An intelligent human factor lighting method

Abstract

The present invention provides a method for grading physiological emotional responses, which is a method for grading physiological emotional responses by establishing an electroencephalogram through a human-centered lighting system and an electroencephalograph. Obtain enhanced spectra for different emotions, where the enhanced spectra are specific color temperatures that have a multiplicative effect on specific physiological emotional responses identified by fMRI. Induce specific physiological emotions in the tester by having the tester wear an electroencephalograph and stimulating the tester with elements having specific emotional stimuli for specific physiological emotions; perform a lighting procedure, activate the human-centered lighting system to perform lighting of different color temperatures on the tester, record and store electroencephalogram files after lighting of different color temperatures under specific emotions; classify the electroencephalogram files of specific emotions; and establish an electroencephalogram grading database.

Description

Technical Field

[0001] The present invention provides an intelligent human factor lighting method, which relates to a method for grading physiological and emotional responses, and particularly to a method for grading physiological and emotional responses by establishing an electroencephalogram through a human factor lighting system and an electroencephalograph. Background Art

[0002] Humans are animals with changeable emotions and will have different emotional responses according to their personal mental states. For example, excitement, amusement, anger, disgust, fear, happiness, sadness, serenity or neutrality, etc. When negative emotions (such as anger, disgust, fear) cannot be relieved in time, they will cause psychological harm or trauma to the human body and finally develop into mental diseases. Therefore, how to timely provide an emotion relief, soothing or treatment system that meets the needs of users has a broad business opportunity in today's highly competitive and stressful society.

[0003] In modern medical equipment, it has been possible to measure the hemodynamic changes caused by neuronal activities through a functional magnetic resonance imaging system (fMRI). Due to the non-invasiveness of fMRI and its relatively low radiation exposure, fMRI is currently mainly used in the research of the brain or spinal cord of humans and animals. At the same time, electroencephalogram (EEG) can also be used to examine the tester. By stimulating emotions in the same way, different emotional responses can be observed. For example, it can be seen that the electroencephalogram patterns of fear and happiness are significantly different. Among them, when observing the responses of a certain emotion under fMRI and electroencephalogram (EEG), for example, in a happy mood (which can be induced through pictures and combined with facial emotion recognition), the blood oxygenation level-dependent (BOLD) response is observed by fMRI, and it is found that there is a significant response in the medial prefrontal cortex (Mpfc) compared to the corresponding emotions (anger and fear). Conversely, for example, in the moods of fear and anger, when observing the blood oxygenation level-dependent (BOLD) response by fMRI, a significant response is found in the amygdala region, indicating that the two types of emotions have different response regions in the brain. Therefore, the current emotional state of the tester can be clearly determined by the blood oxygenation level-dependent (BOLD) response in different regions of the brain. In addition, if the electroencephalogram of the electroencephalogram (EEG) is used to examine and measure the tester, and emotions are stimulated in the same way, it can be seen that the electroencephalogram patterns of fear and happiness are significantly different. Therefore, the current emotional state of the tester can also be judged by the electroencephalogram patterns of different responses. According to the above, for the functional magnetic resonance imaging system (fMRI), emotions are distinguished by different blood oxygenation level-dependent (BOLD) responses, and for the electroencephalogram (EEG), emotions are distinguished by different electroencephalogram patterns. Obviously, the methods and recorded contents used by the two to judge the emotions of the tester are completely different. Therefore, in terms of current technology, the electroencephalogram pattern of the electroencephalogram (EEG) cannot replace the blood oxygenation level-dependent (BOLD) response of the functional magnetic resonance imaging system (fMRI) for the same emotional test result of the same tester.

[0004] The above discussion on the use of functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG) for emotion judgment is because the fMRI system is very expensive and large, so it cannot be used in the human factor lighting commercial system and its method. Similarly, if only the brain wave pattern of the electroencephalogram (EEG) is used to judge the emotions of the test subjects, it may be encountered that different test subjects may have different brain wave patterns for different emotions. Therefore, at present, it is impossible to construct a commercial human factor lighting method and its system by using only the blood oxygenation level-dependent (BOLD) response of the functional magnetic resonance imaging (fMRI) system or only the brain wave pattern of the electroencephalogram (EEG) through the editing of the light formula. Summary of the Invention

[0005] According to the above description, the present invention provides an application of using the brain wave pattern of the electroencephalogram (EEG) as a human factor lighting in a commercial system after establishing the correlation between the brain wave pattern of the electroencephalogram (EEG) and the blood oxygenation level-dependent (BOLD) of the functional magnetic resonance imaging (fMRI) system.

[0006] The present invention first provides a method for grading the physiological emotion response of an electroencephalogram, which is to establish a method for grading the physiological emotion response of an electroencephalogram through a human factor lighting system and an electroencephalogram, including:

[0007] Obtain the enhanced spectra of different emotions, where the enhanced spectra are specific color temperatures that have a multiplicative effect on the specific physiological emotion responses identified by fMRI; induce specific physiological emotions in the test subjects by having the test subjects wear the electroencephalogram and giving elements with specific emotional stimuli to the test subjects for specific physiological emotion stimulation; perform a lighting procedure, which is to start the human factor lighting system to irradiate the test subjects with different color temperatures after inducing specific physiological emotions in the test subjects, record and store the electroencephalogram files after irradiation with different color temperatures under specific emotions; classify the electroencephalogram files of specific emotions, which is to classify the electroencephalogram files of specific emotions by using the learning method of artificial intelligence based on the similarity between the enhanced spectra of specific color temperatures and the electroencephalogram files of specific emotions; establish an electroencephalogram grading database, which is to establish an electroencephalogram grading database according to the similarity ranking of electroencephalogram files of various specific color temperatures.

[0008] The present invention then further provides a method for grading the physiological emotion response of an electroencephalogram, which is established through the cloud, a human factor lighting system and an electroencephalogram, including:

[0009] Obtain enhanced spectra for different emotions, where the enhanced spectra are specific color temperatures that have a multiplicative effect on specific physiological emotional responses identified by fMRI; induce specific physiological emotions in the tester by having the tester wear the electroencephalograph and subjecting the tester to specific physiological emotional stimuli with elements having specific emotional stimuli; perform a lighting procedure, which is to, after inducing specific physiological emotions in the tester, activate the human-centered lighting system to perform lighting of different color temperatures on the tester, record and store the electroencephalogram file after lighting of different color temperatures under specific emotions; establish an electroencephalogram classification and grading database, which is to classify electroencephalogram files of specific emotions by similarity through an artificial intelligence learning method for the enhanced spectra of specific color temperatures and electroencephalogram files of specific emotions, and establish an electroencephalogram grading database by sorting according to similarity, and establish this grading database in the memory module on the cloud; determine whether the lighting parameters for specific emotions are effective by having the cloud give grades to the electroencephalogram grading database by scores and using the score levels as the judgment basis. Among them, when inducing specific physiological emotions in the tester and activating the human-centered lighting system to perform lighting of a specific color temperature on the tester, if the score of the electroencephalogram grading of the tester reaches the standard, it means that the hyperemia reaction in the tester's brain is sufficient, and then store the lighting parameters of the specific color temperature at this time.

[0010] After establishing the artificial intelligence model of the "grading method of electroencephalogram for physiological emotional response", after activating the human-centered lighting system, the present invention can infer the physiological emotional changes of the brain image of a new tester only by observing the interpretation result of the electroencephalogram file of the electroencephalograph. Therefore, it is possible to infer the physiological emotional changes of the brain image according to the artificial intelligence model of the "human-centered lighting parameter database" without the need to use an expensive fMRI system. This enables the promotion and use in commercial applications through the human-centered lighting system. Brief Description of the Drawings

[0011] Figure 1a is the original data collection framework of the human-centered lighting of the present invention for physiological emotional response;

[0012] Figure 1b is the original data collection flow chart of the human-centered lighting of the present invention for physiological emotional response;

[0013] Figure 1c is the judgment process of the human-centered lighting of the present invention for specific physiological emotional response;

[0014] Figure 2a is the method of the present invention for establishing the electroencephalogram of human-centered lighting for physiological emotional response;

[0015] Figure 2b is the lighting database for constructing effective human-centered lighting by the user of the present invention;

[0016] Figure 3 It is the system architecture diagram of the intelligent human factor lighting system of the present invention;

[0017] Figure 4 It is a method for constructing a human factor lighting environment sharing platform of the present invention;

[0018] Figure 5a It is an automatically adjustable intelligent human factor lighting method of the present invention;

[0019] Figure 5b It is the editing process of the context-based dynamic spectrum editing platform of the present invention;

[0020] Figure 5c It is a context-based dynamic spectrum program with a conference function of the present invention; and

[0021] Figure 6 It is the intelligent human factor lighting system applied to commercial operation of the present invention. Detailed implementation manners

[0022] In the following description of the present invention, for the functional magnetic resonance imaging system, it is abbreviated as "fMRI system", and the electroencephalograph is abbreviated as "EEG", and the blood oxygenation level-dependent contrast is abbreviated as "BOLD". In addition, in the embodiments of the color temperature test of the present invention, the test is carried out in units of every 100K. However, in order to avoid overly lengthy explanations, in the following description, the so-called specific emotions refer to excitement or excitement, happiness, pleasure, etc., and 3000K, 4000K and 5700K are used as examples of color temperature tests to illustrate the corresponding specific emotional responses. Therefore, the present invention cannot be limited to the embodiments of these three color temperatures. At the same time, in order to enable those skilled in the technical field to which the present invention pertains to fully understand the technical content, relevant implementation manners and their embodiments are provided herein for explanation. In addition, when reading the implementation manners provided by the present invention, please refer to the drawings and the following description content at the same time. Among them, the shapes and relative sizes of the components in the drawings are only used to assist in understanding the content of this implementation manner, and are not used to limit the shapes and relative sizes of the components. This is stated in advance.

[0023] The present invention uses an fMRI system and a physiological signal measurement method to understand the corresponding relationship between spectrum and emotion in the brain, and formulates a preliminary mechanism for using light to affect human physiological and psychological responses. Since the brain images of the fMRI system can determine which part of the human brain has a hyperemic response when stimulated by light, and can also record the BOLD response. This BOLD response of brain hyperemia is also called the "increase in blood oxygenation-dependent response". Therefore, the present invention can accurately and objectively infer the physiological and emotional changes of the test subject based on the brain hyperemic image data and the "increase in blood oxygenation-dependent response" response of the fMRI system under various emotions. Based on the physiological and emotional states confirmed by the fMRI system, the electroencephalogram (EEG) is further used to record the changes in brain waves to establish the correlation between the two, with the expectation of using the changes in brain waves recorded by the electroencephalogram (EEG) to replace the emotion judgment of the fMRI system.

[0024] Therefore, the main objective of the present invention is to enable the test subject to record the BOLD response of the test subject to a specific emotion through light irradiation during the test of a specific emotion using the fMRI system, so as to screen out which specific "effective color temperatures" can have a multiplicative effect on the specific emotion, and use the color temperature of this light irradiation as the "effective color temperature" corresponding to the specific emotion. Subsequently, the test subject is irradiated with the "effective color temperature", and the electroencephalogram (EEG) is used to record the brain wave pattern under the stimulation of the "effective color temperature". After establishing the correlation between the specific brain wave pattern of the electroencephalogram (EEG) and the specific BOLD response, the specific brain wave pattern of the electroencephalogram (EEG) can be used to assist in judging the emotional changes of the user, so as to construct a commercially operable human factor lighting system and its method, which can solve the problem of having to use an expensive fMRI system to implement the human factor lighting system, reduce the operating cost, and further meet the customized service requirements.

[0025] First, please refer to Figure 1a , which is the original data collection framework of the human factor lighting of the present invention for physiological and emotional responses. As Figure 1a shown, the intelligent human factor lighting system 100 is activated in an environment (such as a test space) that has been configured with various adjustable lighting modules, and provides light signal illumination parameters such as changeable spectrum, light intensity, flicker rate, and color temperature. The present invention uses the compatible image interaction platform 110 (fMRI compatible image interaction platform) formed by the fMRI system for different target emotions, uses voice and image emotion guidance, and simultaneously combines with a specific effective spectrum for 40 seconds of stimulation to observe the change area of the blood oxygen content in the test subject's brain, so as to verify whether the "effective color temperature" can significantly induce the emotional response of the test subject, and the details are as follows.

[0026] Next, please refer to Figure 1b and Figure 1c , where Figure 1b is the flowchart for collecting the original data of the human factor light irradiation on physiological and emotional responses in the present invention, and Figure 1c is the judgment process of the human factor light irradiation on specific physiological and emotional responses. As shown in step 1100 in Figure 1b , each tester is already located on the compatible image interaction platform 110. Next, each tester is guided to be stimulated with various emotions through known pictures. After that, as shown in step 1200, the BOLD responses of various emotions in the brain of the tester after being stimulated by the pictures are recorded through the compatible image interaction platform 110. Then, as shown in step 1300, visual stimulation is performed on the tester by providing spectra with different color temperature parameters through light irradiation. For example: using LED lamps with electronic dimmers to provide spectra with different color temperature parameters. In the embodiment of the present invention, visual stimulations of 9 different color temperatures such as 2700K, 3000K, 3500K, 4000K, 4500K, 5000K, 5500K, 6000K, and 6500K are provided. Among them, after each 40-second effective light irradiation and stimulation, it is possible to choose to apply 1 minute of ineffective light source illumination (full-spectrum non-flickering white light) to the tester to achieve the purpose of emotional relaxation. Further, it is also possible to choose to give the tester 40 seconds of reverse light stimulation to observe whether the response in the area that had a response during the original effective light stimulation decreases. And in the embodiment of the present invention, after the compatible image interaction platform 110 has recorded the BOLD response of a certain specific emotion in the brain of the tester after being stimulated by the pictures, spectra with different color temperature parameters are respectively provided to perform visual stimulation on the tester. As shown in step 1310 in Figure 1c , to provide a spectrum with a color temperature of 3000K. Next, as shown in step 1320, to provide a spectrum with a color temperature of 4000K. Finally, as shown in step 1330, to provide a spectrum with a color temperature of 5700K to perform visual stimulation on the tester.

[0027] Next, as shown in step 1400, the BOLD responses of various emotions in the brain of the tester after being stimulated by light irradiation are recorded through the compatible image interaction platform 110. In the embodiment of the present invention, after the tester is stimulated by light with different color temperature parameters, the compatible image interaction platform 110 sequentially records the BOLD response results of the areas with emotional responses in the limbic system of the tester's corresponding brain. Among them, the parts of the limbic system triggered by different emotions are different, and the above-mentioned limbic system with brain region emotional responses is as shown in Table 1 below.

[0028] Table 1

[0029]

[0030]

[0031] The compatible image interaction platform 110 records the reaction results of BOLD in specific brain regions. These reaction results are judged by calculating the area size of the limbic system with BOLD emotional reactions in the brain region. For example, when the area with BOLD emotional reactions is larger, it represents a stronger specific physiological emotional reaction. In the embodiments of the present invention, as Figure 1c shown in step 1410, it is used to record the reaction results of BOLD after being irradiated by a spectrum with a color temperature of 3000K. Then, as shown in step 1420, it is used to record the reaction results of BOLD after being irradiated by a spectrum with a color temperature of 4000K. Finally, as shown in step 1430, it is used to record the reaction results of BOLD after being irradiated by a spectrum with a color temperature of 5700K. Among them, after the lighting program is induced by the excitement emotion of the tester, the reaction results of BOLD in specific brain regions recorded by the compatible image interaction platform 110 are shown in Table 2.

[0032] Table 2

[0033]

[0034] Among them, after the lighting program is induced by the happiness emotion of the tester, the reaction results of BOLD in specific brain regions recorded by the compatible image interaction platform 110 are shown in Table 3.

[0035] Table 3

[0036]

[0037] Among them, after the lighting program is induced by the amusement emotion of the tester, the reaction results of BOLD in specific brain regions recorded by the compatible image interaction platform 110 are shown in Table 4.

[0038] Table 4

[0039]

[0040] After that, as shown in step 1500, the results of the BOLD-dependent responses that can increase specific emotions at a specific color temperature are screened out by illumination, and this specific color temperature is called the "effective color temperature". In this embodiment, the BOLD response results of the regions with emotional responses in the limbic system of the tester's corresponding brain are recorded to summarize the stimulating effect of the color temperature on the brain, as shown in Tables 1 to 3 above. For the results of the BOLD brain region-dependent responses that can increase specific emotions at a specific color temperature, the reaction effects of those specific color temperatures that can reach the maximum reaction value (i.e., the maximum reaction area value of BOLD) are calculated respectively.

[0041] As shown in step 1510, when the tester has recorded the induction of excitement emotion on the compatible image interaction platform 110 and after completing the illumination program, the maximum reaction value is calculated. For example, according to the record in Table 2, subtract the total score of 4000K (226) from the total score of 3000K (577), and 351 is obtained. Then, subtract the total score of 5700K (-105) from the total score of 3000K (577), and 682 is obtained. The total reaction value under the illumination of 3000K after the induction of excitement emotion is 1033.

[0042] Next, as Figure 1c in step 1520, when the tester has recorded the induction of excitement emotion on the compatible image interaction platform 110 and after completing the illumination program, the maximum reaction value is calculated. For example, according to the record in Table 2, subtract the total score of 3000K (577) from the total score of 4000K (226), and -351 is obtained. Then, subtract the total score of 5700K (-105) from the total score of 4000K (266), and 371 is obtained.

[0043] Then, as Figure 1c in step 1530, when the tester has recorded the induction of excitement emotion on the compatible image interaction platform 110 and completed the illumination program, the maximum reaction value is calculated. For example, according to the record in Table 2, subtract the total score of 3000K (577) from the total score of 5700K (-105), and -682 is obtained. Then, subtract the total score of 4000K (-105) from the total score of 5700K (-105), and 371 is obtained.

[0044] After the above calculations, after the excitement emotion is induced, an illuminance of 3000K can make the excitement emotion reach the maximum response value. That is, an illuminance of 3000K can make the excitement emotion obtain a more obvious additive effect (that is, relative to the total calculated scores of illuminances of 4000K and 5700K, the total calculated score of 3000K illuminance is the highest at 1033), so the illuminance of 3000K is used as the "effective color temperature" for the excitement emotion. For other emotions, such as the "effective color temperatures" of happiness and pleasure, different "effective color temperatures" can be obtained through the calculation results from step 1510 to step 1530 as shown below in Table 5.

[0045] Table 5

[0046] Physiological emotion Effective color temperature Excitement 3000K Happiness 4000K Amusement 5700K

[0047] Next, according to the statistical results in Table 5, the effective color temperature can be used as the result of a specific physiological emotion-dependent response, and this effective color temperature can be regarded as the "enhanced spectrum" of the "blood oxygenation level-dependent (BOLD)" response of fMRI to a certain emotion. For example: an effective color temperature of 3000K can represent the "enhanced spectrum" of the fMRI system in the "excitement" emotion. For example: an effective color temperature of 4000K can represent the "enhanced spectrum" of the fMRI system in the "happiness" emotion. For example: an effective color temperature of 5700K can represent the "enhanced spectrum" of the fMRI system in the "pleasure" emotion.

[0048] Finally, as shown in step 1600, an "enhanced spectrum" database corresponding to the effects of specific emotions can be established in the fMRI system. By stimulating the tester with the above human factor lighting parameters and observing and recording the BOLD response of the tester's brain when it is stimulated by light through the fMRI system, at the same time, recording the fMRI brain images to judge which part of the human brain has a multiplicative response of "increased blood oxygenation level dependence" when stimulated by light, so that a specific effective color temperature can be regarded as the "enhanced spectrum" of the "blood oxygenation level dependence" of fMRI on a certain specific emotion. Obviously, the present invention objectively infers the "enhanced spectrum" of the tester under a specific physiological emotion response based on the statistical results in Table 5 above, where the BOLD of a specific "effective color temperature" has a multiplicative response to a specific emotion, and uses this "enhanced spectrum" as evidence of the physiological emotion response that produces the strongest multiplicative effect for specific emotions (including: excitement, happiness, pleasure, anger, disgust, fear, sadness, calm or neutral, etc.).

[0049] It should be emphasized that the present invention is in Figure 1b and Figure 1cIn the entire implementation process, after conducting complete tests on 100 testers for multiple specific emotions, the statistical results in Table 5 were obtained accordingly. For example, in terms of the emotion of excitement, providing an effective color temperature of 3000K as the "enhanced spectrum" under the physiological emotional response of excitement can cause the physiological emotional response with the strongest multiplicative effect on the tester's excitement emotion. For example, in terms of the emotion of happiness, providing an effective color temperature of 4000K as the "enhanced spectrum" under the physiological emotional response of happiness can cause the physiological emotional response with the strongest multiplicative effect on the tester's happiness emotion. Another example, in terms of the emotion of pleasure, providing an effective color temperature of 5700K as the "enhanced spectrum" under the physiological emotional response of pleasure can cause the physiological emotional response with the strongest multiplicative effect on the tester's pleasure emotion.

[0050] In addition, it should be emphasized that the above only uses three color temperatures as representatives of the embodiments of the present invention, and does not only use the illumination of these three color temperatures as the "enhanced spectrum" for the three physiological emotional responses. In fact, after 2000K color temperature, every increase of 100K can be used as an interval to conduct the Figure 1b and Figure 1c entire process for different emotions (including: excitement, happiness, pleasure, anger, disgust, fear, sadness, calm or neutral, etc.). Therefore, Table 5 of the present invention only discloses partial results and is not used to limit the present invention to only these three embodiments.

[0051] Next, the present invention aims to establish an artificial intelligence model for the "correlation between brain waves and brain images of general physiological emotions" so that in future commercial promotions, the results of other sensing devices can be directly used to infer physiological emotions without using the fMRI system. Among them, the sensing device used in the present invention includes an electroencephalograph (EEG). In the following embodiments, the electroencephalograph 130 is used to establish the human factor lighting's physiological emotional response. And regarding using an eye tracker 150 or an auxiliary program 170 for facial expression recognition technology, etc., they can all be used to replace the implementation method of the fMRI system for physiological emotional response. However, the eye tracker 150 or the auxiliary program 170 for facial expression recognition technology will not be disclosed in the present invention and is hereby declared.

[0052] Please refer to Figure 2a , which is a method for establishing the physiological emotional response of the brain wave map of human factor lighting in the present invention. As Figure 2aAs shown, the present invention is a method for establishing the physiological and emotional responses of human factors lighting through an electroencephalograph 130, including: First, as shown in step 2100, the information of the "enhanced spectrum" database in Table 5 is also stored in the memory of the electroencephalograph 130. Then, as shown in step 2200, the tester wears the electroencephalograph, and each tester is guided to be stimulated with various emotions through the elements of known pictures or videos. After that, as shown in step 2300, the intelligent human factors lighting system 100 is started, and light signal parameters such as changeable spectrum, light intensity, flicker rate, color temperature, etc. are provided to perform lighting stimulation on the tester. Then, the electroencephalograph 130 records the electroencephalogram files after lighting with different color temperatures under specific emotions. For example: In this embodiment, each tester is first stimulated with excitement, and then, as shown in steps 2310 to 2330, different color temperatures of 3000K, 4000K, and 5700K are respectively provided to perform lighting stimulation on the tester, and the electroencephalogram files of the tester's specific emotions after lighting stimulation with different color temperatures during excitement stimulation are respectively recorded and stored in the device of the memory of the electroencephalograph 130. In the embodiment of the present invention, the electroencephalogram files of 100 testers after completing specific emotional stimulation and lighting have been respectively recorded. Therefore, a relatively large memory is required.

[0053] Then, as shown in step 2400, through the learning method of artificial intelligence, the electroencephalogram files of specific emotions (such as excitement, happiness, pleasure, etc.) stored in the memory of the electroencephalograph 130 are learned. Since the electroencephalograph 130 can only store the waveforms of electroencephalograms, the electroencephalogram files currently stored in the memory of the electroencephalograph 130 are the electroencephalogram files after known specific trigger emotional stimuli and lighting with different color temperatures. It should be noted that in actual tests, the electroencephalogram files of different testers after the same emotional stimulus and lighting with the same color temperature are different. Therefore, in the learning process of step 2400 of the present invention, it is necessary to classify the electroencephalogram files of specific emotions through the information of the "enhanced spectrum" database. For example: for the electroencephalogram files of the excitement emotion, only the electroencephalogram files of different testers at a color temperature of 3000K are grouped together. Another example: for the electroencephalogram files of the happiness emotion, only the electroencephalogram files of different testers at a color temperature of 4000K are grouped together. Another example: for the electroencephalogram files of the pleasure emotion, only the electroencephalograms of different testers at a color temperature of 5700K are grouped together. After that, the electroencephalograph is trained through machine learning in artificial intelligence. In the embodiment of the present invention, in particular, a transfer learning model is selected for learning and training.

[0054] During the process of learning and training using the transfer learning model in step 2400, learning and training are carried out by statistically calculating and comparing the similarity of a group of electroencephalogram (EEG) files for a specific emotion. For example, when learning and training on a group of EEG files with a color temperature of 3000K, it is to statistically calculate and compare the rankings with the highest similarity and the lowest similarity of excited emotions in the EEG files with a color temperature of 3000K and other levels. For example, the ranking with the highest similarity can be regarded as the EEG file with the strongest emotion, the ranking with the lowest similarity can be regarded as the EEG file with the weakest emotion, and the EEG file with the strongest emotion ranking can be used as the "target value", and the EEG file with the weakest emotion ranking can be used as the "starting value". For the convenience of explanation, at least one EEG file with the highest similarity is used as the "target value", and at least one EEG file with the lowest similarity is used as the "starting value", and different scores are given. For example, the "target value" is given a similarity score of 90 points, and the "starting value" is given a similarity score of 30 points. Similarly, the EEG files of the happy emotion in the 4000K color temperature category and the EEG files of the surprised emotion in the 5700K color temperature category are completed in sequence. Among them, a similarity score interval can be formed between the "starting value" and the "target value".

[0055] After that, as shown in step 2500, an EEG classification and grading database in artificial intelligence (which can be abbreviated as the artificial intelligence EEG file database) is established. After step 2400, the classification results of giving "target value" scores and "starting value" scores to groups of EEG files with various specific color temperatures form a database and are stored in the memory of the electroencephalograph 130. The purpose of establishing the EEG classification and grading database in step 2500 of the present invention is to obtain the EEG file of an unknown tester after receiving a specific emotion stimulus and being illuminated with a specific color temperature, and then compare the similarity score interval of the EEG file of this unknown tester with the EEG files in the database, and then the current congestion reaction situation in the brain of the unknown tester can be judged or inferred. The detailed process is as Figure 2b shown.

[0056] Next, please refer to Figure 2b , which is the illumination database for the present invention to construct effective human factor illumination for users. First, as shown in step 3100, the tester wears the electroencephalograph 130 and the tester is made to watch pictures that induce specific emotions. After that, as shown in step 3200, the human factor illumination system 100 is started. In an environment where various adjustable multi-spectral lighting modules are configured (for example: a test space), through the management control module 611 (such as Figure 3as shown), to provide light signal illumination parameters such as a spectrum, light intensity, flicker rate, color temperature, etc. that can be changed. Then, as shown in step 3300, an electroencephalogram file of the tester after induced emotion and illumination is obtained and stored in the memory module 617 of the cloud 610 (as Figure 3 shown). Then, as shown in step 3400, the artificial intelligence electroencephalogram file database is imported into the management control module 611. Among them, the management control module 611 will set a score for whether the similarity is sufficient. For example, when the set similarity score reaches 75 points or more, it means that the hyperemia reaction in the tester's brain is sufficient. Then, as shown in step 3500, in the management control module 611, the electroencephalogram file of the tester is compared with the artificial intelligence electroencephalogram file for similarity. For example, when the similarity score after comparing the electroencephalogram file of the tester is 90 points, the management control module 611 immediately determines that the hyperemia reaction in the tester's brain is very sufficient, so step 3600 will be performed to terminate the human factor illumination test for a specific emotion. Then, step 3700 is carried out to record the human factor illumination parameters when the hyperemia reaction in the tester's brain reaches the stimulation as a database and store it in the memory module 617.

[0057] Then, in Figure 2b in the procedure of step 3500, if the similarity score after comparing the electroencephalogram file of the tester with the artificial intelligence electroencephalogram file is 35 points, the management control module 611 will determine that the hyperemia reaction in the tester's brain is insufficient, so step 3800 will be performed. The management control module 611 will continuously strengthen the human factor illumination test, including: it can be controlled by the management control module 611 according to the high or low similarity score to provide an appropriate increase in illumination time or increase in illumination intensity. After that, the electroencephalogram file after increasing the illumination time or increasing the illumination intensity is obtained again through step 3300, and after step 3400, until the similarity score reaches 75 points or more of the set similarity score, the human factor illumination test is stopped. Among them, when the management control module 611 determines that the hyperemia reaction in the tester's brain has reached the stimulation, a human factor illumination parameter data file of the tester will be established in step 3700. Finally, the management control module 611 will form a "human factor illumination parameter database" for each tester's human factor illumination parameters and store it in the memory module 617. Obviously, the more testers there are, the more electroencephalogram files the artificial intelligence electroencephalogram file database of the present invention will learn, making the similarity score of the present invention more and more accurate.

[0058] After establishing the artificial intelligence model of the "Human Factor Lighting Parameter Database", after starting the human factor lighting system 100, the present invention can infer the physiological and emotional changes of the brain image of a new tester only by observing the interpretation result of the electroencephalogram file of the electroencephalograph 130. Therefore, it is possible to infer the physiological and emotional changes of the brain image according to the artificial intelligence model of the "Human Factor Lighting Parameter Database" without using an expensive fMRI system. This enables the human factor lighting system 100 to be promoted and used commercially. In addition, in order to enable the "Human Factor Lighting Parameter Database" to be used commercially, the "Human Factor Lighting Parameter Database" can be further stored in the internal private cloud 6151 in the cloud 610.

[0059] Next, please refer to Figure 3 , which is the system architecture diagram of the intelligent human factor lighting system 600 of the present invention. As Figure 3As shown, the overall architecture of the intelligent human factor lighting system 600 of the present invention can be divided into three blocks, including: a cloud 610, a lighting field end 620, and a client end 630. The connection channel between these three blocks is the Internet. Therefore, the three blocks can be distributed in different regions, or they can of course be configured together. Among them, the cloud 610 further includes: a management and control module 611, which is used for cloud computing, cloud environment construction, cloud management, or using cloud computing resources, etc., and also allows users to access, construct, or modify the content in each module through the management and control module 611. A consumption module 613, connected to the management and control module 611, which is used as a cloud service for user subscription and consumption. Therefore, the consumption module 613 can access each module in the cloud 610. A cloud environment module 615, connected to the management and control module 611 and the consumption module 613, divides the cloud background environment into an internal private cloud 6151, an external private cloud 6153, and a public cloud 6155 (for example, a commercial cloud), etc., and can provide interfaces for external or internal services for system providers or users. A memory module 617, connected to the management and control module 611, which is used as the storage area of the cloud background. The technical content that each module needs to execute in the present invention will be specifically described in different subsequent embodiments. The lighting field end 620 can communicate with the cloud 610 or the client end 630 through the Internet. Among them, a lamp group 621 composed of a plurality of lighting devices is configured in the lighting field end 620. And the client end 630 can communicate with the cloud 610 or the lighting field end 620 through the Internet. Among them, the client end 630 of the present invention includes ordinary users and editors who use the intelligent human factor lighting system 600 of the present invention for various commercial operations, and they all belong to the client end 630 of the present invention. The representative device or apparatus of the client end 630 can be a fixed device with computing functions or a portable intelligent communication device. In the following description, users, creators, editors, or portable communication devices can all represent the client end 630. In addition, in the present invention, the above-mentioned Internet can be an intelligent Internet of Things (AIoT).

[0060] Please refer to Figure 4 , which is a method 400 for constructing a lighting environment sharing platform of the present invention. During the process of Figure 4 , it is during Figure 3It is carried out in the system of the intelligent human factor lighting system 600. Among them, there are multiple lighting devices 621 in the intelligent human factor lighting system 600 that provide different spectra, which can be an LED lamp group. It should be particularly noted that the LED lamp group can be selected to modulate the voltage or current of individual LED lamps to combine a multi-spectral combination of a specific color temperature to provide a multi-spectral combination for lighting. Of course, the present invention can also choose to use multiple LED lamps with specific emission spectra, and each energized LED lamp emits its specific spectrum by providing a fixed voltage or current to combine a multi-spectral combination of a specific color temperature for lighting. In addition, it should be emphasized that the lighting devices 621 with different spectra described in the present invention are based on the actual lighting process, which requires multiple lighting devices 621 to emit different spectra. Therefore, the lighting devices 621 with different spectra can be composed of lighting devices with different spectra, or multiple identical lighting devices, and the spectra emitted by them can be modulated into different spectra by the power provided by the control device. Therefore, the present invention does not limit the implementation manners of the above lighting devices 621 with different spectra, and of course, it also includes forming lighting devices with different spectra by other means.

[0061] First, as shown in step 410, a multi-spectral lighting device cloud database needs to be constructed. The management control module 611 in the cloud 610 loads the "human factor lighting parameter database" stored in the memory module 617 or stored in the internal private cloud 6151 into the management control module 611. Among them, the "human factor lighting parameter database" stored in the cloud 610 already knows that various different color temperatures can cause corresponding emotional stimuli to people (or users). For example: a specific color temperature can have a multiplicative effect on a specific emotion.

[0062] First, as shown in step 410, a multi-spectral lighting device cloud database needs to be constructed. The management control module 611 in the cloud 610 loads the "human factor lighting parameter database" stored in the memory module 617 or stored in the internal private cloud 6151 into the management control module 611. Among them, the "human factor lighting parameter database" stored in the cloud 610 already knows that various different color temperatures can cause corresponding emotional stimuli to people (or users). For example: a specific color temperature can have a multiplicative effect on a specific emotion.

[0063] Next, as shown in step 411, a cloud database of the light scene of a multi-spectral lighting device is to be constructed. Since each color temperature can be combined by different multiple spectra, that is to say, the same color temperature can be composed of different multi-spectral combinations. For example: when we want to establish a spectrum that can provide a color temperature of 4000K, we can choose the multi-spectral combination of Maldives at a color temperature of 4000K, or the multi-spectral combination of Bali, Thailand at a color temperature of 4000K, or further choose the 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 according to factors such as their geographical locations (including: longitude and latitude), time / brightness / flicker rate, etc. Therefore, in step 411, according to the relationship between the color temperature and the corresponding emotions in the "human factors lighting parameter database", different multi-spectral combinations at a specific color temperature in different geographical locations on the earth can be collected through the cloud 610. For example: collect different multi-spectral combinations at a color temperature of 4000K in different geographical locations on the earth (for example: 4000K color temperature when the geographical location is at different longitudes and latitudes), or collect different multi-spectral combinations at a color temperature of 4000K at different times on the earth (for example: 4000K color temperature at 9 am). After that, the different multi-spectral combinations at a specific color temperature in different geographical locations on the earth that are collected are also stored in the memory module 617. Under the control of the management and control module 611 in the intelligent human factors lighting system 600, the parameters of various multi-spectral combinations (that is, different geographical locations or the time at the location of different geographical locations) with a specific color temperature can be adjusted by controlling multiple lighting devices 621 with different spectra. After being stored in the memory module 617, the intelligent human factors lighting system 600 of the present invention can construct a "cloud database of multi-spectral lighting devices" of multi-spectral combinations with various color temperatures formed in different geographical locations. Obviously, the "cloud database of multi-spectral lighting devices" constructed in step 411 is the result adjusted by multiple lighting devices 621 with different spectra. In addition, it should be emphasized that after mastering that different specific color temperatures can have a multiplicative stimulating effect on specific emotions, when the present invention forms multi-spectral combinations with various color temperatures, in addition to the multi-spectral combinations according to different geographical locations on the earth, it can also synthesize or combine multi-spectral combinations different from the actual geographical locations by artificial intelligence after considering factors such as different longitudes and latitudes / time / brightness / flicker rate, and the present invention does not limit this. Obviously, in step 411, the present invention has constructed a light scene database with multiple multi-spectral lighting devices. Therefore, according to the constructed different light scene databases, the intelligent human factors lighting system 600 can provide multi-spectral light irradiation services at different color temperatures through the multi-spectral lighting devices.At this time, the "multi-spectral lighting device cloud database" constructed in step 411 can be stored in the memory module 617, or in the internal private cloud 6151, or in the public cloud 6155 (such as a commercial cloud).

[0064] As shown in step 430, it is necessary to determine whether the irradiation of the multi-spectral combination is effective. Since the effects of the spectra of human-centered lighting on emotional stimuli or influences may vary among different users, it is necessary to adjust the irradiation spectrum of the multi-spectral combination. Then, when the user 630 enters the intelligent human-centered lighting system 600 of the present invention, the user can select the desired emotion from the "multi-spectral lighting device cloud database" in the management control module 611 to the memory module 617, or in the internal private cloud 6151, or in the public cloud 6155. After that, the management control module 611 can select a default multi-spectral combination from the "multi-spectral lighting device cloud database" in the memory module 617, or in the internal private cloud 6151, or in the public cloud 6155, and control the lighting devices 621 with multiple different spectra to adjust the multi-spectral combination of the desired emotion, and perform the lighting procedure on the user with the adjusted multi-spectral combination. For example: when the user wants to adjust the emotion to happy or pleasant, according to the "human-centered lighting parameter database", a color temperature of 4000K can be selected for irradiation. At this time, the user can go to the default multi-spectral combination provided by the "multi-spectral lighting device cloud database" or the user can select a multi-spectral combination that can provide a color temperature of 4000K by himself / herself. Of course, the specific multi-spectral combination used by the most people can also be selected for irradiation. At this time, when the user uses the multi-spectral combination provided in the "multi-spectral lighting device cloud database" established by the human-centered lighting system 600, the present invention is called the default multi-spectral combination.

[0065] Next, as shown in step 430 again, when the user selects a multi-spectral combination preset for a happy or pleasant emotion (for example: the system defaults to the multi-spectral combination of Maldives at a color temperature of 4000K), and after performing the lighting procedure with the multi-spectral combination adjusted by the lighting devices 621 with multiple different spectra, for example: after 15 minutes of the lighting procedure, the user can judge or evaluate whether the irradiation of the multi-spectral combination has effectively achieved a happy or pleasant emotion. Among them, the way for the user to judge or evaluate whether the happy or pleasant emotion has been effectively achieved can be completely determined according to the user's own feelings.

[0066] Continue as shown in step 430. When the user intuitively feels that they have effectively achieved a happy or pleasant mood, they can record and store this usage experience in the external private cloud 6153 or the public cloud 6155. For example, after recording and storing the usage experience in the external private cloud 6153, it can be used as the user's own usage experience file. For example, of course, this usage experience can also be recorded and stored in the public cloud 6155 for other users' reference. If, after 15 minutes of light irradiation, the user feels that they have not achieved a happy or pleasant mood, the user can adjust the multi-spectral combination light irradiation formula through the management control module 611. For example, adjust the irradiation time to 30 minutes, or change the light scene of the multi-spectral combination. For example, go back to step 411 to re-select another light scene of the multi-spectral combination, and change the light scene of the multi-spectral combination from the default Maldives to Bali, Thailand. Then, in step 430, perform the 15-minute multi-spectral light irradiation process again. After waiting for the light irradiation process to complete, once again judge or evaluate whether the irradiation of the multi-spectral combination of Bali has effectively achieved a happy or pleasant mood. Until the user feels that after the multi-spectral light irradiation of the current light scene, they have effectively achieved a happy or pleasant mood, they can record and store the effective light scene usage experience to form a "spectral formula". Finally, store this "spectral formula" in the external private cloud 6153 or the public cloud 6155 to form a sharing platform. Obviously, there are multiple "spectral formulas" stored in the sharing platform. Among them, the content stored in the sharing platform includes: the light scene where the user achieves a specific emotional effect and the light irradiation control parameters (hereinafter referred to as light irradiation parameters) of the multi-spectral combination of the multiple different spectral light-emitting devices 621 that generate the light scene of the specific emotion.

[0067] Finally, as shown in step 470, a shared platform for the lighting environment is constructed. When the user records and stores the effective usage experience in the external private cloud 6153 or the public cloud 6155, in addition to being used as the user's own usage experience file, in step 470, the intelligent human-centered lighting system 600 can perform massive data analysis on the effective experience data of numerous users, and then record and store it in the internal private cloud 6151 or the public cloud 6155, so that the information stored in the public cloud 6155 forms a "shared platform" for the lighting environment. For example: after the intelligent human-centered lighting system 600 performs massive data analysis on the experience data of numerous users, it can obtain the ranking of the "spectral recipes" of different lighting scenes with a specific color temperature being selected by users. This ranking can provide a reference for users when choosing the "spectral recipe". Further, after analyzing these massive data, different indicators can be obtained to provide references for users. For example: for different multi-spectral combinations with a color temperature of 4000K, different usage rankings can be made according to the user's gender, age, race, season, time, etc., so that the shared platform for the lighting environment constructed by the present invention can be used by designers who are interested or willing to provide human-centered lighting recipes to use these indicators for commercial services and operations. Therefore, the shared platform for the lighting environment constructed by the present invention can enable the intelligent human-centered lighting system 600 to provide various usage experiences after curation or algorithm operations as the default multi-spectral combination. In addition, users can also select a "spectral recipe" with the most selections by themselves for lighting according to the usage experience data after the operation.

[0068] In Figure 4 In the embodiment, step 450 may optionally exist. For example: if the user only establishes a database for their own use, they can bypass this step 450 and directly record and store the effective usage experience in the external private cloud 6153 or the public cloud 6155 after the validity is judged in step 430. The database for constructing the "spectral recipe" construction service to be performed in step 450 will be described in the following embodiments.

[0069] Next, in Figure 4In addition, there is another embodiment that can be used for commercial services and operations, which can provide 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" creative platform is provided in the intelligent human factors lighting system 600. The creators 630 who use this "spectral recipe" creative platform can be distributed all over the world and can connect to the "shared platform" of the light environment in the cloud 610 of the present invention through the Internet. Obviously, the present invention defines the "spectral recipe" creative platform here, that is, the "spectral recipe" creative platform means that users or creators 630 can connect to the public cloud 6155 or the "shared platform" in the cloud 610 through the Internet, so that users or creators 630 can use the "spectral recipe" information on the public cloud 6155 or the "shared platform" for editing work. Therefore, when users or creators 630 obtain various calculated usage experience data from the "shared platform", users or creators 630 can then perform personal editing or creation by the creators 630 based on experience data such as the gender, age, race, season, and time of the users, so as to construct an edited multi-scene or multi-emotion multi-spectral combination "spectral recipe".

[0070] First, a first embodiment of the present invention using the "spectral recipe" creative platform for commercial services and operations is, for example: for the emotional stimulation result of a 4000K color temperature, users or creators 630 can combine different light scenes through the "spectral recipe" creative platform. For example: the first segment selected by the creator 630 is the multi-spectral combination of the Maldives, the second segment is the multi-spectral combination of Bali, and finally, the third segment ends with the multi-spectral combination on the beach in Monaco. Thus, after each segment is paired or configured with the spectral irradiation time, a new spectral combination of multiple light scenes can be formed. Finally, storing this spectral combination of multiple light scenes in the "shared platform" can provide other users with the option to select this spectral combination of multiple light scenes as their "spectral recipe" for mood adjustment. Among them, the creative platform of the present invention can also select a specific color temperature at a specific time. For example: when a user wants to perform human factors lighting for emotional stimulation at 9 am, the user can further select the multi-spectral combinations of the aforementioned three segments at 9 am. Furthermore, the multi-spectral irradiation time of each segment can be configured to be the same or different. For example: each segment is irradiated for 15 minutes. It can also be that the first and third segments are configured for 15 minutes, while the second segment is configured for 30 minutes of irradiation. And these same or different time configurations can be selected by the user.

[0071] Secondly, in the second embodiment of the present invention using the "spectral formula" creation platform, combinations can be made for different color temperatures (i.e., multiple emotions) to achieve specific emotional stimulation results through multi-emotional lighting. For example: The creator 630 can make multi-emotional combinations through the "spectral formula" creation platform. For example, the first segment selected by the creator 630 is a multi-spectral combination of 4000K (happy emotion), the second segment is a multi-spectral combination of 3000K (excited emotion), and finally, the third segment ends with a multi-spectral combination of 5700K (pleasant emotion). Thus, after each segment is paired or configured with the multi-spectral irradiation time, a new multi-emotional multi-spectral combination can be formed. Finally, storing this multi-emotional multi-spectral combination in the "sharing platform" can provide users with the option to select this multi-emotional multi-spectral combination as the "spectral formula" for their mood adjustment. Similarly, the creation platform in this embodiment can also select a specific color temperature at a specific time. For example, when a user wants to perform human factor lighting for mood stimulation at 9 am, they can further select the aforementioned three segments of multi-spectral combinations at 9 am. Furthermore, the multi-spectral irradiation time for each segment can be configured to be the same or different. For example, each segment is irradiated for 15 minutes. It can also be that the first and third segments are configured for 15 minutes, while the second segment is configured for 30 minutes. And these same or different time configurations can be selected by the user.

[0072] Next, it should be further explained that after the above first embodiment (multi - spectral combination of multi - light scenes) and the second embodiment (multi - spectral combination of multi - emotion light scenes) are edited or created, they also need to go through the process from step 430 to step 470. For example: First, through step 411, irradiate with the multi - spectrum adjusted by multiple light - emitting devices 621 of different spectra. Then, through step 430, determine whether the combination of the above "spectral formula" achieves the effect that the creator wants to achieve, including: the spectral combination of the multi - light scene in the first embodiment and the corresponding configured irradiation time, as well as the spectral combination of the multi - emotion in the second embodiment and the configured irradiation time. When the effect set by the creator can be achieved, the control parameters of the light - emitting devices 621 required to build these "spectral formulas" can be formed into a database that can provide "spectral formula" building services, as shown in step 450. After that, as shown in step 470, after uploading the database of the "spectral formula" building service constructed in step 450 to the cloud, these "spectral formulas" 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, then return to step 411 to adjust the irradiation time of each segment, or replace the different light - scene combination (in the first embodiment) or replace the different emotion combination (in the second embodiment), until these "spectral formulas" can all achieve the effect set by the creator. Then, through the process from step 430 to step 470, these "spectral formulas" that are determined to be effective can be added to the public cloud 6155 of the present invention to form a light environment "sharing platform".

[0073] In addition, in order for the multi - scene combination or multi - emotion combination of the "spectral formula" creation platform to be effective, it may be necessary to go through specific light - emitting devices 621 or specific configuration diagrams 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, some management information for building the "spectral formula" is embedded in the database of hardware services and the database of software services, including: the installation or transportation of hardware devices, or including: software services such as space design, scene planning, or interface setting required to build these "spectral formulas" provided by the database of software services. In addition, the database of hardware services and the database of software services can be configured at the end of the creator 630, or can be configured in the cloud 610. In this regard, the present invention does not impose any restrictions. Obviously, the present invention is in Figure 4In the embodiments, a process for constructing various "spectral formulas" and a database of "spectral formula" construction services have been provided, and databases of hardware services and software services required for "spectral formula" construction have been established on the light environment "shared platform". It should be particularly noted that the "shared platform" finally established in step 470 can provide "spectral formulas" that can effectively combine spectra of multiple light scenes and spectra of light scenes with multiple emotions. After that, various commercial services and operations can be provided through this "shared platform".

[0074] Next, please refer to Figure 3 and Figure 5a shown in Figure 5a is an automatically adjustable intelligent human factor lighting method 500 of the present invention. First, as shown in step 510, the management control module 611 loads the "human factor lighting parameter database" stored in the memory module 617 into the management control module 611. Among them, the "human factor lighting parameter database" stored in the memory module 617 already knows that various different color temperatures can give people (or users) corresponding emotional stimuli. For example: a specific color temperature can have a multiplicative stimulating effect on a specific emotion.

[0075] Next, as shown in step 530, a multi-spectral formula cloud data database for human factor lighting is constructed. In step 530, the management control module 611 can download the "spectral formula" stored in the "shared platform" established in step 470 as the source for constructing the multi-spectral formula cloud data database with human factor lighting of the present invention. Therefore, the process of forming the "spectral formula" established in step 470 will not be described in detail. Please refer to the detailed description of step 470.

[0076] Next, as shown in step 520, a "contextual dynamic spectrum editing platform" is provided. Similarly, the present invention defines the "contextual dynamic spectrum editing platform" here. Similar to the aforementioned "spectrum formula creation platform", the "contextual dynamic spectrum editing platform" of the present invention means that a user or creator 630 can connect to the public cloud 6155 or the "shared platform" in the cloud 610 through the Internet, enabling the user or creator 630 to use the "spectrum formula" information on the public cloud 6155 or the "shared platform" for contextual editing work. After the "contextual dynamic spectrum editing platform" obtains various "spectrum formula" data from the "shared platform", the "contextual dynamic spectrum editing platform" can perform contextual editing or creation on the "spectrum formula" through software applications to construct an edited "contextual dynamic spectrum program" that achieves (or meets) a specific emotional effect. This "contextual dynamic spectrum program" can also be uploaded to the external private cloud 6153 and the public cloud 6155 in the cloud 610 to form a database of "contextual dynamic spectrum programs" that achieve (or meet) a specific emotional effect.

[0077] Next, the editing process of the "contextual dynamic spectrum program" in step 520 will be described in detail. Please refer to Figure 5b, which is the editing process of the situational dynamic spectrum editing platform of the present invention. As shown in step 5210, the editor 630 downloads the "spectrum formula" stored in the "shared platform" established in step 470 to the editing device used by the editor 630 through the Internet to the management control module 611 in the cloud 610. For example, the editing device can be a computer, a smartphone, or a workstation. In particular, one or more "spectrum formulas" are connected to the system of Software as a Service (SaaS) or Platform as a Service (PaaS) configured in the cloud 610 through the editing device of the editor 630. Then, as shown in step 5220, the downloaded "spectrum formula" is set with specific color temperature (i.e., specific emotion) lighting parameters through the SaaS or PaaS system configured on the cloud. Among them, the setting items of the lighting parameters include: the generation time of the spectrum, the longitude and latitude of the spectrum, the brightness of the spectrum, the contrast of the spectrum, the flicker rate of the spectrum, etc., and are adjusted and set. The above adjustment methods are the same as those described above in the present invention, including: changing the order of light scenes in the "spectrum formula", or changing the light scenes in the "spectrum formula", or deleting specific light scenes in the "spectrum formula", or adding new light scenes in the "spectrum formula", etc. Since these adjustment methods have been described, they will not be elaborated here. For example: when the user downloads a multi-light scene spectrum combination as the "spectrum formula" for achieving a happy (4000K) emotion adjustment, the multi-spectrum brightness and multi-spectrum contrast in the multi-spectrum combination of the Maldives can be finely adjusted through the SaaS or PaaS system, and the spectrum flicker rate in the multi-spectrum combination of the second paragraph of Bali can also be selected for adjustment at the same time, or the lighting order or lighting time of the above three paragraphs of multi-spectrum combinations can be adjusted. Or consider the longitude and latitude of the spectrum or the multi-spectrum combinations provided at each time point of the day. For example: add a multi-spectrum combination in Cannes, France at a color temperature of 4000K through the SaaS or PaaS system, or delete the multi-spectrum combination on the beach in Monaco and replace it with a multi-spectrum combination on Miami Beach, USA at a color temperature of 4000K. For example: when the user or the editor 630 downloads a "spectrum formula" of a multi-light scene spectrum combination, other light scene combinations are performed through the SaaS or PaaS system. In the above adjustment and change process, it is also possible to go to the "human factor lighting parameter database" stored in the memory module 617 in step 510 to perform combinations of other emotions (color temperatures). For example: in the above-mentioned multi-light scene "spectrum formula" of happiness, excitement, and pleasure, add the color temperature of the fourth paragraph of the serene emotion as the end stage of lighting.

[0078] Next, as shown in step 5230, the association between the situational function and the "spectral formula" is edited. In step 5230, the "spectral formula" that has been adjusted or set in step 5220 is associated with the specific situational function that the user or editor 630 wants to achieve. Among them, the association is to divide the specific situational function to be achieved into multiple blocks, and each of these blocks corresponds to a light scene in the "spectral formula". For example: The user downloads a "spectral formula" with multiple light scenes of happiness, excitement, and pleasure in step 5210. And when the user or editor 630 finally wants to achieve a good situational effect in the meeting room (where a good meeting situational effect means, for example, the editor 630 selects that during the meeting, all participants should be relaxed at the beginning, focused during the discussion, and happy at the conclusion), therefore, the original "spectral formula" can be adjusted to a "spectral formula" with multiple light scenes of relaxation, focus, and pleasure through step 5220. And in step 5230, the user or editor 630 further divides the meeting process into three situational blocks: opening, discussing, and conclusion. Then, the three situational blocks of opening, discussing, and conclusion are respectively associated with the "spectral formula" with multiple light scenes of relaxation, focus, and pleasure, so that the situation during the entire meeting process is associated with the "spectral formula" of the multiple light scenes in the meeting room. Next, as shown in step 5240, after the user or editor 630 has completed the association between the situation of the meeting process and the "spectral formula" of the multiple light scenes, and then adds a "time setting" to the situational blocks, a "situational dynamic spectral program" with a meeting situational function can be completed. For example: Set the playback times of the three blocks of the opening, discussion, and conclusion of the meeting to 5 minutes, 15 minutes, and 10 minutes. As Figure 5c shown, a "situational dynamic spectral program" with a meeting situational function can be completed. Obviously, after Figure 5bThe "contextual dynamic spectrum program" obtained from the editing process can be stored in the memory module 617, or the external private cloud 6153, or the public cloud 6155 through step 530. After that, the "contextual dynamic spectrum program" stored in the external private cloud 6153 can become a "contextual dynamic spectrum program" with automatically adjustable intelligent human-centered lighting and be provided for personal use. For example, when a user or editor 630 selects to use a meeting "contextual dynamic spectrum program", during the meeting, the spectrum in the meeting room can be automatically adjusted. Of course, the meeting "contextual dynamic spectrum program" edited by the editor 630 can also be stored in the public cloud 6155, so that commercial behavior of being opened to other users through the cloud 610 can be achieved. Obviously, at this time in step 530, in addition to various "spectrum recipes" downloaded from step 470, it also includes the "contextual dynamic spectrum program". Therefore, in the cloud database established in step 530, it can provide users for human-centered lighting. Additionally, it should be emphasized that in this embodiment, the editing of the "contextual dynamic spectrum program" with multiple light scenarios includes the combination of multiple light scenarios with a single emotion and the combination of multiple light scenarios with multiple emotions. Of course, for a specific emotion in the combination of multiple light scenarios with multiple emotions, multiple light scenarios can also be used for combination, and the present invention does not limit this.

[0079] In addition, during the above Figure 5b editing process, another implementation method can also be selected, that is, after the editor 630 downloads the "spectrum recipe" stored in the "shared platform" established in step 470 to the editing device used by the editor 630 through the Internet to the management control module 611 in the cloud 610, then, the user or editor 630 can first select to edit the specific contextual function to be achieved through the SaaS or PaaS system (that is, first divide the specific contextual function into multiple blocks), and then, make the specific context to be achieved correspond and associate with the already downloaded "human-centered lighting parameter database", so as to complete the correlation editing between multiple context blocks and the corresponding emotions (color temperatures) to form a combination of multiple light scenarios with multiple emotions. For example: The editor has first divided the meeting process into three blocks: opening, discussion, and conclusion, and then selects the "spectrum recipe" of multiple light scenarios corresponding to the corresponding emotions such as relaxation, concentration, and pleasure, or selects the "spectrum recipe" of multiple light scenarios corresponding to pleasure, concentration, and relaxation from the "human-centered lighting parameter database" stored in the memory module 617. Since the method of itinerary correlation editing is the same, it will not be elaborated in this embodiment.

[0080] Next, the present invention further provides another preferred embodiment of an automatically adjustable intelligent human factor lighting method. Since the "contextual dynamic spectrum program" constructed in step 530 is the result of individual editing by individual editors 630, in order to achieve better effects, it is necessary to consider the light stimulation effects of different users on the "spectrum formula", and / or it is necessary to consider whether the lighting hardware configurations in different fields are capable of achieving the light stimulation effects of the "spectrum formula", and all of these need to be adjusted.

[0081] Next, as shown in steps 550 and 570, the user or editor adjusts the "spectrum formula" in the "contextual dynamic spectrum program" to meet emotional needs. First, the user or editor 630 has downloaded a "contextual dynamic spectrum program" from the external private cloud 6153 or the public cloud 6155. This "contextual dynamic spectrum program" can be a "spectrum formula" with multiple emotions and multiple light scenes, or a "spectrum formula" with a single emotion and multiple light scenes. Next, the user or editor 630 needs to be in a "specific environment" to execute the selected "contextual dynamic spectrum program". Among them, in the embodiments of the present invention, the "specific environment" is divided into three states, as shown in step 570, including: a closed lighting system, an intelligent lighting field, and a portable human-centered lighting device. When the "specific environment" is a closed lighting system, where the closed lighting system is an enclosed space with multiple lighting devices (for example: an enclosed cavity that can isolate external light), it can provide one or more users to receive the selected "contextual dynamic spectrum program" for "spectrum formula" irradiation in the enclosed cavity, as shown in step 571. During the spectrum irradiation process, the present invention provides a function with control mode settings. For example: the "spectrum formula" of the multi-light scene can be adjusted through the App on the mobile device used by the user or editor 630 or the control module in the enclosed cavity. For example: under the influence of an ambient light environment, the "spectrum formula" of the selected "contextual dynamic spectrum program" can be adjusted. The adjustment methods include: time / latitude and longitude / brightness / flicker rate, etc., as shown in step 540. In addition, when the "specific environment" is an intelligent lighting field, where the intelligent lighting field is a field with multiple lighting devices that can accommodate multiple people, for example: a meeting room, a classroom, an office, a social place, or a factory, etc., so that multiple users can receive the "contextual dynamic spectrum program" in the intelligent lighting field for "spectrum formula" irradiation, as shown in step 573. During the spectrum irradiation process, the field controller, user, or editor 630 can adjust the "spectrum formula" of the selected "contextual dynamic spectrum program" through the application program (App) on the used mobile device or the control module in the field. For example: under the influence of an ambient light environment, or under the influence of the number of people in the field, the "spectrum formula" is adjusted. The adjustment methods include: time / latitude and longitude / brightness / flicker rate, etc., as shown in step 540.Also, when the "specific environment" is a portable lighting device, the portable human factor lighting device is a virtual device related to the metaverse, such as virtual reality (VR), mixed reality (MR), or extended reality (XR) devices. Users can receive the selected "contextual dynamic spectrum program" through the virtual device for "spectrum formula" irradiation, as shown in step 575. During the spectrum irradiation process, the user or editor 630 can adjust the "spectrum formula" through the App on the mobile device or the control module in the virtual device. For example, under the influence of an ambient light environment, the "spectrum formula" of the selected "contextual dynamic spectrum program" can be adjusted. The adjustment methods include time / latitude and longitude / brightness / flicker rate, etc., as shown in step 540.

[0082] During the operation of the above steps 540, 550, and 570, it is obvious that the default value of the "spectrum formula" for the "specific environment" where the user is located is adjusted. During the execution of this default value adjustment, the ambient light sensor 650 set in the "specific environment" (as Figure 3 or Figure 6 shown) can transmit the ambient light information to the application (App) on the user or editor 630's mobile device or the control module in the "specific environment" through a wireless communication device as a reference for the default value adjustment of the "spectrum formula". In addition, the occupancy sensor 660 set in the "specific environment" (as Figure 3 or Figure 6 shown) can transmit the number of people information in the environment to the application (App) on the user or editor 630's mobile device or the control module in the "specific environment" through a wireless communication device as a reference for the default value adjustment of the "spectrum formula". Among them, this occupancy sensor 660 can be a vibration sensor, which judges the number of people by the vibration frequency. The occupancy sensor 660 can also be a temperature sensor, which judges the number of people by the ambient temperature. In addition, the occupancy sensor 660 can also be a camera system, which judges the number of people through artificial intelligence (AI) face recognition. In addition, the occupancy sensor 660 can also be a gas concentration detector, which is used to detect the concentration changes of oxygen (O2) or carbon dioxide (CO2) to judge the effect of the user's spectrum irradiation. For example, when the temperature in the environment rises and the concentration of carbon dioxide (CO2) also rises, it is judged that the spectrum irradiation reaches the required emotional effect. Obviously, through the operation of steps 540, 550, and 570, an automatically adjustable intelligent human factor lighting "contextual dynamic spectrum program" can be formed.

[0083] The present invention then further provides another preferred embodiment of an automatically adjustable intelligent human factor lighting method. Some sensing devices are further provided to feedback whether the required emotional effect is achieved after the user is irradiated by the "spectral formula" of the above-mentioned "contextual dynamic spectrum program". These sensing devices include: contact physiological sensors (such as step 561) or non-contact optical sensors (such as step 563). Among them, the contact physiological sensor is configured on each user to measure the user's heart rate, blood pressure, pulse, blood oxygen concentration or electrocardiogram, etc., so as to judge whether the user reaches the required emotion. The non-contact optical sensor can be configured in the lighting environment where the user is located to measure the illuminance, color temperature, spectrum, color rendering property, etc. in the "specific environment", so as to judge whether the user reaches the required emotion.

[0084] As shown in step 580, after the user has irradiated the "spectral formula" of a specific "contextual dynamic spectrum program" in a "specific environment", an algorithm is used to determine whether the current spectrum irradiation process has met the user's emotional needs. Among them, the algorithm in step 580 can obtain a ratio by processing the signals between the user's physiological signals (including: heart rate, blood pressure, pulse and breathing rate) through the algorithm. Then, this ratio value is used as the judgment of whether a specific emotional need is met. Therefore, after the calculation and processing of the management control module 611, a database of physiological signal ratios corresponding to various emotions is established and stored in the memory module 617 in the cloud 610 or the internal private cloud 6151. For example: After the user irradiates with a "contextual dynamic spectrum program" of a happy emotion for a period of time, through the contact physiological sensor in step 561, the heart rate, blood pressure and blood oxygen are fed back to the App on the mobile device or the control module in the "specific environment". At this time, the App on the mobile device or the control module in the "specific environment" calculates a ratio value through the algorithm for this feedback data. Then, this ratio value is transmitted to the management control module 611 through the Internet and compared with the ratio value stored in the memory module 617 or the internal private cloud 6151 by the management control module 611. For example: If the ratio value calculated by the algorithm falls between 1.1 and 1.15, and the management control module 611 determines that the probability of this ratio value reaching a happy emotion is 80%, and the probability of reaching a pleasant emotion is 20%. If we determine that the probability of achieving the effect is 75%, then the management control module 611 will determine that after the user irradiates with the "spectral formula" of the selected "contextual dynamic spectrum program", the required happy emotion has been achieved. After the irradiation program of the "contextual dynamic spectrum program" is completed, the irradiation program will be stopped. Immediately, in step 590, the "spectral formula" data of the current "contextual dynamic spectrum program" is stored in the internal private cloud 6151 or the external private cloud 6153 or the public cloud 6155 in the cloud 610. If it is determined that after the user irradiates with the "spectral formula" of the selected "contextual dynamic spectrum program", the ratio value calculated by the algorithm has only a 50% probability of reaching a happy emotion, it means that the required happy emotion of the user has not been achieved. At this time, it is necessary to return to step 550, adjust the "spectral formula" of the selected "contextual dynamic spectrum program" through the control module in step 540, and then perform the irradiation program again. After the ratio calculated by the algorithm for the heart rate, blood pressure and blood oxygen of the user fed back to the App on the mobile device or the control module in the field through the contact physiological sensor in step 561, this ratio is transmitted to the cloud database through the Internet again and compared with the ratio in the cloud database until the required happy emotion is achieved.Obviously, during the storage process in step 590, it will also be stored in step 530 simultaneously. Therefore, in the cloud database established in step 530 at this time, in addition to various "spectral recipes" downloaded from step 470, it also includes the "contextual dynamic spectral program" adjusted by the algorithm. Therefore, the "contextual dynamic spectral program" stored in the cloud database established in step 530 can provide a more effective "contextual dynamic spectral program" for users to perform human-centered lighting. Additionally, it should be emphasized that in this embodiment, the editing of the "contextual dynamic spectral program" for multiple light scenes includes the combination of multiple light scenes for a single emotion and the combination of multiple light scenes for multiple emotions. Of course, it also includes that a specific emotion in the combination of multiple light scenes for multiple emotions can also use multiple light scenes for combination, and the present invention does not limit this.

[0085] For the automatically adjustable intelligent human-centered lighting system or method provided by the present invention, it can determine whether the user has achieved the effect by themselves after being illuminated with the "spectral recipe" they selected through a feedback signal. Among them, the solution provided by the present invention is to judge through the actual physiological signals of the user. Therefore, the above embodiments using physiological signals as the algorithm are only for illustrative purposes to enable the general public to understand the implementation manner of the technical means of the present invention, and thus should not be used as a limiting condition for the scope of rights of the present invention. It should be emphasized that as long as individual comparisons are made through the physiological signals of the user or the physiological signals are processed and then further compared with the data in the cloud database 610, it is within the scope of the "algorithm" described in the present invention.

[0086] According to the above automatically adjustable intelligent human-centered lighting method, the present invention further provides an intelligent human-centered lighting system applied to commercial operation, as Figure 6 shown. The intelligent human-centered lighting system 600 applied to commercial operation of the present invention includes: cloud 610, management control module 611, the lighting field end 620 of intelligent lighting, and portable communication device 630. The devices configured in the lighting field end environment 620 include: lamp group or lighting device 621, at least one occupancy sensor 622, at least one ambient light sensor 623, and switch device 640. Among them, the lighting field end 620 includes a "specific environment". According to Figure 5a shown, the "specific environment" can be divided into three fields, including: a closed space or intelligent lighting field that can provide for multiple people to use, and a portable human-centered lighting device or closed space for personal use.

[0087] First, Figure 6Disclose an intelligent human factor lighting system 600A for commercial operation, which can be applied to embodiments for multiple users. The client can use the portable communication device 630 and download the "spectral formula" or "contextual dynamic spectral program" from the cloud 610 through the Internet, and perform human factor lighting on the activated lamp group 621 through the portable communication device 630 to form an automatically adjustable intelligent human factor lighting system. Among them, in this embodiment, the client can be at a remote location or at a specific environment end at the proximal end. When the client is at a remote location, the Internet is an intelligent Internet of Things (AIoT) formed by the Internet of Things (IoT) and artificial intelligence (AI). When the client is at the proximal end, the Internet is a wireless communication protocol formed by a gateway, including: Wifi or Bluetooth, etc.

[0088] Next, when multiple users are already distributed in a closed space or an intelligent lighting field, specific "spectral formula" or "contextual dynamic spectral program" human factor lighting can be performed on the activated lamp group 621 through the portable communication device 630. Among them, the closed lighting system is a closed space with multiple lighting devices (for example: a closed cavity that can isolate external light), which can provide one or more users with human factor lighting in the closed cavity. And the intelligent lighting field is a field with multiple lighting devices that can accommodate multiple users, such as: a meeting room, a classroom, an office, a social venue, or a factory, etc., which can provide multiple users with human factor lighting in the intelligent lighting field.

[0089] In addition, the lighting unit 621 can be further configured in an enclosed space or an intelligent lighting field. When multiple users perform human-centered lighting in this enclosed space, the enclosed space can provide a space that isolates external environmental interference, allowing users to immerse themselves in the selected "spectral recipe" or "contextual dynamic spectral program". At the same time, in order to enable human-centered lighting to achieve the expected effect faster, contact physiological sensors configured on each user can be used to measure the user's heart rate, blood pressure, pulse, blood oxygen concentration, electrocardiogram, etc., so as to judge whether the user reaches the required mood. In addition, the vibration frequency, ambient temperature, carbon dioxide concentration in the environment, face recognition, and carbon dioxide concentration, spectrum, light intensity, flicker rate, and color temperature in the environment detected by the presence sensor 660 and the background ambient light sensor 650 configured in the intelligent lighting field can be transmitted to the management and control module 611 in the cloud 610 through the intelligent Internet of Things (AIoT) for calculation, so as to judge whether the user has achieved the set effect. Similarly, during the spectral irradiation process, the "spectral recipe" of the multi-light scene can be adjusted through the App on the mobile device used by the user 630 or the control module in the intelligent lighting field. For example, when the ambient light sensor 650 detects that there is ambient light interference, the "spectral recipe" of the selected "contextual dynamic spectral program" can be adjusted. The adjustment methods include: time, longitude and latitude, brightness, flicker rate, etc. (please refer to Figure 4 the operation processes of step 540, step 550, step 570, and step 580 shown).

[0090] Next, Figure 6 Another intelligent human-centered lighting system 600A for the commercial operation shown is disclosed, which is applied to an embodiment for personal use. Users can use the portable communication device 630 and download the "spectral recipe" or "contextual dynamic spectral program" to the cloud 610 through the Internet, and start the portable human-centered lighting device through the portable communication device 630 to perform human-centered lighting, so as to form an automatically adjustable intelligent human-centered lighting system. Especially when the user has worn the portable human-centered lighting device on the user's eyes, the lighting unit 621 configured in the portable human-centered lighting device can be started through the portable communication device 630 to perform human-centered lighting of a specific "spectral recipe" or "contextual dynamic spectral program". Among them, the portable human-centered lighting device is a virtual device related to the metaverse, such as: virtual reality (VR), mixed reality (MX), or extended reality (XR) device, which can provide a single user to receive human-centered lighting through the virtual device.

[0091] In addition, in order to enable the human factor illumination of the portable human factor illumination device to achieve the expected effect faster, a contact physiological sensor configured on the user can be used to measure the user's heart rate, blood pressure, pulse, blood oxygen concentration, electrocardiogram, etc., so as to determine whether the user reaches the required emotion. Similarly, during the spectral irradiation process, the "spectral formula" of the multi-light scene can be adjusted through the App on the mobile device used by the user 630 or the control module in the closed cavity (please refer to the operation processes of step 540, step 550, step 570, and step 580 for details).

[0092] In a preferred embodiment, the configuration of the lamp group 621 can be configured according to the customized requirements through the hardware service database of step 420 and the software service database of step 440. Finally, in the portable communication device 630 in the automatically adjustable intelligent human factor illumination system of the present invention, this portable communication device 630 can be a smart phone, a tablet device, or a workstation. The portable communication device 630 can download the application program (APP) containing intelligent human factor illumination through the intelligent Internet of Things (AIoT) to the management control module 611. Through this APP, the user can connect to the public cloud in the cloud 610, and then select the desired "spectral formula" or "dynamic spectral program" from the public cloud for human factor illumination. At the same time, through this App, the lamp group 621 can also be remotely controlled to be turned on or off through a short-range communication protocol, so as to control the spectrum to achieve the effect of human factor illumination. Among them, if the user confirms that those "spectral formulas" or "contextual dynamic spectral programs" have therapeutic effects, these "spectral formulas" or "contextual dynamic spectral programs" can be downloaded to the portable communication device 630 of the client. After that, through the switch device 640 configured on the client, the "spectral formula" or "contextual dynamic spectral program" can be directly turned on for human factor illumination, without going through the process of Internet connection, which allows the user to quickly enter the human factor illumination program.

[0093] An automatically adjustable intelligent human factor lighting system described above establishes a database of the "increased blood oxygenation level-dependent response" in the brain through the human factor lighting system. After editing the light formula, a multi-spectral lighting device cloud database is constructed from this database of the "increased blood oxygenation level-dependent response" in the brain. The cloud database allows users to set the desired brain emotional needs in the human factor lighting system, and the human factor lighting system determines or recommends the operation logic of the light formula equation, which can be implemented in a closed human factor lighting device, an open intelligent lighting field, and a portable human factor lighting device. Subsequently, when the user experiences the light scenario, the human factor lighting system algorithm judges the user's physiological and psychological states. If the brain emotional needs are not met, the "spectral formula" program is continuously modified by feedback signals from a wireless device, and after readjusting the "spectral formula", it is verified again whether the expected emotional needs are achieved. When the brain meets the emotional needs, the "spectral formula" or "contextual dynamic spectrum program" formed by the human factor lighting that meets the user's emotional needs is provided for the lighting process. Obviously, through the intelligent human factor lighting method and system disclosed in the present invention, the human factor lighting effect for brain emotional needs can be commercially promoted to benefit more users in an environment without the use of fMRI.

[0094] Finally, it should be emphasized once again that the above description is only a preferred embodiment of the present invention and is not intended to limit the scope of the rights of the present invention. At the same time, the above description should be understandable and implementable by those with ordinary knowledge in the relevant technical field. Therefore, other equivalent changes or modifications completed without departing from the concepts disclosed in the present invention should be included in the scope of the patent claims of the present invention.

Claims

1. A method for grading the physiological emotional response by an electroencephalograph, which is a method for establishing the grading of the electroencephalogram for the physiological emotional response through a human-centered lighting system and an electroencephalograph, characterized in that The method includes: Obtaining enhanced spectra of different emotions, where the enhanced spectra are specific color temperatures that have a multiplicative effect on specific physiological emotional responses identified by fMRI; Inducing a specific physiological emotion in a tester by having the tester wear the electroencephalograph and applying elements with specific emotional stimuli to stimulate the tester's specific physiological emotion; Performing an illumination procedure, which is to start the human-centered lighting system to illuminate the tester with different color temperatures after inducing the tester's specific physiological emotion, and record and store the electroencephalogram file after illumination with different color temperatures under a specific emotion; Classifying the electroencephalogram files of the specific emotion, which is to form groups of electroencephalogram files corresponding to the same specific emotion and obtained under the same specific color temperature for the enhanced spectra of the specific color temperature and the electroencephalogram files of the specific emotion, and classify the electroencephalogram files of the specific emotion by similarity through learning the groups; and Establishing an electroencephalogram grading database by sorting the electroencephalogram files of various specific color temperatures according to similarity to establish the electroencephalogram grading database.

2. The method for grading physiological and emotional responses by the electroencephalograph according to claim 1, characterized in that: The different color temperatures are formed by changing the spectral, light intensity, flicker rate, and color temperature of the illumination.

3. A method for grading the physiological and emotional responses by electroencephalogram is a method for grading the physiological and emotional responses by electroencephalogram established through the cloud, the human-centered lighting system and the electroencephalograph, characterized in that, The method includes: Obtaining enhanced spectra of different emotions, where the enhanced spectra are specific color temperatures that have a multiplicative effect on specific physiological emotional responses identified by fMRI; Inducing a specific physiological emotion in a tester by having the tester wear the electroencephalograph and applying elements with specific emotional stimuli to stimulate the tester's specific physiological emotion; Performing an illumination procedure, which is to start the human-centered lighting system to illuminate the tester with different color temperatures after inducing the tester's specific physiological emotion, and record and store the electroencephalogram file after illumination with different color temperatures under the specific emotion; Establishing an electroencephalogram classification and grading database, which is to form groups of electroencephalogram files corresponding to the same specific emotion and obtained under the same specific color temperature for the enhanced spectra of different color temperatures and the electroencephalogram files of the specific emotion, classify the electroencephalogram files of the specific emotion by similarity through learning the groups, establish the electroencephalogram grading database by sorting the similarity, and establish the electroencephalogram grading database in the memory module in the cloud; and Judging whether the illumination parameters of the specific emotion are effective by having the cloud give a score-based grading to the electroencephalogram grading database and using the score level as the judgment criterion; Where when a specific physiological emotion of the tester is induced and the human-centered lighting system is started to illuminate the tester with a specific color temperature, if the score of the electroencephalogram grading of the tester reaches the benchmark, it means that the hyperemia reaction in the tester's brain is sufficient, and then the illumination parameters of the specific color temperature at this time are stored.

4. The method for grading physiological and emotional responses based on electroencephalogram according to claim 3, characterized in that, The method further includes: When determining whether the lighting parameters for the specific emotion are effective, if the score of the electroencephalogram classification of the tester does not reach the benchmark, it means that the hyperemia response in the tester's brain is insufficient. In this case, after adjusting the lighting parameters, the human-centered lighting system needs to be restarted to irradiate the tester with a specific color temperature; and if the score of the electroencephalogram classification of the tester reaches the benchmark, it means that the hyperemia response in the tester's brain is sufficient. At this time, the lighting parameters of the specific color temperature will be stored.

5. The method for classifying physiological emotional responses based on electroencephalogram according to claim 3, wherein: The lighting parameters include the spectrum, light intensity, flicker rate, and color temperature of the lighting.

6. The method for grading physiological emotional responses based on electroencephalogram according to claim 1 or 3, characterized in that: The elements that induce specific emotional stimuli in the tester include pictures or videos.

7. The method for classifying physiological and emotional responses based on electroencephalogram according to claim 1 or 3, characterized in that: The way to learn the group is a transfer learning model.

8. The method for grading physiological and emotional responses using electroencephalogram according to claim 1 or 3, characterized in that: The electroencephalogram file sorted with the highest similarity is used as the target value.

9. The method for grading physiological emotional responses using electroencephalogram as claimed in claim 1 or 3, characterized in that: The electroencephalogram file sorted with the lowest similarity is used as the starting value.

10. The method for grading physiological emotional responses using electroencephalogram as claimed in claim 8, wherein: The electroencephalogram classification database is classified by giving scores to the target values.

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