Photobiological effect-based correlated color temperature setting method for windowless office space

Abstract

The invention discloses a related color temperature setting method for a windowless office based on a photo-biological effect, and relates to the technical field of urban rail transit illumination, and the method comprises the steps: determining a cognitive function related to the work performance according to an obtained actual work scene and a typical work task of the windowless office, and obtaining a cognitive function related to the work performance; a plurality of experiment paradigms are constructed based on the cognitive function so as to represent the work performance of the windowless office space; modulating a correlated color temperature level in a range of 4000-12000K according to a daytime photo-biological effect; determining an experimental environment, an experimental device and an experimental process based on the experimental normal form and the related color temperature level; then carrying out an experiment to obtain subjective experience data, behavior performance data and neural activity data of the subject, and carrying out comprehensive analysis on the data by utilizing the linear hybrid model to obtain a multi-modal optical biological response degree; correlated color temperatures in the morning and afternoon periods are respectively set according to the multi-mode light biological response degree, and the work performance of the windowless office space is improved.

Description

Technical Field

[0001] This application relates to the technical field of urban rail transit lighting, and particularly to a correlated color temperature setting method for windowless office spaces based on photobiological effects. Background Art

[0002] Due to daylight deprivation and isolation, workers in windowless office spaces are prone to problems such as alertness decline and cognitive dissonance, seriously damaging their occupational health and work performance. Artificial lighting has become the main or even the only medium for obtaining visual information in windowless office spaces, playing a crucial role in maintaining human health and improving work performance, which is mainly due to the intrinsically photosensitive retinal ganglion cells (ipRGCs) in the human eye. The light entering the human eye produces photobiological effects through visual and non-visual photobiological effect pathways respectively. The visual photobiological effect pathway transmits light information to the structures involved in imaging in the brain through the optic nerve, chiasm, and tract; while the non-visual photobiological effect pathway transmits light information to the suprachiasmatic nucleus of the hypothalamus, as well as other non-visual nuclei and brain regulatory centers through the retinohypothalamic tract.

[0003] The Illuminating Engineering Society (IES) in the United States further classifies this photobiological effect mediated by ipRGCs into circadian rhythm, neuroendocrine, and neurobehavioral responses. Among them, the neurobehavioral response represents the regulation of light on the nervous system and human behavior, usually including psychological processes such as alertness, cognitive performance, and emotion, as well as physiological states such as cranial nerves and autonomic nerves, which reflects its acute photobiological effect on the nervous system and human behavior, and is directly related to work performance.

[0004] IpRGCs are abnormally sensitive to blue light (the response peak is about 480 nm), which makes the correlated color temperature an important parameter in the artificial lighting environment of windowless office spaces. The correlated color temperature refers to the blackbody temperature corresponding when the light color emitted by a certain light source is closest to the blackbody radiation light color at a certain temperature. The proportion of blue light in visible light determines the level of the correlated color temperature. The higher the correlated color temperature, the greater the proportion of its blue light component; conversely, the lower the correlated color temperature, the smaller the proportion of its blue light component.

[0005] At present, the evaluation of photobiological neurobehavioral responses tends to use the change of correlated color temperature under constant illuminance and color rendering index, because compared with parameters such as spectral distribution and light intensity, correlated color temperature can still cause photoalertness, cognition and emotional effects while ensuring the stability of human melatonin levels and homeostatic sleep drive, thereby better separating the influence of other pathways. However, correlated color temperature is often coupled with its temporal characteristics and acts together on photobiological neurobehavioral responses. At present, the lack of personalized consideration of lighting needs has led to the setting of the same fixed value for the correlated color temperature in the morning and afternoon of the daytime working hours in windowless offices. In addition, the selection of correlated color temperature for windowless office spaces in buildings at home and abroad is mostly limited to the range of 4000K-6500K, and the research and development of lighting solutions above 6500K is insufficient. In addition, there is still a lack of evidence of human neural responses in the evaluation of photobiological neurobehavioral responses, which also restricts the development of healthy lighting solutions. Summary of the invention

[0006] The purpose of this application is to provide a method for setting the correlated color temperature for windowless offices based on the photobiological effect, which can improve work performance by reasonably setting the correlated color temperature levels in the morning and afternoon working hours in the windowless office.

[0007] To achieve the above objectives, this application provides the following solutions:

[0008] In a first aspect, the present application provides a method for setting a correlated color temperature for a windowless office space based on a photobiological effect, comprising:

[0009] According to the actual working scenes and typical work tasks of the windowless office, the cognitive function is determined, and an experimental paradigm is constructed based on the cognitive function; the cognitive function is a cognitive function related to work performance, there are multiple experimental paradigms, and the experimental paradigm is used to characterize the work performance of the windowless office;

[0010] Modulating the correlated color temperature level within the range of 4000K-12000K according to the daytime photobiological effect; the correlated color temperature level is multiple;

[0011] Based on the experimental paradigm and the correlated color temperature level, determine the experimental environment, experimental equipment and experimental process;

[0012] Conducting an experiment based on the experimental environment, the experimental device and the experimental process to obtain the subjective experience data, behavioral performance data and neural activity data of the subjects, and using a linear mixed model to comprehensively analyze the subjective experience data, the behavioral performance data and the neural activity data to obtain a multimodal photobiological response degree;

[0013] The correlated color temperature for the morning period and the correlated color temperature for the afternoon period are set respectively according to the multimodal photobiological response degree.

[0014] Optionally, constructing an experimental paradigm based on the cognitive function specifically includes:

[0015] Mapping the cognitive functions with the acquired traditional cognitive psychology experimental paradigms one by one to obtain the experimental paradigm screening results;

[0016] The experimental paradigm is obtained by screening the results according to the experimental paradigm.

[0017] Optionally, the correlated color temperature level is modulated within the range of 4000K-12000K according to the daytime photobiological effect, specifically including:

[0018] Under the conditions of constant illumination and color rendering index of the working surface, four different correlated color temperature levels are modulated in the range of 4000K-12000K according to the daytime photobiological effect;

[0019] The CL-500A handheld spectroradiometer was used to measure and calibrate four different correlated color temperature levels, and the spectral distribution curves corresponding to the four different correlated color temperature levels were obtained.

[0020] The spectral distribution curves corresponding to four different correlated color temperature levels were calculated using the α-opic equivalent daylight illuminance model, and the photobiological effect values ​​at the human eye level corresponding to four different correlated color temperature levels were obtained.

[0021] Optionally, the calculation formula of the photobiological effect value is:

[0022]

[0023] in, is the photobiological effect value, the unit is lx; E e,α is the α-opic irradiance, which is calculated according to the spectral distribution curve; It is the α-opic light radiation efficiency under standard daylight D65, in mW·lm -1 .

[0024] Optionally, the experimental process specifically includes:

[0025] The subjects came to the experimental site to sign in at different working hours during the day according to the agreed time;

[0026] The subjects were fitted with a 64-lead electrode cap under baseline lighting conditions to ensure that all electrode impedances dropped to 5 kΩ;

[0027] Dark adaptation for k minutes to counteract carryover effects of baseline light exposure;

[0028] Turn on the light to the current correlated color temperature level, perform light adaptation for t minutes, and synchronously collect resting EEG signals for t minutes;

[0029] The experimental paradigm was completed in sequence at the current correlated color temperature level, and the order was balanced within the subjects;

[0030] The subjects filled in the KSS scale and self-reported their subjective alertness at the current correlated color temperature level;

[0031] Collect resting EEG signals for t minutes, and the current correlated color temperature level experience ends;

[0032] Each correlated color temperature level is taken as the current correlated color temperature level, and the process returns to the step of “dark adaptation for k minutes to offset the residual effect of baseline light exposure”.

[0033] Optionally, the subjective experience data includes the subjective alertness of the subjects at different correlated color temperature levels; the behavioral performance data includes reaction time, accuracy and comprehensive performance; and the neural activity data includes the power spectral density of theta waves and alpha waves in the subjects' electroencephalogram signals.

[0034] Optionally, the calculation formula for the reaction time is:

[0035] T=T reac -T onset ;

[0036] Where T is the reaction time of successful trials in the task phase of the ith task; T reac is the time the button is pressed; T onset The time for presentation of experimental stimulus materials;

[0037] The calculation formula of the accuracy is:

[0038] ACC = x i / N;

[0039] Among them, ACC is the accuracy of the i-th task; x i is the number of correct responses made according to the stimulus displayed in the ith task trial; N is the total number of stimulus appearances in the ith task trial;

[0040] The calculation formula of the comprehensive performance is:

[0041]

[0042] Among them, x ij The data generated when the i-th sample performs the j-th task; min{x ij} is the minimum value of all samples of the jth subtask; max{x ij} is the maximum value among all samples of the j-th sub-task.

[0043] Optionally, the calculation process of the linear mixed model is as follows:

[0044] Y ij = X i β + Z i γ i + ε i ;

[0045] where Y ij is the j-th response of the i-th subject, that is, the corresponding subjective experience data, behavioral performance data, and neural activity data of the subject; X i is the design matrix of fixed effects, that is, four different correlated color temperature levels; β is the p regression coefficient vector; Z i is the design matrix of random effects, which is the variability caused by the differences between subjects; γ i is the random effect variable; ε i is the error vector within the subject.

[0046] Optionally, the cognitive functions include visual search, attentional vigilance, sustained attention, working memory, risk decision-making, executive control, and emotion perception;

[0047] The experimental paradigms are successively the digit symbol substitution test task, the psychomotor vigilance task, the Go / No-go task, the letter / space / fractal version 2-back task, the balloon analogue risk task, the second-generation multi-attribute task set, and the emotion perception task.

[0048] Optionally, the work surface illuminance is 500 lx, the color rendering indices are all not less than 90%, and the correlated color temperature levels are 4000K, 6500K, 8500K, and 12000K respectively.

[0049] According to the specific embodiments provided by the present application, the present application discloses the following technical effects:

[0050] The present application provides a method for setting the correlated color temperature for windowless offices based on photobiological effects. Based on the actual working scenes and typical tasks of windowless offices, cognitive functions corresponding to basic and advanced human cognitive abilities are separated, and an experimental paradigm for characterizing the work performance of windowless offices is constructed based on cognitive functions, so as to be more in line with the actual application scenarios, and the evaluation of photobiological cognitive effects can be made more comprehensive and the results more reliable. Moreover, considering the limitation that a single modality evaluation is difficult to ensure the objectivity and accuracy of the evaluation results, a multimodal photobiological effect evaluation and analysis method combining subjective experience, behavioral performance and neural activity is proposed to obtain a more reliable and effective correlated color temperature setting result. In addition, there are multiple correlated color temperature levels in the present application. After further modeling and analysis, the work performance under different correlated color temperature levels is compared, so as to obtain the correlated color temperature levels for work performance intervention in the morning and afternoon working hours of windowless offices, so that the setting of the correlated color temperature level is more reasonable and the work performance is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0052] Figure 1 A flow chart of a method for setting correlated color temperature for a windowless office space based on photobiological effects provided in one embodiment of the present application;

[0053] Figure 2 A flow chart of a method for setting correlated color temperature for a windowless office space based on photobiological effects provided in another embodiment of the present application;

[0054] Figure 3 A schematic diagram of spectral distribution curves corresponding to four correlated color temperature levels provided in another embodiment of the present application;

[0055] Figure 4 A schematic diagram of subjective alertness at different correlated color temperatures during the morning and afternoon periods provided by another embodiment of the present application;

[0056] Figure 5 A schematic diagram of the change of execution control performance under different correlated color temperatures in the morning and afternoon periods provided by another embodiment of the present application;

[0057] Figure 6 A schematic diagram of changes in visual search performance under different correlated color temperatures during the morning and afternoon periods provided by another embodiment of the present application;

[0058] Figure 7 A schematic diagram of working memory performance changes under different correlated color temperatures during the morning and afternoon periods provided by another embodiment of the present application;

[0059] Figure 8 A schematic diagram of theta wave energy changes under different correlated color temperatures in the morning and afternoon periods provided by another embodiment of the present application;

[0060] Fig. 9 A schematic diagram of alpha wave energy variation under different correlated color temperatures during the morning and afternoon periods provided by another embodiment of the present application;

[0061] Fig.10 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0062] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0063] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0064] In an exemplary embodiment, Figure 1 As shown, a method for setting the correlated color temperature for windowless offices based on the photobiological effect is provided, and the method is executed by a computer device, and specifically can be executed by a computer device such as a terminal or a server alone, or can be executed by a terminal and a server together. In the embodiment of the present application, the following steps 201 to 205 are included. Among them:

[0065] Step 201, according to the actual working scenes and typical work tasks of the acquired windowless office, the cognitive functions are determined, and an experimental paradigm is constructed based on the cognitive functions; the cognitive functions are cognitive functions related to work performance, there are multiple experimental paradigms, and the experimental paradigms are used to characterize the work performance of the windowless office.

[0066] Step 202, modulating the correlated color temperature level within the range of 4000K-12000K according to the daytime photobiological effect; the correlated color temperature level is multiple.

[0067] Step 203, based on the experimental paradigm and the correlated color temperature level, determine the experimental environment, experimental equipment and experimental process.

[0068] Step 204: Conduct experiments based on the experimental environment, experimental equipment, and experimental procedures to obtain the subjective experience data, behavioral performance data, and neural activity data of the subjects, and comprehensively analyze the subjective experience data, behavioral performance data, and neural activity data using a linear mixed model to obtain the multi-modal photobiological response degree.

[0069] Step 205: Set the relevant color temperatures for the morning period and the afternoon period respectively according to the multi-modal photobiological response degree.

[0070] By implementing the above Steps 201 to 205, this application extracts the cognitive functions that map to the basic and advanced cognitive abilities of humans by combining the actual work scenarios and typical job tasks, designs an experimental paradigm, uses the relevant color temperature level and the daytime working period as independent variables, and the multi-modal indicators of subjective experience, behavioral performance, and neural activity as dependent variables, conducts an experimental process to collect human photobiological response data, statistically analyzes the indicator data by constructing a linear mixed model, and compares the results at different independent variable levels, so as to screen out the relevant color temperature levels suitable for work performance intervention during different daytime working periods in windowless office spaces.

[0071] Further, according to the actual work scenarios and typical job tasks of the windowless office space obtained, determine the cognitive functions, and construct an experimental paradigm based on the cognitive functions, specifically including:

[0072] Step 2011: Extract the cognitive functions related to work performance from the actual work scenarios and typical job tasks of the windowless office space, map them to the basic and advanced cognitive abilities of humans in cognitive psychology theory, and use them as the basis for screening psychological experimental paradigms; the extracted cognitive functions include: visual search, attentional vigilance, sustained attention, working memory, risk decision-making, executive control, and emotion perception.

[0073] Step 2012: Map the extracted cognitive functions to the traditional cognitive psychology experimental paradigms one by one to obtain the experimental paradigm screening results.

[0074] Step 2013: Obtain 7 experimental paradigms for characterizing work performance in windowless office spaces according to the existing experimental paradigm screening results; the selected experimental paradigms are the digit symbol substitution test task, the psychomotor vigilance task, the Go / No-go task, the letter / space / fractal version 2-back task, the balloon analogue risk task, the second-generation multi-attribute task battery (MATB-II), and the emotion perception task.

[0075] Further, modulate the relevant color temperature levels within the range of 4000K - 12000K according to the daytime photobiological effect, so as to construct an illumination scene composed of different relevant color temperature levels, specifically including:

[0076] Step 2021, under the condition of constant illumination and color rendering index of the working surface, four different correlated color temperature levels are modulated in the range of 4000K-12000K according to the daytime photobiological effect. Among them, the illumination of the working surface is 500lx, the color rendering index is not less than 90%, and the correlated color temperature levels are 4000K, 6500K, 8500K and 12000K respectively.

[0077] Step 2022, using a CL-500A handheld spectroradiometer to measure and calibrate four different correlated color temperature levels, and obtain spectral distribution curves corresponding to the four different correlated color temperature levels, which describe the irradiance in the visible spectrum range (380-780nm) (step size is 5nm).

[0078] Step 2023, using the α-opic equivalent daylight (D65) illuminance (EDI) model, the spectral distribution curves corresponding to the four different correlated color temperature levels are calculated to obtain the photobiological effect values ​​at the human eye level corresponding to the four different correlated color temperature levels.

[0079] First, the α-opic irradiance (α-opic represents the photobiological response induced by the five photoreceptors of humans, and the unit is W·m -2 ), as follows:

[0080] E e,α =∫E e,λ (λ)s α (λ)dλ;

[0081] Among them, E e,α is the α-opic irradiance, E e,λ (λ) is the specific irradiance corresponding to different wavelengths, s α (λ) is the action spectrum within 380-780nm with a step size of 5nm.

[0082] Secondly, calculate the photobiological effect value, that is, the equivalent daylight illuminance, in lx, as shown below:

[0083]

[0084] in, is the photobiological effect value, the unit is lx; E e,α is the α-opic irradiance, which is calculated according to the spectral distribution curve; α-opic light radiation efficiency of standard daylight (D65), in mW·lm -1, calculated by the ratio of the standard daylight α-opic (D65) radiation flux to the standard daylight (D65) luminous flux. The CIE S026-2018 standard specifies the daylight (D65) α-opic light radiation efficiency values ​​for five types of photoreceptors, which are as follows:

[0085]

[0086] in, They represent the light radiation efficiency corresponding to human S-cones, M-cones, L-cones, rods and ipRGCs respectively.

[0087] Furthermore, based on the experimental paradigm and the correlated color temperature level, the experimental environment, experimental device and experimental process were determined; the subject inclusion criteria, experimental design method, experimental duration, etc. were mainly determined. Four different correlated color temperature levels (i.e., light exposure order) were presented in Latin square order; the experimental process specifically included:

[0088] In step 2031, the subjects come to the experimental site to sign in at different working hours during the day according to the agreed time.

[0089] Step 2032: Put a 64-lead electrode cap on the subject under the baseline lighting environment to ensure that all electrode impedances are reduced to 5 kΩ.

[0090] Step 2033, dark adapt for k minutes to offset the carryover effect of baseline light exposure.

[0091] Step 2034, turn on the light to the current correlated color temperature level, perform light adaptation for t minutes, and synchronously collect t minutes of resting-state EEG signals.

[0092] Step 2035, complete the experimental paradigm in sequence at the current correlated color temperature level, and the order is balanced within the subjects.

[0093] In step 2036, the subject fills out the KSS scale to self-report the subjective alertness at the current correlated color temperature level.

[0094] Step 2037, collect t minutes of resting-state EEG signals, and the current correlated color temperature level experience ends.

[0095] In step 2038, each correlated color temperature level is used as the current correlated color temperature level, and the process returns to step "dark adaptation for k minutes to offset the residual effect of baseline light exposure". The four different correlated color temperature levels are presented in Latin square order.

[0096] Furthermore, experiments were conducted based on the experimental environment, experimental equipment and experimental process to obtain the subjects' subjective experience data, behavioral performance data and neural activity data, and a linear mixed model was used to conduct a comprehensive analysis of the subjective experience data, behavioral performance data and neural activity data to obtain the degree of multimodal photobiological response.

[0097] The subjective experience data include the subjective alertness of the subjects at different correlated color temperature levels; the behavioral performance data include reaction time, accuracy and comprehensive performance; the neural activity data include the power spectral density of theta waves and alpha waves in the subjects' EEG signals.

[0098] The calculation formula for the reaction time is:

[0099] T=T reac -T onset ;

[0100] Where T is the reaction time of successful trials in the task phase of the ith task; T reac is the time the button is pressed; T onset The time when the experimental stimulus materials are presented.

[0101] The accuracy is calculated as follows:

[0102] ACC = x i / N;

[0103] Among them, ACC is the accuracy of the i-th task; x i is the number of correct responses to the stimulus displayed in the ith task trial; N is the total number of stimulus appearances in the ith task trial.

[0104] The formula for calculating comprehensive performance is:

[0105]

[0106] Among them, x ij The data generated when the i-th sample performs the j-th task; min{x ij} is the minimum value of all samples of the jth subtask; max{x ij} is the maximum value among all samples of the j-th subtask.

[0107] The Welch method is used to analyze the power spectral density of theta and alpha waves in the frequency domain. Assume that a discrete signal x[n] has a finite length of n=1,2,...,N. This signal is obtained by sampling the continuous signal x[t] at equal time intervals Δt or sampling frequency f. s =1 / Δt is sampled, and the fixed finite length is T=NΔt. The Hamming window expression is as follows:

[0108]

[0109] The DFT calculation formula after windowing is as follows:

[0110]

[0111] The calculation process of the linear mixed model is:

[0112] Y ij =X i β+Z i γ i +ε i .

[0113] Among them, Y ij The jth response of the ith subject, i.e., the subject’s corresponding subjective experience data, behavioral performance data, and neural activity data; X i is the design matrix of fixed effects, i.e., four different levels of correlated color temperature; β is the p regression coefficient vector; Z i is the design matrix of random effects, which is the variability caused by differences between subjects; γ i is a random effect variable; i is the within-subject error vector.

[0114] Compared with the prior art, the present invention has the following beneficial effects:

[0115] (1) This application separates basic and advanced human cognitive abilities based on actual work scenarios and typical work tasks, and maps them one by one with traditional cognitive psychology experimental paradigms, thereby constructing an experimental paradigm for characterizing work performance in windowless offices, which is more in line with actual application scenarios and provides a more comprehensive evaluation of photobiological cognitive effects and more reliable results.

[0116] (2) Taking into account the limitation that a single modality evaluation cannot guarantee the objectivity and accuracy of the evaluation results, this application proposes a multimodal photobiological effect evaluation and analysis method that combines subjective experience, behavioral performance and neural activity to obtain a more reliable and valid correlated color temperature setting result.

[0117] (3) This application designs an experimental paradigm by traversing basic and advanced human cognitive abilities, obtains multimodal data through experiments, and then obtains the degree of human photobiological response under different correlated color temperature levels; after further modeling and analysis, the work performance under different correlated color temperature levels is compared, thereby obtaining the correlated color temperature level for work performance intervention in the morning and afternoon working hours in windowless offices.

[0118] In another exemplary embodiment of the present application, the correlated color temperature level is set for a fully enclosed environment in a dispatching hall of an urban rail transit industry, such as Figure 2 As shown, the method steps include:

[0119] S1. Based on the fully enclosed environment of the dispatching hall in the urban rail transit industry, the train dispatching tasks are analyzed, summarized and generalized, and the cognitive functions closely related to the performance of the train dispatching work are extracted. Based on the relevant theories of cognitive psychology, they are mapped one by one with the basic and advanced cognitive abilities of humans. The following 7 cognitive abilities are: visual search, attention alertness, sustained attention, working memory, risk decision-making, executive control and emotional perception.

[0120] The basic and advanced cognitive abilities were mapped one by one with the traditional cognitive psychology experimental paradigms. Through literature review, these cognitive abilities were loaded into the corresponding 7 experimental paradigms, including: digital symbol substitution test task, psychomotor vigilance task, Go / No-go task, letter / space / fractal board 2-back task, balloon simulation risk task, second generation multi-attribute task battery (MATB-Ⅱ) and emotion perception task. The mapping relationship between cognitive ability and experimental paradigm and the design description of the experimental paradigm are shown in Table 1.

[0121] Table 1 Mapping relationship between cognitive ability and experimental paradigm and design description of experimental paradigm

[0122]

[0123] S2. According to the daytime photobiological effect, four correlated color temperature levels are modulated within the range of 4000K-12000K while ensuring constant illumination and color rendering index of the working surface. Using α-opic equivalent daylight (D65) illumination (Equivalent daylight illuminance (EDI) model calculates the four correlated color temperatures corresponding to the human eye level The photobiological efficacy values ​​are shown in Table 2. The lighting parameters were measured and calibrated using a CL-500A handheld spectroradiometer to obtain the spectral distribution curves of four correlated color temperature levels, as shown in Table 2. Figure 3 shown.

[0124] Table 2 Photobiological efficacy values ​​corresponding to four correlated color temperatures at human eye level

[0125]

[0126] S3. Conduct relevant experiments based on the experimental paradigm designed in step S1 and the correlated color temperature level modulated in step S2. Complete 7 experimental paradigms at each correlated color temperature level, with a duration of 40 minutes. Collect EEG signals throughout the experiment. The light exposure sequence uses a Latin square design to eliminate the interference of light exposure duration on human photobiological response.

[0127] In this embodiment, the overall experimental process is as follows:

[0128] S31. The subjects were randomly assigned to the morning group and the afternoon group. They all signed in at the experimental site at different working hours during the day according to the agreed time. The morning period was 08:00-12:00, and the afternoon working period was 13:00-17:00.

[0129] S32. Put on the 64-lead electrode cap for the subject under the baseline lighting environment and make sure that the impedance of all electrodes is reduced to 5kΩ.

[0130] S33, dark adaptation for 10 min to offset the carryover effect of baseline light exposure.

[0131] S34. Turn on the light to the first correlated color temperature level, perform light adaptation for 5 minutes, and synchronously collect 5 minutes of resting-state EEG signals.

[0132] S35. Complete seven experimental paradigms in sequence at the current correlated color temperature level, and the order is balanced within the subjects.

[0133] S36. The subjects filled in the KSS scale to self-report their subjective alertness at the current correlated color temperature level, as shown in Table 3.

[0134] Table 3 Subjective alertness at current correlated color temperature levels

[0135] Serial number Alertness level classification Scoring Criteria 1 Extremely alert 1 2 Very alert 2 3 vigilance 3 4 Quite alert 4 5 Neither alert nor sleepy 5 6 A little sleepy 6 7 Drowsiness, difficulty staying alert 7 8 Drowsiness, difficulty staying alert 8 9 Very sleepy, trying to stay awake, and fighting sleepiness 9

[0136] S37. Collect resting-state EEG signals for t minutes, and the current correlated color temperature level experience ends.

[0137] S38, switch to the next correlated color temperature level, and repeat steps S33-S37 until all correlated color temperature solutions are completed. The overall experiment lasts for 4 hours.

[0138] S4. Process and analyze the KSS scores, task reaction time / accuracy / comprehensive performance, and theta / alpha wave energy data at different correlated color temperature levels and working hours.

[0139] S41. Determine the reaction time and accuracy of each experimental paradigm, and the data are collected by E-prime software. The calculation formula of reaction time is as follows:

[0140] T=T reac -T onset ;

[0141] Where T is the reaction time of successful trials in the task phase of the ith task; T reac is the time the button is pressed; T onset The time when the experimental stimulus materials are presented.

[0142] The accuracy calculation formula is as follows:

[0143] ACC = x i / N;

[0144] Among them, ACC is the accuracy of the i-th task; x i is the number of correct responses made according to the stimulus displayed in the ith task trial; N is the total number of stimulus appearances in the ith task trial.

[0145] The calculation formula of comprehensive performance is as follows, which is used for the combination of dimensionless performance indicators:

[0146]

[0147] Among them, x ij The data generated when the i-th sample performs the j-th task; min{x ij} is the minimum value of all samples of the jth subtask; max{x ij} is the maximum value among all samples of the j-th subtask.

[0148] The Welch method is used to analyze the power spectral density of theta and alpha waves in the frequency domain. Assume that a discrete signal x[n] has a finite length of n=1,2,...,N. This signal is obtained by sampling the continuous signal x[t] at equal time intervals Δt or sampling frequency f. s =1 / Δt is sampled, and the fixed finite length is T=NΔt. The Hamming window expression is as follows:

[0149]

[0150] The DFT calculation formula after windowing is as follows:

[0151]

[0152] S42. A linear mixed model was constructed to analyze subjective experience, behavioral performance, and neural activity, and the multimodal photobiological response degree at different independent variable levels was obtained. The structure of the linear mixed model is shown below:

[0153] Y ij =X i β+Z i γ i +ε i .

[0154] Among them, Y ij The jth response of the ith subject, i.e., the subject’s corresponding subjective experience data, behavioral performance data, and neural activity data; X i is the design matrix of fixed effects, i.e., four different levels of correlated color temperature; β is the p regression coefficient vector; Z iis the design matrix of random effects, which is the variability caused by differences between subjects; γ i is a random effect variable; i is the within-subject error vector.

[0155] The results of its behavioral performance analysis are shown in Table 4. Figure 4-Figure 9 Data results of subjective experience, partial behavioral performance, and neural activity at different levels of independent variables are presented.

[0156] Table 4 Behavioral performance analysis results

[0157]

[0158]

[0159]

[0160] The results of the KSS scale showed that high levels of correlated color temperature had a significant effect on improving subjective alertness, mainly in that compared with 4000K, the KSS scores were lower at 6500K, 8500K and 12000K, but there was no significant difference between the three levels, and this result was independent of the intervention time. Whether in the morning or afternoon, the accuracy of the visual search task was the highest at 8500K, which shows that this correlated color temperature level is relatively suitable for the execution of the visual search task. For attention and alertness, the reaction speed of exposure to 12000K in the afternoon was significantly higher than that in the morning, but the reaction speed of exposure to 12000K in the morning was significantly lower than that of 6500K and 8500K. For reaction inhibition, the accuracy of exposure to 8500K was significantly higher than that of 4000K, whether in the morning or afternoon. For working memory, the reaction time of exposure to 6500K in the morning was better than that of the other three correlated color temperature levels, but the reaction time of exposure to the same correlated color temperature level in the afternoon was the worst. For the executive control task, the comprehensive performance was the worst in the morning when exposed to 4000K. For risk decision-making ability, the number of inflations in the afternoon when exposed to 12000K was significantly higher than that in the afternoon when exposed to 8500K. For emotional perception ability, it was easier to perceive the emotion of "fear" in the morning when exposed to 4000K than in the morning when exposed to 12000K. The neural activity data provided more reliable results. In all brain regions (except the occipital region), it was found that the theta wave energy in the afternoon when exposed to 12000K was significantly lower than that in the morning; in all brain regions (except the frontal region), it was found that the theta wave energy in the morning when exposed to 6500K was significantly lower than that in the afternoon. In the morning, the theta wave in the frontal region was significantly activated at 4000K compared with the parietal, occipital and temporal regions; and the theta wave in the central and parietal regions was significantly activated at 12000K compared with the frontal, occipital, temporal and whole brain regions. Theta wave energy (especially in the frontal lobe area) is used to characterize the degree of fatigue. The more theta waves are suppressed, the higher the alertness is, and the more theta waves are activated, the higher the fatigue is. Therefore, it is not recommended to use 4000K or 12000K as the lighting environment in the morning. In the morning, the alpha wave activity in the occipital lobe area is significantly activated at 6500K, which indicates physiological activation. Therefore, setting the correlated color temperature to 6500K in the morning and 8500K in the afternoon will stimulate the body's wakefulness and improve work performance.

[0161] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Fig.10As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store processing data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a video tag processing method is implemented.

[0162] Those skilled in the art will understand that Fig.10 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0163] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0164] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0165] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0166] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0167] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0168] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0169] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for setting correlated color temperature for windowless offices based on photobiological effects, characterized in that: The method for setting the correlated color temperature for a windowless office space based on the photobiological effect includes: According to the actual working scenes and typical work tasks of the windowless office, the cognitive function is determined, and an experimental paradigm is constructed based on the cognitive function; the cognitive function is a cognitive function related to work performance, there are multiple experimental paradigms, and the experimental paradigm is used to characterize the work performance of the windowless office; Modulating the correlated color temperature level within the range of 4000K-12000K according to the daytime photobiological effect; the correlated color temperature level is multiple; Based on the experimental paradigm and the correlated color temperature level, determine the experimental environment, experimental equipment and experimental process; Conducting an experiment based on the experimental environment, the experimental device and the experimental process to obtain the subjective experience data, behavioral performance data and neural activity data of the subjects, and using a linear mixed model to comprehensively analyze the subjective experience data, the behavioral performance data and the neural activity data to obtain a multimodal photobiological response degree; The correlated color temperature for the morning period and the correlated color temperature for the afternoon period are set respectively according to the multimodal photobiological response degree.

2. The method for setting correlated color temperature for windowless offices based on photobiological effects according to claim 1, characterized in that: An experimental paradigm was constructed based on the cognitive functions, including: Mapping the cognitive functions with the acquired traditional cognitive psychology experimental paradigms one by one to obtain the experimental paradigm screening results; The experimental paradigm is obtained by screening the results according to the experimental paradigm.

3. The method for setting correlated color temperature for windowless offices based on photobiological effects according to claim 1, characterized in that: The correlated color temperature level is modulated in the range of 4000K-12000K according to the daytime photobiological effect, including: Under the conditions of constant illumination and color rendering index of the working surface, four different correlated color temperature levels are modulated in the range of 4000K-12000K according to the daytime photobiological effect; The CL-500A handheld spectroradiometer was used to measure and calibrate four different correlated color temperature levels, and the spectral distribution curves corresponding to the four different correlated color temperature levels were obtained. The spectral distribution curves corresponding to four different correlated color temperature levels were calculated using the α-opic equivalent daylight illuminance model, and the photobiological effect values ​​at the human eye level corresponding to four different correlated color temperature levels were obtained.

4. The method for setting correlated color temperature for windowless offices based on photobiological effects according to claim 3, characterized in that: The calculation formula of the photobiological effect value is: in, is the photobiological effect value, the unit is lx; E e,α is the α-opic irradiance, which is calculated according to the spectral distribution curve; It is the α-opic light radiation efficiency under standard daylight D65, in mW·lm -1 .

5. The method for setting correlated color temperature for windowless offices based on photobiological effects according to claim 1, characterized in that: The experimental process specifically includes: The subjects came to the experimental site to sign in at different working hours during the day according to the agreed time; The subjects were fitted with a 64-lead electrode cap under baseline lighting conditions to ensure that all electrode impedances dropped to 5 kΩ; Dark adaptation for k minutes to counteract carryover effects of baseline light exposure; Turn on the light to the current correlated color temperature level, perform light adaptation for t minutes, and synchronously collect t minutes of resting EEG signals; The experimental paradigm was completed in sequence at the current correlated color temperature level, and the order was balanced within the subjects; The subjects filled in the KSS scale and self-reported their subjective alertness at the current correlated color temperature level; Collect resting EEG signals for t minutes, and the current correlated color temperature level experience ends; Each correlated color temperature level is taken as the current correlated color temperature level one by one, and the step of "dark adaptation for k minutes to offset the residual effect of baseline light exposure" is returned.

6. The method for setting correlated color temperature for windowless offices based on photobiological effects according to claim 1, characterized in that: The subjective experience data include the subjective alertness of the subjects at different correlated color temperature levels; the behavioral performance data include reaction time, accuracy and comprehensive performance; the neural activity data include the power spectral density of theta waves and alpha waves in the subjects' electroencephalogram signals.

7. The method for setting correlated color temperature for windowless offices based on photobiological effects according to claim 6, characterized in that: The calculation formula for the reaction is: T=T reac -T onset ; Where T is the reaction time of successful trials in the task phase of the ith task; T reac is the time the button is pressed; T onset The time for the experimental stimulus materials to be presented; The calculation formula of the accuracy is: ACC=x i / N; Among them, ACC is the accuracy of the i-th task; x i is the number of correct responses made according to the stimulus displayed in the ith task trial; N is the total number of stimulus appearances in the ith task trial; The calculation formula of the comprehensive performance is: Among them, x ij The data generated when the i-th sample performs the j-th task; min{x ij } is the minimum value of all samples of the jth subtask; max{x ij } is the maximum value among all samples of the j-th subtask.

8. The method for setting correlated color temperature for windowless offices based on photobiological effects according to claim 1, characterized in that: The calculation process of the linear mixed model is: Y ij =X i β+Z i c i +e i ; Among them, Y ij The jth response of the ith subject, i.e., the subject’s corresponding subjective experience data, behavioral performance data, and neural activity data; X i is the design matrix of fixed effects, i.e., four different levels of correlated color temperature; β is the p regression coefficient vector; Z i is the design matrix of random effects, which is the variability caused by differences between subjects; γ i is a random effect variable; i is the within-subject error vector.

9. The method for setting correlated color temperature for windowless offices based on photobiological effects according to claim 1, characterized in that: Said cognitive functions include visual search, attentional vigilance, sustained attention, working memory, risky decision making, executive control, and emotion perception; The experimental paradigms are, in order, the digit symbol substitution test task, the psychomotor vigilance task, the Go / No-go task, the letter / space / fractal board 2-back task, the balloon simulation risk task, the second generation multi-attribute task battery, and the emotion perception task.

10. The method for setting correlated color temperature for windowless offices based on photobiological effects according to claim 3, characterized in that: The illumination of the working surface is 500 lx, the color rendering index is not less than 90%, and the correlated color temperature levels are 4000K, 6500K, 8500K and 12000K respectively.

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