Method of performing emotional navigation using personal physiological data

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, and emotion coordinate information and personal physiological data of a user are stored in the cloud end. The emotion navigation method comprises the following steps: firstly, confirming an initial emotion of a user, and storing the initial emotion to a cloud end; then, setting a target emotion according to a user demand, and synchronizing the target emotion to the cloud; and then, obtaining personal physiological data of the user from the cloud, and selecting a relay emotion to complete emotion navigation path setting. And editing a multispectral formula according to the emotion path, and executing an illumination program of relaying the emotion. And then, judging whether a neutral emotion is reached or not, if so, executing an irradiation program of the target emotion, and finally, confirming whether the target emotion is reached or not and stopping the irradiation program.

Description

Technical Field

[0001] The present invention provides a smart human factor lighting method, especially a smart human factor lighting method that measures the emotional state through human physiological signals and then adjusts the emission spectrum, and further achieves emotional navigation for transferring emotions through the process of smart human factor lighting. Background Art

[0002] Humans are animals with variable emotions and will have different emotional reactions according to their personal psychological states. For example, excitement, amusement, anger, disgust, fear, happiness, sadness, serenity, or neutrality, etc. When negative emotions (such as anger, disgust, fear) cannot be resolved in a timely manner, they will cause psychological harm or trauma to the human body, and finally develop into mental illnesses. Therefore, how to timely provide an emotional relief, relaxation, or treatment system that meets the needs of users has a vast business opportunity in today's society full of high competition and high pressure at any time.

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

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

[0005] According to the above description, the present invention provides a method for establishing a correlation between the brain wave pattern of an electroencephalogram (EEG) and the blood oxygenation level-dependent (BOLD) of a functional magnetic resonance imaging (fMRI) system. After establishing the correlation, the brain wave pattern of the electroencephalogram (EEG) can be used to apply an intelligent human factors lighting system as a shared platform for providing human factors lighting. Then, the present invention further provides a method and system for emotion navigation that can achieve the transfer of the user's emotions through the process of intelligent human factors lighting.

[0006] The present invention first provides a method for performing emotion navigation using an intelligent human factors lighting system, including: in step one, first confirm the "initial emotion", and then, in step two, set the "target emotion", and in step three, determine the "relay emotion" to complete the setting of the "emotion navigation path". After that, in step four, edit a multi-spectral 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 multi-spectral formula. Step six: If it is determined that the "target emotion" has not been reached, further provide the physiological signal data of the user, and according to the physiological signal data of the user, find the corresponding multi-spectral formula of the emotion that can be adjusted to the "target emotion", 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 further provides a method for performing emotion navigation using an intelligent human factors lighting system, which is executed by an intelligent human factors lighting system. The human factors lighting system is composed of a cloud, a lighting field end, and a client device and is interconnected through the Internet. The cloud stores emotion coordinate information. The characteristics of the emotion navigation method are as follows:

[0008] Step one, confirm the "initial emotion" of the user, which is to confirm the "initial emotion" of the user through a physiological monitoring device or by selecting to use IAPS stimulation at the lighting field end, and store the "initial emotion" in the cloud;

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

[0010] Step 3, selecting a "relay emotion" to complete the emotion navigation path setting, is that the client device connects to the cloud through the Internet, selects the "relay emotion" from the emotion coordinate information in the cloud, and stores 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 "target emotion" selected by the emotion navigation path;

[0012] Step 5, executing the light irradiation procedure of the "multi-spectral formula" corresponding to the "relay emotion", is to control the lamp group in the light irradiation field end by the client device to perform a light irradiation process on the user for a set time according to the "multi-spectral formula" corresponding to the "relay emotion";

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

[0014] Step 7, executing the light irradiation procedure of the "multi-spectral formula" corresponding to the "target emotion", is to control the lamp group in the light irradiation field end by the client device to perform a light irradiation process on the user for a set time 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 9, stopping the light irradiation procedure, is to stop the light irradiation procedure when it is determined that the user's emotion has reached the "target emotion".

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

[0018] Step 1: Confirm the user's "initial emotion". This is done at the light irradiation field end by a physiological monitoring device or by choosing to use IAPS stimulation to confirm the user's "initial emotion", and storing the "initial emotion" in the cloud.

[0019] Step 2: Set the "target emotion". This is set on the client device according to the user's needs, and the "target emotion" is stored in the cloud.

[0020] Step 3: Obtain the user's personal physiological data. This is obtained by the client device from the cloud, where the user's personal physiological data has been stored in the memory module.

[0021] Step 4: Select a "relay emotion" to complete the emotion navigation path setting. This is done by the client device connecting to the cloud via the Internet, selecting the "relay emotion" from the emotion coordinate information in the cloud, and storing the "relay emotion" in the cloud.

[0022] Step 5: Edit the "multi - spectral formula". This is done according to the light formula for the "relay emotion" and "target emotion" selected in the emotion navigation path, as well as the information on the user's personal physiological data, to edit the "multi - spectral formula" corresponding to the "target emotion" and the "multi - spectral formula" corresponding to the "relay emotion".

[0023] Step 6: Execute the light irradiation procedure for the "multi - spectral formula" of the "relay emotion". This is done by the client device controlling the lamp group in the light irradiation field end to perform a light irradiation process on the user for a set time according to the "multi - spectral formula" corresponding to the "relay emotion".

[0024] Step 7: Determine whether the "neutral emotion" has been reached. This is done by a physiological monitoring device to determine whether the user's emotion has reached the "neutral emotion".

[0025] Step 8: Execute the light irradiation procedure for the "multi - spectral formula" of the "target emotion". This is done after determining that the user has reached the "neutral emotion", by the client device controlling the lamp group in the light irradiation field end to perform a light irradiation process on the user for a set time according to the "multi - spectral formula" corresponding to the "target emotion".

[0026] Step 9: Determine whether the "target emotion" has been reached. This is done by a physiological monitoring device to determine whether the user's emotion has reached the "target emotion".

[0027] Step 10: Stop the light irradiation procedure. This is done when it is determined that the user's emotion has reached the "target emotion", and the light irradiation procedure is stopped.

[0028] In the above method for performing emotion navigation, the personal physiological data of the user can be further used as the illumination parameter adjustment for the "multi-spectral formula".

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

[0030] In the above method for performing emotion navigation, the "multi-spectral formula" is a formula formed by a Peripheral System Score (LSS):

[0031] LSS = t x [a x f eeg (freq) + b x f eeg (Ra) + c x f eeg (CTI) + d x f eeg (I)], where a, b, c, d are variable coefficients, CTI is the color temperature, and t is the illumination time.

[0032] The present invention has provided a result of emotion navigation, that is, after determining the current emotion of the user, in the first stage, some relay emotion spectra with complementary emotions to the initial emotion are irradiated first, and then in the second stage, the spectrum of the target emotion is irradiated, which can enable the user to reach the index of the target emotion. In particular, when it is further confirmed that the user has transferred the emotion to a neutral emotion after the spectrum irradiation of the complementary emotion in the first stage, and then the spectrum irradiation of the target emotion is carried out in the second stage, the index of the target emotion can be greatly improved.

[0033] In addition, after the relay emotion irradiation and before reaching the neutral emotion, the personal physiological data of the user can be further provided. It is characterized in that: the personal physiological data of the user is the physiological data of the user's health examination, and the color temperature, illuminance, flash frequency, and color rendering index (Ra) of the user's illumination are adjusted according to it. And only after confirming that the emotion has been transferred to a neutral emotion or near the origin of the emotion coordinate, can the index of the target emotion be greatly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1a is the original data collection framework of the human factor illumination on physiological emotion response of the present invention;

[0035] Figure 1b is the original data collection flow chart of the human factor illumination on physiological emotion response of the present invention;

[0036] Figure 1c is the judgment flow of the human factor illumination on specific physiological emotion response of the present invention;

[0037] Figure 2aIt is a method of the present invention for establishing electroencephalogram of human factors under illumination for physiological and emotional responses;

[0038] Figure 2b It is a lighting database constructed by the present invention for users to perform effective human factors lighting;

[0039] Figure 3 It is a system architecture diagram of the intelligent human factors lighting system of the present invention;

[0040] Figure 4a It is an emotional coordinate system of the present invention;

[0041] Figure 4b It is an electroencephalogram of a specific emotion of the present invention;

[0042] Figure 4c It is an electroencephalogram of Emotion Transfer Test 1 of the present invention;

[0043] Figure 4d It is an electroencephalogram of Emotion Transfer Test 2 of the present invention;

[0044] Figure 4e It is an electroencephalogram of Emotion Transfer Test 3 of the present invention;

[0045] Figure 4f It is a navigation path of Emotion Navigation Example 1 of the present invention;

[0046] Figure 4g It is a navigation path of Emotion Navigation Example 2 of the present invention;

[0047] Figure 4h It is a navigation path of Emotion Navigation Example 3 of the present invention;

[0048] Figure 5 It is a method of the present invention for performing emotion navigation;

[0049] Figure 6 It is another method of the present invention for performing emotion navigation; and

[0050] Figure 7 It is yet another method of the present invention for performing emotion navigation. Detailed implementation manners

[0051] In the following description of the present invention, for a functional magnetic resonance imaging system, it is abbreviated as "fMRI system", an electroencephalograph is abbreviated as "EEG", and blood oxygenation level-dependent contrast is abbreviated as "BOLD". In addition, in the embodiment of the color temperature test of the present invention, the test is carried out in units of every 100K. However, in order to avoid overly lengthy explanations, in the following description, the so-called specific emotions refer to excitement or excitement, happiness, pleasure, etc., and the color temperature test examples of 3000K, 4000K, and 5700K will be used to illustrate the corresponding specific emotional responses. Therefore, the present invention cannot be limited to only the embodiments of these three color temperatures. At the same time, in order to enable those skilled in the art to fully understand the technical content of the present invention, the relevant implementation manners and their embodiments are provided here for explanation. In addition, when reading the implementation manners provided by the present invention, please refer to the drawings and the following description content at the same time. Among them, the shapes and relative sizes of the components in the drawings are only used to assist in understanding the content of this implementation manner, and are not used to limit the shapes and relative sizes of the components. This is stated in advance.

[0052] The present invention uses an fMRI system to understand the correspondence between spectrum and emotion in the brain through a physiological signal measurement method, and formulates a preliminary mechanism for using light to affect human physiological and psychological reactions. Since the brain images of the fMRI system can determine which part of the human brain has a hyperemic reaction when stimulated by light, and can also record the BOLD response. This BOLD response of cerebral hyperemia is also called the "increased blood oxygenation level-dependent response" condition. Therefore, the present invention can accurately and objectively infer the physiological and emotional changes of the test subject based on the brain hyperemic image recording data and the "increased blood oxygenation level-dependent response" response of the fMRI system in various emotions. After that, based on the physiological emotions confirmed by the fMRI system, an electroencephalograph (EEG) is further used to record the brain wave changes to establish the correlation between the two, in order to be able to use the brain wave changes recorded by the electroencephalograph (EEG) to replace the emotion judgment of the fMRI system.

[0053] Therefore, the main objective of the present invention is to enable a tester, during the process of testing a specific emotion in an fMRI system, to record the BOLD response of the tester to the specific emotion by illuminating the tester, so as to screen out which specific "effective color temperatures" can have a multiplicative effect on the specific emotion, and use the color temperature of this illumination as the "effective color temperature" corresponding to the specific emotion. Subsequently, the tester is illuminated with the "effective color temperature", and the brain wave pattern under the stimulation of the "effective color temperature" is recorded through an electroencephalograph (EEG). After establishing the correlation between the specific brain wave pattern of the electroencephalograph (EEG) and the specific BOLD response, the emotional changes of the user can be assisted in judgment through the specific brain wave pattern of the electroencephalograph (EEG), so as to construct a human factor lighting system and its method that can be commercially operated, thereby solving the problem that an expensive fMRI system must be used to implement the human factor lighting system, reducing the operation cost, and further meeting the customized service requirements.

[0054] First, please refer to Figure 1a , which is the original data collection framework of the human factor lighting of the present invention for physiological emotion responses. As Figure 1a shown, the intelligent human factor lighting system 100 is started in an environment (such as a test space) that has been configured with various adjustable lighting modules, and lighting parameter light signals such as spectrum, light intensity, flicker rate, and color temperature that can be changed are provided. For different target emotions, the present invention uses the compatible image interaction platform 110 (fMRI compatible image interaction platform) formed by the fMRI system, with voice and image emotion guidance, and at the same time, stimulates for 40 seconds with a specific effective spectrum, so as to observe the changes in the area of blood oxygen content in the tester's brain, to verify whether the "effective color temperature" can significantly induce the emotional response of the tester, and the details are as follows.

[0055] Next, please refer to Figure 1b and Figure 1c , where Figure 1b is the original data collection flow chart of the human factor lighting of the present invention for physiological emotion responses, and Figure 1c is the judgment flow of the human factor lighting for specific physiological emotion responses. As Figure 1bAs shown in step 1100, each tester is already located on the compatible image interaction platform 110. Then, each tester is guided to be stimulated with various emotions through known pictures. After that, as shown in step 1200, the BOLD responses of various emotions in the brain of the tester after being stimulated by the pictures are recorded through the compatible image interaction platform 110. Then, as shown in step 1300, visual stimulation is provided to the tester by illuminating with spectra of different color temperature parameters. For example: using an LED lamp with an electronic dimmer to provide spectra of different color temperature parameters. In an embodiment of the present invention, visual stimulation of 9 different color temperatures such as 2700K, 3000K, 3500K, 4000K, 4500K, 5000K, 5500K, 6000K, and 6500K is provided. Among them, after each 40-second effective light illumination and stimulation, it is possible to choose to apply 1 minute of ineffective light source illumination (full-spectrum non-flickering white light) to the tester to achieve the purpose of emotional relaxation. Further, it is also possible to choose to give the tester 40 seconds of reverse light stimulation to observe whether the response in the area that had a response during the original effective light stimulation decreases. And in an embodiment of the present invention, after the compatible image interaction platform 110 has recorded the BOLD response of a certain specific emotion in the brain of the tester after being stimulated by the pictures, spectra of different color temperature parameters are respectively provided to the tester for visual stimulation, as Figure 1c shown in step 1310 therein, to provide a spectrum with a color temperature of 3000K. Then, as shown in step 1320, to provide a spectrum with a color temperature of 4000K. Finally, as shown in step 1330, to provide a spectrum with a color temperature of 5700K for visual stimulation of the tester.

[0056] Then, as shown in step 1400, the BOLD responses of various emotions in the brain of the tester after being stimulated by the light illumination are recorded through the compatible image interaction platform 110. In an embodiment of the present invention, after the tester is stimulated by light illumination with different color temperature parameters, the compatible image interaction platform 110 sequentially records the BOLD response results of the areas in the tester's corresponding limbic system in the brain that have emotional responses. Among them, the parts of the limbic system triggered by different emotions are different, and the above-mentioned limbic system with brain region emotional responses is as shown in Table 1 below.

[0057] Table 1

[0058]

[0059] The compatible image interaction platform 110 records the reaction results of BOLD in specific brain regions. These reaction results are judged by calculating the area size of the limbic system with BOLD emotional reactions in the brain region. For example, when the area with BOLD emotional reactions is larger, it represents a stronger specific physiological emotional reaction. In the embodiments of the present invention, as shown in step 1410 of Figure 1c , it is used to record the reaction results of BOLD after being irradiated with a spectrum of 3000K color temperature. Then, as shown in step 1420, it is used to record the reaction results of BOLD after being irradiated with a spectrum of 4000K color temperature. Finally, as shown in step 1430, it is used to record the reaction results of BOLD after being irradiated with a spectrum of 5700K color temperature. Among them, after the lighting procedure induced by the excitement emotion of the tester, the compatible image interaction platform 110 records the reaction results of BOLD in specific brain regions as shown in Table 2. Obviously, when irradiating with a color temperature of 3000K, the excitement can be enhanced more. Therefore, according to the results of the embodiments of the present invention, the optimal stimulation color temperature falls between 3000K and 4000K. However, it should be noted that after irradiating with a color temperature of 5700K, a negative inhibitory effect will be produced on the excitement emotion.

[0060] Table 2

[0061]

[0062] Among them, after the lighting procedure induced by the happiness emotion of the tester, the compatible image interaction platform 110 records the reaction results of BOLD in specific brain regions as shown in Table 3. Obviously, when irradiating with a color temperature of 4000K compared to irradiating with the other two color temperatures, the color temperature of 4000K can enhance the BOLD reaction in the brain region in the happy situation more. Therefore, according to the results of the embodiments of the present invention, the optimal stimulation color temperature in the happy situation is around 4000K.

[0063] Table 3

[0064]

[0065] Among them, after the lighting procedure induced by the amusement emotion of the tester, the compatible image interaction platform 110 records the reaction results of BOLD in specific brain regions as shown in Table 4. Obviously, all three color temperatures can enhance the BOLD reaction in the brain region of the amusement feeling, especially when the color temperature is higher, the BOLD reaction in the brain region of the amusement feeling is stronger.

[0066] Table 4

[0067]

[0068] ​Among them, after the lighting procedure following the induction of the Serene Index emotion in the tester, the compatible image interaction platform 110 recorded the BOLD response results in specific brain regions as shown in Table 5. Obviously, when irradiating with a low color temperature of 3000K, the sense of serenity or relaxation can be enhanced. However, as the color temperature increases, a negative inhibitory effect on the Serene Index emotion will occur. In particular, the higher the color temperature, the more obvious the negative inhibitory effect.

[0069] Table 5

[0070]

[0071] After that, as shown in step 1500, by lighting, the results of the BOLD-dependent responses of specific color temperatures that can increase specific emotions are screened out, and this specific color temperature is called the "effective color temperature". In this embodiment, by recording the BOLD response results of the tester corresponding to the regions with emotional responses in the limbic system of the brain, the stimulating effects of color temperature on the brain are summarized, as shown in Tables 2 to 5 above. For the screened results of the BOLD brain region-dependent responses of specific color temperatures that can increase specific emotions, the maximum response values are calculated respectively for those specific color temperatures that can make the response effects of specific emotions reach the maximum response value (i.e., having the maximum response area value of BOLD).

[0072] As Figure 1c shown in step 1510, when the tester has recorded the induction of excitement emotion on the compatible image interaction platform 110 and then completed the lighting procedure, the maximum response value begins to be calculated. For example: According to the records in Table 2, subtracting the total score of 4000K (226) from the total score of 3000K (577), we get 351. Then, subtracting the total score of 5700K (-105) from the total score of 3000K (577), we get 682. Therefore, the total response value score after the induction of excitement emotion and at an illuminance of 3000K is 1033.

[0073] Next, as Figure 1c shown in step 1520, when the tester has recorded the induction of excitement emotion on the compatible image interaction platform 110 and then completed the lighting procedure, the maximum response value begins to be calculated. For example: According to the records in Table 2, subtracting the total score of 3000K (577) from the total score of 4000K (226), we get -351. Then, subtracting the total score of 5700K (-105) from the total score of 4000K (266), we get 371. Therefore, the total response value score after the induction of excitement emotion and at an illuminance of 4000K is 20.

[0074] Next, as in Figure 1c Step 1530 in, when the tester has recorded the induction of excitement emotion on the compatible image interaction platform 110 and completed the lighting procedure, the maximum response value is calculated. For example: According to the records in Table 2, subtract the total score of 3000K (577) from the total score of 5700K (-105), getting -682. Then, subtract the total score of 4000K (266) from the total score of 5700K (-105), getting -371. So, the total response value score after the induction of excitement emotion and under 5700K illuminance is -1033.

[0075] After the above calculations, after the induction of excitement emotion, it is the 3000K illuminance that can make the excitement emotion reach the maximum response value. That is, the 3000K illuminance can make the excitement emotion get a more obvious additive effect (that is, compared with the calculated total scores of 4000K and 5700K illuminances, the calculated total score of 3000K illuminance is the highest at 1033). Therefore, the 3000K illuminance is used as the "effective color temperature" of the excitement emotion. For other emotions, such as: happiness, pleasure, and tranquility, the "effective color temperatures" can be obtained through the calculation results such as steps 1510 to 1530 above, as shown in Table 6 below.

[0076] Table 6

[0077] Physiological Emotion Effective Color Temperature Excitement 3000K Happiness 4000K Amusement 5700K Serene 3000K

[0078] Next, according to the statistical results in Table 6, the effective color temperature can be used as the result of the specific physiological emotion-dependent response, and this effective color temperature can be regarded as the "enhanced spectrum" of the "blood oxygenation level-dependent (BOLD)" response of fMRI to a certain emotion. For example: The effective color temperature of 3000K can represent the "enhanced spectrum" of the fMRI system in the "excitement" emotion. Among them, the optimal stimulation color temperature should fall between 3000K and 4000K. For example: The effective color temperature of 4000K can represent the "enhanced spectrum" of the fMRI system in the "happiness" emotion. Among them, the optimal stimulation color temperature in the happy scenario is around 4000K. For example: The effective color temperature of 5700K can represent the "enhanced spectrum" of the fMRI system in the "pleasure" emotion. For example: The effective color temperature of 3000K can also represent the "enhanced spectrum" of the fMRI system in the "tranquility" emotion. Among them, the optimal stimulation color temperature in the tranquil scenario is around 3000K.

[0079] Finally, as shown in step 1600, a "light recipe" database of "enhanced spectrum" corresponding to the effects of specific emotions can be established in the fMRI system. By stimulating the tester with human factor lighting parameters as described above, and observing and recording the BOLD response of the tester's brain when being stimulated by light through the fMRI system. At the same time, by recording the fMRI brain images to determine which part of the human brain has a multiplicative response of "increased blood oxygenation level dependence" when being stimulated by light, so that a specific effective color temperature can be regarded as the "light recipe" of the "blood oxygenation level dependence" of fMRI for a specific emotion. Obviously, the present invention objectively infers the "light recipe" of the tester under a specific physiological emotion response based on the statistical results of the multiplicative response of BOLD for a specific emotion at a specific "effective color temperature" in Table 6 above, and uses this "light recipe" as evidence of the physiological emotion response that produces the strongest multiplicative effect for a specific emotion (including: excitement, happiness, pleasure, anger, disgust, fear, sadness, calm or neutral, etc.).

[0080] It should be emphasized that in the entire implementation process of the present invention Figure 1b and Figure 1c after a complete test of multiple specific emotions was conducted on 100 testers respectively, the statistical results in Table 6 were obtained accordingly. For example, in terms of the emotion of excitement, providing an effective color temperature of 3000K as the "enhanced spectrum" under the physiological emotion response of excitement as the "light recipe" can make the physiological emotion response of the tester's excitement produce the strongest multiplicative effect. For example, in terms of the emotion of happiness, providing an effective color temperature of 4000K as the "enhanced spectrum" under the physiological emotion response of happiness as the "light recipe" can make the physiological emotion response of the tester's happiness produce the strongest multiplicative effect. Another example, in terms of the emotion of pleasure, providing an effective color temperature of 5700K as the "enhanced spectrum" under the physiological emotion response of pleasure as the "light recipe" can make the physiological emotion response of the tester's pleasure produce the strongest multiplicative effect.

[0081] In addition, it should also be emphasized that the above only takes three color temperatures as representatives of the embodiments of the present invention, and does not only use the lighting of these three color temperatures as the "enhanced spectrum" under the physiological emotion response. In fact, after 2000K color temperature, every increase of 100K can be used as an interval to conduct Figure 1b and Figure 1c the entire process, therefore, Table 6 of the present invention only discloses partial results and is not used to limit the present invention only to these embodiments.

[0082] Next, the present invention aims to establish an artificial intelligence model for the "correlation between brain waves and brain images of general physiological emotions" so that in future commercial promotion, the results of other sensing devices can be directly used to infer physiological emotions without the need to use an fMRI system. Among them, the sensing device used in the present invention includes an electroencephalograph (EEG). In the following embodiments, the electroencephalograph 130 is used to establish the physiological emotional response to human factor lighting. Regarding the use of an eye tracker 150 or an auxiliary program 170 for facial expression recognition technology, etc., they can all be used to replace the implementation method of the fMRI system for physiological emotional response. However, the eye tracker 150 or the auxiliary program 170 for facial expression recognition technology will not be disclosed in the present invention and is hereby declared in advance.

[0083] Please refer to Figure 2a , which is a method for grading the physiological emotional response of the brain wave map of human factor lighting in the present invention. As Figure 2a shown, the present invention is a method for establishing the physiological emotional response to human factor lighting through the electroencephalograph 130, including: First, as shown in step 2100, the "enhanced spectrum" database information in Table 6 is also stored in the memory of the electroencephalograph 130. Next, as shown in step 2200, the tester wears the electroencephalograph, and each tester is guided to be stimulated with various emotions through elements of known pictures or videos. For example, the emotional stimuli of known pictures or videos can be selected to use the International Affection Picture System (IAPS). After that, as shown in step 2300, the intelligent human factor lighting system 100 is started, and light signal parameters such as changeable spectrum, light intensity, flicker rate, and color temperature are provided to perform lighting stimulation on the tester. Then, the electroencephalograph 130 records the brain wave map files after lighting with different color temperatures under specific emotions. For example: In this embodiment, each tester is first stimulated with excitement. After that, as shown in steps 2310 to 2330, different color temperatures of 3000K, 4000K, and 5700K are respectively provided to perform lighting stimulation on the tester, and the brain wave map files of the tester's specific emotions after lighting stimulation with different color temperatures when passing through excitement stimulation are respectively recorded and stored in the device in the memory of the electroencephalograph 130. In the embodiment of the present invention, the brain wave map files of 100 testers after completing specific emotional stimuli and lighting have been respectively recorded. Therefore, a larger memory is required.

[0084] Next, as shown in step 2400, through the learning method of artificial intelligence, the electroencephalogram (EEG) pattern files of specific emotions (such as excitement, happiness, pleasure, etc.) stored in the memory of the EEG device 130 are learned. Since the EEG device 130 can only memorize the waveforms of brain waves, the EEG patterns currently stored in the memory of the EEG device 130 are EEG pattern files of known specific triggering emotional stimuli and after illumination with different color temperatures. It should be noted that in actual tests, the EEG pattern files of different testers for the same emotional stimulus and the same color temperature illumination are different. Therefore, in the learning process of step 2400 of the present invention, it is necessary to classify the EEG pattern files of specific emotions through the information in the "light recipe" database of the "enhanced spectrum". For example, for the EEG pattern files of the excitement emotion, only the EEG pattern files of different testers at a color temperature of 3000K are grouped. Another example: for the EEG pattern files of the happiness emotion, only the EEG pattern files of different testers at a color temperature of 4000K are grouped. Another example: for the EEG pattern files of the pleasure emotion, only the EEG pattern files of different testers at a color temperature of 5700K are grouped. After that, the EEG device is trained through machine learning in artificial intelligence. In the embodiment of the present invention, in particular, a transfer learning model is selected for learning and training.

[0085] In the process of using the transfer learning model for learning and training in step 2400, it is to learn and train the EEG pattern file groups of specific emotions by statistically calculating and comparing similarities. For example, when learning and training the EEG pattern file group at a color temperature of 3000K, it is to statistically calculate and compare the rankings with the highest similarity and the lowest similarity, etc. of the EEG pattern files of the excitement emotion at a color temperature of 3000K. For example, the ranking with the highest similarity can be regarded as the EEG pattern file of the strongest emotion, and the ranking with the lowest similarity can be regarded as the EEG pattern file of the weakest emotion. And the EEG pattern file of the strongest emotion ranking can be used as the "target value", and the EEG pattern file of the weakest emotion ranking can be used as the "starting value". For the sake of easy explanation, at least one EEG pattern file with the highest similarity is used as the "target value", and at least one EEG pattern file with the lowest similarity is used as the "starting value", and different scores are given. For example, the "target value" is given a similarity score of 90 points, and the "starting value" is given a similarity score of 30 points. Similarly, the EEG pattern files of the happiness emotion in the series of the 4000K color temperature category and the EEG pattern files of the surprise emotion in the series of the 5700K color temperature category are completed in sequence. Among them, a similarity score range can be formed between the "starting value" and the "target value".

[0086] After that, as shown in step 2500, a brain wave map classification and grading database in artificial intelligence (which can be abbreviated as the artificial intelligence brain wave map file database) is established. After step 2400, the grading results of "target value" scores and "starting value" scores for various groups of brain wave map files with specific color temperatures are formed into a database and stored in the memory of the electroencephalograph (EEG) 130. The purpose of establishing the brain wave map classification and grading database in step 2500 of the present invention is to obtain the brain wave map file of an unknown tester after the unknown tester receives a specific emotional stimulus and is illuminated with a specific color temperature, and then compare the similarity score range between the brain wave map file of this unknown tester and the brain wave map files in the database, so as to judge or infer the current state of the unknown tester's brain congestion reaction. The detailed process is as Figure 2b shown.

[0087] Next, please refer to Figure 2b , which is the illumination database constructed by the present invention for the user to perform effective human factors illumination. First, as shown in step 3100, the tester wears the electroencephalograph (EEG) 130, and the tester is allowed to view pictures that induce specific emotions. After that, as shown in step 3200, the human factors illumination system 100 is activated to irradiate the tester with a "light formula" in an environment where various adjustable multi-spectral lighting modules are configured (for example: a test space). The lighting parameter signals such as spectral, light intensity, flicker rate, color temperature, and exposure time that can be changed are provided through the management control module 611 (as Figure 3 shown). Next, as shown in step 3300, the brain wave map file of the tester after induced emotions and illumination is obtained and recorded, and stored in the memory module 617 of the cloud 610 (as Figure 3 shown). Next, as shown in step 3400, the artificial intelligence brain wave map file database is imported into the management control module 611. Among them, the management control module 611 will set a score for whether the similarity is sufficient. For example, when the similarity score reaches 75 points or more, it means that the brain congestion reaction of the tester is sufficient. Then, as shown in step 3500, in the management control module 611, the brain wave map file of the tester is compared with the artificial intelligence brain wave map file for similarity. For example, when the similarity score of the tester's brain wave map file after comparison is 90 points, the management control module 611 immediately determines that the brain congestion reaction of the tester is very sufficient, so step 3600 will be performed to terminate the human factors illumination test for specific emotions. Then, step 3700 is performed to record the human factors illumination parameters when the brain congestion reaction of the tester reaches the stimulation as a database and store it in the memory module 617.

[0088] Next, in Figure 2bIn step 3500 of the program, if the similarity score after comparing the brain wave map file of the tester with the artificial intelligence brain wave map file is 35 points, the management control module 611 will determine that the hyperemia response in the tester's brain is insufficient. Therefore, step 3800 will be performed, and the management control module 611 will continuously strengthen the human factor lighting test, including: it can be controlled by the management control module 611 according to the high or low similarity score to provide an appropriate increase in 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. After passing through step 3400, until the similarity score reaches 75 points or more, the human factor lighting test will be stopped. Among them, when the management control module 611 determines that the hyperemia response in the tester's brain has reached stimulation, in step 3700, a human factor lighting parameter data file of the tester will be established. Finally, the management control module 611 will form a "human factor lighting parameter database" from the human factor lighting parameters of each tester and store it in the memory module 617. Obviously, the more testers there are, the more brain wave map files the artificial intelligence brain wave map file database of the present invention will learn, making the similarity score of the present invention more and more accurate.

[0089] After establishing the artificial intelligence model of the "human factor lighting parameter database", after starting the human factor lighting system 100, the present invention can infer the physiological and emotional changes of the brain image of a new tester only by observing the interpretation result of the brain wave map file of the electroencephalograph 130. Therefore, it is not necessary to use an expensive fMRI system, and the physiological and emotional changes of the brain image can be inferred according to the artificial intelligence model of the "human factor lighting parameter database". This enables the human factor lighting system 100 to be promoted and used commercially. In addition, in order to enable the "human factor lighting parameter database" to be used commercially, the "human factor lighting parameter database" can be further stored in the internal private cloud 6151 in the cloud 610.

[0090] Next, please refer to Figure 3 , which is the system architecture diagram of the intelligent human factor lighting system 600 of the present invention. As Figure 3As shown, the overall architecture of the intelligent human factor lighting system 600 of the present invention can be divided into three blocks, including: the cloud 610, the lighting field end 620, and the client device 630. The connection channel between these three blocks is the Internet. Therefore, the three blocks can be distributed in different regions or can be configured together. Among them, the cloud 610 further includes: a management and control module 611, which is used for cloud computing, cloud environment construction, cloud management, or using cloud computing resources, etc., and also allows users to access, construct, or modify the content in each module through the management and control module 611. A consumption module 613 is connected to the management and control module 611 and is used as a cloud service for users to subscribe and consume. Therefore, the consumption module 613 can access each module in the cloud 610. A cloud environment module 615 is connected to the management and control module 611 and the consumption module 613, and divides the cloud background environment into an internal private cloud 6151, an external private cloud 6153, and a public cloud 6155 (for example, a commercial cloud), etc., which can provide interfaces for external or internal services of system providers or users. A memory module 617 is connected to the management and control module 611 and is used as the storage area of the cloud background. The technical content that each module needs to execute in the present invention will be specifically described in subsequent different 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 a plurality of lighting 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 commercial operations, and all belong to the client device 630 of the present invention. The representative device or apparatus of the client device 630 can be a fixed device or a portable intelligent communication device with computing functions (including edge computing). In the following description, users, creators, editors, or portable communication devices can all represent the client device 630. In addition, in the present invention, the above-mentioned Internet can be an intelligent Internet of Things (AIoT).

[0091] After a relatively complete electroencephalograph experiment process of the present invention, for example: after the tester wears the electroencephalograph 130, in step 2300, the intelligent human factor 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 irradiating the tester, through the results of the aforementioned BOLD brain region test and then through the method of literature search, the light signal parameters of each emotion on the emotion coordinate system as shown in Figure 4a can be obtained. Among them, the spectra or light signal parameters of some emotions on the emotion coordinate system are summarized in Table 7 below:

[0092] Table 7

[0093]

[0094] In Table 7, K refers to color temperature, lux refers to illuminance, Hz refers to the flicker rate, and Ra refers to color rendering (the full name is the average color rendering index, general color rendering index). In addition, from Figure 4a Table 7, a trend can be seen, that is, the emotions in coordinate area I and coordinate area III have a complementary effect, and the emotions in coordinate area II and coordinate area IV also have a complementary effect. This phenomenon can be used as a navigation direction when emotions transfer.

[0095] Obviously, in order to construct a commercially operable human-centered lighting system and its method, so as to solve the problem of having to use an expensive fMRI system to implement the human-centered lighting system, it is necessary to use the specific brain wave patterns of an electroencephalograph (EEG) to assist in judging the emotional changes of users, which can further meet the customized service requirements and at the same time reduce the operating costs.

[0096] When performing emotional localization of the fMRI system and the electroencephalograph (EEG), based on the emotional results obtained by the fMRI system as the standard basis, we define it as the Limbic System Score (LSS). The reason for using the Limbic System Score (LSS) as an indicator is that the limbic system refers to the brain area that includes the hippocampus and amygdala and supports various emotions, behaviors, and long-term memories. For example, when the BOLD index in the fMRI is higher, it represents a greater emotional response. Another example is that when the LSS can represent the Arousal (validity) of emotions, the higher its value, the more excited the emotion. Therefore, the present invention will use the Limbic System Score (LSS) to establish a formula that combines various optical signal parameters such as various spectra, light intensities, flicker rates, color temperatures, and color rendering (Ra), so as to define Figure 4a the optical signal parameters of each emotion on the emotional coordinate system.

[0097] According to the paper "fMRI BOLD Correlates of EEG Independent Components: Spatial Correspondence With the Default Mode Network" published in the neuroscience journal Frontiers in Human Neuroscience on November 27, 2018, two important pieces of information were revealed. First, the Alpha wave has no significant effect on emotions. Second, the correlations of the delta wave, theta wave, beta2 wave, and gamma wave with the blood oxygen response in brain regions are -0.291, -0.26, 0.269, and -0.345 respectively.

[0098] Next, according to the present invention, the number of corresponding brain regions for different brain waves is 13, 18, 14, and 17 brain regions respectively. Among them, 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 -0.291 x 0.2097 = -0.0610. Calculated in the same way (theta = 18 / (13 + 18 + 14 + 17 = 0.2903, -0.26 x 0.2903 = -0.0755)), the following Equation 1 is obtained, and the correlations between light parameters such as frequency (f), color rendering index (Ra), color temperature index (CTI), and light intensity (I) are derived from this formula:

[0099] LSS = C 1 delta – C 2 theta + C 3 beta2 – C 4 gamma Equation 1

[0100] Among them, the coefficient C 1 = -0.061, C 2 = 0.0755, C 3 = 0.0607, and C 4 = 0.0945.

[0101] Next, Equation 1 needs to be converted into an emotion equation related to (f, Ra, CTI, I) in the electroencephalograph. First, when the color temperature index of a certain emotion obtained by the fMRI system is a fixed value, then

[0102] fMRI(CTI) = LSS

[0103] Next, decompose the electroencephalograph into 4 optical parameter results, and make each optical parameter equal to the corresponding parameter of fMRI. Then

[0104]

[0105] Among them, 1 / W freq 、1 / W Ra 、1 / W CTI 、1 / W I are the adjustment ratios of the fMRI system and the electroencephalograph (EEG) for each optical parameter.

[0106] After performing the normalization process with 1 / W CTI , the weight relationships between the four complete variance coefficients (a, b, c, d) can be obtained. After that, the final Peripheral System Score (LSS) formula can be obtained:

[0107] LSS = t x [a x f eeg (freq) + b x f eeg (Ra) + c x f eeg (CTI) + d x f eeg (I)]

[0108] ………………………………………………Program 3

[0109] Among them,

[0110] a = w freq / w CTI

[0111] b = w Ra / w CTI

[0112] c = w CTI / w CTI = 1

[0113] d = w I / w CTI

[0114] t = illumination time. It should be noted that when the illumination time (t) is larger, it means that the user receives illumination for a longer time, and it will have a higher reaction to emotions. Therefore, in the subsequent description of the present invention, the illumination time (t) is assumed to be 1.

[0115] According to the above formula, the present invention can obtain Figure 4a the optical signal parameters of each emotion on the emotion coordinate system. For example: in a preferred embodiment of the excitement scenario of the present invention, its LSS formula is as shown in Program 4 below:

[0116] LSS = t x (-0.0002freq 2 + 0.0393freq + 0.0334Ra - 0.2854CTI - 0.0000009ΔI 2 + 0.0004ΔI - 4.4441) Equation 4

[0117] For example: In a preferred embodiment in the Happiness scenario of the present invention, its LSS formula is as shown in Equation 5 below:

[0118] LSS = t x (-0.0002freq 2 + 0.0393freq + 0.0334Ra - 0.6374CTI - 0.0000009ΔI 2 + 0.0004ΔI - 4.4436) Equation 5

[0119] Wherein, the above-mentioned ΔI 2 refers to the change in illumination intensity.

[0120] According to the formula of the above-mentioned Peripheral System Score (LSS), the amount of emotional change under the condition of known various light parameters can be obtained. For example:

[0121] ■ LSS Example 1: For a lamp with 50Hz, Ra = 90, and color temperature of 6000K, within the user's visual range, if the illuminance increases by 200lux and after illumination for a specific time (t), then how excited is the user at this time?

[0122] · Substitute into Equation 4, and let t = 1, freq = 50Hz, Ra = 90, CTI = (6000 - 3000) / 3000 = 1, ΔI = 200.

[0123] Then we get

[0124] · LSS = -0.1787, that is, the excitement level decreases by 0.1787

[0125] ■ LSS Example 2: For a lamp with 60Hz, Ra = 95, and color temperature of 4000K, within the user's visual range, if the illuminance increases by 400lux and after illumination for a specific time (t), then how excited is the user at this time?

[0126] · Substitute into Equation 4, and let t = 1, freq = 60Hz, Ra = 95, CTI = (4000 - 3000) / 3000 = 0.33, ΔI = 400. Then we get

[0127] · LSS = 0.4324, that is, the excitement level increases by 0.4324.

[0128] ■ LSS Example 3: For a lamp with a frequency of 60 Hz, Ra = 95, and a color temperature of 4000 K, within the user's visual range, the illuminance increases by 400 lux. After illumination for a specific time (t), what is the user's feeling of happiness at this time?

[0129] · Apply Equation 5, and let t = 1, freq = 60 Hz, Ra = 95, CTI = (4000 - 4000) / 4000 = 0, ΔI = 400. Then we get

[0130] · LSS = 0.5270, which means the happiness level increases by 0.5270.

[0131] ■ LSS Example 4: For a lamp with a frequency of 50 Hz, Ra = 85, and a color temperature of 2700 K, within the user's visual range, the illuminance increases by 400 lux. After illumination for a specific time (t), what is the user's feeling of happiness at this time?

[0132] · Apply Equation 5, and let t = 1, freq = 50 Hz, Ra = 85, CTI = [(2700 - 4000) / 4000] = -0.325, ΔI = 400.

[0133] · LSS = -0.1871, which means the happiness level decreases by 0.1871.

[0134] From the calculation results of Example 1 and Example 2, we can draw a conclusion that to achieve the same level of excitement, there are many different means, such as: improving the color rendering index (Ra), improving the stroboscopic effect, increasing (or decreasing) the light intensity (because there is an optimal value), and reducing the color temperature, etc. Because in the Excitement scenario, the higher the CTI, the lower the level of excitement. On the contrary, from another perspective, by adjusting the color rendering index (Ra), stroboscopic effect, light intensity, and color temperature, etc., different levels of excitement can also be obtained. In addition, the calculation results of Example 3 and Example 4 can also lead to the same conclusion. At this time, the present invention collectively refers to the "light recipe" after combining lighting parameters such as the color rendering index (Ra), stroboscopic effect, light intensity, and color temperature as the "multi - spectral recipe". Obviously, Equation 3 is the equation of the multi - spectral recipe of the present invention. Among them, Equations 4 and 5 are only examples of the present invention applying Equation 3 to excitement and happiness, and do not limit the conditions of Equation 3. In other words, by controlling the "multi - spectral recipe" such as the color rendering index (Ra), stroboscopic effect, light intensity, and color temperature, the present invention can combine Figure 4aThe different emotions and different degrees of emotions in the shown emotion coordinates. Therefore, when the constructed lighting system of the present invention is in commercial operation, an experienced operator (e.g., a technician after professional training) can, according to the user's emotions and physiological conditions, use a workstation or an App on a portable intelligent 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), so as to edit a "multi-spectral recipe" for performing lighting, and use it to control the lighting program of the lighting system at the lighting field end 620 to execute a specific "multi-spectral recipe" to meet the user's needs.

[0135] In terms of the general emotion conversion method, when we want to perform emotion conversion, we can perform emotion conversion by giving the "multi-spectral recipe" of the emotion we want to convert to. For example, when we want to convert to a happy emotion, according to Table 7 or Figure 4a as shown, we can directly give a color temperature of 4000K. Further, for example: when it is known that the user is currently in a nervous emotional state and the user's goal is to convert the emotion to a happy state. Intuitively, as long as 4000K light is continuously given for a period of time, the user's emotion can reach a happy level. However, this is inaccurate because, according to the present invention under the conditions of Equation 3, it can be known that for the same emotion, there can be different degrees of manifestation, and this different degree of manifestation can be adjusted and obtained through the lighting parameters of the "multi-spectral recipe" such as color rendering index (Ra), stroboscopic effect, light intensity, and color temperature.

[0136] Next, the present invention can provide an effective emotion transfer method through the following process. In an embodiment of the present invention, it is to let the user convert from a nervous emotion to a happy emotion, and this process is to conduct an experiment using the electroencephalogram measured by an electroencephalograph (EEG). Among them, Figures 4b to 4e the coordinate dimensions in are the numbers after being normalized.

[0137] As Figure 4b shown, it is the relative intensity index diagram of a specific electroencephalogram of the present invention. The relative intensity index of the electroencephalogram is defined using the definition of NeuroSky Corporation. Among them, the electroencephalogram waveform diagram and the definition of the relative intensity index related to the emotions in this embodiment include: nervous, relaxed, and happy, as Figure 4b shown. Among them, Figure 4bThe brain wave waveform diagram shown is the intensity value (High) of Beta waves, the intensity value (Low) of Beta waves, the intensity value (High) of Alpha waves, and the intensity value (Low) of Alpha waves under a specific condition. It should be noted that in the following experiments, after different light stimulation is given, the values of the brain wave diagrams with the same emotion may not be the same, but the trends of the intensity values of Beta waves and Alpha waves are similar. Among them, the calculation methods of the relative intensity indicators for different emotions are also different. Among them, according to the definition of NeuroSky company for the relative intensity indicators of tense, relaxed, and happy emotions, they are as follows, including:

[0138] Relative intensity index of tension = (BetaHigh + BetaLow) / (AlphaLow + AlphaHigh)

[0139] Relative intensity index of relaxation = (AlphaLow + AlphaHigh) / (BetaHigh + BetaLow)

[0140] Relative intensity index of happiness = (AlphaLow + AlphaHigh + BetaHigh) / (BetaLow)

[0141] Next, please refer to Figure 4c , which is the brain wave diagram of Emotion Transfer Test 1 of the present invention. For the first emotion transfer test, a happy color temperature of 4000K is directly given. The process is to first confirm that the user is already in a tense emotion. For example, the user is required to answer some math questions completely within 2 minutes, which may make them fall into a tense emotion. When the brain wave diagram of the user shows a waveform diagram as shown on the left side of Figure 4c , and it is judged that the user is already in a tense emotion, then, after directly irradiating the user with a color temperature of 4000K for 2 minutes, the brain wave diagram of the user is obtained as shown on the right side of Figure 4c . Then, calculate the relative intensity index of happiness 3.34 shown by the brain waves.

[0142] Next, please refer to Figure 4d , which is the brain wave diagram of Emotion Transfer Test 2 of the present invention. For the second emotion transfer test, the user is made to go from tense to relaxed and then to happy. The process is to first confirm that the user is already in a tense emotion. For example, the user is required to answer some math questions completely within 2 minutes, which may make them fall into a tense emotion. When the brain wave diagram of the user shows a waveform diagram as shown on the left side of Figure 4d , and it is judged that the user is already in a tense emotion, then, first irradiate with a relaxing spectrum (orange light of 10Hz) for 5 minutes. After that, irradiate the user with a color temperature of 4000K for 2 minutes, and the brain wave diagram of the user is obtained as shown in Figure 4dAs shown in the middle and on the right, then, calculate the relative intensity index 4 of the happiness shown by the brain waves.

[0143] Then, please refer to Figure 4e , which is the electroencephalogram of the third mood transfer test of the present invention. Conduct the third mood transfer test to let the user go from tension to neutrality and then to happiness. The process is to first confirm that the user is already in a tense mood. For example, the user is required to answer some math questions completely within 2 minutes, which may make them fall into a tense mood. When the electroencephalogram of the user shows a waveform diagram as shown in Figure 4e on the left, and it is judged that the user is in a tense mood, then, first irradiate with a relaxation spectrum (10Hz orange light) for 2 minutes to guide them into a neutral mood by reducing the sense of tension. For example, from Figure 4e the relaxation electroencephalogram in the middle shows that its relative intensity pointer 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 has entered a neutral mood at this time. Finally, after irradiating the user with a color temperature of 4000K for 2 minutes, the electroencephalogram of the user is as shown in Figure 4e on the right. Then, calculate the relative intensity index 10 of the happiness shown by the brain waves.

[0144] 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, first give some other spectra that can relieve the tense mood, such as: Table 7 or Figure 4a some complementary mood spectra in it are irradiated, and then the second-stage happy spectrum irradiation is carried out, which can make the user obtain a better happy mood index. In particular, when it is further confirmed that after the user has transferred their mood to a neutral mood after the first-stage mood-relieving light irradiation, and then the second-stage happy spectrum irradiation is carried out, the happy mood index can be greatly improved. The theoretically neutral index (Neutral Index) refers to the BOLD response of the limbic system being zero. Among them, the neutral mood is at Figure 4aNear the center point or the origin of the emotional coordinate graph, its theoretical characteristic is that it can keep the average person in a balanced and stable psychological state, not being influenced by excessive positive or negative emotions, so as to be able to view things and problems more objectively. Especially through the above experimental process, if the user can first be irradiated by the complementary emotional spectrum in the first stage and it is judged that the user's emotion has returned to the neutral emotion, and then be irradiated by the final desired emotional spectrum, the best emotional transfer effect can be adjusted. And this process of first confirming the current emotion, then setting the irradiation spectrum in the first stage according to the current emotion, and after judging that the user's emotion has reached the neutral emotion after the first-stage light irradiation, then performing the irradiation of the final target emotional spectrum in the second stage. This kind of planning of the path or process to reach the target emotion is called Motion Navigation.

[0145] In addition, the present invention also finds that the change and transfer of emotions are not linear. For example, when the physiological conditions of different users are different or the social statuses of different users are different, it will cause different users to have different degrees of reactions to the same emotion. For example: in terms of physiological conditions, users suffering from epilepsy cannot be stimulated by stroboscopic light and must be strengthened in terms of color temperature or intensity. For example: in terms of different social statuses, different understandings of happiness will result in different degrees of reactions. Therefore, a more rigorous way is that before we provide the light stimulation of the target emotion, we must consider the "current state" of the user. This is because for users in different emotional states (degrees), by adjusting the light irradiation parameters in the formula of the surrounding system score (LSS), different "multi-spectral formulations" of stimulation are given to achieve the same final effect.

[0146] According to the above emotional transfer test results, the present invention provides three different emotional transfer paths to execute the process of the emotional navigation of the present invention.

[0147] ■ Example 1 of Emotional Navigation:

[0148] For example: The user is currently in a nervous state, and the goal is to transfer the emotion to happiness.

[0149] 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 current nervous state of the user needs to be alleviated. Therefore, a "multi-spectral formulation" of serene can be selected for light irradiation (give light irradiation with a color temperature of 3000K according to Table 5). After that, a "multi-spectral formulation" of the target emotion of happiness is given for light irradiation (give light irradiation with a color temperature of 4000K according to Table 5). When it is near the desired emotion, the light irradiation program is stopped. For the navigation path of Example 1 of emotional navigation, please refer to Figure 4eSchematic diagram.

[0150] ■ Emotional Navigation Example 2:

[0151] Emotional Navigation Example 2 is a preferred embodiment of the present invention, especially by adding a neutral indicator to the emotional navigation program. For example: The user is currently in a stressed state, and the goal is to transfer the emotion to excitement. The process of emotion transfer can be divided into two steps:

[0152] The first step: is to first eliminate the stressed state in order to pull the user's emotion back to neutral or Figure 4a the origin point. Therefore, according to Figure 4a the emotional coordinate diagram shown, the relatively relaxed emotion item opposite to the stress emotion can be selected for complementarity. So, we need to first give the "multi-spectral formula" that can achieve relaxation for illumination (give orange light with a frequency of 10 Hz according to Table 5), and at the same time monitor the user's physiological signals (such as brain area responses) to judge whether the user's emotion has returned to neutral or near the origin point. If it has returned to neutral or near the origin point, it means that the stress has been eliminated. Or, after interviewing or conducting a questionnaire on the user, it can be judged that the user's emotion has returned to neutral or near the origin point. After that,

[0153] The second step: Give the excitement "multi-spectral formula": After confirming that the user's emotion has returned to neutral or the origin point, we then give the excitement "multi-spectral formula" for illumination (give light with a color temperature of 3000K according to Table 5). At the same time, monitor the user's physiological signals (such as brain area responses) to judge whether the user's emotion has reached near excitement. If it has reached near excitement, then stop the illumination program. For the navigation path of Emotional Navigation Example 2, please refer to Figure 4f the schematic diagram.

[0154] ■ Emotional Navigation Example 3:

[0155] The present invention further discloses another preferred embodiment. For example: The user is currently in a sadness state, and the goal is to transfer the emotion to erotic. The transfer process includes two steps:

[0156] The first step: is to first eliminate the sadness state in order to pull the user's emotion back to neutral or the origin point. Therefore, according to Figure 4aAs shown in the emotional coordinate diagram, one can choose the emotion item of Happiness, which is opposite to sadness, for complementarity. Therefore, we first provide the "multi-spectral formula" that can achieve happiness for illumination (provide illumination with a color temperature of 4000K according to Table 5), and at the same time monitor the user's physiological signals (such as brain region responses). Judge whether the user's emotion has returned to neutral or near the origin. If it has returned to neutral or near the origin, it means that the sadness has been eliminated. After that,

[0157] Step 2: Provide the "multi-spectral formula" for lust: After the user's emotion returns to the origin, provide the "multi-spectral formula" for lust for illumination (provide illumination with a stroboscopic 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 region responses). Judge whether the user's emotion has reached the vicinity of lust. If it has reached the vicinity of lust, then stop the illumination program. For the navigation path of Emotion Navigation Example 3, please refer to Figure 4g the schematic diagram.

[0158] As described above, all are examples of emotion navigation disclosed by the present invention. Its purpose is to explain the concept of the execution of emotion navigation of the present invention in a concise manner. In practice, according to the physiological conditions of different users or different life experiences, it may be necessary to navigate to the target emotion through multiple emotion conversions. At this time, the final goal of emotion navigation can be achieved by adjusting means such as color rendering index (Ra), stroboscopic frequency, light intensity, and color temperature. Therefore, the present invention does not limit the number of emotion conversions required to reach the target emotion.

[0159] Next, the present invention will further disclose a preferred embodiment that can be specifically operated.

[0160] According to the above, it is obvious that when the present invention performs emotion navigation, it is necessary to first know the user's emotion state at the time of emotion conversion (i.e., the current emotion state), secondly, the emotion change situation during the emotion navigation process, and finally whether the target emotion is reached. The emotion states in these several 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 electroencephalograph (EEG) or a wearable electronic device (such as: mobile phone or wearable device, etc.) or choose to use an emotion picture library) for stimulation, such as: International Affection Picture System (IAPS).

[0161] Next, please refer to Figure 5, which is a method for implementing emotional navigation in the present invention. First, as shown in step 3510, the "initial emotion" of the user is confirmed. For example, when the user is in the illumination field 620, after measuring the brain waves through the wearable electroencephalograph 130, according to the brain wave recording data, it shows what state the user's current "initial emotion" is in. For example, the "initial emotion" is in a nervous state. Among them, the "initial emotion" has been uploaded by the electroencephalograph 130 and stored in the memory module 617 of the cloud 610 (as shown in Figure 3 ). Then, step 3520 is carried out.

[0162] Step 3520: Set the "target emotion". When the user wants to adjust or convert the "initial emotion" to a happy (Happiness) emotion, the user can set the "target emotion" to Happiness through the requirements of the client device 630 in the intelligent human factors illumination system 600. After that, it will also be uploaded by the client device 630 and stored in the memory module 617 of the cloud 610. Then, step 3530 is carried out.

[0163] Step 3530: Select the "intermediate emotion" to complete the emotional navigation path setting. According to the user's "initial emotion" and "target emotion", through the client device 630 to the management control module 611 of the cloud 610, select one or more "intermediate emotions" that are different from the "initial emotion" or "target emotion" to form an order from the "initial emotion" to the "intermediate emotion" and then to the "target emotion", and this order is called the "emotional navigation path". For example, when the user's "initial emotion" is in a tense state and the "target emotion" has been confirmed to be happy, the user can select serene as the "intermediate emotion" through the client device 630 to the management control module 611 of the cloud 610, so that the "emotional navigation path" is from tense to serene and then to happy. Or select the "intermediate emotion" to go through calm first and then to serene, so that the "emotional navigation path" is from tense to calm, then to serene, and finally to happy. In the above setting of the emotional navigation path, the "intermediate emotion" can be selected by the user according to their own experience, or by a professional according to the user's "initial emotion" and "target emotion". Then, step 3540 is carried out.

[0164] Step 3540: Edit the "multi-spectral formula" according to the emotional navigation path. When step 3530 has confirmed the "emotional navigation path", it is necessary to find the multi-spectral formulas corresponding to the "intermediate emotion" and the "target emotion". For example, when Figure 4aWhen the emotional coordinate information has been stored in the memory module 617 of the cloud 610, the user can find the "multi-spectral formula" corresponding to the "relay emotion" and "target emotion" from the cloud environment module 615 through the client device 630 in the intelligent human factor lighting system 600, including: the "multi-spectral formula" (color temperature of 3000K) that provides a serene emotion, or the "multi-spectral formula" (stroboscopic frequency of 4Hz, illuminance less than 7 lux, color temperature of 3000K) that provides a calm emotion, and the "multi-spectral formula" (color temperature of 4000K) that provides a happy emotion. Among them, 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, etc. Then, step 3550 is performed. It should be noted that during the above process of editing the "multi-spectral formula", the "multi-spectral formula" for performing lighting is edited by adjusting the characteristics of the lighting parameters in the peripheral system score (LSS) formula one by one.

[0165] Step 3550: Execute the lighting program of the "multi-spectral 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-spectral formula" corresponding to the "relay emotion" and "target emotion". The other control path is that the management control module 611 in the cloud 610 controls the lamp group 621 in the lighting field end 620 through the intelligent Internet of Things (AIoT) to perform the lighting process on the user in sequence according to the edited "multi-spectral formula" corresponding to the "relay emotion" and "target emotion". For example: both control methods irradiate the user's "relay emotion" for 10 minutes and then irradiate the user's "target emotion" for 15 minutes.

[0166] 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;

[0167] Step 3570: Stop the lighting program. If it is determined that the user's emotion has reached the "target emotion", then stop the lighting program. Among them, the determination described in step 3560 is based on the information displayed by the physiological monitoring device configured on the user. Among them, the physiological monitoring device can be an electroencephalograph or a wearable device that can detect sympathetic and parasympathetic nerve signals.

[0168] 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 examined for adjustment. 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 perform emotion adjustment on the section that has not reached the set emotion. After that, a new "emotion navigation path" can be reset. For example: The originally set "emotion navigation path" is from calm to serene. Then, examine the illumination interval from calm to serene on the physiological monitoring device to see if calm or serene has not reached the set emotion, and then adjust these emotions. The adjustment method can be that the management control module 611 selects a new "relay emotion" near the emotion that has not reached the set emotion. For example: If the examination result shows that calm has not reached the set emotion, then reselect Relax as the new "relay emotion". Then, repeat steps 3540 to 3560. Among them, after returning to step 3530, a new "emotion navigation path" will be formed, which is from tense to relaxed to serene, and finally to happy. Finally, until it is determined that the user's emotion has reached the "target emotion", then go to step 3570 to stop the illumination program. In a preferred embodiment, the selection of the new "relay emotion" can be adjusted in the management control module 611 of the client device 630 or the cloud 610 by the aforementioned Equation 3 (color rendering - Ra, stroboscopic, light intensity, or color temperature, etc.) "multi - spectral formula" illumination parameters. For example: Increasing the color rendering (Ra) can make the calm emotion reach a stronger level.

[0169] In addition, if step 3580 has determined which section has not reached the set emotion through the physiological monitoring device, the client device 630 can further go to step 3590 to obtain the user's personal physiological data that has been stored in the cloud 610, such as: the physiological data of the user's health check. Another example: According to the physiological data of the health check showing that the user has hypertension, diabetes, or epilepsy, the parameters of the "multi - spectral formula" in Equation 3 (color rendering - Ra, stroboscopic, light intensity, or color temperature, etc.) can be adjusted accordingly. For example: When the user has epilepsy, since stroboscopic can stimulate epilepsy and may induce epilepsy, in Equation 3, reinforcement must be given to color rendering - Ra, color temperature, or intensity. Then, repeat steps 3530 to 3560. According to the user's physiological signal data, find a new "relay emotion" that can be adjusted to the "target emotion" and form a new "emotion navigation path". Until it is determined that the user's emotion has reached the "target emotion", then go to step 3570 to stop the illumination program.

[0170] It should be emphasized that when the present invention uses the physiological data of health checks to adjust the lighting parameters of the "multi-spectral formula" such as (color rendering index - Ra, stroboscopic, light intensity, or color temperature) in Equation 3, the limitations of the lighting parameters of the "multi-spectral formula" corresponding to each disease, such as (color rendering index - Ra, stroboscopic, light intensity, or color temperature), can be adjusted according to medical information. For example, too low a color temperature will affect the clarity of the user's vision. Therefore, when the user needs exciting stimulation in the working environment, lowering the color temperature is not the best means, but rather strengthening other parameter items. For example, a higher color rendering index (Ra) can be given to compensate for the need to use parameters with too low a color temperature to maintain excitement at a certain level. Therefore, in the above embodiment of the present invention, the limiting conditions of stroboscopic for epilepsy patients are only for illustrative purposes and are not used to limit the parameter adjustment of the "multi-spectral formula" such as (color rendering index - Ra, stroboscopic, light intensity, or color temperature) in Equation 3 to only the embodiment of epilepsy.

[0171] Furthermore, since the client device 630 and the cloud 610 in the intelligent human factor lighting system 600 of the present invention communicate using intelligent Internet of Things (AIoT), the "emotional navigation paths" used by many users will be stored in the cloud environment module 615, forming a large amount of data. For example, after performing algorithm operations on this large amount of data stored in the private cloud 6151 or the public cloud 6153 using artificial intelligence, the ranking of the "emotional navigation paths" most used during various emotional conversion processes can be obtained. Therefore, when the current user wants to perform a specific emotional conversion, they can search in the private cloud 6151 or the public cloud 6153 through the client device 630 for the "emotional navigation path" most used in the data of the specific emotional conversion as a shortcut for providing step 3530: completing the setting of the emotional navigation path. Obviously, since the "emotional navigation path" of the present invention operates 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.

[0172] Please refer to Figure 6 , which is another method for the present invention to perform emotional navigation.

[0173] First, perform step 4510: first confirm the "initial emotion". The detailed process is the same as step 3510, so please refer to step 3510 and will not be repeated here. The "initial emotion" is in a stressed state. Then, proceed to step 4520.

[0174] Step 4520: Set the "target emotion" again. The detailed process is the same as that of Step 3520, so please refer to Step 3520 and will not be repeated here. Among them, the "target emotion" is set to Excitement. Then, proceed to Step 4530.

[0175] Step 4530: Select the "relay emotion" to complete the setting of the "emotion navigation path". In this embodiment, Step 4530 is based on the processes of Emotion Navigation Example 2 and Emotion Navigation Example 3 to set the "emotion navigation path". For example: Taking 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, select to set the "emotion navigation path". Among them, the first step is to first eliminate the stressful state so as to pull the user's emotion back to Neutral or the origin. Therefore, in this embodiment, according to Figure 4a the shown emotion coordinate diagram, the Relaxed emotion item corresponding to the stress can be selected as the "relay emotion" in 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 emotion. For example: The "relay emotion" can first select the corresponding calm emotion and then further select the relaxed emotion. Therefore, in this embodiment, the setting of the "emotion navigation path" is 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 the "relay emotion". Then, proceed to Step 4540.

[0176] Step 4540: Edit the "multi-spectral formula" according to the emotion navigation path. When Step 4530 has confirmed the "emotion navigation path", it is necessary to find the corresponding multi-spectral formulas for the "relay emotion" and the "target emotion". For example: When Figure 4aWhen the emotional coordinate information has been stored in the cloud environment module 615, the user can find the "multi-spectral formula" corresponding to the "relay emotion" and "target emotion" from the cloud environment module 615 through the client device 630, including: a "multi-spectral formula" that provides a relaxing emotion (orange light with a flash frequency of 10 Hz), and a "multi-spectral formula" that provides excitement (a color temperature of 3000K). Among them, 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, etc. After that, step 4550 is performed. It should be particularly noted that during the process of editing the "multi-spectral formula" in step 4540, the characteristics of the lighting parameters in the peripheral system score (LSS) formula are adjusted one by one to edit the "multi-spectral formula" for performing lighting.

[0177] Step 4550: Perform the first-stage lighting. According to the "emotional navigation path" set in step 4530, through the management control module 611 in the client device 630 or the cloud 610, and then through the intelligent Internet of Things (AIoT) to control the lamp group 621 in the lighting field terminal 620. In this embodiment, performing the first-stage lighting is only to first execute the lighting program of the edited "multi-spectral formula" for a relaxing emotion (orange light with a flash frequency of 10 Hz). For example, after irradiating the user with the edited "multi-spectral formula" for a relaxing emotion for 10 minutes, the lighting program is stopped first. At this time, the first-stage multi-spectral formula irradiation program is completed. If the "relay emotion" is a combination of more than one different emotion, it is also necessary to irradiate the user with these multiple different emotions before stopping the lighting program. After that, step 4560 is performed.

[0178] Step 4560: Determine whether the user's stress emotion has been eliminated. It is determined according to the physiological monitoring device whether the user's current emotion has been adjusted to Figure 4c neutral or near the origin of the emotional coordinate information after the first-stage lighting. If it is determined that the user's emotion after the first-stage lighting has not reached Figure 4c neutral or near the origin of the emotional coordinate, it means that the stress emotion has not been completely eliminated, and step 4570 is executed. If it is confirmed that it has reached Figure 4c neutral or near the origin of the emotional coordinate, then step 4580 is executed.

[0179] Step 4570: If it is determined that the user's emotion has not reached "neutral or origin", the user's personal physiological data (e.g., physiological data from the user's health check) can be further examined to adjust the "relay emotion". 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 from the user's health check. Then, according to the information on the user's personal physiological data, the lighting parameters in the Peripheral System Score (LSS) formula for adjusting the "relay emotion" are adjusted. For example, when the physiological data from the health check shows that the user has hypertension, diabetes, or epilepsy, the lighting parameters of the "multi-spectral formula" (such as color rendering index - Ra, stroboscopic, light intensity, or color temperature, etc.) in Equation 3 can be adjusted according to these diseases. Then, going back to Step 4530, a new "emotion navigation path" will be formed. After that, Steps 4550 and 4560 are repeatedly executed until it is determined that the user's emotion has reached "neutral or origin", and then Step 4580 is performed.

[0180] Step 4580: Execute the second-stage multi-spectral formula illumination program. According to the "emotion navigation path" multi-spectral formula in Step 4540, again through the management control module 611 in the client device 630 or the cloud 610, the lighting fixtures group 621 in the lighting field terminal 620 is controlled through the intelligent Internet of Things (AIoT) to execute the illumination program of the exciting "multi-spectral formula" (3000K color temperature). For example, after irradiating the user with the exciting emotion "multi-spectral formula" for 15 minutes, the illumination program is stopped, and at this time, the second-stage multi-spectral formula illumination program is completed. Then, Step 4590 is performed.

[0181] 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", then return to Step 4530, and the client device 630 goes to Step 4570 to obtain the user's personal physiological data that has been stored in the cloud 610, such as the physiological data of the user's health check. Then, according to the information on the user's personal physiological profile, adjust the lighting parameters in the "multi-spectral formula" of the "target emotion". For example, when the physiological data of the health check shows that the user has hypertension, diabetes, or epilepsy, the lighting parameters of the "multi-spectral formula" (such as color rendering - Ra, stroboscopic, light intensity, or color temperature, etc.) in Equation 3 can be adjusted according to these diseases, and then stored in the cloud 610. Then, directly go to Step 4580. The user uses the client device 630 to find the lighting parameters of the "multi-spectral formula" corresponding to the adjusted "target emotion" in the cloud 610. Then, repeat Step 4580 and Step 4590 until it is determined that the user's emotion has reached the "target emotion", then perform Step 4610: Stop the lighting program.

[0182] Please refer to Figure 7 , which is the third method for implementing emotion navigation of the present invention.

[0183] First, perform Step 6510: First, confirm the "initial emotion". The detailed process is the same as Step 4510, so please refer to Step 4510 and will not be repeated here. Among them, the "initial emotion" is in a stressed state. Then, proceed to Step 6520.

[0184] Step 6520: Then set the "target emotion". The detailed process is the same as Step 4520, so please refer to Step 4520 and will not be repeated here. Among them, the "target emotion" is set to excitement. Then, proceed to Step 6530.

[0185] Step 6530: Obtain the user's personal physiological data. The client device 630 goes to the cloud 610 to obtain the user's personal physiological data that has been stored in the memory module 617, such as the physiological data of the user's health check. Then, proceed to Step 6540.

[0186] Step 6540: Select "Relay Emotion" to complete the setting of the "Emotion Navigation Path". In this embodiment, the Emotion Navigation Example 2 is used as an illustration. When the user has confirmed in Step 6510 that the "Initial Emotion" is in a stressful state, and has also confirmed in Step 6520 that the emotion is to be transferred to the "Target Emotion" of excitement. Then, through the client device 630 to the management control module 611 of the cloud 610, the setting of the "Emotion Navigation Path" is selected. Among them, the first step is to first eliminate the stressful state in order to pull the user's emotion back to neutral or the origin. Therefore, in this embodiment, according to Figure 4a the shown emotion coordinate diagram, the Relaxed emotion item corresponding to the 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 view the user's personal physiological data and adjust the parameters in the "Multi-Spectral Recipe" of the "Relay Emotion" according to the information on the user's personal physiological data. For example: when the user suffers from epilepsy, since stroboscopic flashes can stimulate epilepsy and may thus induce epilepsy, in Equation 3, the proportion of stroboscopic flashes must be reduced or removed, so it is necessary to strengthen the color rendering index - Ra, color temperature or intensity, resulting in 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 Relaxed emotion of the "Relay Emotion" and then to the excitement of the "Target Emotion", where the "Multi-Spectral Recipe" parameters of the adjusted Relaxed emotion are adjusted through the user's personal physiological data. Then, Step 6550 is performed.

[0187] Step 6550: Edit the multi-spectral recipe according to the "Emotion Navigation Path". When Step 6530 has confirmed the "Emotion Navigation Path", it is necessary to find the corresponding multi-spectral recipes for the "Relay Emotion" and the "Target Emotion". For example: when Figure 4aWhen the emotional coordinate information has been stored in the cloud environment module 615, the user can find the "multi-spectral formula" corresponding to the "relay emotion" and "target emotion" from the cloud environment module 615 through the client device 630, including: providing an adjusted "multi-spectral formula" for relaxation emotion, and providing an "exciting multi-spectral formula" (color temperature of 3000K). Among them, the adjusted "multi-spectral formula" for relaxation emotion 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, a personal digital assistant (PDA), a notebook computer (NB), or a personal computer (PC) in a workstation, etc. Then, step 6560 is performed. It should be particularly noted that during 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 peripheral system score (LSS) formula one by one.

[0188] Step 6560: Perform the first-stage lighting. After completing the editing of the "emotion navigation path" multi-spectral formula in step 6550, through the management control module 611 in the client device 630 or the cloud 610, and then through the intelligent Internet of Things (AIoT) to control the lamp group 621 in the lighting field terminal 620. In this embodiment, performing the first-stage lighting is to only first execute the lighting program of the edited "multi-spectral formula" for relaxation emotion. For example: after irradiating the user with the "multi-spectral formula" for relaxation emotion for 15 minutes, the lighting program is stopped first. At this time, the first-stage multi-spectral formula irradiation program is completed. If the "relay emotion" is a combination of more than one different emotion, it is also necessary to irradiate the user with these multiple different emotions before stopping the lighting program. Then, step 6570 is performed.

[0189] Step 6570: Determine whether the user's stress emotion has been eliminated. It is determined according to the physiological monitoring device whether the user's current emotion has been adjusted to neutral or the origin after the first-stage lighting. If it is determined that the user's emotion after the first-stage lighting has not reached Figure 4c the neutral or origin of the emotion coordinate, it means that the stress emotion has not been completely eliminated, and then return to step 6530. If it is confirmed that it has reached Figure 4c the neutral or origin of the emotion coordinate, then step 6580 is executed.

[0190] If it is determined in step 6570 that the user's emotion has not reached "neutral or origin", then it will return to step 6530, and the user's personal physiological data (e.g., physiological data of the user's health check) can be further examined to adjust the "relay emotion". In a preferred embodiment, the client device 630 obtains the physiological data of the user that has been stored in the memory module 617 from the cloud 610. Then, according to the information on the user's health check, the illumination parameters in the formula of the peripheral system score (LSS) of the "relay emotion" are adjusted again. For example, when the physiological data of the health check shows that the user has hypertension or diabetes, the illumination parameters of the "multi-spectral formula" (such as color rendering index - Ra, stroboscopic, light intensity or color temperature, etc.) in Equation 3 can be adjusted according to these diseases. Then, steps 6540 and 6570 are repeatedly executed until it is determined that the user's emotion has reached "neutral or origin", and then step 6580 is performed. Obviously, during the process of adjusting the illumination parameters of the "multi-spectral formula" corresponding to the "relay emotion" again, it can be selected not to change the original "emotion navigation path" setting in step 6540, that is, only adjust the illumination parameters of the originally set "relay emotion".

[0191] Step 6580: Execute the second-stage multi-spectral formula illumination program. According to the "emotion navigation path" multi-spectral formula in step 6550, again through the management control module 611 in the client device 630 or the cloud 610, the lighting group 621 in the lighting field terminal 620 is controlled through the intelligent Internet of Things (AIoT) to execute the illumination program of the exciting "multi-spectral formula" (3000K color temperature). For example, after irradiating the user with the exciting emotion "multi-spectral formula" for 15 minutes, the illumination program is stopped, and at this time, the second-stage multi-spectral formula illumination program is completed. Then, step 6590 is performed.

[0192] 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", then 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. Then, according to the information on the user's personal physiological data of the health check, adjust the lighting parameters in the "multi-spectral formula" of the "target emotion". For example, when the physiological data of the health check shows that the user has hypertension, diabetes, or epilepsy, the lighting parameters of the "multi-spectral formula" (such as color rendering index - Ra, stroboscopic, light intensity, or color temperature, etc.) in Equation 3 can be adjusted according to these diseases to obtain the adjusted "target emotion", and then store it in the cloud 610. Then, directly go to step 6550. The user uses the client device 630 to find the lighting parameters of the "multi-spectral formula" corresponding to the adjusted "target emotion" in the cloud 610. Then, repeat steps 6590 to step 6530 to step 6550, and then directly go from step 6550 to step 6580 until the user's emotion has reached the "target emotion". Then, perform step 6610.

[0193] Step 6610: Stop the lighting program.

[0194] Finally, it should be emphasized again that when the present invention uses the physiological data of the health check to adjust the parameters of the "multi-spectral formula" (such as color rendering index - Ra, stroboscopic, light intensity, or color temperature) in Equation 3, the limitations of the parameters of the "multi-spectral formula" (such as color rendering index - Ra, stroboscopic, light intensity, or color temperature) corresponding to each disease can be adjusted according to medical information. For another example, too low a color temperature will affect the clarity of the user's vision. 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. For example, a higher color rendering index (Ra) can be given to compensate for the need to use parameters with too low a color temperature to maintain excitement at a certain level. Therefore, in the above embodiment of the present invention, the limitation conditions of stroboscopic for epilepsy patients are only illustrative examples and are not used to limit the parameter adjustment of the "multi-spectral formula" (such as color rendering index - Ra, stroboscopic, light intensity, or color temperature) in Equation 3 of the present invention to only the embodiment of epilepsy.

[0195] Finally, it should be emphasized again that the above description is only the preferred embodiment of the present invention and is not used to limit the scope of the rights of the present invention. At the same time, the above description should be understandable and implementable by those with ordinary knowledge in the relevant technical field. Therefore, other equivalent changes or modifications made without departing from the concepts disclosed by the present invention should all be included in the scope of the patent claims of the present invention.

Claims

1. A method for performing emotion navigation is executed 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 through the Internet. The cloud stores emotion coordinate information and the user's personal physiological data. Wherein, The emotion navigation method is characterized in that: Step S1, confirm the user's "initial emotion". The "initial emotion" of the user is confirmed at the lighting field end through a physiological monitoring device or by selecting to use IAPS stimulation, and the "initial emotion" is stored in the cloud. Step S2, set the "target emotion", which is set according to the user's needs on the client device and the "target emotion" is stored in the cloud. Step S3, obtain the user's personal physiological data, which is obtained by the client device from the cloud where the user's personal physiological data has been stored in the memory module. Step S4, select the "relay emotion" to complete the emotion navigation path setting. The client device connects to the cloud through the Internet, selects the "relay emotion" from the emotion coordinate information in the cloud, and stores the "relay emotion" in the cloud. Step S5, edit the "multi-spectral formula". The "multi-spectral formula" corresponding to the "target emotion" and the "multi-spectral formula" corresponding to the "relay emotion" are edited according to the light formula of the "relay emotion" and the "target emotion" selected by the emotion navigation path and the information on the user's personal physiological data. Step S6, execute the lighting program of the "multi-spectral formula" of the "relay emotion". The client device controls the lamp group in the lighting field end to perform a lighting process on the user for a set time according to the "multi-spectral formula" corresponding to the "relay emotion". Step S7, judge whether the "neutral emotion" has been reached. It is judged by the physiological monitoring device whether the user's emotion has reached the "neutral emotion". Step S8, execute the lighting program of the "multi-spectral formula" of the "target emotion". After it is judged that the user has reached the "neutral emotion", the client device controls the lamp group in the lighting field end to perform a lighting process on the user for a set time according to the "multi-spectral formula" corresponding to the "target emotion". Step S9, judge whether the "target emotion" has been reached. It is judged by the physiological monitoring device whether the user's emotion has reached the "target emotion". And Step S10, stop the lighting program. When it is judged that the user's emotion has reached the "target emotion", the lighting program is stopped.

2. The emotion navigation method according to claim 1, characterized in that : The "relay emotion" in step S3 is selected to be an emotion that is complementary to the user's "initial emotion".

3. The emotion navigation method according to claim 1, characterized in that : When determining whether the user's emotion has reached the "neutral emotion", it is to determine whether the user's emotion is neutral or near the origin.

4. The method of emotion navigation according to claim 1, characterized in that : The user's personal physiological data is a physiological data of the user's health check.

5. The method of emotion navigation according to claim 1, characterized in that : If it is determined that the user's emotion has not reached the "neutral emotion", after adjusting the corresponding "multi-spectral formula" of the "relay emotion" according to the user's personal physiological data, steps S6 to S7 are re-executed.

6. The method of emotion navigation according to claim 1, characterized in that : The physiological monitoring device can be an electroencephalograph (EEG) or a wearable electronic device, including: a smart phone or a wearable device or a wearable device with the ability to measure sympathetic and parasympathetic nerve signals.

7. The method of emotion navigation according to claim 1, characterized in that : The "multi-spectral formula" is at least composed of the following light parameters, and the light parameters include the color temperature, illuminance, flash frequency, and color rendering index (Ra) of the illumination.

8. The method of emotion navigation according to claim 7, characterized in that : The "multi-spectral formula" is a formula formed by a Peripheral System Score (LSS): LSS = t x [a x f eeg (freq) + b x f eeg (Ra) + c x f eeg (CTI) + d x f eeg (I)], where a, b, c, and d are variable factor coefficients, CTI is the color temperature, and t is the illumination time.

9. The method of emotion navigation according to claim 1, characterized in that: When determining whether the user's emotion has reached the "neutral emotion", it is to determine whether the user's emotion is near the center point or the origin on the emotion coordinate diagram.

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