Method of performing emotion navigation using neutral emotion

Abstract

The invention provides an emotion navigation method which is realized through an intelligent human factor irradiation system. The system is composed of a cloud end, an illumination field domain end and client equipment which are connected with one another through the Internet. First, an initial emotion of a user is confirmed using a physiological monitoring device or IAPS stimulation and stored to a cloud. Then, setting a target emotion according to a user demand and storing the target emotion to the cloud; then, a relay emotion is selected through client equipment, an emotion navigation path is set, and a multispectral formula is edited according to the emotion path; the system executes an irradiation procedure according to the formula of the relayed emotion and judges whether a neutral emotion is reached or not through physiological monitoring. And if so, irradiating according to the formula of the target emotion, and finally judging whether the target emotion is reached and stopping the program.

Description

Technical Field

[0001] The present invention provides an intelligent human-caused lighting method, in particular, an intelligent human-caused lighting method that measures emotional states through human physiological signals and then adjusts the luminous spectrum, and then achieves emotional navigation by transferring emotions through the process of intelligent human-caused lighting. Background Art

[0002] Human beings are animals with changeable emotions. They will have different emotional reactions according to their psychological state, such as excitement, amusement, anger, disgust, fear, happiness, sadness, serene or neutral. When negative emotions (such as anger, disgust, fear) cannot be properly resolved, they will cause psychological harm or trauma to the human body, and eventually develop into mental illness. Therefore, how to provide an emotional resolution, relief or treatment system that can meet the needs of users in a timely manner is a huge business opportunity in today's highly competitive and high-pressure society.

[0003] In modern medical equipment, functional Magnetic Resonance Imaging (fMRI) systems can be used to measure changes in blood dynamics caused by neuronal activity. Due to the non-invasiveness of fMRI and its low radiation exposure, fMRI is currently mainly used in the study of the brain or spinal cord of humans and animals. At the same time, the test subject can also be examined through the electroencephalogram (EEG) of the electroencephalogram (EEG). When the same method is used to stimulate emotions, the reactions of different emotions can be seen. For example, the EEG patterns of fear and happiness are obviously different. Among them, when observing the reaction of a certain emotion under fMRI and EEG, for example, under the emotion of happiness (which can be induced by pictures and combined with facial emotion recognition), the blood oxygen concentration dependent contrast (BOLD) reaction is observed by fMRI, and it is found that there is a significant reaction phenomenon in the medial prefrontal cortex (Mpfc) that is different from the corresponding emotions (anger and fear). In contrast, for example, when observing the BOLD response under the emotions of fear and anger, fMRI was used to observe that there was a significant response in the amygdala region, indicating that the two types of emotions have different response areas in the brain. Therefore, the BOLD response in different areas of the brain can be used to clearly determine what emotion the test subject is currently in. In addition, if the EEG of an electroencephalogram (EEG) is used to examine and measure the test subject, the same method is used to stimulate the generation of emotions, and it can be seen that the brain wave patterns of fear and happiness are significantly different. Therefore, the different response brain wave patterns can also be used to determine what emotion the test subject is currently in. According to the above, in terms of functional magnetic resonance imaging (fMRI), emotions are distinguished by different BOLD responses, while in terms of electroencephalogram (EEG), emotions are distinguished by different brain wave patterns. Obviously, the methods used by the two to judge the emotions of the test subjects and the content of the records are completely different. Therefore, based on current technology, the test results of the same emotion of the same test subject cannot be replaced by the brain wave pattern of the electroencephalograph (EEG) to replace the blood oxygen concentration dependent contrast (BOLD) response of the functional magnetic resonance imaging system (fMRI).

[0004] The above discussion on the judgment of emotions by functional magnetic resonance imaging (fMRI) and electroencephalograph (EEG) is because the fMRI system is very expensive and large, so it is impossible to use the fMRI system in the commercial system and method of human-caused lighting. Similarly, if only the brain wave pattern of the electroencephalograph (EEG) is used to judge the emotions of the test subject, it may be encountered that the brain wave patterns of different test subjects for different emotions may be different. Therefore, it is currently impossible to use the blood oxygen concentration dependent contrast (BOLD) response of the functional magnetic resonance imaging system (fMRI) alone, or the brain wave pattern of the electroencephalograph (EEG) alone, through the editing of light formulas, to construct a commercial human-caused lighting method and system. Summary of the invention

[0005] According to the above description, the present invention provides a method for establishing a correlation between the brain wave pattern of the electroencephalogram (EEG) and the blood oxygen concentration dependent contrast (BOLD) of the functional magnetic resonance imaging system (fMRI), and then using the brain wave pattern of the electroencephalogram (EEG) to apply the intelligent human-caused lighting system as a shared platform for providing human-caused lighting. Next, the present invention further provides a method and system for emotional navigation that can achieve the purpose of shifting the user's emotions through the process of intelligent human-caused lighting.

[0006] The present invention first provides a method for performing emotional navigation using an intelligent human factor lighting system, including: in step one, first confirming the "initial emotion", then, in step two, setting the "target emotion", and in step three, after determining the "relay emotion", completing the "emotion navigation path" setting. Then, in step four, edit the multispectral formula related to the "relay emotion" and the "target emotion" according to the "emotion navigation path", and then, in step five, execute the lighting program of the multispectral formula, step six: if it is determined that the "target emotion" has not been reached, further provide the user's physiological signal data, and find the multispectral formula that can be adjusted to the corresponding emotion of the "target emotion" according to the user's physiological signal data, and repeat steps four to six. Finally, if it is determined that the "target emotion" has been reached, stop the lighting program.

[0007] The present invention then provides a method for performing emotion navigation using an intelligent human-factor lighting system, which is performed by an intelligent human-factor lighting system, wherein the human-factor lighting system is composed of a cloud, a lighting field end, and a client device and is interconnected via the Internet, and the cloud stores emotion coordinate information, wherein the emotion navigation method is characterized in that:

[0008] Step 1, confirming the user's "initial emotion", is to confirm the user's "initial emotion" at the illumination field end through a physiological monitoring device or by selecting to use IAPS stimulation, and store the "initial emotion" in the cloud;

[0009] Step 2, setting the "target emotion" is to set it on the client device according to the needs of the user, and store the "target emotion" in the cloud;

[0010] Step 3, selecting "relay emotion" to complete the emotion navigation path setting, is to connect the client device to the cloud through the Internet, select the "relay emotion" from the emotion coordinate information in the cloud, and store the "relay emotion" in the cloud;

[0011] Step 4, editing the "multi-spectral formula", is to edit the "multi-spectral formula" corresponding to the "target emotion" and the "multi-spectral formula" corresponding to the "relay emotion" according to the light formula on the "relay emotion" and the "target emotion" selected by the emotion navigation path;

[0012] Step 5, executing the "multi-spectrum recipe" lighting program corresponding to the "relay emotion", which is to control the lamp group in the lighting field end through the client device to perform a lighting process for a set time on the user according to the "multi-spectrum recipe" corresponding to the "relay emotion";

[0013] Step 6, determining whether the user has reached a "neutral emotion" is to determine whether the user's emotion has reached the "neutral emotion" through a physiological monitoring device;

[0014] Step 7, executing the lighting program of the "multi-spectral formula" corresponding to the "target emotion", is to control the lamp group in the lighting field end through the client device to perform a lighting process for a set time on the user according to the "multi-spectral formula" corresponding to the "target emotion" after determining that the user has reached the "neutral emotion";

[0015] Step 8, determining whether the "target emotion" has been reached, is to determine whether the user's emotion has reached the "target emotion" through a physiological monitoring device;

[0016] Step nine, stopping the lighting process, is to stop the lighting process when it is determined that the user's emotion has reached the "target emotion".

[0017] The present invention then provides a method for performing emotion navigation, which is performed by an intelligent human-factor lighting system. The human-factor lighting system is composed of a cloud, a lighting field end, and a client device and is interconnected via the Internet. The cloud stores emotion coordinate information and the user's personal physiological data. The emotion navigation method is characterized in that:

[0018] Step 1, confirming the user's "initial emotion", is to confirm the user's "initial emotion" at the illumination field end through a physiological monitoring device or by selecting to use IAPS stimulation, and store the "initial emotion" in the cloud;

[0019] Step 2, setting the "target emotion" is to set it on the client device according to the needs of the user, and store the "target emotion" in the cloud;

[0020] Step 3, obtaining the personal physiological data of the user, is to obtain the personal physiological data of the user stored in the memory module from the client device to the cloud;

[0021] Step 4, selecting "relay emotion" to complete the emotion navigation path setting, is to connect the client device to the cloud through the Internet, select the "relay emotion" from the emotion coordinate information in the cloud, and store the "relay emotion" in the cloud;

[0022] Step 5, editing the "multi-spectral formula", is to edit the "multi-spectral formula" corresponding to the "target emotion" and the "multi-spectral formula" corresponding to the "relay emotion" according to the light formula on the "relay emotion" selected by the emotion navigation path and the information on the personal physiological data of the user;

[0023] Step 6, executing the "multi-spectrum recipe" lighting program of the "relay emotion", is to control the lamp group in the lighting field end through the client device to perform a lighting process for a set time on the user according to the "multi-spectrum recipe" corresponding to the "relay emotion";

[0024] Step 7, determining whether the user has reached the "neutral emotion", is to determine whether the user's emotion has reached the "neutral emotion" through a physiological monitoring device;

[0025] Step 8, executing the lighting program of the "multi-spectral recipe" of the "target emotion", is to control the lamp group in the lighting field end through the client device to perform a lighting process for a set time on the user according to the "multi-spectral recipe" corresponding to the "target emotion" after determining that the user has reached the "neutral emotion";

[0026] Step nine, determining whether the "target emotion" has been reached, is to determine through a physiological monitoring device whether the user's emotion has reached the "target emotion";

[0027] Step ten, stopping the lighting process, is to stop the lighting process when it is determined that the user's emotion has reached the "target emotion".

[0028] In the above-mentioned method for performing emotion navigation, the user's personal physiological data can be further used as the lighting parameter adjustment for the "multi-spectral recipe".

[0029] In the above-mentioned method for performing emotion navigation, the lighting parameters of the "multi-spectral recipe" at least include the color temperature, illumination, flicker frequency, and color rendering index (Ra) of the lighting.

[0030] In the above method for performing emotion navigation, the “multispectral formula” is a formula formed by the surrounding system score (LSS):

[0031] LSS=tx[axf eeg (freq)+bxf eeg (Ra)+cxf eeg (CTI)+dxf eeg (I)], where

[0032] a, b, c, d are the coefficients of variation, CTI is the color temperature, and t is the exposure time.

[0033] The present invention has provided a result of emotional navigation, that is, after determining the current emotion of the user, in the first stage, some relay emotion spectrums with complementary emotions to the initial emotion are first irradiated, and then the spectrum of the target emotion is irradiated in the second stage, so that the user can reach the target emotion index. In particular, when it is further confirmed that the user has transferred the emotion to the neutral emotion after the spectrum of complementary emotions in the first stage, the spectrum of the target emotion in the second stage is then irradiated, which can greatly improve the target emotion index.

[0034] In addition, after relaying emotional irradiation, if neutral emotion has not been reached, the user's personal physiological data can be further provided, characterized in that: the user's personal physiological data is a physiological data of the user's health check, and the color temperature, illumination, flicker frequency, and color rendering (Ra) of the user's lighting are adjusted. After confirming that the emotion has been transferred to the neutral emotion or near the origin of the emotion coordinate, the target emotion index can be greatly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1a It is the original data collection framework of the present invention on the physiological and emotional response of human beings to lighting;

[0036] Figure 1b It is a flow chart of collecting original data of human physiological and emotional response to lighting according to the present invention;

[0037] Figure 1c It is the judgment process of the human factor lighting to specific physiological emotional response of the present invention;

[0038] Figure 2a The present invention is a method for establishing a human brain wave graph to physiological emotional response due to light exposure;

[0039] Figure 2b The present invention constructs a lighting database for users to perform effective human factors lighting;

[0040] Figure 3 is a system architecture diagram of the intelligent human factor lighting system of the present invention;

[0041] Figure 4a is the emotion coordinate system of the present invention;

[0042] Figure 4b It is the brain wave map of the specific emotion of the present invention;

[0043] Figure 4c is the EEG of the emotion transfer test 1 of the present invention;

[0044] Figure 4d This is the brain wave diagram of the emotion transfer test 2 of the present invention;

[0045] Figure 4e is the EEG of the Emotion Transfer Test 3 of the present invention;

[0046] Figure 4f is the navigation path of the emotion navigation example 1 of the present invention;

[0047] Figure 4g is the navigation path of the emotional navigation example 2 of the present invention;

[0048] Figure 4h is the navigation path of the emotional navigation example 3 of the present invention;

[0049] Figure 5 is a method of performing emotion navigation of the present invention;

[0050] Figure 6 is another method of performing emotion navigation of the present invention; and

[0051] Figure 7 Another method for performing emotion navigation of the present invention. DETAILED DESCRIPTION

[0052] In the following description of the present invention, the functional magnetic resonance imaging system is referred to as "fMRI system", the electroencephalogram is referred to as "EEG", and the blood oxygen concentration dependent contrast is referred to as "BOLD". In addition, in the embodiment of the color temperature test of the present invention, the test is performed in units of 100K. However, in order to avoid too lengthy descriptions, in the following descriptions, the so-called specific emotions refer to excitement or excitement, happiness, pleasure, etc., and 3000K, 4000K and 5700K will be used as color temperature test examples to illustrate the corresponding specific emotional reactions, so the present invention cannot be limited to the embodiments of these three color temperatures. At the same time, in order to enable the technical field of the present invention to fully understand its technical content, the relevant implementation methods and embodiments are provided here to illustrate. In addition, when reading the implementation methods provided by the present invention, please refer to the drawings and the following description content at the same time, wherein the shapes and relative sizes of the components in the drawings are only used to assist in understanding the content of the present implementation method, and are not used to limit the shapes and relative sizes of the components, so as to explain in advance.

[0053] The present invention uses an fMRI system to understand the correspondence between the spectrum and emotions in the brain through a physiological signal measurement method, and develops a preliminary mechanism for using light to affect human physiological and psychological reactions. Since the brain image of the fMRI system can determine which part of the human brain undergoes a hyperemia reaction when stimulated by light, the BOLD reaction can also be recorded. This BOLD reaction of brain hyperemia is also called the "blood oxygen concentration dependent reaction increase" condition. Therefore, the present invention can accurately and objectively infer the physiological emotional changes of the tester based on the image recording data of brain hyperemia under various emotions of the fMRI system and the reaction of the "blood oxygen concentration dependent reaction increase". Afterwards, based on the physiological emotions confirmed by the fMRI system, an electroencephalogram (EEG) is further used to record brain wave changes to establish the correlation between the two, in order to use the brain wave changes recorded by the electroencephalogram (EEG) to replace the emotional judgment of the fMRI system.

[0054] Therefore, the main purpose of the present invention is to record the BOLD response of the tester to the specific emotion by illuminating the tester during the test of the specific emotion in the fMRI system, so as to screen out which specific "effective color temperature" can produce a multiplying effect on the specific emotion, and use the color temperature of the illumination as the "effective color temperature" corresponding to the specific emotion. After that, the tester is illuminated with "effective color temperature", and the brain wave pattern under the stimulation of "effective color temperature" is recorded by the electroencephalogram (EEG), so that the specific brain wave pattern of the electroencephalogram (EEG) is associated with the specific BOLD response, and 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 set of human-factor illumination system and method that can be commercially operated, so as to solve the problem of having to use an expensive fMRI system to implement the human-factor illumination system, reduce the operating cost, and further meet the customized service needs.

[0055] First, please refer to Figure 1a , is the original data collection framework of the present invention on the physiological and emotional response of human beings to lighting. Figure 1a As shown, the intelligent human factor lighting system 100 is activated in an environment (e.g., a test space) that has been configured with various adjustable lighting modules, and provides light signal lighting parameters such as spectrum, light intensity, flicker rate, and color temperature that can be changed. The present invention uses the compatible image interaction platform 110 (fMRI compatible image interaction platform) formed by the fMRI system for different target emotions, and uses voice and image emotion guidance, while using a specific effective spectrum for 40 seconds of stimulation to observe the changes in the blood oxygen content in the brain of the tester, to verify whether the "effective color temperature" can significantly induce the tester's emotional response, and is described in detail as follows.

[0056] Next, please refer to Figure 1b and Figure 1c ,in, Figure 1b is a flow chart of the original data collection of the physiological and emotional response of human beings to light according to the present invention, and Figure 1c It is the process of judging people's specific physiological and emotional reactions to lighting. Figure 1bAs shown in step 1100 in the figure, each tester is already on the compatible image interaction platform 110. Then, each tester is guided to perform various emotional stimulations through known pictures. Afterwards, as shown in step 1200, the BOLD response of the tester in the brain after being stimulated by the picture is recorded through the compatible image interaction platform 110. Then, as shown in step 1300, the tester is visually stimulated by providing a spectrum with different color temperature parameters through illumination. For example, LED lamps are used in combination with electronic dimmers to provide a spectrum with different color temperature parameters. In an embodiment of the present invention, 9 groups of visual stimulations with different color temperatures, such as 2700K, 3000K, 3500K, 4000K, 4500K, 5000K, 5500K, 6000K, and 6500K, are provided. Among them, after completing 40 seconds of effective light irradiation and stimulation each time, the tester can be selected to be illuminated by an invalid light source for 1 minute (full spectrum white light without flicker) to achieve the purpose of emotional relaxation. Furthermore, the test subject may be given a 40-second counter-effect light stimulus to observe whether the area that was responsive to the original effective light stimulus has a reduced response. In the embodiment of the present invention, after the compatible image interaction platform 110 has recorded the BOLD response of a certain emotion in the brain of the test subject after being stimulated by the picture, spectra with different color temperature parameters are provided to provide visual stimulation to the test subject, such as Figure 1c As shown in step 1310, a spectrum with a color temperature of 3000K is provided. Then, as shown in step 1320, a spectrum with a color temperature of 4000K is provided. Finally, as shown in step 1330, a spectrum with a color temperature of 5700K is provided to provide visual stimulation to the tester.

[0057] Next, as shown in step 1400, the compatible image interaction platform 110 records the BOLD responses of the various emotions in the brain of the tester after being stimulated by light. In an 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 emotional response area in the tester's corresponding limbic system. Among them, the parts of the limbic system triggered by different emotions are different, and the above-mentioned limbic system with emotional response in the brain area is shown in Table 1 below.

[0058] Table 1

[0059]

[0060] The compatible image interaction platform 110 records the response results of BOLD in specific brain regions. The response results are determined by calculating the area size of these emotional response sites when there are more limbic systems with BOLD emotional responses in the brain region. For example, the larger the area with BOLD emotional responses, the stronger the response to specific physiological emotions. In the embodiment of the present invention, Figure 1c As shown in step 1410, the reaction result of BOLD after being irradiated with a spectrum of color temperature of 3000K is recorded. Then, as shown in step 1420, the reaction result of BOLD after being irradiated with a spectrum of color temperature of 4000K is recorded. Finally, as shown in step 1430, the reaction result of BOLD after being irradiated with a spectrum of color temperature of 5700K is recorded. Among them, after the tester has gone through the lighting procedure after the excitement (excitement) emotion is induced, the reaction result of BOLD in a specific area of ​​the brain recorded by the compatible image interaction platform 110 is shown in Table 2. Obviously, when irradiated with a color temperature of 3000K, the excitement can be further enhanced. Therefore, according to the results of the embodiment of the present invention, the optimal stimulation color temperature falls between 3000K and 4000K. However, it should be noted that after irradiation with a color temperature of 5700K, a negative inhibitory effect will be produced on the excitement emotion.

[0061] Table 2

[0062]

[0063] Among them, after the tester passed the lighting procedure after the happiness emotion was induced, the compatible image interaction platform 110 recorded the BOLD response results in specific brain areas as shown in Table 3. Obviously, when irradiating with a color temperature of 4000K, compared with irradiating with the other two color temperatures, the color temperature of 4000K can enhance the BOLD response of the brain area in the happiness situation. Therefore, according to the results of the embodiment of the present invention, the optimal stimulus color temperature for the happiness situation is around 4000K.

[0064] Table 3

[0065]

[0066] Among them, after the tester passed the lighting procedure after the amusement emotion was induced, the compatible image interaction platform 110 recorded the BOLD response results in specific brain areas as shown in Table 4. Obviously, the three color temperatures can enhance the BOLD response in the amusement brain area, especially when the color temperature is higher, the BOLD response in the amusement brain area is stronger.

[0067] Table 4

[0068]

[0069] Among them, after the tester passed the lighting procedure after the serene index emotion was induced, the compatible image interaction platform 110 recorded the response results of BOLD in specific brain areas as shown in Table 5. Obviously, when irradiating with a low color temperature of 3000K, the sense of tranquility or relaxation can be enhanced, however, when the color temperature is higher, it will have a negative inhibitory effect on the serene index emotion, especially, the higher the color temperature, the more obvious the negative inhibitory effect.

[0070] Table 5

[0071]

[0072] Then, as shown in step 1500, the specific color temperature is screened out by illumination to increase the BOLD dependent response of a specific emotion, and this specific color temperature is called "effective color temperature". In this embodiment, the BOLD response results of the emotional response area in the limbic system of the tester are recorded to summarize the stimulation effect of the color temperature on the brain, as shown in Tables 2 to 5 above. For the results of the BOLD brain area dependent response that can increase a specific emotion by screening out a specific color temperature, it is calculated that the specific color temperatures can make the response effect of the specific emotion reach the maximum response value (i.e., the maximum response area value of BOLD).

[0073] like Figure 1c As shown in step 1510 in FIG. 1 , the maximum response value is calculated only after the tester has recorded the excitement emotion on the compatible image interaction platform 110 and completed the illumination procedure. For example, according to the record in Table 2, the total score of 3000K (577) is subtracted from the total score of 4000K (226), and 351 is obtained. Then, the total score of 3000K (577) is subtracted from the total score of 5700K (-105), and 682 is obtained. Therefore, the total response value after the excitement emotion is induced and under the illumination of 3000K is 1033.

[0074] Then, if Figure 1c In step 1520, the maximum response value is calculated after the tester has recorded the excitement emotion on the compatible image interaction platform 110 and completed the illumination procedure. For example, according to the record in Table 2, the total score of 4000K (226) is subtracted from the total score of 3000K (577), and the result is -351. Then, the total score of 4000K (266) is subtracted from the total score of 5700K (-105), and the result is 371. Therefore, the total response value after the excitement emotion is induced and under the illumination of 4000K is 20.

[0075] Then, if Figure 1c In step 1530, the maximum response value is calculated only after the tester has recorded the excitement emotion induction on the compatible image interaction platform 110 and completed the lighting procedure. For example, according to the record in Table 2, the total score of 5700K (-105) is subtracted from the total score of 3000K (577), and the result is -682. Then, the total score of 5700K (-105) is subtracted from the total score of 4000K (266), and the result is -371. Therefore, the total response value after the excitement emotion induction and under the illumination of 5700K is -1033.

[0076] According to the above calculation, after the excitement emotion is induced, the 3000K illumination can make the excitement emotion reach the maximum reaction value. That is, the 3000K illumination can make the excitement emotion have a more obvious additive effect (that is, relative to the calculated total score of 4000K and 5700K illumination, the calculated total score of 3000K illumination is 1033, which is the highest), so the 3000K illumination is used as the "effective color temperature" of the excitement emotion. The "effective color temperature" of other emotions, such as happiness, pleasure and tranquility, can be obtained through the calculation results of the above steps 1510 to 1530, as shown in Table 6 below.

[0077] Table 6

[0078] Physiological emotions Effective color temperature Excitement 3000K Happiness 4000K Amusement 5700K Serene 3000K

[0079] Next, according to the statistical results in Table 6, the effective color temperature can be regarded 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 oxygen concentration dependence" of fMRI on a certain emotion. For example: an effective color temperature of 3000K can represent the "enhanced spectrum" of the fMRI system in the "excited" emotion, in which the optimal stimulus color temperature should fall between 3000K and 4000K. For example: an effective color temperature of 4000K can represent the "enhanced spectrum" of the fMRI system in the "happy" emotion, in which the optimal stimulus color temperature of the happy situation is around 4000K. For example: an effective color temperature of 5700K can represent the "enhanced spectrum" of the fMRI system in the "pleasant" emotion. For example: an effective color temperature of 3000K can also represent the "enhanced spectrum" of the fMRI system in the "quiet" emotion, in which the optimal stimulus color temperature of the quiet situation is around 3000K.

[0080] Finally, as shown in step 1600, a "light recipe" database of "enhanced spectrum" corresponding to the effect of a specific emotion can be established in the fMRI system. By stimulating the test subject with the human factor lighting parameters, and observing and recording the BOLD reaction of the test subject's brain when the light is stimulated by the fMRI system, and at the same time, recording the fMRI brain image to determine which part of the human brain has an additive reaction of "increased blood oxygen concentration dependence" when the light is stimulated, the specific effective color temperature can be regarded as the "light recipe" of the "blood oxygen concentration dependence" of fMRI for a specific emotion. Obviously, the present invention objectively infers the "light recipe" of the test subject under a specific physiological emotional reaction based on the statistical results of the BOLD additive reaction to a specific emotion at a specific "effective color temperature" in Table 6, and uses this "light recipe" as the physiological emotional reaction evidence of the strongest additive effect for a specific emotion (including: excitement, happiness, pleasure, anger, disgust, fear, sadness, calmness or neutrality, etc.).

[0081] It should be emphasized that the present invention Figure 1b and Figure 1c In the entire implementation process, 100 testers were tested for multiple specific emotions, and the statistical results in Table 6 were obtained. 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 as a "light formula" can make the tester's excitement produce the strongest multiplying effect of the physiological emotional response. For example: in terms of happy emotions, providing an effective color temperature of 4000K as the "enhanced spectrum" under the physiological emotional response of happiness as a "light formula" can make the tester's happy emotions produce the strongest multiplying effect of the physiological emotional response. Another example: in terms of pleasant emotions, providing an effective color temperature of 5700K as the "enhanced spectrum" under the physiological emotional response of pleasant emotions as a "light formula" can make the tester's pleasant emotions produce the strongest multiplying effect of the physiological emotional response.

[0082] In addition, it should be emphasized that the above three color temperatures are only used as representatives of the embodiments of the present invention, and these three color temperatures are not the only ones used as the "enhanced spectrum" for physiological emotional responses. In fact, after the 2000K color temperature, each 100K increase can be used as an interval to enhance different emotions (including: excitement, happiness, pleasure, anger, disgust, fear, sadness, calmness or neutrality, etc.). Figure 1b and Figure 1c Therefore, Table 6 of the present invention only discloses part of the results and is not intended to limit the present invention to these embodiments.

[0083] Next, the present invention is to establish an artificial intelligence model of "the correlation between brain waves and brain images of general physiological emotions" so that in future commercial promotion, other sensing device results can be directly used to infer physiological emotions without using an fMRI system. Among them, the sensing device used in the present invention includes an electroencephalogram (EEG). In the following embodiment, the electroencephalogram 130 is used to establish the physiological emotional response of people due to lighting, and the eye tracker 150 or the expression recognition technology auxiliary program 170 can be used to replace the implementation method of the fMRI system for physiological emotional response. However, the eye tracker 150 or the expression recognition technology auxiliary program 170 will not be disclosed in the present invention, but will be announced first.

[0084] Please refer to Figure 2a , is a method of establishing a classification of physiological and emotional responses of people to light based on their brain waves. Figure 2a As shown, the present invention is a method for establishing human-induced lighting response to physiological emotions through an electroencephalogram 130, including: first, as shown in step 2100, the "enhanced spectrum" database information of Table 6 is also stored in the memory of the electroencephalogram 130. Then, as shown in step 2200, let the tester wear the electroencephalogram, and guide each tester to stimulate various emotions through elements of known pictures or videos. For example, the emotional stimulation of known pictures or videos can choose to use the International Affection Picture System (IAPS). Afterwards, as shown in step 2300, start the intelligent human-induced lighting system 100, and provide light signal parameters such as changeable spectrum, light intensity, flicker rate, color temperature, etc. to stimulate the tester with light. Then, the electroencephalogram 130 records the brain wave image file after being illuminated with different color temperatures under specific emotions. For example, in this embodiment, each test subject is first stimulated with excitement, and then, as in steps 2310 to 2330, different color temperatures of 3000K, 4000K and 5700K are provided to illuminate the test subject, and the brain wave images of the test subject's specific emotions after the excitement stimulation and the different color temperatures are illuminated to the test subject are recorded and stored in the memory of the electroencephalogram 130. In the embodiment of the present invention, the brain wave images of 100 test subjects after the specific emotion stimulation and illumination have been recorded, so a larger memory is required.

[0085] Next, as shown in step 2400, the brain wave graphs of specific emotions (e.g., excitement, happiness, pleasure, etc.) stored in the memory of the electroencephalogram 130 are learned through the learning method of artificial intelligence. Since the electroencephalogram 130 can only remember the waveform of the brain wave, the brain wave graphs currently stored in the memory of the electroencephalogram 130 are brain wave graphs of known specific triggering emotional stimuli and different color temperature illumination. It should be noted that in actual tests, the brain wave graphs of different testers for the same emotional stimulus and the same color temperature illumination are different. Therefore, in the learning process of step 2400, the present invention needs to classify the brain wave files of specific emotions through the information of the "light recipe" database of the "enhanced spectrum", for example: for the brain wave files of excitement, only the brain wave files of different testers at a color temperature of 3000K are grouped, and for example: for the brain wave files of happiness, only the brain wave files of different testers at a color temperature of 4000K are grouped, and for example: for the brain wave files of pleasure, only the brain wave files of different testers at a color temperature of 5700K are grouped. Afterwards, the electroencephalogram is trained through machine learning in artificial intelligence. In the embodiment of the present invention, a transfer learning model is particularly selected for learning and training.

[0086] In the process of learning and training using the transfer learning model in step 2400, the learning and training is carried out by counting, calculating and comparing the similarity of the brain wave image file group of a specific emotion. For example, when learning and training the brain wave image file group of 3000K color temperature, the ranking of the highest similarity and the lowest similarity in the brain wave image file of 3000K color temperature is statistically calculated and compared. For example, the ranking with the highest similarity can be regarded as the brain wave image file of the strongest emotion, and the ranking with the lowest similarity can be regarded as the brain wave image file of the weakest emotion. The brain wave image file of the strongest emotion ranking can be used as the "target value", and the brain wave image file of the weakest emotion ranking can be used as the "starting value". For the convenience of explanation, at least one of the most similar brain wave image files is used as the "target value", and at least one of the least similar brain wave image files is used as the "starting value", and different scores are given, for example, the "target value" is given a similarity of 90 points, and the "starting value" is given a similarity of 30 points. Similarly, the brain wave graphs of the happy emotion in the 4000K color temperature category and the brain wave graphs of the surprised emotion in the 5700K color temperature category are completed in sequence. Among them, the "starting value" and the "target value" can form a similarity score range.

[0087] Afterwards, as shown in step 2500, an artificial intelligence EEG classification and grading database (which may be referred to as an artificial intelligence EEG file database) is established. After step 2400, the EEG file groups of various specific color temperatures are given a grading result of "target value" scores and "starting value" scores to form a database, which is stored in the memory of the electroencephalograph (EEG) 130. The purpose of the present invention in establishing an EEG classification and grading database in step 2500 is to obtain an EEG file of an unknown tester after the unknown tester receives specific emotional stimulation and is illuminated with a specific color temperature, and then compare the EEG file of the unknown tester with the EEG file similarity score interval in the database, so as to judge or infer the current congestion reaction condition in the brain of the unknown tester. The detailed process is as follows. Figure 2b shown.

[0088] Next, please refer to Figure 2b , is a lighting database for constructing effective human-factor lighting for users in the present invention. First, as shown in step 3100, the tester is asked to wear an electroencephalogram (EEG) 130 and watch pictures that induce specific emotions. Then, as shown in step 3200, the human-factor lighting system 100 is activated to irradiate the tester with a "light recipe" in an environment (e.g., a test space) that has been configured with various adjustable multi-spectrum light modules, through the management control module 611 (e.g., Figure 3 Then, as shown in step 3300, the brain wave image of the tester after the emotion induction and light exposure is obtained and recorded, and stored in the memory module 617 of the cloud 610 (as shown in step 3300). Figure 3 Then, as shown in step 3400, the artificial intelligence electroencephalogram file database is imported into the management and control module 611. Among them, the management and control module 611 will set a score to determine whether the similarity is sufficient. For example, when the similarity score is set to be above 75 points, it means that the congestion reaction in the brain of the tester is sufficient. Then, as shown in step 3500, in the management and control module 611, the electroencephalogram file of the tester and the artificial intelligence electroencephalogram file are compared for similarity. For example, when the similarity score after the comparison of the electroencephalogram file of the tester is 90 points, the management and control module 611 immediately determines that the congestion reaction in the brain of the tester is sufficient, so step 3600 is performed to terminate the human factor lighting test of a specific emotion. Then, step 3700 is performed to record the human factor lighting parameters when the congestion reaction in the brain of the tester has reached the stimulation into a database and store it in the memory module 617.

[0089] Then, in Figure 2bIn the step 3500 procedure, if the similarity score after comparing the tester's brain wave map file with the artificial intelligence brain wave map file is 35 points, the management control module 611 will determine that the tester's brain congestion reaction is insufficient, so it will proceed to step 3800, and the management control module 611 will continue to strengthen the test of human-caused lighting, including: the management control module 611 can control according to the similarity score to provide appropriate increase in lighting time or increase in lighting intensity. After that, the brain wave map file after increasing the lighting time or increasing the lighting intensity is obtained again through step 3300, and the human-caused lighting test is stopped only when the similarity score reaches the set similarity score of 75 points or more through step 3400. Among them, when the management control module 611 determines that the tester's brain congestion reaction has reached the stimulation, it will establish the tester's human-caused lighting parameter data file in step 3700. Finally, the management control module 611 forms a "human factor lighting parameter database" with the human factor lighting parameters of each tester and stores it in the memory module 617. Obviously, when there are more testers, the artificial intelligence brain wave map file database of the present invention will learn more brain wave map files, making the similarity score of the present invention more and more accurate.

[0090] After the artificial intelligence model of the "human factor lighting parameter database" is established, after the human factor lighting system 100 is started, the present invention can infer the physiological and emotional changes of the brain images of the new tester only by observing the brain wave image interpretation results of the electroencephalogram 130. Therefore, it is not necessary to use the expensive fMRI system, and the physiological and emotional changes of the brain images can be inferred based on the artificial intelligence model of the "human factor lighting parameter database". The human factor lighting system 100 can 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.

[0091] Next, please refer to Figure 3 , is a system architecture diagram of the intelligent human factor lighting system 600 of the present invention. Figure 3As shown, the overall architecture of the intelligent human factor lighting system 600 of the present invention can be divided into three blocks, including: cloud 610, lighting field end 620 and client device 630. The three blocks are connected through the Internet. Therefore, the three blocks can be distributed in different areas, and of course, they can also be configured together. Among them, the cloud 610 further includes: management control module 611, which is used for cloud computing, cloud environment construction, cloud management or use of cloud computing resources, etc., and also allows users to access, construct or modify the content in each module through the management control module 611. The consumption module 613 is connected to the management control module 611 and is used as a cloud service subscribed and consumed by users. Therefore, the consumption module 613 can access each module in the cloud 610. The cloud environment module 615 is connected to the management control module 611 and the consumption module 613, which divides the environment of the cloud backend into internal private cloud 6151, external private cloud 6153 and public cloud 6155 (for example, commercial cloud), etc., and can provide an interface for external or internal services of system providers or users. The memory module 617 is connected to the management control module 611 and is used as a storage area for the cloud backend. The technical content 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 device 630 through the Internet. Among them, a lamp group 621 composed of multiple light-emitting devices is configured in the lighting field end 620. And the client device 630 can communicate with the cloud 610 or the lighting field end 620 through the Internet. Among them, the client device 630 of the present invention includes general users and editors who use the intelligent human-factor lighting system 600 of the present invention for various business operations, all of which belong to the client device 630 of the present invention, and the representative device or device of the client device 630 can be a fixed device with computing function (including edge computing) or a portable intelligent communication device. In the following description, users, creators, editors or portable communication devices can represent client devices 630. In addition, in the present invention, the above-mentioned Internet can be an intelligent Internet of Things (AIoT).

[0092] The present invention undergoes a relatively complete electroencephalogram experiment process, for example, after the test subject wears the electroencephalogram 130, in step 2300, the intelligent human factors lighting system 100 is started to provide various spectra that can be changed, including light intensity (illuminance), flicker rate, color temperature, and average color rendering index (Ra) and other light signal parameters. After the test subject is illuminated, the results of the aforementioned BOLD brain area test are used, and then the results can be obtained through literature search. Figure 4a The light signal parameters of each emotion on the emotion coordinate system shown, wherein the spectrum or light signal parameters of some emotions on the emotion coordinate system are summarized in the following Table 7:

[0093] Table 7

[0094]

[0095] In Table 7, K refers to color temperature, lux refers to illuminance, Hz refers to flicker rate, and Ra refers to color rendering index (full name is general color rendering index). Figure 4a From Table 7, we can see a trend that the emotions in coordinate area I and coordinate area III have complementary effects, and the emotions in coordinate area II and coordinate area IV also have complementary effects. This phenomenon can be used as a navigation direction when transferring emotions.

[0096] Obviously, in order to construct a commercially viable human-caused lighting system and method thereof, it is necessary to use an expensive fMRI system to implement the human-caused lighting system. Therefore, it is necessary to use specific brain wave patterns of an electroencephalogram (EEG) to assist in judging the user's emotional changes, which can further meet customized service needs and reduce operating costs at the same time.

[0097] When performing emotion localization using an fMRI system and an electroencephalogram (EEG), the emotion results obtained by the fMRI system are used as the standard basis. We define it as the Limbic System Score (LSS). The reason why the Limbic System Score (LSS) is used as an indicator is because the limbic system refers to the brain area that includes the hippocampus and amygdala, and supports a variety of emotions, behaviors, and long-term memory. For example, the higher the BOLD index in the fMRI, the greater the emotional response. For example, when LSS can represent the Arousal (validity) of emotions, the higher its value means the more excited the emotions are. Therefore, the present invention will use the Limbic System Score (LSS) to establish a formula that combines various light signal parameters such as spectrum, light intensity, flicker rate, color temperature, and color rendering (Ra) to define the parameters that are used as the emotional signal. Figure 4a Light signal parameters of each emotion on the emotion coordinate system.

[0098] According to the paper "fMRIBOLD Correlates of EEG Independent Components: Spatial Correspondence With the Default Mode Network" published in the Journal of Neuroscience (Front.Hum.Neurosci) on November 27, 2018, two important pieces of information were revealed. One is that Alpha waves have no significant effect on emotions. The other is that the correlation between delta waves, theta waves, beta2 waves and gamma waves and blood oxygen response in the brain area are -0.291, -0.26, 0.269 and -0.345 respectively.

[0099] Next, the present invention has 13, 18, 14, and 17 brain regions corresponding to different brain waves, wherein the number of brain regions represents the probability of affecting the peripheral system (LSS). For example, the delta wave affects 13 brain regions. In equation 1 of the present invention, its probability is 13 / (13+18+14+17)=0.2097. Therefore, the weight of delta should be adjusted from -0.291 to -0.291x0.2097=-0.0610. Calculated in the same way (theta=18 / (13+18+14+17=0.2903, -0.26x0.2903=-0.0755), equation 1 is obtained as follows, and this formula is used to derive the relationship between light parameters such as frequency (f), color rendering (Ra), color temperature (Color Temperature Index, CTI) and light intensity (I):

[0100] LSS = C1 delta – C2 theta + C3 beta2 – C4 gamma Equation 1

[0101] Among them, coefficients C1 = -0.061, C2 = 0.0755, C3 = 0.0607 and C4 = 0.0945.

[0102] Next, we need to convert equation 1 into an emotion equation related to (f, Ra, CTI, I) in the EEG. First, let the color temperature index of a certain emotion obtained by the fMRI system be a certain value, then

[0103] fMRI(CTI)=LSS

[0104] Next, the EEG is decomposed into four light parameter results, and each light parameter is made equal to the corresponding parameter of fMRI.

[0105]

[0106] Among them, 1 / W freq, 1 / W Ra , 1 / W CTI , 1 / W I It is the adjustment ratio of each light parameter of the fMRI system and the electroencephalogram (EEG).

[0107] Then 1 / W CTI After the normalization process, the weight relationship between the four variable coefficients (a, b, c, d) can be obtained. Then, the final surrounding system score (LSS) formula can be obtained:

[0108] LSS=tx[axf eeg (freq)+bxf eeg (Ra)+cxf eeg (CTI)+dxf eeg (I)]

[0109] …………………………………………Procedure 3

[0110] among,

[0111] a=w freq / w CTI

[0112] b=w Ra / w CTI

[0113] c=w CTI / w CTI =1

[0114] d=w I / w CTI

[0115] t = illumination time. It should be noted that when the illumination time (t) is larger, it means that the user is exposed to the illumination for a longer time, and will have a higher reaction to the emotion. Therefore, in the subsequent description of the present invention, the illumination time (t) is assumed to be 1.

[0116] According to the above formula, the present invention can obtain Figure 4a The light signal parameters of each emotion on the emotion coordinate system. For example, in a preferred embodiment of the present invention under the excitement scenario, the LSS formula is shown in the following equation 4:

[0117] LSS=tx(-0.0002freq 2 +0.0393freq+0.0334Ra-0.2854CTI-0.0000009ΔI 2 +0.0004ΔI-4.4441)Equation 4

[0118] For example, in a preferred embodiment of the present invention under the happiness scenario, the LSS formula is shown in the following equation 5:

[0119] LSS=tx(-0.0002freq 2 +0.0393freq+0.0334Ra-0.6374CTI-0.0000009ΔI 2 +0.0004ΔI-4.4436)Equation 5

[0120] Among them, the above ΔI 2 Refers to the change in light intensity.

[0121] According to the above formula of surrounding system score (LSS), the change of emotion under various light parameters can be obtained, for example:

[0122] ■LSS Example 1: If a 50Hz, Ra=90, 6000K color temperature lamp has an illuminance increase of 200 lux within the user's visual range, after a specific time (t), how excited will the user feel at this time?

[0123] Apply equation 4 and set t = 1, freq = 50 Hz, Ra = 90, CTI = (6000 - 3000) / 3000 = 1, ΔI = 200.

[0124] Then we get

[0125] LSS = -0.1787, which means the excitement level decreased by 0.1787

[0126] ■LSS Example 2: If a 60Hz, Ra=95, 4000K color temperature lamp has an illuminance increase of 400 lux within the user's visual range, after a specific time (t), how excited will the user feel at this time?

[0127] Apply equation 4 and set t = 1, freq = 60 Hz, Ra = 95, CTI = (4000-3000) / 3000 = 0.33, ΔI = 400. Then we get

[0128] LSS = 0.4324, which means the excitement increased by 0.4324.

[0129] ■LSS Example 3: If a 60Hz, Ra=95, 4000K color temperature lamp has an illuminance increase of 400 lux within the user's visual range, how happy will the user feel after a specific time (t) of illumination?

[0130] Apply equation 5 and set t = 1, freq = 60 Hz, Ra = 95, CTI = (4000-4000) / 4000 = 0, ΔI = 400. Then we get

[0131] LSS = 0.5270, which means that happiness increased by 0.5270.

[0132] ■LSS Example 4: If a 50Hz, Ra=85, color temperature 2700K lamp has an illuminance increase of 400 lux within the user's visual range, how happy will the user feel after a specific time (t) of illumination?

[0133] Apply equation 5 and set t = 1, freq = 50 Hz, Ra = 85, CTI = [(2700 - 4000) / 4000] = 0.325, ΔI = 400.

[0134] LSS = -0.1871, which means that happiness decreased by 0.1871.

[0135] From the calculation results of Examples 1 and 2, we can draw a conclusion that there are many different means to achieve the same level of excitement, such as: improving color rendering (Ra), increasing flicker, increasing (or reducing) light intensity (because there is an optimal value) and reducing color temperature, because in the excitement situation, the higher the CTI, the lower the excitement. On the other hand, by adjusting color rendering (Ra), flicker, light intensity and color temperature, we can also get different levels of excitement. In addition, the calculation results of Examples 3 and 4 can also get the same conclusion. At this time, the present invention refers to the "light formula" after combining the lighting parameters such as color rendering (Ra), flicker, light intensity and color temperature as a "multi-spectral formula". Obviously, Equation 3 is the equation of the multi-spectral formula of the present invention, wherein Equation 4 and Equation 5 are just embodiments of the present invention applying Equation 3 to excitement and happiness, and are not used to limit the conditions of Equation 3. In other words, by controlling the "multi-spectral formula" such as color rendering index (Ra), flicker, light intensity and color temperature, the present invention can combine Figure 4a Therefore, when the lighting system constructed by the present invention is in commercial operation, an experienced operator (e.g., a professionally trained technician) can use a workstation or an App on a portable smart device at the lighting field end 620 to adjust the characteristics of the lighting parameters in the surrounding system score (LSS) formula (i.e., equation 3) according to the user's emotions and physiological conditions, and edit a "multi-spectral recipe" for executing lighting, so as to control the lighting system to execute a specific "multi-spectral recipe" lighting program at the lighting field end 620 to meet the user's needs.

[0136] In terms of general emotion conversion methods, when we want to convert emotions, we can convert emotions by giving the "multi-spectrum formula" of the emotions we want to convert. For example, if we want to convert to a happy emotion, according to Table 7 or Figure 4a As shown, a color temperature of 4000K can be directly given. Furthermore, for example, when it is known that the user is currently in a state of nervousness, the user's goal is to convert the emotion to a state of happiness. Intuitively, as long as the 4000K light is continuously applied for a period of time, the user's emotion can reach the level of happiness. However, this is inaccurate, because according to the present invention, under the condition of equation 3, it can be known that for the same emotion, there can be different degrees of expression, and this different degree of expression can be adjusted and obtained by adjusting the lighting parameters of the "multi-spectral formula" such as color rendering (Ra), flicker, light intensity and color temperature.

[0137] Next, the present invention can provide an effective method of emotion transfer through the following process. In the embodiment of the present invention, the user is allowed to change from a nervous emotion to a happy emotion. This process is conducted by using the brain wave graph measured by an electroencephalogram (EEG) to conduct an experiment. Figure 4b to Figure 4e The coordinate sizes in are normalized numbers.

[0138] like Figure 4b As shown in FIG. 1 , it is a relative intensity index diagram of a specific brain wave diagram of the present invention. The relative intensity index of the brain wave diagram is determined using the definition of NeuroSky, wherein the definitions of the brain wave waveform diagram and relative intensity index of emotions related to the present embodiment include: tension, relaxation and happiness, such as Figure 4b As shown. Among them, Figure 4b The brain wave waveform shown is the intensity value (High) of the Beta wave, the weakness value (Low) of the Beta wave, the intensity value (High) of the Alpha wave and the weakness value (Low) of the Alpha wave under a specific condition. It should be noted that in the following experiment, after different light stimulations, the values ​​of the brain wave graph of the same emotion may be different, but the trends of the intensity values ​​of the Beta wave and the Alpha wave are similar. Among them, the calculation method of the relative intensity index of different emotions is also different. Among them, according to the definition of the relative intensity index of the nervous, relaxed and happy emotions by NeuroSky, it includes:

[0139] Relative Strength Index = (BetaHigh+BetaLow) / (AlphaLow+AlphaHigh)

[0140] Relaxed relative strength index = (AlphaLow + AlphaHigh) / (BetaHigh + BetaLow)

[0141] Happiness Relative Strength Index = (AlphaLow + AlphaHigh + BetaHigh) / (BetaLow)

[0142] Next, please refer to Figure 4c , is the EEG of the emotion transfer test 1 of the present invention. The first emotion transfer test is to directly give a happy color temperature of 4000K. The process is to first confirm that the user is already in a nervous mood, for example, requiring the user to answer some math questions completely within 2 minutes, which may make them nervous. When the user's EEG shows Figure 4c After seeing the waveform shown on the left, it is determined that the user is already in a state of nervousness. Then, the user is directly exposed to a color temperature of 4000K for 2 minutes, and the user's brain wave graph is obtained as follows Figure 4c As shown on the right, the relative intensity index of happiness expressed by the brain waves is calculated as 3.34.

[0143] Next, please refer to Figure 4d , is the EEG of the emotion transfer test 2 of the present invention. The second emotion transfer test is conducted to make the user go from nervous to relaxed and then to happy. The process is to first confirm that the user is already in a nervous mood, for example, requiring the user to answer some math questions completely within 2 minutes, which may make them nervous. When the user's EEG shows as follows Figure 4d After the waveform shown on the left, if the user is judged to be in a tense mood, then the user is first exposed to a relaxing spectrum (10Hz orange light) for 5 minutes. After that, the user is exposed to a color temperature of 4000K for 2 minutes, and the user's brain wave graph is obtained as follows Figure 4d As shown in the middle and right sides, the relative intensity index 4 of happiness expressed by the brain waves is then calculated.

[0144] Next, please refer to Figure 4e , is the EEG of the emotion transfer test 3 of the present invention. The third emotion transfer test is conducted to let the user change from nervous to neutral and then to happy. The process is to first confirm that the user is already in a nervous mood, for example, asking the user to answer some math questions completely within 2 minutes, which may make them nervous. When the user's EEG shows as follows Figure 4e After seeing the waveform shown on the left, if the user is judged to be in a tense mood, then a relaxing spectrum (10Hz orange light) is first irradiated for 2 minutes to guide them into a neutral mood by reducing tension. Figure 4eThe middle relaxation brain wave graph shows that its relative intensity index is 1.15, which is lower than the relative intensity index of the second test process. Therefore, it is judged that the user's emotional state at this time has entered a neutral state. Finally, after the user is exposed to a color temperature of 4000K for 2 minutes, the user's brain wave graph is as follows: Figure 4e As shown on the right, the relative intensity index 10 of happiness expressed by the brain waves is then calculated.

[0145] According to the above experimental process, a result can be obtained, that is, after determining that the user is in a tense mood, in the first stage, some other spectra that can relieve the tense mood are given, such as: Table 7 or Figure 4a After the complementary emotional spectrum is irradiated, the second stage of the happy spectrum irradiation can allow the user to obtain a better index of happy emotions. In particular, after further confirming that the user has shifted his emotions to neutral emotions after the first stage of the emotional relief irradiation, the second stage of the happy spectrum irradiation can greatly improve the index of happy emotions. Theoretically, the neutral index (Neutral Index) refers to the BOLD response of the limbic system returning to zero, where neutral emotions are Figure 4a Theoretically, the characteristics of the emotional coordinate graph near the center or origin are that it can keep the average person in a balanced and stable psychological state, and not be swayed by excessive positive or negative emotions, so that they can look at things and problems more objectively. In particular, after the above-mentioned experimental process, if the user can first be exposed to the complementary emotional spectrum in the first stage, and it is judged that the user's emotions have returned to neutral emotions, and then the final desired emotional spectrum is exposed, the best emotional transfer effect can be adjusted. This first confirms the current emotion, and then sets the first stage of the exposure spectrum according to the current emotion. After judging that the user's emotions have reached neutral emotions after the first stage of illumination, the second stage of the final target emotional spectrum is exposed. This path or process of planning to reach the target emotion is called emotional navigation (Motion Navigation).

[0146] In addition, the present invention also found that the change of emotions is not linear. For example, when the physiological conditions of different users are different or the social status of different users is different, different users will have different degrees of response to the same emotion. For example: in terms of physiological conditions, users with epilepsy cannot be stimulated by stroboscopic light, and must be reinforced in terms of color temperature or intensity. For example: in terms of different social status, different experiences of happiness will cause different degrees of response. Therefore, a more rigorous way is that before we provide lighting stimulation for the target emotion, we must consider the user's "current state". This is because for users in different emotional states (degrees), different "multi-spectral formula" stimulations are given by adjusting the lighting parameters in the peripheral system score (LSS) formula to achieve a similar final effect.

[0147] According to the above-mentioned emotion transfer test results, the present invention provides three different emotion transfer paths to execute the emotion navigation process of the present invention.

[0148] ■Emotional Navigation Example 1:

[0149] For example: the user is currently in a state of nervousness, and the goal is to transfer the emotion to happiness.

[0150] The emotional navigation path of the transfer process can be set according to the experience of the user or the instructor. For example: First, the user's current state of tension must be eased, so the user can choose to use the "multi-spectrum formula" of serene for illumination (based on Table 5, 3000K color temperature illumination), and then use the "multi-spectrum formula" of target emotional happiness for illumination (based on Table 5, 4000K color temperature illumination). If the user has reached the vicinity of lust, the illumination process is stopped. For the navigation path of emotional navigation example 1, please refer to Figure 4e Schematic diagram of .

[0151] ■Emotional Navigation Example 2:

[0152] Emotional navigation example 2 is a preferred embodiment of the present invention, especially adding neutral indicators to the emotional navigation program. For example: the user is currently in a stressed state, and the goal is to transfer emotions to excitement. The process of emotional transfer can be divided into two steps:

[0153] The first step is to eliminate the stressed state in order to bring the user's emotions back to neutral or Figure 4a Therefore, according to Figure 4aAs shown in the emotional coordinate diagram, we can choose the Relaxed emotion item that is opposite to the stress emotion to complement it, so we first need to give the "multi-spectrum formula" that can achieve relaxation for illumination (give 10Hz orange light according to Table 5), and monitor the user's physiological signals (such as brain area reactions) at the same time to determine whether the user's emotions have returned to neutral or near the origin. If they have returned to neutral or near the origin, it means that the stress has been eliminated. Alternatively, we can judge whether the user's emotions have returned to neutral or near the origin through interviews or questionnaires with the user. After that,

[0154] Step 2: Give an exciting "multi-spectral formula": After confirming that the user's emotions have returned to neutral or the origin, we will give an exciting "multi-spectral formula" for lighting (give a color temperature of 3000K lighting according to Table 5). At the same time, monitor the user's physiological signals (such as brain area reactions) to determine whether the user's emotions have reached the level of excitement. If the user's emotions have reached the level of excitement, the lighting process will be stopped. For the navigation path of emotional navigation example 2, please refer to Figure 4f Schematic diagram of .

[0155] ■Emotional Navigation Example 3:

[0156] The present invention continues to disclose another preferred embodiment, for example: the user is currently in a state of sadness, and the goal is to transfer emotions to erotic. The transfer process includes two steps:

[0157] The first step is to eliminate the state of sadness in order to bring the user's emotions back to neutral or the starting point. Figure 4a As shown in the emotional coordinate diagram, we can choose the happiness emotion item that is opposite to sadness to complement it. Therefore, we must first provide the "multi-spectrum formula" that can achieve happiness for lighting (based on Table 5, provide lighting with a color temperature of 4000K), and at the same time monitor the user's physiological signals (such as brain area reactions) to determine whether the user's emotions have returned to neutral or near the origin. If they have returned to neutral or near the origin, it means that sadness has been eliminated. After that,

[0158] Step 2: Give the "multi-spectrum formula" of lust: After the user's emotions return to the starting point, give the "multi-spectrum formula" of lust for lighting (given the light with a strobe frequency of 4-7Hz and a color temperature of 3500K according to Table 5). At the same time, monitor the user's physiological signals (such as brain area reactions) to determine whether the user's emotions have reached the level of lust. If the user has reached the level of lust, stop the lighting process. For the navigation path of emotional navigation example 3, please refer to Figure 4g Schematic diagram of .

[0159] The above are all examples of the emotion navigation disclosed by the present invention, and the purpose is to explain the concept of the emotion navigation execution of the present invention in a concise way. In practice, according to the physiological conditions or different life experiences of different users, it may be necessary to navigate to the target emotion through multiple emotion conversions. At this time, the ultimate goal of emotion navigation can be achieved by adjusting the color rendering (Ra), strobe, light intensity and color temperature. Therefore, the present invention does not limit how many emotion conversions are required to reach the target emotion.

[0160] Next, the present invention will further disclose preferred embodiments that can be specifically operated.

[0161] According to the above, it is obvious that when the present invention performs emotion navigation, it is necessary to first know the user's emotional state at the time of emotion conversion (i.e., the current emotional state), and then the emotional changes during the emotion navigation process, and whether the target emotion is finally reached. The emotional states in these stages must be recorded using a physiological monitoring device as a basis for correcting the emotion navigation path. Among them, the physiological monitoring device described in the present invention can be an electroencephalogram (EEG) or a wearable electronic device (e.g., a mobile phone or a wearable device, etc.) or choose to use an emotion picture library) for stimulation, such as the International Affection Picture System (IAPS).

[0162] Next, please refer to Figure 5 , is a method of performing emotional navigation of the present invention. First, as shown in step 3510, the user's "initial emotion" is confirmed first. For example, the user is in the illumination field end 620, and after the wearable electroencephalogram 130 measures the brain waves, the user's current "initial emotion" is displayed according to the brain wave recording data. For example, the "initial emotion" is in a nervous state. Among them, the "initial emotion" has been uploaded through the electroencephalogram 130 and stored in the memory module 617 of the cloud 610 (such as Figure 3 Then, proceed to step 3520.

[0163] Step 3520: Setting the "target emotion". When the user wants to adjust or convert the "initial emotion" to happiness, the user can set the "target emotion" to happiness through the client device 630 in the intelligent human factor lighting system 600. After that, it will be uploaded and stored in the memory module 617 of the cloud 610 through the client device 630. Then, proceed to step 3530.

[0164] Step 3530: Select "relay emotion" to complete the setting of the emotion navigation path. According to the user's "initial emotion" and "target emotion", one or more "relay emotions" different from the "initial emotion" or "target emotion" are selected from the management control module 611 of the cloud 610 through the client device 630 to form a sequence from "initial emotion" to "relay emotion" and then to "target emotion", and this sequence is called "emotion navigation path". For example: when the user's "initial emotion" is in a state of tension, and it has been confirmed that the "target emotion" is happy, then the client device 630 can select serene as the "relay emotion" in the management control module 611 of the cloud 610, so that the "emotion navigation path" is from tension to serene and then to happiness. Or the "relay emotion" is selected to go through calm (Calm) first and then to serene, so that the "emotion navigation path" is from tension to calm to serene, and finally to happiness. The “relay emotion” in the above-mentioned setting of the emotion navigation path can be selected by the user based on his / her own experience, or by professionals based on the user's “initial emotion” and “target emotion”. Next, step 3540 is performed.

[0165] Step 3540: Edit the "multi-spectral formula" according to the emotional navigation path. When the "emotional navigation path" has been confirmed in step 3530, it is necessary to find the multi-spectral formula corresponding to the "relay emotion" and the "target emotion". Figure 4a When the emotion coordinate information of the target emotion has been stored in the memory module 617 of the cloud 610, the user finds the "multi-spectral formula" corresponding to the "relay emotion" and the "target emotion" in the cloud environment module 615 through the client device 630 in the intelligent human factor lighting system 600, including: a "multi-spectral formula" (3000K color temperature) for providing a peaceful emotion, or a "multi-spectral formula" (3000K color temperature with a strobe of 4Hz and an illumination of less than 7lux) for providing a calm emotion, and a "multi-spectral formula" (4000K color temperature) for a happy emotion. The client device 630 can be a smart phone, a personal digital assistant (PDA), a notebook computer (NB), or a personal computer (PC) in a workstation. Then, step 3550 is performed. It should be particularly noted that in the process of editing the "multi-spectral formula" mentioned above, the "multi-spectral formula" for executing lighting is edited by adjusting the characteristics of the lighting parameters in the surrounding system score (LSS) formula one by one.

[0166] Step 3550: Execute the lighting program of the "multi-spectrum formula". When executing the lighting program, the intelligent human-factor lighting system 600 of the present invention can be controlled through two control paths. One of the control paths is to control the lamp group 621 in the lighting field end 620 through the client device 630 to perform the lighting process on the user in sequence according to the "multi-spectrum formula" corresponding to the "relay emotion" and the "target emotion". The other control path is to control the lamp group 621 in the lighting field end 620 through the intelligent Internet of Things (AIoT) through the management control module 611 in the cloud 610 to perform the lighting process on the user in sequence according to the "multi-spectrum formula" corresponding to the edited "relay emotion" and the "target emotion". For example: Both control methods are to illuminate the user's "relay emotion" for 10 minutes, and then illuminate the user's "target emotion" for 15 minutes.

[0167] Step 3560: if it is determined that the user's emotion has reached the "target emotion", go to step 3570; if it is determined that the user's emotion has not reached the "target emotion", go to step 3580;

[0168] Step 3570: Stop the illumination process. If it is determined that the user's emotion has reached the "target emotion", the illumination process is stopped. The determination in step 3560 is based on the information displayed by the physiological monitoring device configured on the user, wherein the physiological monitoring device can be an electroencephalogram or a wearable device that can measure sympathetic and parasympathetic nerve signals.

[0169] Step 3580: If it is determined that the user's emotion has not reached the "target emotion", the information displayed by the physiological monitoring device configured on the user can be checked to adjust it. According to the "emotion navigation path", it is determined which section (i.e., the "relay emotion" or "target emotion" section) has not reached the set emotion. Then, the management control module 611 from the client device 630 to the cloud 610 can be used to adjust the emotion of the section that has not reached the set emotion. After that, a new "emotion navigation path" can be reset. For example, if the originally set "emotion navigation path" is from calm to serene, then the physiological monitoring device is checked in the lighting interval from calm to serene. If it is calm or serene that has not reached the set emotion, then these emotions are adjusted. The adjustment method can be that the management control module 611 selects a new "relay emotion" near the set emotion. For example, if the inspection result is calmness and does not reach the set emotion, then relax is selected as the new "relay emotion". Then, steps 3540 to 3560 are repeated. After returning to step 3530, a new "emotion navigation path" is formed from tension to relaxation, then to tranquility, and finally to happiness. Finally, when it is determined that the user's emotion has reached the "target emotion", step 3570 is performed to stop the lighting program. In a preferred embodiment, the selection of a new "relay emotion" can be in the client device 630 or the management control module 611 of the cloud 610, and the lighting parameters of the "multi-spectral formula" such as (color rendering index-Ra, strobe, light intensity or color temperature) are adjusted through the above equation 3. For example, increasing the color rendering index (Ra) can make the calm emotion reach a stronger level.

[0170] In addition, if the physiological monitoring device has determined which segment has not reached the set emotion in step 3580, the client device 630 can further proceed to step 3590 to obtain the user's personal physiological data stored in the cloud 610, such as the physiological data of the user's health check. For another example, when the physiological data of the health check shows that the user suffers from hypertension, diabetes or epilepsy, the parameters of the "multi-spectral formula" in equation 3 (color rendering index-Ra, flicker, light intensity or color temperature, etc.) can be adjusted according to these diseases. For example, when the user suffers from epilepsy, since flicker will stimulate epilepsy and may induce epilepsy, in equation 3, color rendering index-Ra, color temperature or intensity must be reinforced. Afterwards, repeat steps 3530 to 3560, find a new "relay emotion" that can be adjusted to the "target emotion" according to the user's physiological signal data, and form a new "emotion navigation path" until it is determined that the user's emotion has reached the "target emotion", then proceed to step 3570 to stop the lighting program.

[0171] It should be emphasized that when the present invention uses the physiological data of health examination to adjust the lighting parameters of the "multi-spectral formula" such as (color rendering - Ra, flicker, light intensity or color temperature) in equation 3, the restrictions on the lighting parameters of the "multi-spectral formula" corresponding to each disease (color rendering - Ra, flicker, light intensity or color temperature, etc.) can be adjusted according to medical information. For example, too low color temperature will affect the user's visual clarity. Therefore, when the user needs exciting stimulation in the working environment, lowering the color temperature is not the best means, but should be strengthened in other parameter items, such as giving a higher color rendering (Ra) to compensate for the need to use too low color temperature parameters to maintain excitement to a certain extent. Therefore, in the above-mentioned embodiment of the present invention, the restriction condition of using flicker on epilepsy patients is only an example, and is not used to limit the present invention to the embodiment of epilepsy through the adjustment of the parameters of the "multi-spectral formula" such as (color rendering - Ra, flicker, light intensity or color temperature) in equation 3.

[0172] Furthermore, since the client device 630 and the cloud 610 in the intelligent human factor lighting system 600 of the present invention use the intelligent Internet of Things (AIoT) for communication, the "emotional navigation paths" used by many users will be stored in the cloud environment module 615 to form a large amount of data. For example, after the large amount of data stored in the private cloud 6151 or the public cloud 6153 is calculated by the artificial intelligence algorithm, the "emotional navigation paths" most used by the most people in various emotion conversion processes can be obtained. Therefore, when the current user wants to perform a specific emotion conversion, the client device 630 can be used to find the "emotional navigation path" most used in the data of the specific emotion conversion from the private cloud 6151 or the public cloud 6153, as a shortcut path for providing step 3530: completing the setting of the emotion navigation path. Obviously, since the "emotional navigation path" of the present invention is operated through a network platform and also provides public cloud services, the intelligent human factor lighting system 600 of the present invention is very suitable for various professionals to provide better "emotional navigation path" services through the cloud platform.

[0173] Please refer to Figure 6 , is another method for performing emotion navigation of the present invention.

[0174] First, execute step 4510: first confirm the "initial emotion". The detailed process is the same as step 3510, so please refer to step 3510 and do not repeat it. Among them, the "initial emotion" is in a stressed state. Then, proceed to step 4520.

[0175] Step 4520: Set the "target emotion" again. The detailed process is the same as step 3520, so please refer to step 3520 and will not be repeated. The "target emotion" is set to excitement. Then, proceed to step 4530.

[0176] Step 4530: Select "Relay Emotion" to complete the "Emotion Navigation Path" setting. In this embodiment, step 4530 is based on the process of Emotion Navigation Example 2 and Emotion Navigation Example 3 to set the "Emotion Navigation Path". For example: Take Emotion Navigation Example 2 as an example. When the user has confirmed in step 4510 that the "initial emotion" is in a stressful state, and in step 4520, has also confirmed that the emotion is to be transferred to the excited "target emotion". Then, through the client device 630 to the management control module 611 of the cloud 610, choose to set the "Emotion Navigation Path", where the first step is to eliminate the stressful state in order to pull the user's emotions back to neutral (Neutral) or the origin. Therefore, in this embodiment, it is based on Figure 4a As shown in the emotion coordinate diagram, the relaxed emotion item corresponding to the stress can be selected as the "relay emotion" of this embodiment. At this time, the "emotion navigation path" completed in this step is from the stress of the "initial emotion" to the relaxation of the "relay emotion" and then to the excitement of the "target emotion". Of course, the "relay emotion" in this embodiment can also be a combination of more than one different emotions. For example, the "relay emotion" can first select the corresponding calm emotion, and then further select the relaxed emotion. Therefore, the setting of the "emotion navigation path" in this embodiment is to transfer from the stress of the "initial emotion" to the calmness and relaxation of the "relay emotion" and then to the excitement of the "target emotion". Therefore, the present invention does not limit the number of combinations of "relay emotions". Next, proceed to step 4540.

[0177] Step 4540: Edit the "multi-spectral formula" according to the emotion navigation path. When the "emotion navigation path" has been confirmed in step 4530, it is necessary to find the multi-spectral formula corresponding to the "relay emotion" and the "target emotion". Figure 4aWhen the emotion coordinate information of the target emotion has been stored in the cloud environment module 615, the user finds the "multi-spectral formula" corresponding to the "relay emotion" and the "target emotion" in the cloud environment module 615 through the client device 630, including: a "multi-spectral formula" for providing a relaxing emotion (orange light with a flash frequency of 10Hz), and a "multi-spectral formula" for providing excitement (color temperature of 3000K). Among them, the client device 630 can be a smart phone or a personal digital assistant (PDA), a notebook computer (NB), or a personal computer (PC) in a workstation. After that, step 4550 is performed. It should be particularly noted that in the process of editing the "multi-spectral formula" in step 4540, the "multi-spectral formula" for executing lighting is edited by adjusting the characteristics of the lighting parameters in the surrounding system score (LSS) formula one by one.

[0178] Step 4550: Execute the first stage of lighting. According to the "emotional navigation path" set in step 4530, the lamp group 621 in the lighting field end 620 is controlled through the client device 630 or the management control module 611 in the cloud 610, and then through the intelligent Internet of Things (AIoT). In this embodiment, the execution of the first stage of lighting is to first execute the lighting program of the edited relaxing emotion "multi-spectrum formula" (orange light with a flash frequency of 10Hz). For example: after irradiating the user with the edited relaxing emotion "multi-spectrum formula" for 10 minutes, the lighting program is stopped first, and the first stage of the multi-spectrum formula irradiation program is completed. If the "relay emotion" is a combination of more than one different emotions, it is also necessary to irradiate the user with these multiple different emotions before stopping the lighting program. After that, proceed to step 4560.

[0179] Step 4560: Determine whether the user's stress has been eliminated. This is based on the physiological monitoring device determining whether the user's current mood has been adjusted to the level after the first stage of illumination. Figure 4c If the user's emotion after the first stage of illumination does not reach the neutral or origin point of the emotion coordinate information, Figure 4c When the emotional coordinates are neutral or near the origin, it means that the stress emotion has not been completely eliminated, and then step 4570 is executed. Figure 4c When the emotion coordinates are neutral or near the origin, execute step 4580.

[0180] Step 4570: If it is determined that the user's emotions have not reached "neutral or origin", the user's personal physiological data (e.g., physiological data of the user's health check) can be further examined to adjust the "relay emotions". In a preferred embodiment, the client device 630 obtains the user's personal physiological data stored in the memory module 617 from the cloud 610, such as the physiological data of the user's health check. Afterwards, according to the information on the user's personal physiological data, the lighting parameters in the peripheral system score (LSS) formula of the "relay emotions" are adjusted. For example, when the physiological data of the health check show that the user suffers from hypertension, diabetes or epilepsy, the lighting parameters of the "multi-spectral formula" in equation 3 (color rendering-Ra, flicker, light intensity or color temperature, etc.) can be adjusted according to these diseases. Then, return to step 4530, and a new "emotion navigation path" will be formed. Afterwards, steps 4550 and 4560 are repeated until it is determined that the user's emotions have reached "neutral or origin", and then step 4580 is performed.

[0181] Step 4580: Execute the second-stage multi-spectral formula irradiation program. According to the multi-spectral formula of the "emotional navigation path" in step 4540, the lighting program of the "multi-spectral formula" (3000K color temperature) of excitement is executed by controlling the lamp group 621 in the lighting field end 620 through the intelligent Internet of Things (AIoT) through the client device 630 or the management control module 611 in the cloud 610. For example, after irradiating the user with the "multi-spectral formula" of excitement for 15 minutes, the lighting program is stopped, and the second-stage multi-spectral formula irradiation program is completed. Then, step 4590 is performed.

[0182] Step 4590: If it is determined that the user's emotion has reached the "target emotion", go to step 4610. If it is determined that the user's emotion has not reached the "target emotion", return to step 4530, and the client device 630 goes to step 4570 to obtain the user's personal physiological data stored in the cloud 610, such as: the user's physiological data of the health check. Afterwards, according to the information on the user's personal physiological data, adjust the lighting parameters in the "multi-spectral recipe" of the "target emotion". For example, if the physiological data of the health check shows that the user suffers from hypertension, diabetes or epilepsy, the lighting parameters of the "multi-spectral recipe" in equation 3 (color rendering index-Ra, flicker, light intensity or color temperature, etc.) can be adjusted according to these diseases, and then stored in the cloud 610. Next, go directly to step 4580, where the user uses the client device 630 to find the lighting parameters of the "multi-spectral recipe" corresponding to the adjusted "target emotion" in the cloud 610. Thereafter, steps 4580 and 4590 are repeated until it is determined that the user's emotion has reached the "target emotion", then step 4610 is performed: stop the lighting program.

[0183] Please refer to Figure 7 , which is the third method of performing emotion navigation of the present invention.

[0184] First, execute step 6510: confirm the "initial emotion". The detailed process is the same as step 4510, so please refer to step 4510 and do not repeat it. Among them, the "initial emotion" is in a stressed state. Then, proceed to step 6520.

[0185] Step 6520: Set the "target emotion" again. The detailed process is the same as step 4520, so please refer to step 4520 and do not repeat it. The "target emotion" is set to excitement. Then, proceed to step 6530.

[0186] Step 6530: Obtain the user's personal physiological data. The client device 630 obtains the user's personal physiological data stored in the memory module 617 from the cloud 610, such as the user's physiological data from a health checkup. Then, step 6540 is performed.

[0187] Step 6540: Select "Relay Emotion" to complete the "Emotion Navigation Path" setting. In this embodiment, the emotion navigation example 2 is used as an example. After the user has confirmed in step 6510 that the "initial emotion" is in a stressful state, and in step 6520, has also confirmed that the emotion is to be transferred to the excited "target emotion". Then, through the client device 630 to the management control module 611 of the cloud 610, choose to set the "Emotion Navigation Path", where the first step is to eliminate the stressful state in order to pull the user's emotions back to neutral (Neutral) or the origin. Therefore, in this embodiment, it is based on Figure 4a As shown in the emotional coordinate diagram, the Relaxed emotional item corresponding to stress can be selected as the "relay emotion" of this embodiment. In addition, in this embodiment, the management control module 611 of the cloud 610 will also simultaneously review the user's personal physiological data, and adjust the parameters in the "multi-spectral formula" of the "relay emotion" according to the information on the user's personal physiological data. For example: when the user suffers from epilepsy, since the strobe will stimulate epilepsy and may induce epilepsy, in equation 3, the proportion of strobe must be reduced or removed, so it is necessary to strengthen the color rendering -Ra, color temperature or intensity to generate a new "relay emotion". At this time, the "emotion navigation path" completed in this step is from the stress emotion of the "initial emotion" to the adjusted relaxation emotion of the "relay emotion" and then to the excitement of the "target emotion", wherein the parameters of the "multi-spectral formula" of the adjusted relaxation emotion are adjusted by the user's personal physiological data. Next, step 6550 is performed.

[0188] Step 6550: Edit the multispectral formula according to the "emotional navigation path". After the "emotional navigation path" has been confirmed in step 6530, it is necessary to find the multispectral formula corresponding to the "relay emotion" and the "target emotion". Figure 4aWhen the emotion coordinate information of the target emotion has been stored in the cloud environment module 615, the user finds the "multi-spectral formula" corresponding to the "relay emotion" and the "target emotion" in the cloud environment module 615 through the client device 630, including: providing a "multi-spectral formula" for relaxing emotions after adjustment, and providing a "multi-spectral formula" for excitement (color temperature of 3000K). Among them, the "multi-spectral formula" for relaxing emotions after adjustment is to adjust the parameters of the "multi-spectral formula" such as Ra, light intensity or color temperature in equation 3. In addition, the client device 630 can be a smart phone or a personal digital assistant (PDA), a notebook computer (NB) or a personal computer (PC) in a workstation. After that, step 6560 is performed. It should be particularly noted that in the process of editing the "multi-spectral formula" in step 6550, the "multi-spectral formula" for performing lighting is edited by adjusting the characteristics of the lighting parameters in the surrounding system score (LSS) formula one by one.

[0189] Step 6560: Execute the first stage of lighting. After completing the editing of the multi-spectral recipe of the "emotional navigation path" in step 6550, the lighting set 621 in the lighting field end 620 is controlled through the client device 630 or the management control module 611 in the cloud 610, and then through the intelligent Internet of Things (AIoT). In this embodiment, the execution of the first stage of lighting is to only execute the lighting program of the edited relaxing emotion "multi-spectral recipe" first. For example: after irradiating the user with the "multi-spectral recipe" of relaxing emotions for 15 minutes, the lighting program is stopped first, and the first stage of the multi-spectral recipe irradiation program is completed. If the "relay emotion" is a combination of more than one different emotions, it is also necessary to irradiate the user with these multiple different emotions before stopping the lighting program. Afterwards, proceed to step 6570.

[0190] Step 6570: Determine whether the user's stress has been eliminated. The physiological monitoring device determines whether the user's current mood has been adjusted to neutral or the origin after the first stage of illumination. If the user's mood has not reached the neutral or origin point after the first stage of illumination, the physiological monitoring device determines whether the user's mood has been adjusted to neutral or the origin point. Figure 4c When the emotional coordinates are at the neutral or origin, it means that the stress emotion has not been completely eliminated, and then return to step 6530. Figure 4c When the emotion coordinate is neutral or the origin, execute step 6580.

[0191] If step 6570 determines that the user's emotion has not reached "neutral or origin", it will return to step 6530, and the user's personal physiological data (for example: the physiological data of the user's health check) can be further checked to adjust the "relay emotion". In a preferred embodiment, the client device 630 obtains the user's physiological data stored in the memory module 617 from the cloud 610. Afterwards, according to the information on the user's health check, the lighting parameters in the peripheral system score (LSS) formula of the "relay emotion" are adjusted again. For example, when the physiological data of the health check show that the user suffers from hypertension or diabetes, the lighting parameters of the "multi-spectral formula" in equation 3 (color rendering-Ra, flicker, light intensity or color temperature, etc.) can be adjusted according to these diseases. Afterwards, steps 6540 and 6570 are repeated until it is determined that the user's emotion has reached "neutral or origin", and then step 6580 is performed. Obviously, when adjusting the lighting parameters of the "multi-spectral recipe" corresponding to the "relay emotion" again, you can choose not to change the original "emotion navigation path" setting in step 6540, that is, only adjust the lighting parameters of the originally set "relay emotion".

[0192] Step 6580: Execute the second-stage multi-spectral formula irradiation program. According to the multi-spectral formula of the "emotional navigation path" in step 6550, the lighting program of the "multi-spectral formula" (3000K color temperature) of excitement is executed by controlling the lamp group 621 in the lighting field end 620 through the intelligent Internet of Things (AIoT) through the client device 630 or the management control module 611 in the cloud 610. For example, after irradiating the user with the "multi-spectral formula" of excitement for 15 minutes, the lighting program is stopped, and the second-stage multi-spectral formula irradiation program is completed. Then, step 6590 is performed.

[0193] Step 6590: If it is determined that the user's emotion has reached the "target emotion", go to step 6610. If it is determined that the user's emotion has not reached the "target emotion", return to step 6530, and the client device 630 obtains the physiological data of the user's health check that has been stored in the cloud 610. Afterwards, according to the information on the personal physiological data of the user's health check, adjust the lighting parameters in the "multi-spectral recipe" of the "target emotion". For example: when the physiological data of the health check shows that the user suffers from hypertension, diabetes or epilepsy, the lighting parameters of the "multi-spectral recipe" in equation 3 (color rendering index-Ra, flicker, light intensity or color temperature, etc.) can be adjusted according to these diseases to obtain the adjusted "target emotion", which is then stored in the cloud 610. Then, the process directly proceeds to step 6550, where the user uses the client device 630 to find the lighting parameters of the "multi-spectral recipe" corresponding to the adjusted "target emotion" in the cloud 610, and then repeats steps 6590 to 6530 to 6550, and then directly proceeds to step 6580 from step 6550 until the user's emotion reaches the "target emotion". Then, the process proceeds to step 6610.

[0194] Step 6610: Stop the illumination process.

[0195] Finally, it is also necessary to reiterate that when the present invention uses the physiological data of health examination to adjust the parameters of the "multi-spectral formula" such as (color rendering - Ra, flicker, light intensity or color temperature) in equation 3, the restrictions of the parameters of the "multi-spectral formula" such as (color rendering - Ra, flicker, light intensity or color temperature) corresponding to each disease can be adjusted according to medical information. For example, too low color temperature will affect the clarity of the user's vision. Therefore, when the user needs exciting stimulation in the working environment, then lowering the color temperature is not the best means, but should be strengthened in other parameter items, such as: giving a higher color rendering (Ra) to compensate for the need to use too low color temperature parameters to achieve the excitement. Maintaining a certain degree of excitement. Therefore, in the above embodiment of the present invention, the restriction condition of using flicker on epilepsy patients is only an example, and is not used to limit the present invention to the embodiment of epilepsy through the adjustment of the parameters of the "multi-spectral formula" such as (color rendering - Ra, flicker, light intensity or color temperature) in equation 3.

[0196] Finally, it should be emphasized 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 clear and implementable to those with ordinary knowledge in the relevant technical field, so other equivalent changes or modifications that do not deviate from the concept disclosed by the present invention should be included in the scope of the patent claims of the present invention.

Claims

1. A method for performing emotional navigation is performed by an intelligent human-factor lighting system, wherein the human-factor lighting system is composed of a cloud, a lighting field end, and a client device and is interconnected via the Internet, and the cloud stores emotional coordinate information, wherein: The emotion navigation method is characterized by: Step S1, confirming the "initial emotion" of the user, is to confirm the "initial emotion" of the user at the illumination field end through a physiological monitoring device or by selecting to use IAPS stimulation, and store the "initial emotion" in the cloud; Step S2, setting the "target emotion", is to set it on the client device according to the needs of the user, and store the "target emotion" in the cloud; Step S3, selecting "relay emotion" to complete the emotion navigation path setting, is that the client device is connected to the cloud through the Internet, and the "relay emotion" is selected from the emotion coordinate information in the cloud, and the "relay emotion" is stored in the cloud; Step S4, editing the "multi-spectral formula", is to edit the "multi-spectral formula" corresponding to the "target emotion" and the "multi-spectral formula" corresponding to the "relay emotion" according to the light formula on the "relay emotion" selected by the emotion navigation path and the "target emotion"; Step S5, executing the lighting program of the "multi-spectrum recipe" corresponding to the "relay emotion", is to control the lamp group in the lighting field end through the client device to perform a lighting process for a set time on the user according to the "multi-spectrum recipe" corresponding to the "relay emotion"; Step S6, determining whether the user has reached a "neutral emotion", wherein the physiological monitoring device is used to determine whether the user's emotion has reached the "neutral emotion"; Step S7, executing the lighting program of the "multi-spectral formula" corresponding to the "target emotion", is to control the lamp group in the lighting field end through the client device to perform a lighting process for a set time on the user according to the "multi-spectral formula" corresponding to the "target emotion" after determining that the user has reached the "neutral emotion"; Step S8, determining whether the "target emotion" has been reached, by using a physiological monitoring device to determine whether the user's emotion has reached the "target emotion"; Step S9, stopping the lighting process, is to stop the lighting process when it is determined that the user's emotion has reached the "target emotion".

2. The method of emotion navigation as claimed in claim 1, characterized in that :The "relay emotion" in step S3 is an emotion selected to complement the "initial emotion" of the user.

3. The method of emotion navigation as claimed in claim 1, characterized in that :When judging whether the user's emotion has reached the "neutral emotion", it is to judge whether the user's emotion is neutral or near the origin.

4. The method of emotion navigation as claimed in claim 1, characterized in that If it is determined that the user's emotion has not reached the "neutral emotion", the method further includes step S10, providing personal physiological data of the user.

5. The method of emotion navigation as claimed in claim 4, characterized in that :The personal physiological data of the user is a physiological data of the user's health check.

6. The method of emotion navigation as claimed in claim 4, characterized in that If it is determined that the user's emotion has not reached the "neutral emotion", the "multi-spectral formula" corresponding to the "relay emotion" is adjusted according to the user's personal physiological data, and steps S5 to S6 are re-executed.

7. The method of emotion navigation as claimed in claim 1, characterized in that The physiological monitoring device may be an electroencephalogram (EEG) or a wearable electronic device, including a smart phone or a wearable device or a wearable device capable of measuring sympathetic and parasympathetic nerve signals.

8. The method of emotion navigation as claimed in claim 1, characterized in that The "multi-spectrum formula" is composed of at least the following light parameters, including the color temperature, illumination, flicker frequency, and color rendering index (Ra) of the lighting.

9. The method of emotion navigation as claimed in claim 8, characterized in that The "multi-spectral formula" is a formula formed by the surrounding system score (LSS): LSS=tx[axf eeg (freq)+bxf eeg (Ra)+cxf eeg (CTI)+dxf eeg (I)], where a, b, c, d are the coefficients of variation, CTI is the color temperature, and t is the illumination time.

10. The method of emotion navigation according to claim 1, characterized in that: When determining whether the user's emotion reaches the "neutral emotion", it is determined whether the user's emotion is close to the center point or the origin of the emotion coordinate graph.

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