bioRxiv preprint doi: https://doi.org/10.1101/596957; this version posted April 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

1 Visual and non-visual properties of filters manipulating short- 2 wavelength light

3 Manuel Spitschan1, 2, 3 ¶, [0000-0002-8572-9268], Rafael Lazar2, 3, [0000-0001-7972-5634], & Christian Cajochen2, 3, [0000- 4 0003-2699-7171]

5

6 1 Department of Experimental Psychology, University of Oxford, United Kingdom

7 2 Centre for Chronobiology, Psychiatric Hospital of the University of Basel, Switzerland

8 3 Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, Switzerland

9

10 ¶ To whom correspondence should be addressed: Dr Manuel Spitschan, [email protected]

11

12

13 Abstract

14 Optical filters and tints manipulating short-wavelength light (so-called “blue-blocking” or 15 “blue-attenuating”) are used as a remedy for a range of ocular, retinal, neurological and 16 psychiatric disorders. In many cases, the only available quantification of the optical effects of 17 a given optical filter is the spectral transmittance, which specifies the amount of light 18 transmitted as a function of wavelength. Here, we propose a novel physiologically relevant 19 and retinally referenced framework for quantifying the visual and non-visual effects of these 20 filters, incorporating the attenuation of luminance (luminance factor), the attenuation of 21 melanopsin activation (melanopsin factor), the shift in colour, and the reduction of the colour 22 gamut (gamut factor). We examined a novel data base of optical transmittance filters (n=120) 23 which were digitally extracted from a variety of sources and find a large diversity in the 24 alteration of visual and non-visual properties. We suggest that future studies and 25 examinations of the physiological effects of optical filters quantify the visual and non-visual 26 effects of the filters beyond the spectral transmittance, which will eventually aid in 27 developing a mechanistic understanding of how different filters affect physiology.

28

29

30 Acknowledgements

31 M.S. is supported by a Sir Henry Wellcome Trust Fellowship (Wellcome Trust 32 204686/Z/16/Z) and a Junior Resaerch Fellowship from Linare College, University of 33 Oxford.

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34 Introduction

35 Optical filters can be used to modify the visual input by blocking or attenuating light at 36 specific parts of the visible spectrum1,2. So-called blue-blocking or blue-attenuating filters 37 reduce the amount of short-wavelength light at the eye’s surface, the cornea. Optically, this is 38 typically realised using one of two ways: 1) using a cut-off filter, which blocks or attenuates 39 light below a specific wavelength, 2) using a notch filter, which blocks or attenuates light 40 within a specific short-wavelength light.

41 Optical filters alter the spectral distribution of the light incident on the retinal surface relative 42 to no filtering3. This has direct effects on the activation of the cones and rods in the retina, 43 which allow us to see during the day and night, respectively. In addition, the activity of the 44 melanopsin-containing retinal ganglion cells, is also modulated by the use of optical filters. 45 These cells, though only making up <1% of retinal ganglion cells, are of great importance to 46 non-visual functions, such as entrainment by the circadian rhythm to the environmental light- 47 dark cycle, and the suppression of melatonin in response to light4.

48 Previous investigations have examined the effects of blue-blocking or -attenuating filters on 49 visual performance5-11, colour vision11-13, and steady-state and dynamic parameters of pupil 50 size14,15. Furthermore, they have received attention in the domain of sleep medicine and 51 chronobiology, where their effects on melatonin suppression16-23, circadian rhythmicity24-28, 52 sleep6,15,19,23,27-31, modulation of alertness by light32,33, and for use by shift or night 53 workers34,35 have been investigated.

54 In addition, blue-blocking or -attenuating filters have been employed in the management of 55 psychiatric and neurological (bipolar disorder36-38, depression30, ADHD39, blepharospasm40,41, 56 migraine42-44, photosensitive epilepsy45, insomnia30,39,46) and retinal conditions (rod 57 monochromacy/achromatopsia47-50, retinitis pigmentosa51, others52), as well as for reducing 58 non-specific photophobia44,53 and eye fatigue54. Coloured filters have also been used 59 previously to improve reading difficulties and relieve visual stress55,56 and symptoms of 60 migraine57, though these are not specifically attenuating short-wavelength light58 (but may, 61 depending on the chosen chromaticity).

62 Across these studies, filters by different manufacturers were used. The terms “blue-blocking” 63 or “blue-attenuating” are not well-defined standardised and therefore, there is great ambiguity 64 about the exact properties of filters carrying those names. The unique characteristic of a filter 65 is its spectral transmittance, which is a quantified specification of how much light is passed 66 through the filter at a given wavelength. But it is impossible to determine the precise effects 67 on various visual and non-visual functions just by examining the spectral transmittance 68 function of a filter. While the transmittance is necessary to determine these effects 69 quantitatively, this cannot be done “by eye”.

70 By changing the spectral distribution of the transmitted light can have a range of different 71 effects. Here, we considered four main effects (Fig. 1), all of which are important to assess 72 the properties of a given filter:

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73 1. Luminance factor [%]: By changing the spectral properties of the incident light, the 74 luminance of the effective stimulus is altered. This attenuation can be expressed as the 75 ratio between the luminance of the filtered spectral distribution to the luminance of 76 the unfiltered spectral distribution. We call this the luminance factor. A luminance 77 factor of 100% corresponds to no change in luminance by the filter. Values >100% 78 are not possible. 79 2. Melanopsin factor [%]: Similarly, the activation of melanopsin may be reduced by the 80 optical filter under investigation. Similar to the luminance factor, the melanopsin 81 factor is expressed as the proportion of melanopsin activation with filter relative to 82 without filter. 83 3. Colour shift: Optical filters with non-uniform transmittance also lead to a shift in the 84 colour appearance of a colour which would appear as white without filter. With blue- 85 blocking filters, these shifts typically occur in the yellow, orange or amber directions. 86 We quantify this colour shift using a Euclidian distance metric in the uniform CIE

87 1976 u’10v’10 colour space based on the CIE 1964 10° observer. 88 4. Gamut factor [%]: Objects of different colours will appear different when seen with a 89 filter. Without the filter, the distribution of differently coloured objects is called the 90 gamut, which is simply the area which the object colours “inhabit” in a colour space. 91 We can compare the area of the gamut when objects are seen through a filter with the 92 area of the gamut without the filter.

93 94 Figure 1: Visual effects of filters. Luminance factor is given as the ratio between the luminance of daylight seen with filter 95 (shown as the beige area) to without filter (shown as the white area). In this case, the luminance with the filter is only about a 96 quarter (23.1%), i.e. the light is only a quarter as bright. Melanopsin factor follows the same calculation, except for the 97 melanopsin photopigment. Because the cut-off wavelength of the filter is outside of the spectral sensitivity of melanopsin, 98 the attenuation is far larger compared to luminance (3.1%). Colour shift is the Euclidian distance in the uniform colour space 99 used here. The smaller the number, the smaller the colour shift. Gamut factor refers to the reduction of the colour space 100 which common surface reflectances inhabit, with and without the filter. In this case, the colour gamut with the filter is only 101 around one fifth (20.1%) of the gamut without the filter. For demonstration purpose, the spectral power distribution was 102 assumed that to be of noon daylight (D65, daylight with a correlated colour temperature [CCT] of 6500K).

103 We note that these four properties of filter are by no means exhaustive, but they allow for a 104 strongly quantifiable and yet intuitive approach of the effects of different optical filters on 105 visual and non-visual function. We also note that our analysis does not include consideration 106 of transmission of light in the UV band and makes no claims about damaging effects of UV 107 or other radiation. Similarly, we did not consider the polarization properties of the filters.

108 We started examining the visual and non-visual filters using simulated filters. We used an 109 analytic description of the typical transmittance profile using a sigmoid function (Fig. 2). The 110 model parameters were the (1) cut-off wavelength, (2) the upper asymptote, and (3) the slope

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111 of the function. By changing each of these parameters in isolation, we can examine how 112 properties of the spectral transmittance functions affect the derived parameters.

113 114 Figure 2: Exploring effects of cut-off filters. Layout follows that of Fig. 3. Spectral transmittance of cut-off filters is 115 analytically modelled using the sigmoid function of the form �(�) = , where L is the upper asymptote, k is the (() 116 slope, and λ0 is the cut-off wavelength. Left column: Varying cut-off wavelengths (λ0), with L = 0.9, k = 0.5. Middle column: 117 Varying top asymptote L, with λ0 = 550 nm, k = 0.5. Right column: Varying slope k, with λ0 = 560 nm, L = 0.9.

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118 Varying the cut-off wavelength systematically affects all four parameters (Fig. 2, left 119 column). Moving the cut-off wavelength to longer wavelengths, leads to both more 120 luminance attenuation and more melanopsin attenuation. However, because melanopsin 121 spectral sensitivity has its peak at shorter wavelengths than the luminosity function, the 122 increase in melanopsin attenuation happens at a faster rate than the increase in luminance 123 attenuation. In the colour domain, cut-off filters move the chromaticity towards the spectral 124 locus, with larger deviations with longer cut-off wavelengths.

125 At a fixed wavelength and slope, varying the asymptote, i.e. the “plateau” and maximum 126 transition systematically effects only luminance and melanopsin, though to the same amount 127 (Fig. 2, middle column), producing a line that is parallel to the neutral density locus as one 128 would expect. The chromaticity of filters with varying plateaus is the same. The slope of the 129 transmittance function (Fig. 2, right column) at a fixed cut-off wavelength affects largely the 130 attenuation of melanopsin and the change in colour properties, but not so much luminance, 131 though we expect that this will depend on the cut-off wavelength itself.

132 In this work, we examined 120 “blue-blocking” or “blue-attenuating” filters (either for 133 spectacles or for contact lenses) with respect to their luminance factor, melanopsin factor, 134 colour shift, and gamut factor. These filters were obtained using digital data extraction 135 techniques from a variety of sources, including published graphs from scientific articles, 136 informative patient brochures and manufacturer brochures. We classify these filters in three 137 loose yet intuitive ad-hoc categories: medical filter (n=77), safety filters (n=11) and 138 recreational filters (n=32), which is subdivided into filters for sports (n=12), driving (n=4), 139 visual display unit (VDU) (n=7) use and a catch-all “Other” category (n=8). In this analysis, 140 we are agnostic to the materials that these filters are applied on or produced from, though this 141 is an important consideration for practical use.

142 143 Figure 3: Ad-hoc taxonomy for the examined filters.

144 In our analysis we find that there is large variability in the visual and non-visual properties of 145 so-called “blue-blocking” or “blue-attenuating” filters.

146

147 Methods

148 Data sourcing and extraction

149 Published graphs of the spectral transmittance for “blue-blocking” and “blue-attenuating” 150 filters were sourced using informal searches on PubMed, Google Scholar, and Google,

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151 yielding a total of 120 filters under consideration. Where data were obtained from 152 manufacturers’ or other websites, those websites were submitted to the Internet Archive 153 Wayback Machine for permanent archiving (https://web.archive.org/).

154 Transmittance spectra were extracted by one operator (author of this study, R.L.) from 155 published graphs using WebPlotDigitzer 4.159, a free visual tool for extraction of data points 156 from published graphs where no tabulated data are available. WebPlotDigitizer has been 157 found to provide rather high levels of reliability60. After extraction, data were then 158 interpolated to 1 nm resolution using piecewise cubic hermite interpolating polynomial 159 (PCHIP) interpolation. At wavelengths at which no data was available, the transmittance was 160 set to 0, which has the effect that light at those wavelengths is not factored into the 161 calculation.

162 Calculations

163 For calculation of melanopsin activation, we used the spectral sensitivity recently 61 164 standardised by the CIE , which assumes a Govardovskii nomogram (λmax = 480 nm) as well 165 as a custom lens function synthesizing different lens transmittance functions4. While the 166 standard also recommends functions for the cones62, we opted for the CIE 1964 10° observer 167 in this work to maximise compatibility of the colorimetric calculations. This observer

168 prescribes XYZ functions which are converted to the well-known u’10v’10 diagram. 169 Luminance factor was calculated as the ratio between the luminance of the light seen with or 170 without the filter incorporated as a wavelength-wise multiplication. The same procedure was 171 used for the melanopsin factor calculation. Colour differences were calculated using the

172 Euclidiean distance between two points in the diagram u’10v’10. The colour gamut was 173 calculated using a set of 99 representative reflectances63. The gamut was calculated using the 174 ratio of the area of the convex hulls of these 99 reflectance functions seen with and without 175 the filter. The different effects are visualised in Figure 1. For all calculations, we assumed a 176 spectrally-neutral equal energy white (EEW), which has equal power at all wavelengths. We 177 realise that this illuminant is at best a hypothetical one, but suggest that it is a suitable one for 178 the purpose of objectively comparing the filtering properties of different filters without 179 recourse to a specific class of illuminants.

180 Data and software availability

181 All tabulated transmittance spectra and code to produce the unedited versions in the figures in 182 this report are available on GitHub (https://github.com/spitschan/bbFilter).

183

184 Results

185 Large diversity of filters

186 Across all categories, the spectral transmittances of the “blue-blocking” and “blue- 187 attenuating” filters are rather diverse (Fig. 3, Row 1). This diversity is exhibited in whether 188 the filter is a cut-off, notch or has some other filter shape. The cut-off filters differ largely in 189 the wavelength at which they transmit 50% of light. Another differing factor is the “plateau” 190 of transmission at wavelengths longer than the cut-off wavelength.

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191 192 Figure 4: Visual and non-visual properties of “blue-blocking” and “blue-attenuating” optical filters. Columns 193 correspond to the three main filter categories we identified (Fig. 2). Row 1: Spectral transmittances of filters. Row 2: 194 Luminance factor vs. melanopsin factor. Dashed line indicates equal reduction of luminance and melanopsin, as would be 195 the case with a spectrally uniform neutral density (ND) filter. Row 3: Chromaticity diagram. Red plus indicates chromaticity 196 of equal-energy white (EEW) and white squares indicate chromaticities of EEW seen through the respective filters. Row 4: 197 Colour shift vs. gamut factor. See Introduction and Fig. 1 for explanation.

198 Nearly all filters show more relative melanopsin attenuation than luminance attenuation (Fig. 199 3, Row 2). This is evidenced by the fact that all data points lie under the “diagonal”, which 200 corresponds to a spectrally flat filter which decreases the activation of all photopigments by

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201 the same amount. It appears as though there is a “fan” effect in the relationship between 202 luminance and melanopsin attenuation, bounded by the neutral density diagonal at the upper 203 end.

204 Nearly all filters show a move of the chromaticity of the EEW white point towards the 205 spectral locus, which is given by the edge of the chromaticity diagram. This locus 206 corresponds to the chromaticity of monochromatic and therefore highly saturated lights. 207 Interestingly, there is again a “fan” effect in the relationship between luminance and 208 chromaticity. The intuition here is that the colour matching functions used to calculate 209 chromaticity of the white point include the luminosity function, and therefore, these effects 210 are not independent except under special conditions.

211 Regarding the colour rendering properties of the filters quantified using the gamut 212 attenuation, we find no clear pattern. We find that some filters severely reduce the colour 213 gamut of the worlds seen with the filter, reducing it to only <1% of the gamut seen with the 214 filter. This is obviously correlated with the shift of the filter towards the spectral locus, as all 215 surfaces seen under monochromatic illumination appear to only change in lightness, and not 216 colour (because the surfaces can only reflect the light that is there). As would be expected, 217 larger colour differences (i.e. shift of the colour towards the spectral locus) translate to a 218 reduced colour gamut.

219

220 Discussion

221 General discussion

222 In our analysis we find that there is large variability in the visual and non-visual properties of 223 so-called “blue-blocking” or “blue-attenuating” filters. While the spectral transmittance of a 224 filter necessarily needs to be known for quantifying the four outcomes we investigated here, 225 it in itself is not of any use as to determine a filter’s effect on the retina. Rather than simply 226 (or not, in some cases) providing transmittance spectra in graphical or tabulated form, future 227 studies should quantify the effect of a filter using the metrics described here.

228 For many of the applications of filters manipulating short-wavelength light reaching the 229 retina, we still lack a mechanistic understanding of how the different photoreceptors 230 contribute to the effects. For example, at present (2019), we do not know how cones and rods 231 contribute to the basic physiological regulation of melatonin secretion by light. A retinally 232 referenced, or “physiologically relevant” framework to quantify effects of a filters is the first 233 step in using optical filters for developing such mechanistic understanding.

234 Pupil size effects

235 The reduction of illumination at cornea by optical filters reduces the retinal illuminance, i.e. 236 the incident light on the retinal surface. However, retinal illuminance itself is regulated by the 237 pupil area. With a reduction in light intensity, the pupil area becomes bigger. The dynamic 238 range, however, is rather limited, with a maximum possible modulation of retinal illuminance 239 just by pupil size by a factor of ~16 (between a maximally constricted 2 mm pupil and a 240 maximally dilated 8 mm pupil). We investigated the effect of reducing the corneal

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241 illuminance with optical filters on the effective retinal illuminance using the unified Watson 242 & Yellott model64 (Fig. 5). We assumed a field size of 150°, a 32-year old observer, as well 243 as binocular stimulation as an approximation to real world viewing conditions, and 244 investigated how the predicted retinal illuminance depends on the luminance of the viewed 245 stimulus with and without neutral density filters of varying densities (ND1.0, ND2.0 and 246 ND3.0). With the near-parallel lines of log luminance vs. log retinal illuminance, it can be 247 seen that the primary determinant of retinal illuminance is luminance “seen” through the 248 filter.

249 Chung and Pease 14 note that at equivalent luminance, “yellow” filters lead to larger pupils 250 than neutral-density filters. This is consistent with the view that melanopsin activation, which 251 significantly drives steady-state pupil size in humans65,66, is severely reduced under short- 252 wavelength filters. Under most real-world conditions, the correlation between luminance and 253 melanopsin activation is probably well-constrained, except with chromatic filters and 254 experimental conditions in which the decoupling can be lead to up to a three-fold difference 255 in melanopsin activation with no or little nominal difference in luminance67,68. Importantly, 256 optical quality of the retinal image depends on pupil size69, which needs to be factored into 257 filter assessments.

258 259 Figure 5: Pupil size effects of neutral-density filters. Top panel: Predicted pupil size for a 32-year old observer viewing a 260 150° field at varying luminances with both eyes. Bottom panel: Predicted retinal illuminance (luminance × pupil area) when 261 viewed either through the natural pupil (dashed lines indicate maximum retinal illuminance given maximum difference in 262 pupil size), or through spectrally uniform filters of varying transmittance (ND1.0, ND2.0, ND3.0).

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263 Digital data extraction

264 This study relied on digital data extraction from published graphs. This was necessary 265 because spectral transmittance data are rarely available in digital or tabulated form, even 266 though data storage as supplementary material is often available at scientific journals at the 267 time of writing this article (2019). As shown in this article, this need not be a limitation since 268 data can be extracted from graphs and be subjected to rigorous novel or reanalyses. A 269 limitation of our data-driven approach is that tabulated spectra given by manufacturers are 270 here treated as bona fide measurements of transmittance spectra. The process of data 271 extraction may also lead to small inaccuracies in the tabulated transmittance spectra. Optical 272 effects such as scattering or polarisation and other higher-order effects are not captured by 273 the simple filter model that we have applied here.

274 Other considerations

275 In addition to filters affecting the retinal stimulus, light of different colours may also have 276 psychological or higher-order effects70. Another effect worth considering is stigma towards 277 wearers of coloured spectacles71. Here, we only considered the visual and non-visual 278 properties of different optical filters, though these effects will need to be factored into the 279 feasibility of using specific optical filters for a desired physiological or psychological effect.

280

281 Conclusion

282 We find large diversity in the visual and non-visual properties of different “blue-blocking” or 283 “blue-attenuating” filters. We propose that to evaluate the effect of a given optical filter, the 284 spectral transmittance is only the first step in characterising the effect of a filter on the 285 illumination at the eye and suggest a retinally referenced framework to quantify these effects, 286 incorporating the attenuation of luminance, the attenuation of melanopsin activation, shifts in 287 colour, and reduction of colour gamut.

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288 Tables

289

290 Table 1

291

Luminance Melanopsin Colour Gamut factor Manufacturer Product name Source factor [%] factor [%] difference [%]

MEDICAL

Brain Power Inc. DiamondDye 5 40 nm BPI 72 19.6 1.5 0.1576 4.2

Brain Power Inc. DiamondDye 550 nm BPI 72 28.9 1.4 0.1994 3.6

Brain Power Inc. Euro-Brown BPI 72 14.3 6.6 0.0913 39.6

Brain Power Inc. FL-41 Tint Herz and Yen 41 30.2 11.4 0.1092 60.3

Brain Power Inc. Monochrome 600nm BPI 72 6.1 0.5 0.2999 8.3

Corning Corning 511 Plum and Gerull 73 44.4 10.7 0.1086 14.8

Corning Corning 527 Plum and Gerull 73 34.2 5.7 0.1328 18.4

Corning Corning 550 Plum and Gerull 73 20.3 3.0 0.1739 23.8

Corning CPF550S Schwerdtfeger and Gräf 50 20.5 1.6 0.1971 10.0

DAO-AG 0C1 Website (archived) 76.5 50.1 0.052 60.1

DAO-AG L450 Website (archived) 81.5 46.7 0.0812 15.5

DAO-AG L480-50 Website (archived) 45.3 36.9 0.0332 79.6

DAO-AG L480-75 Website (archived) 23.2 15.7 0.0574 62.7

DAO-AG L480-90 Website (archived) 7.1 3.2 0.0988 27.9

DAO-AG L500 Website (archived) 71.7 34.6 0.0756 36.1

DAO-AG L500-H Website (archived) 64.6 19.5 0.1005 4.5

DAO-AG L511 Website (archived) 52.6 9.4 0.1225 3.9

DAO-AG L511-H Website (archived) 53.4 9.3 0.1207 2.5

DAO-AG L527 Website (archived) 44.8 5.3 0.1396 2.6

DAO-AG L527-H Website (archived) 48.1 6.0 0.1337 1.9

DAO-AG L540-50 Website (archived) 50.2 17.3 0.0934 23.1

DAO-AG L540-70 Website (archived) 33.3 5.3 0.1259 5.9

DAO-AG L550 Website (archived) 34.4 2.0 0.1781 2.7

DAO-AG L585 Website (archived) 18.4 0.9 0.2373 3.5

DAO-AG LC1-H Website (archived) 72.6 30.6 0.0899 9.0

Eschenbach 450 Plum and Gerull 73 82.1 52.9 0.0708 30.9

Eschenbach 511 Plum and Gerull 73 59.7 15.3 0.1072 8.7

Eschenbach 527 Plum and Gerull 73 45.7 5.8 0.1385 5.4

Eschenbach 550 Plum and Gerull 73 31.8 2.0 0.1814 3.3

Eschenbach 450 POL Plum and Gerull 73 33.6 16.9 0.0764 34.6

Eschenbach 511 POL Plum and Gerull 73 14.3 3.0 0.1398 20.7

Eschenbach 527 POL Plum and Gerull 73 17.1 3.9 0.1264 14.0

Eschenbach 550 POL Plum and Gerull 73 13.2 2.2 0.1528 18.1

Eschenbach Solar Shield Ultra Sasseville, et al. 21 25.8 1.0 0.194 0.7

Eschenbach Wellness PROTECT wp15 Krüger, et al. 74 48.0 14.3 0.1009 7.5

Essilor Orma RT 50% Plum and Gerull 73 26.9 17.9 0.0629 66.6

11 bioRxiv preprint doi: https://doi.org/10.1101/596957; this version posted April 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Essilor Orma RT 85% Plum and Gerull 73 12.8 5.3 0.1106 49.0

Hoggan et al 2015 N/A – 480nm notch filter Hoggan, et al. 44 60.0 40.7 0.0266 96.4

Hoggan et al 2015 N/A – 620nm notch filter Hoggan, et al. 44 56.7 67.4 0.0345 94.1

Multilens 450 Plum and Gerull 73 73.1 46.7 0.0738 25.5

Multilens 511 Plum and Gerull 73 50.8 10.8 0.1138 11.2

Multilens 527 Plum and Gerull 73 41.5 5.4 0.1398 10.0

Multilens 550 Plum and Gerull 73 19.1 2.4 0.207 16.9

Multilens 450 POL Plum and Gerull 73 25.8 14.8 0.0658 45.1

Multilens 511 POL Plum and Gerull 73 21.7 8.2 0.0908 27.8

Multilens 527 POL Plum and Gerull 73 16.4 4.7 0.1139 29.1

Multilens 550 POL Plum and Gerull 73 8.7 1.5 0.1871 25.3

NoIR 47 Website (archived) 45.0 29.8 0.0722 61.2

NoIR 72 Website (archived) 57.1 44.0 0.0382 86.8

NoIR 90 Website (archived) 15.0 0.2 0.2778 0.5

NoIR 93 Website (archived) 6.5 0.2 0.2749 1.5

NoIR 553 Website (archived) 29.5 1.2 0.1975 0.9

NoIR 570 Website (archived) 13.6 0.6 0.2127 2.0

NoIR N/A – amber lens Burkhart and Phelps 29 49.6 4.1 0.142 1.1

Rodenstock L660 Schwerdtfeger and Gräf 50 17.6 4.3 0.1083 3.3

Rodenstock L660 80% Plum and Gerull 73 16.5 3.9 0.1153 19.9

Rodenstock L660 90% Plum and Gerull 73 10.0 2.3 0.1206 22.2

Rosenblum et al 2000 N/A - filter albino patients Rosenblum, et al. 52 14.8 10.2 0.049 78.0

Rosenblum et al 2000 N/A - filter aphakic patients Rosenblum, et al. 52 87.0 72.9 0.031 77.3

Rosenblum et al 2000 N/A - filter initial cataract patients Rosenblum, et al. 52 76.9 47.7 0.0617 51.1

solsecur / AugenLichtSchutz Typ31: P90 Website (archived) 9.4 4.1 0.1014 43.7

SomniLight Migraine Relief Lenses Website (archived) 6.7 0.8 0.288 12.8

SwissLens SLF450 Website (archived) 84.3 47.3 0.0811 16.3

SwissLens SLF511 Website (archived) 49.3 6.2 0.1372 1.9

SwissLens SLF527 Website (archived) 39.0 3.1 0.1625 1.7

SwissLens SLF550 Website (archived) 22.8 0.8 0.23 2.0

Ultravision International Soft contact lenses - orange Giménez, et al. 19 57.0 31.8 0.0671 70.6

Woehlk HydroFlexRP Schwerdtfeger and Gräf 50 14.4 2.1 0.1467 16.5

Zeiss F540 Plum and Gerull 73 52.4 12.9 0.1083 12.5

Zeiss F560 Plum and Gerull 73 39.3 6.0 0.1396 14.3

Zeiss F580 Schwerdtfeger and Gräf 50 25.5 0.5 0.2204 0.0

Zeiss F580 Plum and Gerull 73 25.4 3.2 0.187 17.3

Zeiss F60 Plum and Gerull 73 22.4 6.3 0.1088 31.5

Zeiss F80 Plum and Gerull 73 9.2 2.7 0.1196 41.0

Zeiss F90 Plum and Gerull 73 4.6 2.2 0.097 67.8

N/A - final modified red contact ZELTZER X-CHROM lens Zeltzer 49 4.2 0.1 0.2621 1.5

ZELTZER X-CHROM N/A - modified red contact lens Zeltzer 49 9.1 0.6 0.2295 12.3

SAFETY

Technical fact sheet, from website 3M 2846 red-orange (archived) 51.9 8.1 0.1292 2.9

12 bioRxiv preprint doi: https://doi.org/10.1101/596957; this version posted April 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Honeywell Uvex SCT Orange Sasseville, et al. 34 40.5 2.3 0.1577 0.6

Honeywell Uvex SCT Orange (Ultraspec 2000) Ostrin, et al. 15 51.4 5.7 0.1326 5.7

Offenh‰user + Berger Laserschutzbrille 0000001012726 GmbH red Website (archived) 26.8 0.6 0.2227 1.4

Offenh‰user + Berger Laserschutzbrille 0000001012731 GmbH orange Website (archived) 8.1 0.5 0.113 1.1

Offenh‰user + Berger Laserschutzbrille 0000003013447 GmbH red-orange Website (archived) 25.3 0.8 0.1849 0.6

Offenh‰user + Berger Laserschutzbrille 2054110000002 GmbH yellow Kayumov, et al. 20 61.1 9.5 0.115 0.2

Offenh‰user + Berger Laserschutzbrille 2054110000002 GmbH yellow Website (archived) 60.9 9.4 0.115 0.4

SAF-T-CURE ORANGE UV FILTER GLASSES Figueiro and Rea 17 44.5 3.2 0.1506 2.0

solsecur / AugenLichtSchutz red_xd Website (archived) 33.6 1.4 0.1868 0.4

Yamamoto Kogaku Co. Ltd O 360S UV Orange Esaki, et al. 30 43.6 2.6 0.1575 1.3

RECREATIONAL – Sports

Brain Power Inc. Golf Tint BPI 72 29.6 23.0 0.0365 78.3

Brain Power Inc. Golfer Advantage BPI 72 30.8 36.4 0.0133 93.9

Brain Power Inc. Golfer Blu BPI 72 34.4 55.9 0.0736 143.4

Brain Power Inc. Skeet Tint BPI 72 42.5 20.6 0.0832 81.6

Brain Power Inc. Ski Tint BPI 72 19.9 9.1 0.1126 34.7

Brain Power Inc. Sport Tint BPI 72 25.9 15.6 0.0856 51.0

Brain Power Inc. Tennis Tint BPI 72 86.4 63.8 0.0551 50.8

NoIR 50 Website (archived) 84.4 49.2 0.0835 11.2

NoIR 60 Website (archived) 47.4 3.5 0.146 0.2

NoIR 465 Website (archived) 77.7 36.2 0.0816 21.1

NoIR 505 Website (archived) 27.8 4.4 0.1219 3.6

NoIR 533 Website (archived) 23.8 7.3 0.1057 43.0

Zeiss Skylet Sport Plum and Gerull 73 10.4 5.1 0.0835 59.3

RECREATIONAL – Driving

Brain Power Inc. Driver Tint BPI 72 19.4 1.3 0.1588 2.5

Technical fact sheet, from website Multilens LLR Night Cover (archived) 86.6 69.5 0.0427 63.8

solsecur / AugenLichtSchutz yellow sx Website (archived) 71.9 36.0 0.0777 29.6

Zeiss Skylet Road Plum and Gerull 73 19.9 11.4 0.0668 55.4

RECREATIONAL – VDU use

DAO-AG L400 Website (archived) 93.3 91.5 0.0072 94.5

DAO-AG L41-A Website (archived) 83.2 77.5 0.011 95.2

DAO-AG L41-B Website (archived) 71.6 59.8 0.0241 95.4

DAO-AG L41-C Website (archived) 47.0 26.9 0.0686 82.8

JINS CO. LTD Screen Clear Lin, et al. 54 94.0 87.6 0.028 77.0

JINS CO. LTD Screen Night Lin, et al. 54 71.6 50.1 0.0484 65.6

NoIR 68 Website (archived) 62.4 14.9 0.1017 23.3

13 bioRxiv preprint doi: https://doi.org/10.1101/596957; this version posted April 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

RECREATIONAL – Other

Brain Power Inc. Winter Sun BPI 72 81.1 43.5 0.0832 13.4

Chron-Optic inc N/A - orange lens van der Lely, et al. 33 23.1 4.9 0.1559 11.3

Chron-Optic inc. N/A - orange lens Sasseville, et al. 34 44.9 6.3 0.1363 4.0

Chron-Optic inc. N/A - orange lens Sasseville and Hébert 35 25.9 1.1 0.1927 1.8

Blue Light Blocking Glasses-Sleep LowBlueLights Glasses Esaki, et al. 26 42.8 2.7 0.1543 0.9

solsecur / AugenLichtSchutz red Zerbini, et al. 23 44.9 13.3 0.1092 34.6

SomniLight Amber Sleep Glasses Website (archived) 28.5 1.2 0.202 2.5

Zeiss Skylet Fun Plum and Gerull 73 29.1 10.3 0.0937 45.4

292

293

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