tolerance range of ± 0.5 mm. The time dependency seems to be more essential than the spectral dependency when using polychromatic spectra.

Preliminary measure for the characterization of the usefulness of light sources.

A preliminary usefulness metric is defined. The metric is intended to characterize the energy efficiency of light sources in a more comprehensive way than the luminous efficacy of a source by taking selected spectral aspects of human centric lighting into consideration. The presented version of the metric is a combination of well-established measures of color quality, brightness and the circadian effect derived from the spectral power distribution of the light source. The metric includes a limited application dependence: it yields different values for interior and exterior applications, static and dynamic as well as relaxing and activating light source spectra. Light source categories (A-G) with preliminary category limits were also computed in the two-dimensional diagram associated with the metric. The metric should be considered as a basis for further discussions and not as a final solution.

Long-term memory color investigation: culture effect and experimental setting factors.

Memory colors generated continuous interest in the color community. Previous studies focused on reflecting color chips and color samples in real scenes or on monitors. The cognitive effect of culture was rarely considered. In this paper, we performed a comprehensive investigation of the long-term memory colors of 26 familiar objects using the asymmetric color matching method among Chinese and German observers on a display. Three experiments were conducted to evaluate the variations introduced by culture, context-based gray image, and initial matching color. Memory colors of important objects were collected and representative memory colors were quantified in terms of CIELAB L*, a*, and b* values. The intra- and inter-observer variations were analyzed by mean-color-difference-from-mean values and chromatic ellipses. The effects of different cultural groups and experimental settings were also shown.

Evolution and Spatiotemporal Dynamics of Enterovirus A71 Subgenogroups in Vietnam.

Background: Enterovirus A71 (EV-A71) is the major cause of severe hand, foot, and mouth disease and viral encephalitis in children across the Asia-Pacific region, including in Vietnam, which has experienced a high burden of disease in recent years. Multiple subgenogroups (C1, C4, C5, and B5) concurrently circulate in the region with a large variation in epidemic severity. The relative differences in their evolution and epidemiology were examined within Vietnam and globally. Methods: A total of 752 VP1 gene sequences were analyzed (413 generated in this study combined with 339 obtained from GenBank), collected from patients in 36 provinces in Vietnam during 2003-2013, along with epidemiological metadata. Globally representative VP1 gene datasets of subgenogroups were used to coestimate time-resolved phylogenies and relative genetic diversity to infer virus origins and regional transmission network. Results: Despite frequent virus migration between countries, the highest genetic diversity of individual subgenogroups was maintained independently for several years in specific Asian countries representing genogroup-specific sources of EV-A71 diversity. Conclusion: This study highlights a persistent transmission network of EV-A71, with specific Asian countries seeding other countries in the region and beyond, emphasizing the need for improved EV-A71 surveillance and detailed genetic and antigenic characterization.

Effect of chromatic mechanisms on the detection of mesopic incremental targets at different eccentricities.

Spectral sensitivity functions for the threshold detection of mesopic incremental targets were compared for different target eccentricities (10, 20, and 30 degrees ) and for different mesopic backgrounds (0.1, 0.5 and 1.0 cd m(-2)). Relative responsivities of achromatic mechanisms (L + M and rods) and chromatic mechanisms (S and /L-M/) were estimated for each eccentricity and background. Chromatic mechanisms contribute significantly to detection but their effect is lower at 30 degrees . A new contrast metric (C(CHC2)) is introduced to account for the selective adaptation of the photoreceptors and the effects of the chromatic mechanisms i.e. broadening of the range of spectral sensitivity with multiple local maxima and yellow sub-additivity of detection performance. The C(CHC2) metric is compared with the achromatic contrast metric of the MOVE model (C(MOVE)). For the same target, C(CHC2) generally predicts a higher visibility level than C(MOVE). However, in accordance with visual observations, for grey or yellowish incremental targets appearing at the eccentricities of 20 and 30 degrees , the visibility predicted by C(CHC2) is less than the visibility predicted by C(MOVE).