Lighting method with multi-spectral rhythmic lighting scenarios

Abstract

A lighting method with multi-spectral rhythmic lighting scenarios includes: downloading a multi-spectral rhythmic lighting scenario database from the cloud; selecting a multi-spectral lighting parameter and a rhythm parameter from the multi-spectral rhythmic lighting scenario database to activate a light-emitting device for lighting; illuminating a subject with the light-emitting device; testing the subject's blood or saliva to obtain a psychological stress index value; and transmitting the rhythm parameter and psychological stress index value to the cloud using a portable communication device; wherein the rhythm parameter includes a rhythmic lighting parameter and a rhythmic scenario parameter.

Description

Technical Field

[0001] The present invention relates to a system and method for establishing a multi-spectral rhythmic lighting scenario database, and more particularly to a lighting process that adjusts the human body's circadian rhythm through multi-spectral lighting parameters and rhythmic parameters. Background Art

[0002] Humans are highly emotional beings, experiencing varying emotions depending on their state of mind. These emotions range from excitement, amusement, anger, disgust, fear, happiness, sadness, calmness, and neutrality. When negative emotions (such as anger, disgust, and fear) are not properly managed, they can cause psychological harm or trauma, ultimately developing into mental illness. Therefore, in today's highly competitive and stressful society, providing a timely emotional resolution, relief, or treatment system that meets user needs presents significant business opportunities.

[0003] Modern medical equipment now uses functional magnetic resonance imaging (fMRI) systems to measure changes in blood dynamics caused by neuronal activity. Due to its non-invasive nature and low radiation exposure, fMRI is currently primarily used for brain and spinal cord research in humans and animals. Electroencephalography (EEG) can also be used to examine subjects using the same emotional stimulation to reveal responses to different emotions. For example, distinct EEG patterns can be observed for fear and happiness. When observing the responses to specific emotions under fMRI and EEG, for example, when stimulating happiness (e.g., through image induction and facial emotion recognition), fMRI blood oxygenation-dependent contrast (BOLD) responses have revealed significant responses in the medial prefrontal cortex (MPFC) compared to corresponding emotions (anger and fear). In contrast, for example, when examining the blood oxygen concentration-dependent contrast (BOLD) response during fear and anger, fMRI reveals a significant response in the amygdala, indicating that the two emotions are responsive to distinct brain regions. Therefore, the BOLD response in these different brain regions can be used to clearly identify the subject's current emotion. Furthermore, when using an electroencephalogram (EEG) to examine and measure a subject, using the same emotional stimulation, distinct brainwave patterns can be observed for fear and happiness. Therefore, these different brainwave patterns can also be used to identify the subject's current emotion. As mentioned above, fMRI distinguishes emotions through different BOLD responses, while EEG distinguishes emotions through different brainwave patterns. Obviously, the methods used by the two to judge the test subject's emotions and the content of the records are completely different. Therefore, based on current technology, it is impossible to use the brain wave patterns of an electroencephalogram (EEG) to replace the blood oxygen concentration-dependent contrast (BOLD) response of a functional magnetic resonance imaging (fMRI) system for the test results of the same emotion on the same test subject.

[0004] The above discussion of the use of functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) for emotion judgment is based on the fact that fMRI systems are very expensive and bulky, making them unsuitable for commercial systems and methods for human-induced lighting. Similarly, if only EEG brainwave patterns are used to judge a subject's emotions, different subjects may have different brainwave patterns for different emotions. Therefore, it is currently impossible to construct a commercially viable human-induced lighting method and system using only the blood oxygenation-dependent contrast (BOLD) response of a functional magnetic resonance imaging (fMRI) system or only EEG brainwave patterns through light recipe editing.

[0005] In addition, humans also have distinct biological rhythms, known as circadian rhythms ("biological clocks"), which are controlled by the body's biological clocks, and the control of these biological clocks is inferred to be affected by light. Later, in the study of the impact of light on physiological stimulation, it has been found that light sources with high color temperature at night suppress the secretion of melatonin more than light sources with low color temperature. In addition, from newer studies, it has been found that the human eye and physiological effects are highly correlated, thus further proving the relationship between light sources and the secretion and physiological effects of melatonin. Therefore, if the human body works at night, it will put the body in a nocturnal rhythm, so it cannot be alert. It is necessary to provide a spectral component with daytime light sources in order to enable the human body to provide work efficiency when working at night. Summary of the Invention

[0006] According to the above description, the present invention provides a lighting method with multi-spectral rhythmic lighting scenarios, which is to configure a light-emitting device and a lighting system in a space, wherein the lighting system is composed of a portable communication device, a management and control module, a cloud, and an ambient light sensor. The method includes: capturing a multi-spectral rhythmic lighting scenario database, wherein the portable communication device downloads the multi-spectral rhythmic lighting scenario database to the cloud via the Internet; activating lighting in the rhythmic lighting scenario, wherein the portable communication device selects multi-spectral lighting parameters and rhythm parameters from the multi-spectral rhythmic lighting scenario database to activate the light-emitting device to perform lighting for the lighting subject; performing a cortisol test, wherein the blood or saliva of the lighting subject is tested to obtain the psychological stress index value of the lighting subject; and establishing a database of the relationship between multi-spectral rhythmic lighting scenarios and psychological stress, wherein the portable communication device or the management and control module transmits the rhythm parameters and the psychological stress index value to the cloud.

[0007] The present invention then provides a lighting method with multi-spectral rhythmic lighting scenarios, which comprises configuring a light-emitting device and a lighting system in a space, wherein the lighting system is composed of a portable communication device, a management and control module, a cloud, and an ambient light sensor. The method includes: capturing a multi-spectral rhythmic lighting scenario database, wherein the portable communication device downloads the multi-spectral light-emitting device cloud database from the cloud via the Internet; activating lighting in the rhythmic lighting scenario, wherein the portable communication device selects multi-spectral lighting parameters and rhythm parameters from the multi-spectral rhythmic lighting scenario database, transmits the parameters to the ambient light sensor, and then activates the light-emitting device to perform lighting for the subject; performing a cortisol test, wherein the subject's blood or saliva is sampled and tested to obtain a psychological stress index value; and establishing a database of the relationship between multi-spectral rhythmic lighting scenarios and psychological stress, wherein the portable communication device or the management and control module transmits the rhythm parameters and the psychological stress index value to the cloud.

[0008] In establishing the above-mentioned lighting method with multi-spectral rhythmic lighting scenarios, it is characterized in that the rhythmic parameters include: rhythmic lighting parameters and rhythmic scenario parameters.

[0009] In the lighting method for establishing the above-mentioned multi-spectral rhythmic lighting scenario, it is characterized in that: the multi-spectral lighting parameters are lighting parameters such as the spectrum, light intensity, flicker rate and color rendering index (Ra) of the light-emitting device.

[0010] In establishing the above-mentioned lighting method with a multi-spectral rhythmic lighting scenario, it is characterized in that the rhythmic lighting parameters include: equivalent black vision illuminance (EML), physiological stimulation value (CAF), sunlight illuminance and color temperature changes, etc.

[0011] In establishing the above-mentioned lighting method with multi-spectral rhythmic lighting scenarios, it is characterized in that the rhythmic scenario parameters are composed of light from the direct lighting device and the indirect lighting device.

[0012] In the lighting method for establishing the above-mentioned multi-spectral rhythmic lighting scenario, it is characterized in that the direct lighting device is composed of recessed lamps, pendant lamps and ceiling lamps.

[0013] In the lighting method for establishing the above-mentioned multi-spectral rhythmic lighting scenario, it is characterized in that: indirect lighting is the light reflected by the wall from the lighting of the lamp.

[0014] In the lighting method with the multi-spectral rhythmic lighting scenario, the feature is that the psychological stress index value is a cortisol index value.

[0015] In establishing the above-mentioned lighting method with multi-spectral rhythmic lighting scenarios, it is characterized in that: the information established in the relational database includes: psychological stress index values ​​and rhythm parameters.

[0016] After establishing the above-mentioned multi-spectral rhythmic lighting scenario cloud database, it can be confirmed that the lighting field end can provide multi-spectral lighting parameters and rhythmic parameters of an effective rhythmic lighting scenario, so that the present invention can provide a lighting field end and lamp group for an effective rhythmic lighting scenario, so that the lighting field can be promoted and used commercially. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1a This is the original data collection framework of the present invention on the physiological and emotional responses of people to light;

[0018] Figure 1b This is a flow chart for collecting original data on human physiological and emotional responses to light exposure according to the present invention;

[0019] Figure 1c This is the process of judging the human response to specific physiological emotions due to illumination in the present invention;

[0020] Figure 2a The present invention establishes a classification method for the physiological and emotional responses of people to light-induced electroencephalograms;

[0021] Figure 2b The present invention constructs a lighting database for users to perform effective ergonomic lighting.

[0022] Figure 3 This is a system architecture diagram of the intelligent human-centered lighting system of the present invention;

[0023] Figure 4 This is a method of the present invention for constructing a human-induced lighting environment sharing platform;

[0024] Figure 5 This is a schematic diagram of indoor light distribution according to the present invention;

[0025] Figure 6 The present invention is a lighting system applied to spectral rhythm lighting situations;

[0026] Figure 7 The present invention provides a method for establishing a multi-spectral rhythmic lighting database;

[0027] Figure 8 The present invention provides a method for establishing a database of correlation between multi-spectral rhythmic lighting and psychological stress indicators;

[0028] Figure 9 The present invention provides a lighting method with a multi-spectral rhythmic lighting scenario. DETAILED DESCRIPTION

[0029] In the following description of this invention, the functional magnetic resonance imaging system is referred to as the "fMRI system," the electroencephalogram (EEG) is referred to as the "EEG," and the blood oxygen concentration-dependent contrast (BOLD) is referred to as the "BOLD." Furthermore, in the color temperature test embodiment of this invention, the test is performed in 100K increments. However, to avoid excessive length, the specific emotions referred to in the following description refer to excitement, happiness, or pleasure, and the corresponding specific emotional responses will be described using color temperatures of 3000K, 4000K, and 5700K as examples. Therefore, the invention is not limited to these three color temperature embodiments. Furthermore, to facilitate a thorough understanding of the technical content of this invention by those skilled in the art, related embodiments and examples are provided herein. When reading the embodiments of this invention, please refer to the drawings and the following description. The shapes and relative sizes of the components in the drawings are provided solely to facilitate understanding of the present embodiments and are not intended to limit the shapes and relative sizes of the components. For this purpose, please note that the following description of the embodiments of this invention is provided in conjunction with the accompanying drawings. The shapes and relative sizes of the components in the drawings are provided solely to facilitate understanding of the present embodiments and are not intended to limit the shapes and relative sizes of the components.

[0030] The present invention uses an fMRI system to measure physiological signals, understanding the correspondence between light spectrum and emotion in the brain and developing a preliminary mechanism for how light influences human physiological and psychological responses. Because the fMRI system's brain images can determine which part of the brain experiences hyperemia when stimulated by light, they can also record the BOLD response. This BOLD response to brain hyperemia is also known as a "blood oxygen concentration-dependent increase." Therefore, the present invention can accurately and objectively infer the subject's physiological emotional changes based on the fMRI system's recorded brain hyperemia data under various emotions and the "blood oxygen concentration-dependent increase" response. Based on the physiological emotions confirmed by the fMRI system, electroencephalography (EEG) is used to record brainwave changes and establish a correlation between the two. This approach aims to replace the fMRI system's emotional judgments with those recorded by the EEG.

[0031] Therefore, the main purpose of the present invention is to record the BOLD response of the subject to the specific emotion while the subject is being tested with an fMRI system. This is done to identify specific "effective color temperatures" that have a synergistic effect on the specific emotion, and to use this color temperature as the "effective color temperature" corresponding to the specific emotion. The subject is then illuminated with light at the "effective color temperature," and the brainwave pattern under the stimulation of the "effective color temperature" is recorded using an electroencephalogram (EEG). Once a correlation is established between the specific EEG brainwave pattern and the specific BOLD response, the EEG brainwave pattern can be used to assist in determining the user's emotional changes. This results in a commercially viable human-factor lighting system and method. This eliminates the need for expensive fMRI systems to implement human-factor lighting systems, reduces operating costs, and further meets customized service needs.

[0032] First, please refer to Figure 1a , is the original data collection framework of the present invention on the physiological and emotional response of people to light. Figure 1a As shown, the intelligent human-centered lighting system 100 is activated in an environment (e.g., a test space) equipped with various adjustable lighting modules, providing variable light signal parameters such as spectrum, light intensity, flicker rate, and color rendering index (Ra). The present invention utilizes an fMRI-compatible image interaction platform 110, developed by an fMRI system, to target different target emotions. This platform uses voice and image guidance, along with a specific effective spectrum for 40 seconds of stimulation. This observation allows for observation of changes in the blood oxygen content of the subjects' brains to verify whether the "effective color temperature" can significantly induce emotional responses in the subjects. This is explained in detail below.

[0033] Next, please refer to Figure 1b and Figure 1c ,in, Figure 1b This is a flow chart of the original data collection of the physiological and emotional response of people to light. Figure 1c It is the process of judging people’s specific physiological and emotional reactions to light. Figure 1bAs shown in step 1100, each subject is already on the compatible image interaction platform 110. Next, each subject is guided through known images to experience various emotional stimulations. Subsequently, as shown in step 1200, the compatible image interaction platform 110 records the BOLD responses in the subject's brain to various emotions after being stimulated by the images. Next, as shown in step 1300, visual stimulation is provided to the subject by providing a spectrum of light with different color temperature parameters. For example, LED lamps are used in conjunction with electronic dimmers to provide a spectrum of different color temperature parameters. In an embodiment of the present invention, nine sets of visual stimulations with different color temperatures are provided: 2700K, 3000K, 3500K, 4000K, 4500K, 5000K, 5500K, 6000K, and 6500K. After each 40-second period of effective light exposure and stimulation, the subject can be given one minute of ineffective light (full-spectrum, flicker-free white light) to achieve emotional relaxation. Furthermore, the test subject may be given a 40-second counter-effect light stimulus to observe whether the area that responded to the original effective light stimulus has a reduced response. In the embodiment of the present invention, after the compatible image interaction platform 110 has recorded the BOLD response of a specific emotion in the brain of the test subject after being stimulated by the picture, the test subject is visually stimulated by providing spectra with different color temperature parameters, such as Figure 1c As shown in step 1310, a spectrum with a color temperature of 3000K is provided. Then, as shown in step 1320, a spectrum with a color temperature of 4000K is provided. Finally, as shown in step 1330, a spectrum with a color temperature of 5700K is provided to provide visual stimulation to the tester.

[0034] Next, as shown in step 1400, the compatible image interaction platform 110 records the BOLD responses of the test subject's brain to various emotions after being stimulated by light. In an embodiment of the present invention, after the test subject is stimulated by light with different color temperature parameters, the compatible image interaction platform 110 sequentially records the BOLD response results of the emotional response areas in the test subject's corresponding limbic system. Among them, the parts of the limbic system triggered by different emotions are different, and the above-mentioned limbic system with emotional response brain areas are shown in Table 1 below.

[0035] Table 1

[0036]

[0037] The compatible image interaction platform 110 records the BOLD response results in specific brain regions. The response results are determined by calculating the area size of the emotional response sites when there are more limbic systems with BOLD emotional responses in the brain region. For example, the larger the area with BOLD emotional response, the stronger the response to a specific physiological emotion. In the embodiment of the present invention, Figure 1c Step 1410 records the BOLD response after exposure to a spectrum with a color temperature of 3000K. Next, step 1420 records the BOLD response after exposure to a spectrum with a color temperature of 4000K. Finally, step 1430 records the BOLD response after exposure to a spectrum with a color temperature of 5700K. After the subject underwent the light exposure procedure to induce excitement, the compatible image interaction platform 110 recorded the BOLD response in specific brain regions, as shown in Table 2.

[0038] Table 2

[0039]

[0040] Among them, after the test subject went through the light exposure procedure after the happiness emotion was induced, the compatible image interaction platform 110 recorded the BOLD response results in specific brain areas as shown in Table 3.

[0041] Table 3

[0042]

[0043] Among them, after the test subject went through the light exposure procedure after the amusement emotion was induced, the compatible image interaction platform 110 recorded the BOLD response results in specific brain areas as shown in Table 4.

[0044] Table 4

[0045]

[0046] Next, as shown in step 1500, the specific color temperature that increases the BOLD-dependent response to a specific emotion is screened through illumination. This specific color temperature is referred to as the "effective color temperature." In this embodiment, the BOLD response results of the corresponding emotionally responsive regions in the subject's limbic system are recorded to summarize the stimulating effects of color temperature on the brain, as shown in Tables 1 through 3. To screen the specific color temperatures that increase the BOLD-dependent response to a specific emotion, the specific color temperatures that maximize the response to that specific emotion (i.e., the area with the largest BOLD response) are calculated.

[0047] As shown in step 1510, after the tester has recorded the excitement emotion on the compatible image interaction platform 110 and completed the illumination procedure, the maximum response value is calculated. For example, according to the record in Table 2, the total score of 3000K (577) is subtracted from the total score of 4000K (226), resulting in 351. Then, the total score of 3000K (577) is subtracted from the total score of 5700K (-105), resulting in 682. The total response value score under 3000K illumination after the excitement emotion is induced is 1033.

[0048] Then, if Figure 1c In step 1520, after the tester has recorded the excitement emotion on the compatible image interaction platform 110 and completed the lighting procedure, the maximum response value is calculated. For example, according to the records in Table 2, the total score of 4000K (226) is subtracted from the total score of 3000K (577), resulting in -351. Then, the total score of 4000K (266) is subtracted from the total score of 5700K (-105), resulting in 371.

[0049] Then, if Figure 1c In step 1530, after the tester has recorded the excitement emotion on the compatible image interaction platform 110 and completed the lighting procedure, the maximum response value is calculated. For example, according to the records in Table 2, the total score of 5700K (-105) is subtracted from the total score of 3000K (577), resulting in -682. Then, the total score of 5700K (-105) is subtracted from the total score of 4000K (-105), resulting in 371.

[0050] According to the above calculations, after excitement is induced, an illuminance of 3000K maximizes the response. This means that 3000K produces a more pronounced boost in excitement (i.e., compared to the calculated total scores for 4000K and 5700K, 3000K achieves the highest total score of 1033). Therefore, 3000K is used as the "effective color temperature" for excitement. For other emotions, such as happiness and joy, different "effective color temperatures" can be obtained using the calculations from steps 1510 to 1530, as shown in Table 5.

[0051] Table 5

[0052] Physiological emotions Effective color temperature Excitement 3000K Happiness 4000K Amusement 5700K

[0053] Next, based on the statistical results in Table 5, the effective color temperature can be considered the result of a specific physiological emotion-dependent response. This effective color temperature can be considered the "enhancement spectrum" of the fMRI system's "blood oxygen concentration dependence" on a particular emotion. For example, an effective color temperature of 3000K can represent the "enhancement spectrum" of the fMRI system for the emotion of "excitement." For example, an effective color temperature of 4000K can represent the "enhancement spectrum" of the fMRI system for the emotion of "happiness." For example, an effective color temperature of 5700K can represent the "enhancement spectrum" of the fMRI system for the emotion of "pleasure."

[0054] Finally, as shown in step 1600, an "enhancement spectrum" database corresponding to the effects of specific emotions can be established within the fMRI system. By stimulating the subject with the aforementioned human-induced lighting parameters, observing and recording the BOLD response of the subject's brain during the illumination stimulation using the fMRI system, and simultaneously recording fMRI brain images, determining which part of the brain experiences an additive "blood oxygen concentration dependency" response to the illumination stimulation, a specific effective color temperature can be considered the fMRI "enhancement spectrum" of the "blood oxygen concentration dependency" of a specific emotion. Clearly, based on the statistical results of the additive BOLD response to specific emotions at specific "effective color temperatures" as shown in Table 5, the present invention objectively infers the subject's "enhancement spectrum" for specific physiological emotional responses. This "enhancement spectrum" serves as evidence of the physiological emotional response that produces the strongest additive effect for a specific emotion (including excitement, happiness, pleasure, anger, disgust, fear, sadness, calmness, or neutrality).

[0055] It should be emphasized that the present invention Figure 1b and Figure 1c In the entire implementation process, 100 testers were subjected to complete tests on multiple specific emotions, and the statistical results in Table 5 were obtained. For example: in terms of excitement, providing an effective color temperature of 3000K as the "enhanced spectrum" under the physiological emotional response of excitement can make the tester's excitement produce a physiological emotional response with the strongest additive effect. For example: in terms of happiness, providing an effective color temperature of 4000K as the "enhanced spectrum" under the physiological emotional response of happiness can make the tester's happiness produce a physiological emotional response with the strongest additive effect. For another example: in terms of pleasure, providing an effective color temperature of 5700K as the "enhanced spectrum" under the physiological emotional response of pleasure can make the tester's pleasure produce a physiological emotional response with the strongest additive effect.

[0056] In addition, it should be emphasized that the above three color temperatures are only used as examples of the present invention, and do not limit the use of these three color temperatures as the "enhanced spectrum" for the three physiological emotional responses. In fact, after the color temperature of 2000K, each 100K increase can be used as an interval to enhance different emotions (including: excitement, happiness, pleasure, anger, disgust, fear, sadness, calmness or neutrality, etc.). Figure 1b and Figure 1c Therefore, Table 5 of the present invention only discloses part of the results and is not intended to limit the present invention to these three embodiments.

[0057] Next, the present invention aims to establish an artificial intelligence model for the correlation between brain waves and brain images of general physiological emotions. This allows for future commercialization, allowing the inference of physiological emotions directly from other sensing devices without the need for an fMRI system. The sensing device used in the present invention includes an electroencephalogram (EEG). In the following embodiment, an EEG device 130 is used to establish physiological emotional responses to light. Alternatively, an eye tracker 150 or an expression recognition technology-assisted program 170 could be used to replace the fMRI system for physiological emotional responses. However, the eye tracker 150 and expression recognition technology-assisted program 170 will not be disclosed in this invention, but this is forewarned.

[0058] Please refer to Figure 2a , is a method of establishing a classification of physiological and emotional responses of people to light-induced EEG. Figure 2a As shown, the present invention uses an electroencephalogram (EEG) device 130 to establish physiological and emotional responses to human-induced lighting. The method includes the following steps: First, as shown in step 2100, the "enhanced spectrum" database information in Table 5 is stored in the memory of the EEG device 130. Next, as shown in step 2200, the subject wears the EEG device and is guided through various emotional stimulations using known images or video elements. Next, as shown in step 2300, the intelligent human-induced lighting system 100 is activated and provides variable light signal parameters such as spectrum, light intensity, flicker rate, and color rendering index (Ra) to stimulate the subject. The EEG device 130 then records brainwave patterns after exposure to light of different color temperatures under specific emotions. For example, in this embodiment, each subject is first stimulated with excitement. Subsequently, as in steps 2310 to 2330, different color temperatures of 3000K, 4000K, and 5700K are provided to the subject for light stimulation. EEG patterns of the subject's specific emotions during the excitement stimulation and after the different color temperature light stimulation are recorded and stored in the memory of the electroencephalogram 130. In this embodiment of the present invention, the EEG patterns of 100 subjects after the specific emotional stimulation and light exposure are recorded, thus requiring a larger memory.

[0059] Next, as shown in step 2400, the EEG pattern files corresponding to specific emotions (e.g., excitement, happiness, and joy) stored in the EEG device 130's memory are learned through artificial intelligence learning. Because the EEG device 130 can only memorize brainwave waveforms, the EEG patterns currently stored in the EEG device 130's memory are those generated in response to specific known triggering emotional stimuli and illumination at different color temperatures. It should be noted that in actual testing, different test subjects will experience different EEG patterns in response to the same emotional stimulus and illumination at the same color temperature. Therefore, during the learning process in step 2400, the present invention uses information from the "enhanced spectrum" database to classify EEG files related to specific emotions. For example, for EEG files related to excitement, only EEG files from different test subjects at a color temperature of 3000K are grouped together. For another example, for EEG files related to happiness, only EEG files from different test subjects at a color temperature of 4000K are grouped together. For another example, for EEG files related to pleasure, only EEG files from different test subjects at a color temperature of 5700K are grouped together. The EEG device is then trained using machine learning within artificial intelligence. In this embodiment of the present invention, a transfer learning model is specifically selected for learning and training.

[0060] During the learning and training process using the transfer learning model in step 2400, the learning and training is performed by statistically analyzing, calculating, and comparing similarities for groups of EEG patterns for specific emotions. For example, when learning and training a group of EEG patterns with a color temperature of 3000K, the learning and training is performed by statistically analyzing, calculating, and comparing the most similar and least similar EEG patterns for excitement, among the EEG patterns with a color temperature of 3000K. For example, the EEG patterns with the highest similarity can be considered the EEG patterns with the strongest emotions, while the patterns with the lowest similarity can be considered the EEG patterns with the weakest emotions. The EEG patterns ranked for the strongest emotions can be used as the "target value," while the patterns ranked for the weakest emotions can be used as the "starting value." For ease of explanation, the most similar EEG pattern is used as the "target value," while the least similar EEG pattern is used as the "starting value." Different scores are assigned, for example, a similarity score of 90 is assigned to the "target value," and a similarity score of 30 is assigned to the "starting value." Similarly, complete the EEG files of the happiness emotion level in the 4000K color temperature category and the surprise emotion level in the 5700K color temperature category. The "starting value" and "target value" can be made to form a similarity score range.

[0061] Afterwards, as shown in step 2500, an artificial intelligence electroencephalogram classification and grading database (which may be referred to as an artificial intelligence electroencephalogram file database) is established. After step 2400, the electroencephalogram file groups of various specific color temperatures are given "target value" scores and "starting value" scores to form a database with the grading results, which is stored in the memory of the electroencephalogram (EEG) 130. The purpose of the present invention in establishing an electroencephalogram classification and grading database in step 2500 is to obtain the electroencephalogram file of an unknown tester after the unknown tester receives specific emotional stimulation and is given light of a specific color temperature, and then compare the electroencephalogram file of the unknown tester with the electroencephalogram file similarity score interval in the database, so as to judge or infer the current congestion reaction condition of the unknown tester in the brain. The detailed process is as follows. Figure 2b shown.

[0062] Next, please refer to Figure 2b , is a lighting database constructed by the present invention for users to conduct effective human-factor lighting. First, as shown in step 3100, the test subject wears an electroencephalogram (EEG) 130 and is asked to watch pictures that induce specific emotions. Then, as shown in step 3200, the human-factor lighting system 100 is started in an environment (e.g., a test space) that has been equipped with various adjustable multi-spectral lighting modules, through the management control module 611 (e.g., Figure 3 Then, as shown in step 3300, the brainwave image of the test subject after the emotion induction and light exposure is obtained and stored in the memory module 617 of the cloud 610 (as shown in step 3300). Figure 3 Then, as shown in step 3400, the artificial intelligence electroencephalogram file database is imported into the management and control module 611. The management and control module 611 will set a score to determine whether the similarity is sufficient. For example, when the similarity score is set to 75 points or above, it means that the test subject's brain congestion reaction is sufficient. Then, as shown in step 3500, the management and control module 611 will compare the similarity of the test subject's electroencephalogram file and the artificial intelligence electroencephalogram file. For example, when the similarity score after the comparison of the test subject's electroencephalogram file is 90 points, the management and control module 611 will immediately determine that the test subject's brain congestion reaction is very sufficient, so it will proceed to step 3600 to terminate the human factor illumination test for a specific emotion. Then, step 3700 is performed to record the human factor illumination parameters when the test subject's brain congestion reaction has reached the stimulation level into a database and store it in the memory module 617.

[0063] Then, in Figure 2bIn step 3500, if the similarity score after comparing the subject's EEG file with the artificial intelligence EEG file is 35, the management and control module 611 will determine that the subject's brain hyperemia response is insufficient and will proceed to step 3800. The management and control module 611 will continue to strengthen the human-factor illumination test, including providing appropriate increases in illumination time or intensity based on the similarity score. Then, step 3300 is repeated to obtain EEG files after increasing illumination time or intensity. The human-factor illumination test will not be terminated until the similarity score reaches a set similarity score of 75 or above, proceeding through step 3400. If the management and control module 611 determines that the subject's brain hyperemia response has reached a stimulation level, a human-factor illumination parameter data file will be created for the subject in step 3700. Finally, the management control module 611 compiles each test subject's human factors lighting parameters into a "human factors lighting parameter database" and stores it in the memory module 617. Obviously, as more test subjects are included, the artificial intelligence EEG file database of the present invention will learn more EEG files, making the similarity score of the present invention increasingly accurate.

[0064] After establishing the artificial intelligence model for the "Human Factor Lighting Parameter Database," the present invention can, upon activation of the human factor lighting system 100, infer physiological and emotional changes in a new test subject's brain images simply by observing the electroencephalogram (EEG) analysis results from the electroencephalogram (EEG) monitor 130. This eliminates the need for expensive fMRI systems, as the artificial intelligence model for inferring physiological and emotional changes in brain images can be used. This allows the human factor lighting system 100 to be promoted and used commercially. Furthermore, to facilitate commercial use of the "Human Factor Lighting Parameter Database," the "Human Factor Lighting Parameter Database" can be stored in an internal private cloud 6151 within the cloud 610.

[0065] Next, please refer to Figure 3 , is a system architecture diagram of the intelligent human factor lighting system 600 of the present invention. Figure 3As shown, the overall architecture of the intelligent human-centered lighting system 600 of the present invention can be divided into three blocks: a cloud 610, a lighting field end 620, and a client 630. These three blocks are connected via the internet, so they can be located in different regions or deployed together. The cloud 610 further includes a management and control module 611, which is used for cloud environment construction, cloud computing, cloud management, and the use of cloud computing resources. Users can also access, construct, or modify the content within each module through the management and control module 611. A consumption module 613, connected to the management and control module 611, serves as a cloud service for users to subscribe to and consume. Therefore, the consumption module 613 can access each module within the cloud 610. A cloud environment module 615, connected to the management and control module 611 and the consumption module 613, divides the cloud backend environment into an internal private cloud 6151, an external private cloud 6153, and a public cloud 6155 (e.g., a commercial cloud), providing interfaces for external or internal services for system providers or users. The memory module 617 is connected to the management control module 611 and is used as a storage area for the cloud backend. The technical content required to be executed by each module in the present invention will be specifically described in the subsequent different embodiments. Figure 3 The lighting field end 620 can communicate with the cloud 610 or the client 630 through the Internet. Among them, a lamp group 621 composed of multiple light-emitting devices is configured in the lighting field end 620. And the client 630 can communicate with the cloud 610 or the lighting field end 620 through the Internet. Among them, the client 630 of the present invention includes general users and editors who use the intelligent human-induced lighting system 600 of the present invention to carry out various business operations, all of which belong to the client 630 of the present invention, and the representative device or apparatus of the client 630 can be a fixed device with computing function or a portable intelligent communication device. In the following description, users, creators, editors or portable communication devices can represent the client 630. In addition, in the present invention, the above-mentioned Internet can be an intelligent Internet of Things (AIoT).

[0066] Please refer to Figure 4 , is a method 400 of constructing a lighting environment sharing platform of the present invention. Figure 4 In the process of Figure 3The intelligent human-centered lighting system 600 is carried out in a system, wherein the intelligent human-centered lighting system 600 has a plurality of light-emitting devices 621 providing different spectrums, which can be a group of LED lamps. The present invention particularly illustrates that the LED lamp group can selectively combine a multi-spectrum combination of a specific color temperature by modulating the voltage or current of individual LED lamps to provide a multi-spectrum combination for lighting. Of course, the present invention can also choose to use a plurality of LED lamps with specific light emission spectra, and by providing a fixed voltage or current to allow each energized LED lamp to emit its specific spectrum, to combine a multi-spectrum combination of a specific color temperature for lighting, wherein each multi-spectrum combination of a specific color temperature can be formed by changing the light signal parameters of the LED lamp, such as the spectrum, light intensity, flicker rate, and color rendering index (Ra). Furthermore, it should be emphasized that the light-emitting devices 621 with different spectra described in the present invention are based on the fact that the actual illumination process requires multiple light-emitting devices 621 to emit different spectra. Therefore, the light-emitting devices 621 with different spectra can be composed of light-emitting devices with different spectra, or they can be multiple identical light-emitting devices, and the emitted spectra can be adjusted to different spectra by the power provided by the control device. Therefore, the present invention is not limited to the above-mentioned embodiments of the light-emitting devices 621 with different spectra, and of course also includes light-emitting devices with different spectra formed by other methods.

[0067] First, as shown in step 410, a multi-spectral lighting device cloud database is constructed. The management and control module 611 in the cloud 610 loads the "human-factor lighting parameter database" stored in the memory module 617 or the internal private cloud 6151 into the management and control module 611. The "human-factor lighting parameter database" stored in the cloud 610 already knows how different color temperatures can stimulate people (or users) with corresponding emotions. For example, a specific color temperature can stimulate a specific emotion with a synergistic effect.

[0068] Next, as shown in step 411, a cloud database of light scenes of a multi-spectral lighting device is constructed. Since each color temperature can be combined through different multiple spectra, that is to say, the same color temperature can be obtained by different multi-spectral combinations. For example, when we want to establish a spectrum that can provide a 4000K color temperature, we can choose a multi-spectral combination of the Maldives at a color temperature of 4000K, or a multi-spectral combination of Bali, Indonesia at a color temperature of 4000K, or further choose a multi-spectral combination of Monaco Beach at a color temperature of 4000K. Obviously, these multi-spectral combinations with a color temperature of 4000K have different multi-spectral combinations based on their geographical location (including: longitude and latitude), time / brightness / flicker rate and other factors. Therefore, in step 411, based on the relationship between color temperature and corresponding emotions in the "human-centric lighting parameter database," different multispectral combinations at specific color temperatures at different geographic locations on Earth can be collected through the cloud 610. For example, different multispectral combinations at a color temperature of 4000K at different geographic locations on Earth can be collected (e.g., 4000K color temperature at different longitudes and latitudes), or different multispectral combinations at a color temperature of 4000K at different times on Earth (e.g., 4000K color temperature at 9:00 AM). These collected multispectral combinations at specific color temperatures at different geographic locations on Earth are then stored in the memory module 617. Under the control of the management and control module 611 in the intelligent human-centric lighting system 600, the parameters of various multispectral combinations at specific color temperatures (i.e., at different geographic locations or at different times at different geographic locations) can be adjusted by controlling the multiple light-emitting devices 621. After storage in the memory module 617, the intelligent human-centric lighting system 600 of the present invention constructs a "multispectral lighting device cloud database" of multispectral combinations at various color temperatures at different geographic locations. Clearly, the "multi-spectral lighting device cloud database" constructed in step 411 is the result of adjustments made using multiple light-emitting devices 621 with different spectra. Furthermore, it should be emphasized that, having understood how specific color temperatures can have a stimulating effect on specific emotions, the present invention can, in addition to creating multi-spectral combinations based on different geographic locations, also utilize artificial intelligence to synthesize or combine multi-spectral combinations that differ from actual geographic locations, taking into account factors such as latitude and longitude, time, brightness, and flicker rate. This is not a limitation of the present invention. Clearly, in step 411, the present invention has already constructed a light scene database comprising multiple multi-spectral lighting devices. Therefore, based on this constructed database of different light scenes, the intelligent human-centered lighting system 600 can provide multi-spectral lighting services at different color temperatures using multi-spectral lighting devices.At this point, the "multi-spectral light emitting device cloud database" constructed in step 411 can be stored in the memory module 617 or the internal private cloud 6151 or the public cloud 6155 (eg, a commercial cloud).

[0069] As shown in step 430, the effectiveness of the multi-spectral combination illumination is determined. Because the effects of human-centric lighting spectrum on emotional stimulation or influence may vary among different users, the illumination spectrum of the multi-spectral combination needs to be adjusted. Next, when user 630 enters the intelligent human-centric lighting system 600 of the present invention, they can select the desired emotion from the "multi-spectral lighting device cloud database" in the memory module 617, the internal private cloud 6151, or the public cloud 6155 through the management and control module 611. The management and control module 611 then selects a default multi-spectral combination from the memory module 617, the internal private cloud 6151, or the public cloud 6155. The management and control module 611 then controls multiple light devices 621 with different spectra to adjust the multi-spectral combination to achieve the desired emotion, and then uses this adjusted multi-spectral combination to illuminate the user. For example, if a user wants to adjust their mood to happiness or joy, a color temperature of 4000K can be selected based on the "human-centric lighting parameter database." At this point, the user can select the default multispectral combination provided by the "Multispectral Lighting Device Cloud Database" or choose a multispectral combination that provides a color temperature of 4000K. Of course, the user can also select a specific multispectral combination that is widely used for illumination. In this case, when the user uses the multispectral combination provided by the human factor lighting system 600 in the "Multispectral Lighting Device Cloud Database", the present invention refers to it as the default multispectral combination.

[0070] Next, as shown in step 430, when the user selects a multi-spectral combination preset for a happy or pleasant emotion (for example, the system defaults to the Maldives multi-spectral combination at a color temperature of 4000K), and a lighting program is performed using the multi-spectral combination adjusted by multiple light-emitting devices 621 with different spectra, for example, after 15 minutes of lighting, the user can determine or evaluate whether the multi-spectral combination illumination has effectively achieved a happy or pleasant emotion. The user can determine or evaluate whether the multi-spectral combination illumination has effectively achieved a happy or pleasant emotion based on their own feelings.

[0071] Continuing with step 430, when the user intuitively feels that they have effectively achieved a happy or joyful mood, they can record and store this usage experience in an external private cloud 6153 or a public cloud 6155. For example, after recording and storing the usage experience in the external private cloud 6153, it can serve as the user's personal experience archive. For example, this usage experience can also be recorded and stored in the public cloud 6155 for reference by other users. If the user still feels that they have not achieved a happy or joyful mood after 15 minutes of light exposure, the user can adjust the multi-spectral combination lighting recipe through the management and control module 611, for example, by adjusting the exposure time to 30 minutes or changing the multi-spectral combination light scene. For example, returning to step 411 and reselecting another multi-spectral combination light scene, such as changing the default multi-spectral combination light scene from the Maldives to Bali, Indonesia. Then, in step 430, the multispectral lighting process is repeated for 15 minutes. After the lighting process is completed, it is once again determined or evaluated whether the Bali multispectral combination lighting has effectively achieved a happy or pleasant mood. Once the user feels that the multispectral lighting of the current light scene has effectively achieved a happy or pleasant mood, the effective light scene usage experience can be recorded and stored to form a "spectral recipe." Finally, this "spectral recipe" is stored in an external private cloud 6153 or a public cloud 6155 to form a shared platform. Obviously, multiple "spectral recipes" are stored on the shared platform. The content stored in the shared platform includes: the "spectral recipe" that the user uses to achieve a specific emotional effect and the lighting control parameters (hereinafter referred to as lighting parameters) of the multispectral combination of light-emitting devices 621 with different spectra that produce the specific emotional "spectral recipe."

[0072] Finally, as shown in step 470, a shared platform for the lighting environment is established. After users record and store their effective user experience in an external private cloud 6153 or public cloud 6155, this not only serves as the user's personal experience archive, but the intelligent human-centered lighting system 600 can also, in step 470, perform a massive data analysis on this extensive user experience data and then record and store it in the internal private cloud 6151 or public cloud 6155. This allows the information stored in the public cloud 6155 to form a shared platform for the lighting environment. For example, after performing a massive data analysis on the user experience data, the intelligent human-centered lighting system 600 can determine the ranking of different "spectral recipes" selected by users for a specific color temperature. This ranking can provide users with a reference when selecting a "spectral recipe." Furthermore, after analyzing this massive data, various indicators can be generated for user reference. For example, different multi-spectral combinations of a 4000K color temperature can be ranked based on the user's gender, age, race, season, time of day, and so on. This allows the light environment sharing platform constructed by the present invention to serve as a platform for other designers interested in or willing to provide human-factor lighting recipes, using these indicators to conduct commercial services and operations. Therefore, the light environment sharing platform constructed by the present invention allows the intelligent human-factor lighting system 600 to provide various user experiences that have been curated or algorithmically calculated as default multi-spectral combinations. Furthermore, users can also select a most popular "spectral recipe" for lighting based on the calculated user experience data.

[0073] exist Figure 4 In this embodiment, step 450 is optional. For example, if the user is only creating a database for their own use, step 450 can be skipped. After the user determines that the data is valid in step 430, the valid usage experience can be recorded and stored in an external private cloud 6153 or public cloud 6155. The database for the "spectral recipe" establishment service to be established in step 450 will be described in a later embodiment.

[0074] Then, in Figure 4Another embodiment that can be used for commercial services and operations provides a creative platform that allows different users or creators to create new "spectral recipes" through this creative platform. As shown in step 460, a "spectral recipe" creation platform is provided in the intelligent human-centered lighting system 600. Creators 630 using this "spectral recipe" creation platform can be distributed around the world and can connect to the "sharing platform" of the light environment in the cloud 610 of the present invention via the Internet. Obviously, the present invention defines a "spectral recipe" creation platform as one that allows users or creators 630 to connect to the public cloud 6155 or "sharing platform" in the cloud 610 via the Internet, allowing users or creators 630 to use the "spectral recipe" information on the public cloud 6155 or "sharing platform" to perform editing work. Therefore, when the user or creator 630 obtains various calculated usage experience data from the "sharing platform", the user or creator 630 can edit or create the creator 630 personally based on the user's gender, age, race, season, time and other experience data to construct an edited "spectral formula" of multi-scene or multi-emotional multi-spectral combination.

[0075] First, the present invention uses a "spectral recipe" creation platform for commercial services and operations in a first embodiment. For example, for an emotionally stimulating result of a 4000K color temperature, users or creators 630 can use the "spectral recipe" creation platform to create combinations of different light scenes. For example, creator 630 might select a multispectral combination of the Maldives for the first segment, a multispectral combination of Bali for the second segment, and finally, a multispectral combination of a beach in Monaco for the third segment. By combining or configuring the spectral exposure time for each segment, a new spectral combination of multiple light scenes is formed. Finally, this spectral combination of multiple light scenes is stored on the "sharing platform," allowing other users to select this spectral combination of multiple light scenes as their "spectral recipe" for mood adjustment. The creation platform of the present invention also allows for the selection of specific color temperatures at specific times. For example, if a user wants to perform emotionally stimulating human-induced lighting at 9 AM, they can further select the aforementioned three multispectral combinations for 9 AM. Furthermore, the multispectral exposure time for each segment can be configured to be the same or different, for example, each segment can be exposed for 15 minutes. Alternatively, the first and third segments may be configured for 15 minutes, while the second segment may be configured for 30 minutes. These same or different time configurations may be selected by the user.

[0076] Secondly, in the second embodiment of the present invention using the "Spectral Recipe" creation platform, different color temperatures (i.e., multiple emotions) can be combined to achieve specific emotional stimulation results through multi-emotional lighting. For example, creator 630 can use the "Spectral Recipe" creation platform to create a multi-emotional combination. For example, creator 630 can select a multi-spectral combination of 4000K (happy mood) for the first segment, 3000K (excited mood) for the second segment, and finally, 5700K (pleasant mood) for the third segment. By combining or configuring the multi-spectral illumination time for each segment, a new multi-emotional multi-spectral combination is formed. Finally, this multi-emotional multi-spectral combination is stored on the "sharing platform," allowing users to select this multi-emotional multi-spectral combination as their "spectral recipe" for mood adjustment. Similarly, the creation platform in this embodiment can also select a specific color temperature for a specific time. For example, if a user wants to perform emotionally stimulating human-induced lighting at 9 AM, they can further select the aforementioned three multi-spectral combinations for 9 AM. Furthermore, the multi-spectral exposure time can be configured to be the same or different for each segment, for example, each segment can be 15 minutes. Alternatively, the first and third segments can be configured for 15 minutes, while the second segment can be configured for 30 minutes. These same or different time configurations can be selected by the user.

[0077] Next, it should be further explained that after the editing or creation of the first embodiment (multi-spectral combination of multiple light scenes) and the second embodiment (multi-spectral combination of multiple mood light scenes) are completed, the process from steps 430 to 470 is also required. For example, first, in step 411, a multi-spectral combination of light-emitting devices 621 with different spectra is used for illumination. Next, in step 430, it is determined whether the above-mentioned "spectral recipe" combination achieves the desired effect. This includes the spectral combination and corresponding illumination time of the multi-light scene in the first embodiment, and the spectral combination and configured illumination time of the multi-mood light scene in the second embodiment. If the desired effect is achieved, the lighting parameters of the light-emitting devices 621 required to create these "spectral recipes" can be compiled into a database that provides a "spectral recipe" creation service, as shown in step 450. Then, as shown in step 470, after the "spectral recipe" creation service database constructed in step 450 is uploaded to the cloud, these "spectral recipes" can be added to the public cloud 6155 of the present invention to form a light environment "sharing platform." If, after step 430, it is determined that a certain "spectral formula" does not achieve the effect set by the creator, the process can return to step 411 to adjust the exposure time of each segment, or change different "spectral formula" combinations (first embodiment) or change different emotion combinations (second embodiment) until these "spectral formulas" can achieve the effect set by the creator. Then, through the process of steps 430 to 470, these "spectral formulas" that have been determined to be effective can be added to the public cloud 6155 of the present invention to form a light environment "sharing platform."

[0078] In addition, in order to enable the multi-scene combination or multi-emotion combination of the "spectral formula" creation platform to have an effect, it may be necessary to pass through a specific lighting device 621 or a specific configuration diagram to achieve the best effect. Therefore, the present invention is further configured with a database of hardware services, as shown in step 420, and further configured with a database of software services, as shown in step 440. Among them, the database of hardware services and the database of software services also embed some management information when building "spectral formulas", including: installation or transportation of hardware devices, or including: providing software services such as space design, scene planning or interface settings required to build these "spectral formulas" through the database of software services. In addition, the database of hardware services and the database of software services can be configured on the creator 630 side, or in the cloud 610, and the present invention does not limit this. Obviously, the present invention is Figure 4In this embodiment, the process for creating various "spectral recipes" and the database of "spectral recipe" creation services are provided. The database of hardware and software services required for "spectral recipe" creation is also established on the light environment "sharing platform." It is important to note that the "sharing platform" ultimately established in step 470 is capable of providing effective "spectral recipes" for multiple light scenes and multiple mood light scenes. Subsequently, various commercial services and operations can be provided through this "sharing platform."

[0079] Please refer to Figure 5 , is a schematic diagram of the rhythmic lighting situation formed by the lamp group in a space of the present invention. Figure 5 As shown, the present invention configures a plurality of lamps in a space 500, including recessed lamps 521 embedded in the ceiling, ceiling lamps 523 protruding from the ceiling, and chandeliers 525 hanging from the ceiling. The light emitted by these three types of lamps directly illuminates the surface of an object (for example, a tabletop 510). The present invention refers to these lamp groups as direct (or horizontal) lighting lamp groups 520. In addition, the present invention also configures multiple other lamps in the same space 500, and the light emitted by these lamp groups first shines on the wall 501, and then the wall 501 reflects (reflecting) or diffuses (scattering) the light onto the surface 510 of the object. The present invention refers to these lamp groups as indirect (or vertical) lighting lamp groups 530. Among them, the indirect (or vertical) lighting lamp group 530 includes a ceiling lamp 531 that shines light on the wall 501 at an angle, and a chandelier or track-type chandelier 533 that shines light on the wall 501 at an angle. Obviously, the present invention configures multiple direct (or horizontal) lighting lamp groups 520 and multiple indirect (or vertical) lighting lamp groups 530 in the space 500, and controls the proportion of light emitted by these lighting lamp groups that shines on the surface 510 of the object to serve as the lighting scenario of the present invention. The light ratio of these lighting fixture groups can be controlled directly by using a light sensor (e.g., ambient light sensor 650) to provide lighting according to the scene ratio. In addition, the present invention can also use the controller 611 to control the light sensor 650 to provide lighting according to the scene ratio provided by the controller.

[0080] Next, please refer to Table 6, which illustrates an embodiment of a rhythmic lighting scenario database for indoor lighting provided by the present invention. As shown in Table 6, the rhythmic lighting scenario database is based on pre-defined time intervals, such as individual work and rest habits or work cycles, within the 24-hour daily daylight demand cycle. These time intervals map corresponding circadian rhythm changes or daylight variations to the rhythmic light parameters of indoor lighting, including equivalent melanopic lux (EML), circadian action factor (CAF), daylight lux (Lux), and color temperature variations, allowing users to quickly select the desired indoor rhythmic lighting. The EML is calculated by multiplying the vertical visual illuminance in a space by the ratio of the light source. Therefore, the EML value indicates the degree of stimulation of indoor light on the human circadian cycle and is used to quantify the biological effects of light on humans. Therefore, different daily activities are suited to different EML values. For example, a high EML is desirable during daytime hours (8:00 AM - 12:00 PM) or when concentration is required; conversely, a low EML is desirable during nighttime hours (10:00 PM - 7:00 AM) or when relaxation is desired. Furthermore, the CAF (Constant Irradiation Factor) is primarily calculated based on the illumination provided by a lighting fixture. It measures the level of stimulation the fixture provides to the human body. For example, a higher CAF value indicates a higher physiological stimulation, which can be energizing. A lower CAF value indicates a lower physiological stimulation, which can be relaxing. The obvious difference between CAF and EML is that the former measures the stimulation of the fixture's light spectrum, while the latter measures the level of stimulation that indoor light provides to the human circadian cycle. However, the two share the same principle: higher values ​​indicate a higher stimulation, which can boost energy; lower values ​​indicate a lower stimulation, which can promote relaxation.

[0081] Table 6

[0082]

[0083] According to the above, in the embodiment of the rhythmic lighting situation database of indoor lighting of the present invention, as shown in Table 6, the 24 hours of a day are divided into seven sections according to the physiological rhythm of the human body, namely deep sleep (22:00-07:00), waking up in the morning (07:00-08:00), morning (08:00-12:00), lunch break (12:00-13:30), afternoon (13:30-17:00), evening (17:00-21:00) and before going to bed (21:00-22:00). Afterwards, the corresponding indoor rhythmic lighting parameters of these sections are formulated to form a rhythmic lighting situation database of indoor lighting, among which EML, CAF and illuminance (lux) in Table 6 all refer to the threshold values ​​of the indoor rhythmic lighting parameters (that is, the minimum value to be reached). For example, the circadian rhythm between 22:00 and 07:00 is deep sleep. Therefore, the indoor circadian lighting parameters for this period should be set as low as possible. Therefore, the EML setting in the database should be less than 50, the CAF setting should reach 0.3, the illuminance (lux) setting should reach 100, and the color temperature (K) setting should be less than 3000. Another example: during the morning (08:00-12:00), since daylight gradually increases during this time and human activity and alertness are at their highest, the EML setting in the database should be greater than 200, the CAF setting should reach 0.86, the illuminance (lux) setting should be greater than 500, and the color temperature (K) setting should be greater than 5700.

[0084] Furthermore, to allow the human circadian rhythm to experience a more realistic lighting experience, the present invention specifically regulates the lighting of indoor lighting fixtures in a contextual manner, establishing rhythmic context parameters. As shown in the context column of Table 6, for example, the circadian rhythm between 22:00 and 07:00 is deep sleep. Therefore, the rhythmic context parameters for indoor lighting during this time are primarily provided by the indirect (or vertical) lighting fixture set 530. In a preferred embodiment of the present invention, the rhythmic context parameters are set so that the indirect (or vertical) lighting fixture set 530 provides 80-100% of the light, while the direct (or horizontal) lighting fixture set 520 provides 0-20% of the light. For example, during the morning hours (8:00-12:00), as daylight gradually increases, the indoor light is primarily provided by the indirect (or vertical) lighting fixture set 530. In a preferred embodiment of the present invention, the circadian scenario parameter setting is for the direct (or horizontal) lighting fixture set 520 to provide 80-100% of the light, while the indirect (or vertical) lighting fixture set 530 provides 0-20% of the light. For another example, during the evening hours (5:00-9:00 PM), as daylight has already set, the ambient light is uniform or soft. During this time, the indoor light is primarily provided by both the direct (or horizontal) lighting fixture set 520 and the indirect (or vertical) lighting fixture set 530. Therefore, the circadian scenario parameter setting is for both lighting fixture sets to provide 40-60% of the light. The above-mentioned direct (or horizontal) lighting fixture group 520 and indirect (or vertical) lighting fixture group 530 are as follows: Figure 5 shown.

[0085] Based on the above, in addition to the standard time divisions set out in Table 6, the present invention can also customize the time intervals according to the user's needs, as shown in Table 7 below. For example, according to the user's needs, a specific time interval is given as follows:

[0086] (1) Lighting scenario setting for three-shift 8-hour work

[0087] (2) Lighting setting for the refreshing morning hours from 06:30 to 08:30

[0088] (3) Lighting settings for the leisurely afternoon from 13:30 to 17:30

[0089] (4) Lighting settings for relaxing sleep from 20:00 to 23:00

[0090] Obviously, the present invention can provide different time divisions and corresponding rhythm parameter settings according to the needs or preferences of the user. Among them, the embodiment of the specific operation of the three-shift system in the first item above is described as follows. For example: if the user wants to set the lighting scenario setting for the 8-hour work of the three-shift system, it means that the 8-hour work period of the three-shift system (including: 8 am to 5 pm for the normal shift, 4 pm to 1 am the next morning for the afternoon shift, and 12 midnight to 9 am the next morning for the night shift) is expected to control the physiological state to be in "suppressing melatonin secretion and making people feel awake and excited, which is suitable for daytime working environment", then the work environment during the 8-hour work period of the three-shift system can be in the same lighting scenario.

[0091] Table 7

[0092]

[0093] It is particularly important to note that in the embodiments of the present invention, the rhythmic lighting parameters (including EML, CAF, daylight illuminance, and color temperature) set in the indoor lighting rhythmic lighting scenario database in Tables 6 and 7 are generated by direct (or horizontal) lighting fixture group 520 and indirect (or vertical) lighting fixture group 530 based on time. The rhythmic scenario parameters of the present invention are used to provide indoor lighting scenarios, enabling the indoor lighting system constructed in the present invention to provide a more comfortable and realistic rhythmic lighting effect. In the following embodiments, the rhythmic lighting parameters and rhythmic scenario parameters in Tables 6 and 7 will be collectively referred to as rhythmic parameters.

[0094] The present invention further provides a lighting system, such as Figure 6 As shown. This lighting system can be used to establish a multi-spectral rhythmic lighting database, and can also be a lighting system that provides multi-spectral rhythmic lighting scenario information. The lighting system 600 of the present invention includes: a cloud 610, a management control module 611, a lighting field end 620 of intelligent lighting, and a portable communication device 630. Among them, the device configured in the lighting field end 620 includes: a lamp group or a light-emitting device 621, at least one presence sensor (Occupancy Sensor) 660, at least one ambient light sensor (Ambient Light Sensor) 650, and a switch device 640. The lamp group 621 configured in the lighting field end 620 and the lamp group configured in the space 500 ( Figure 5) are the same as the multiple direct lighting fixture groups 520 and the multiple indirect lighting fixture groups 530 in the embodiment. Furthermore, a client can use a portable communication device 630 to download the "multi-spectral lighting device cloud database" from the cloud 610 via the internet. The client can then activate the fixture group 621 via the portable communication device 630 to establish a multi-spectral rhythmic lighting scenario database, thereby forming a lighting system with multi-spectral rhythmic lighting scenarios. In this embodiment, the client can be remote or local in the space 500. When the client is remote, the internet is an intelligent internet of things (AIoT) formed by the Internet of Things (IoT) and artificial intelligence (AI). When the client is local, the internet is a wireless communication protocol formed by a gateway, including Wi-Fi, ZeeBee, or Bluetooth. In this embodiment of the present invention, the lighting device field end 620 or space 500 can be a conference room, classroom, office, social venue, or factory, etc., providing multiple users with rhythmic lighting scenarios within the smart lighting field.

[0095] Next, please refer to Figure 7 , is a method of establishing a multi-spectral rhythmic lighting database according to the present invention. First, as shown in step 710, a portable communication device 630 can retrieve a "multi-spectral lighting device cloud database" from the cloud 610 via a network (e.g., AIoT). The "multi-spectral lighting device cloud database" can be the same as the database formed in step 411. Since step 411 has already constructed a light scene database comprising multiple multi-spectral lighting devices, once the lighting system 600 has obtained the light scene data of the multi-spectral lighting devices in step 710, it can drive the lamp set 621 (or multi-spectral lighting device) using the multi-spectral lighting parameters of the selected specific color temperature to provide lighting services at different color temperatures. The multi-spectral lighting parameters of the lamp set 621 include spectrum, light intensity, flicker rate, and color rendering index (Ra).

[0096] Next, the "rhythmic lighting scenario lighting" process begins, as shown in step 720. During this process, the lighting system 600's lamp assembly 621 provides a multispectral lighting service with a specific color temperature for the specific location via a portable communication device. Next, the application program (APP) in the portable communication device 630 activates or accesses the rhythmic lighting scenario database in Table 6, as shown in step 730. At this point, the lamp assembly 621 adjusts the set rhythmic parameters based on the actual time, ensuring that the lighting at the lighting field 620 achieves the set values ​​for equivalent blackout illuminance (EML), physiological stimulation value (CAF), daylight illuminance (Lux), and color temperature variation. In this embodiment of the present invention, the portable communication device 630 selects a 5700K multispectral recipe for the specific location from the "multispectral lighting device cloud database" in the cloud, and also obtains the rhythmic parameter settings for the physiological rhythm during the morning hours (08:00-12:00) in step 730. At this time, the portable communication device 630 can choose to directly control the lamp group 621 to execute the 5700K multi-spectral formula and rhythmic parameter lighting. In addition, the portable communication device 630 can also choose to transmit the 5700K multi-spectral formula and rhythmic parameter settings to the ambient light sensor 650, and the ambient light sensor 650 drives the lamp group 621 to illuminate.

[0097] Next, it is necessary to further confirm whether the lighting results of the illumination field end 620 can achieve the set rhythmic lighting lighting scenario, as shown in step 740. When confirming whether the illumination field end 620 can achieve the set rhythmic lighting lighting scenario, the equivalent blackout illuminance (EML) in the illumination field end 620 can be measured using a handheld spectrometer (not shown) or a full-beam integrating sphere (not shown), as shown in step 7410, and the physiological stimulation value (CAF), as shown in step 7420. The handheld spectrometer performs measurements within a specific range from the lamp assembly 621, while the full-beam integrating sphere performs measurements with the lamp assembly 621 placed in a specific space.

[0098] The software then calculates and records the equivalent blackout illuminance (EML) and the color temperature (CAF) values. Therefore, in this embodiment, the goal is to confirm whether the equivalent blackout illuminance (EML) is above 200 and whether the color temperature (CAF) is above 0.86. Furthermore, at the illumination field end 620, the ambient light sensor 650 provides information on whether the detected illuminance is greater than 500 Lux and the color temperature is greater than 5700K. Furthermore, in this embodiment of the present invention, the ambient light sensor 650 further controls the scene parameters. For example, the direct lighting fixture group 520 within the scene parameters provides 80-100% light, while the indirect lighting fixture group 530 provides 0-20% light. These measured and detected values ​​are transmitted back to the portable communication device 630 or the management and control module 611.

[0099] Next, as shown in step 750, a determination is made as to whether the lighting at the lighting field end 620 or the space 500 meets the requirements of the rhythmic lighting scenario. This determination process can be performed by the portable communication device 630 or the management and control module 611. For example, if the portable communication device 630 or the management and control module 611 determines that the rhythmic parameters of the rhythmic lighting scenario at the lighting field end 620 or the space 500 have reached the set values, then, as shown in step 770, the portable communication device 630 or the management and control module 611 in the lighting system 600 transmits the current multispectral lighting parameters and rhythmic parameters to the cloud 610 or the switch device 640 to establish a multispectral rhythmic lighting scenario database. Obviously, the parameter information recorded in the multi-spectral rhythmic lighting scenario database established in step 770 includes multi-spectral lighting parameters such as spectrum, light intensity, flicker rate and color rendering index (Ra) of the lamp group (for example, LED lamps), as well as various rhythmic parameters in Table 6 or Table 7, among which the rhythmic parameters include rhythmic lighting parameters and rhythmic scenario parameters.

[0100] When the portable communication device 630 or the management control module 611 determines that the multi-spectral lighting parameters or rhythmic parameters of the rhythmic lighting scenario of the lighting field end 620 or the space 500 have not reached the set value, it will return to step 720, and the ambient light sensor 650 will adjust the lighting parameters of the lamp group 621 or adjust the lighting ratio of the scenario parameters. Then, the portable communication device 630 or the management control module 611 will determine whether the multi-spectral lighting parameters or rhythmic parameters of the rhythmic lighting scenario of the lighting field end 620 or the space 500 have reached the set value. This process will be executed until each time-divided physiological rhythm in Table 6 or Table 7 reaches the set value and a complete multi-spectral rhythmic lighting scenario database has been established. Only then can the lighting system 600 fully confirm that the lighting field end 620 or the space 500 can provide effective rhythmic parameters of the rhythmic lighting scenario. It should be further emphasized that when using devices such as handheld spectrometers or full-beam integrating spheres to measure rhythmic lighting parameters, testing space, time, and costs are required to complete the measurement. Therefore, it is necessary to distinguish the corresponding physiological rhythm cycles for the 24 hours of each day, pre-measure the lighting environment parameters of various rhythmic lighting, and establish a rhythmic lighting database. This allows the method of constructing a multi-spectral rhythmic lighting scenario database of the present invention to achieve commercial application through the collection of massive data and then through AI learning. In a preferred embodiment of the present invention, the adjustment of rhythmic parameters is basically based on controlling the rhythmic scenario parameters of the direct lighting fixture group 520 and the indirect lighting fixture group 530 as the main adjustment method. This is because the lighting field end 620 may be affected by other surrounding light sources.

[0101] After confirming that the lighting field end 620 or the space 500 can provide the multi-spectral lighting parameters and rhythmic parameters of an effective rhythmic lighting scenario, the present invention can provide a lighting field end 620 and a lamp set 621 of an effective rhythmic lighting scenario. Next, the present invention provides a method for establishing a database of the correlation between multi-spectral rhythmic lighting and psychological stress, such as Figure 8 As shown. Figure 8 This method can be used to determine the status of the person being illuminated by an effective rhythmic lighting situation through indicators of psychological stress.

[0102] First, as shown in step 810, a portable communication device 630 can retrieve a "multi-spectral rhythmic lighting scenario database" from the cloud 610 via a network (e.g., AIoT). Subsequently, a specific circadian rhythm parameter for a specific time can be selected via the portable communication device 630. The app on the portable communication device 630 can then be used to directly control the lighting set 621 to provide the circadian rhythm parameter settings for that time. Alternatively, the portable communication device 630 can provide the retrieved "multi-spectral rhythmic lighting scenario database" to the ambient light sensor 650, which then controls the lighting to provide the circadian rhythm parameter settings for that time. The parameter information recorded in the multi-spectral rhythmic lighting scenario database includes multi-spectral lighting parameters such as spectrum, light intensity, flicker rate, and color rendering index (Ra) of the lighting set 621 (e.g., LED lamps), as well as various rhythmic parameters listed in Table 6 or Table 7. Rhythmic parameters include rhythmic lighting parameters and rhythmic scenario parameters.

[0103] Next, as shown in step 820, "activating rhythmic lighting scenario lighting" involves using the application program (APP) in the portable communication device 630 to activate the lamp assembly 621 to illuminate according to the multispectral lighting parameters and rhythmic parameters set according to the actual time, so that the lighting at the lighting field end 620 or space 500 reaches the set values ​​of equivalent blackout illuminance (EML), physiological stimulation value (CAF), daylight illuminance (Lux), and color temperature variation. In an embodiment of the present invention, the portable communication device 630 can select the rhythmic parameter settings for the physiological rhythm in the morning (08:00-12:00) from the "Multispectral Rhythmic Lighting Scenario Database" in the cloud 610 via a network (e.g., AIoT). At this time, the portable communication device 630 can choose to directly control the lamp assembly 621 to implement the physiological rhythm parameter lighting. Furthermore, the portable communication device 630 can also choose to transmit the physiological rhythm parameter settings to the ambient light sensor 650, which then drives the lamp assembly 621 to illuminate. Obviously, the present invention is not limited to whether the portable communication device 630 or the ambient light sensor 650 drives the lamp assembly 621 to illuminate.

[0104] Next, as shown in step 840, the present invention can quickly detect whether the multispectral lighting parameters and rhythmic parameters of the illumination field end 620 have reached the set values ​​through the light sensing device on the ambient light sensor 650. It should be noted that the rapid detection of the ambient light sensor 650 described in this embodiment is due to the fact that the ambient light sensor 650 detects the multispectral lighting parameters and rhythmic parameters in a 10-second cycle and transmits the detection results to the portable communication device 630 or the management and control module 611. Therefore, it can quickly determine whether the multispectral lighting parameters and rhythmic parameters of the illumination field end 620 or the space 500 have reached the set values. Therefore, this embodiment can be operated commercially.

[0105] Next, as shown in step 850, when the portable communication device 630 or the management and control module 611 determines that both the multispectral lighting parameters and the circadian parameters have reached the set values, the process proceeds to step 860. After the user receives the lighting for a period of time, the process proceeds to step 870 where a cortisol level test is performed on the user to determine changes in the stress hormone cortisol and confirm that the user has met the lighting requirements of the rhythmic lighting scenario. For example, after the user receives the multispectral lighting parameters and circadian parameters for a certain period of time in the morning (8:00-12:00), the process proceeds to step 870 where a blood or saliva sample is immediately taken to measure the level of bioactive stress hormones in the user's blood or saliva. In this embodiment of the present invention, the test primarily focuses on cortisol. For example, if the user's cortisol level is between 3.7 and 19.4, it indicates that the user has met the lighting requirements of the rhythmic lighting scenario. In this embodiment of the present invention, the user's cortisol index value is tested to determine changes in the stress hormone cortisol, confirming that the user has met the lighting requirements of the rhythmic lighting scenario. In other words, it confirms that the change in the user's cortisol index value, the stress hormone, is within the set range when the user meets the rhythmic lighting requirements.

[0106] Finally, the present invention, through step 880, records the subject's cortisol test value in a database related to rhythmic lighting and psychological stress. This allows the present invention, through the method of constructing a multispectral rhythmic lighting scenario database, to collect massive amounts of data, and then through AI learning, to more accurately determine whether the subject has met the lighting requirements of the rhythmic lighting scenario based on changes in the subject's cortisol index value, thereby achieving commercial application. Obviously, the information recorded in the multispectral rhythmic lighting scenario database established in step 880 includes multispectral lighting parameters such as the spectrum, light intensity, flicker rate, and color rendering index (Ra) of the lamp group (e.g., LED lamp), the various rhythmic parameters and cortisol index values ​​listed in Table 6 or Table 7, etc.

[0107] Next, the present invention further provides a simple lighting method for multi-spectral rhythmic lighting scenarios, such as Figure 9 First, as shown in step 910, it is necessary to confirm that the lighting field end 620 or the space 500 can provide multispectral lighting parameters and various rhythmic parameters for an effective rhythmic lighting scenario. The portable communication device 630 retrieves the "multispectral rhythmic lighting scenario database" from the cloud 610 via a network (e.g., AIoT), so that the present invention can provide a lighting field end 620 and a lamp group 621 for an effective rhythmic lighting scenario. The parameter information recorded in the above-mentioned multispectral rhythmic lighting scenario database includes: multispectral lighting parameters such as spectrum, light intensity, flicker rate, and color rendering index (Ra) of the lamp group 621 (e.g., LED lamps), as well as various rhythmic parameters in Table 6 or Table 7, etc., wherein the rhythmic parameters include: rhythmic lighting parameters and rhythmic scenario parameters.

[0108] Next, in step 920, the portable communication device 630 app is used to select and activate the lighting set 621 to provide the circadian parameter settings at the specified time. Of course, in step 920, the present invention can also select to provide the obtained "multi-spectral rhythmic lighting scenario database" to the ambient light sensor 650 through the portable communication device 630, and the ambient light sensor 650 can then determine the multi-spectral lighting parameters and the timing of the circadian lighting. The present invention is not limited to this.

[0109] Next, as shown in step 930, the user is exposed to light for a period of time. Next, step 940 determines whether the user's cortisol index value is within a set range. For example, after the user receives multispectral lighting parameters and rhythmic parameters for a certain period of time in the morning (8:00-12:00), blood or saliva samples are collected and the levels of bioactive stress hormones in the blood or saliva are tested. In this embodiment of the present invention, the test primarily targets cortisol. For example, if the user's cortisol value is between 3.7 and 19.4, it indicates that the user has met the lighting requirements of the rhythmic lighting scenario. In this embodiment of the present invention, the cortisol test is used to determine changes in the stress hormone cortisol and confirm that the user has met the lighting requirements of the rhythmic lighting scenario, as shown in step 950.

[0110] Next, as shown in step 950, after confirming that the user has met the lighting requirements of the rhythmic lighting scenario, step 960 is used to record the index value of the adrenal cortisol test of the light user into the rhythmic lighting and psychological stress correlation database to form a "multi-spectral rhythmic lighting scenario cloud database."

[0111] If it is determined that the user does not meet the lighting requirements of the rhythmic lighting scenario, for example, if the user's cortisol index value is not within the index value range listed in Table 6 or Table 7, the process returns to step 920. After selecting new multispectral lighting parameters through the app of the portable communication device 630, the portable communication device 630 or the ambient light sensor 650 can drive the lamp assembly 621 to illuminate the user with the new multispectral lighting parameters and the rhythmic parameters at the specified time, as shown in step 930. After the user has been illuminated for a period of time, the process proceeds to step 940 to determine whether the user's cortisol index value is within the set range. Obviously, steps 920 to 940 can be repeated until it is determined that the cortisol index value of the person being illuminated is within the set range. Then, as shown in steps 950 and 960, the index value of the cortisol test of the person being illuminated is recorded in the rhythmic lighting and psychological stress correlation database to form a "multi-spectral rhythmic lighting scenario cloud database."

[0112] By building the aforementioned "multi-spectral rhythmic lighting scenario cloud database," the present invention can collect massive amounts of data and, through AI learning, more accurately determine whether a user has met the lighting requirements of a rhythmic lighting scenario based on changes in their cortisol index, thereby achieving commercial application. Clearly, the information recorded in the multi-spectral rhythmic lighting scenario database established in step 960 includes multi-spectral lighting parameters such as the spectrum, light intensity, flicker rate, and color rendering index (Ra) of a lamp group (e.g., an LED lamp), the various rhythmic parameters listed in Table 6 or Table 7, and the cortisol index.

[0113] Finally, we must once again emphasize that the above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of the present invention. Furthermore, the above description should be readily apparent to those skilled in the relevant art and should be readily applicable. Therefore, any equivalent changes or modifications that do not depart from the concepts disclosed herein are intended to be encompassed by the claims of the present invention.

Claims

1. A lighting method with a multi-spectral rhythmic lighting scenario is to configure a light-emitting device and a lighting system in a space, wherein: The lighting system is composed of a portable communication device, a management and control module, a cloud, and an ambient light sensor, and is characterized in that the lighting method includes: Retrieving a multi-spectral rhythmic lighting scenario database by downloading the multi-spectral rhythmic lighting scenario database from a cloud via the Internet by the portable communication device; Activating the rhythmic lighting scenario involves the portable communication device providing a multi-spectral lighting service with a color temperature at a specific geographic location or at a specific time, and selecting multi-spectral lighting parameters and rhythmic parameters for the specific geographic location or the location within the specific geographic location at a specific time from the multi-spectral rhythmic lighting scenario database to drive the light-emitting device to perform lighting for the target; Performing an adrenal cortisol test by testing the blood or saliva of the light-treated person to confirm that the change in the light-treated person's adrenal cortisol index value is within a set range when the light-treated person meets the conditions of rhythmic light treatment requirements, thereby obtaining the light-treated person's psychological stress index value, wherein the psychological stress index value is the adrenal cortisol index value; and A database of correlation between multi-spectral rhythmic lighting situations and psychological stress is established, and the rhythmic parameters and the psychological stress index values ​​are transmitted to the cloud by a portable communication device or a management control module.

2. A lighting method with a multi-spectral rhythmic lighting scenario is to configure a light-emitting device and a lighting system in a space, wherein: The lighting system is composed of a portable communication device, a management and control module, a cloud, and an ambient light sensor, and is characterized in that the lighting method includes: Retrieving a multi-spectral rhythmic lighting scenario database by downloading the multi-spectral rhythmic lighting scenario database from a cloud via the Internet by the portable communication device; Activating the rhythmic lighting scenario involves the portable communication device providing a multispectral lighting service with a color temperature at a specific geographic location or at a specific time, selecting multispectral lighting parameters and rhythmic parameters for the specific geographic location or the location where the specific geographic location is located at a specific time from the multispectral rhythmic lighting scenario database, transmitting the multispectral lighting parameters and rhythmic parameters to the ambient light sensor, and then the ambient light sensor driving the light-emitting device to illuminate the target. The adrenal cortisol test is performed by sampling and testing the blood or saliva of the light-treated person to confirm that the change of the adrenal cortisol index value of the light-treated person is within a set range when the light-treated person meets the rhythmic light treatment requirements, so as to obtain the psychological stress index value of the light-treated person, wherein the psychological stress index value is the adrenal cortisol index value; and A database of correlation between multi-spectral rhythmic lighting situations and psychological stress is established, and the rhythmic parameters and the psychological stress index values ​​are transmitted to the cloud by a portable communication device or a management control module.

3. The lighting method with multi-spectral rhythmic lighting scenario as claimed in claim 1 or 2, characterized in that :The rhythm parameters include: rhythm lighting parameters and rhythm situation parameters.

4. The lighting method with multi-spectral rhythmic lighting scenario as claimed in claim 1 or 2, characterized in that :The multispectral lighting parameters are the spectrum, light intensity, flicker rate and color rendering of the light-emitting device.

5. The lighting method with multi-spectral rhythmic lighting scenario as claimed in claim 3, characterized in that :The rhythmic lighting parameters include: equivalent black vision illuminance, physiological stimulation value, sunlight illuminance and color temperature change.

6. The lighting method with multi-spectral rhythmic lighting scenario as claimed in claim 3, characterized in that :The rhythmic situation parameters are composed of the light from the direct lighting device and the indirect lighting device.

7. The lighting method with multi-spectral rhythmic lighting scenario as claimed in claim 6, characterized in that The direct lighting device is composed of recessed lamps, pendant lamps and ceiling lamps.

8. The lighting method with multi-spectral rhythmic lighting scenario as claimed in claim 6, characterized in that The indirect lighting is the light from the lamp reflected by the wall.

9. The lighting method with multi-spectral rhythmic lighting scenario as claimed in claim 1 or 2, characterized in that : Establishing the multi-spectral rhythmic lighting situation and psychological stress correlation database includes: the psychological stress index value and the rhythm parameter.

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