A method and system for emotion analysis based on pulse wave sequence parameter phase space

Abstract

The present invention provides a method and system for emotion analysis based on pulse wave order parameter phase space, comprising: a data acquisition unit for acquiring pulse wave signals from pulse sites; a data preprocessing unit for determining optimal compression pressure and order parameters that dominate pulse wave motion; an artificial intelligence training platform for obtaining personalized phase space balance centers and balance parameters; an order parameter phase space construction unit for obtaining the coordinates of the center points of each measurement site; and an emotion analysis unit for analyzing different emotion patterns based on the relationship between the center point coordinates of each measurement site and the phase space balance parameters. The solution provided by the present invention has the following beneficial effects: by determining personalized phase space balance parameters, a personalized order parameter phase space is constructed, enabling personalized emotion analysis.

Description

Technical Field

[0001] The present application relates to the field of medical equipment, and in particular to a method and system for emotion analysis based on pulse wave sequence parameter phase space. Background Art

[0002] There is a growing awareness of the significant impact that emotions have on health. Negative emotions can impact both physical and mental well-being, while positive emotions can promote health. Different emotional expressions can also have varying impacts on health. Therefore, the question of how to objectively quantify emotions and use them to guide rehabilitation is a crucial topic.

[0003] Modern medicine has studied the impact of emotions on health, including the immune, nervous, and endocrine systems, as well as their effects on human function and structure. However, there is no definitive way to apply these findings to guide human health. Traditional Chinese Medicine (TCM) focuses on the relationship between the human body and the universe, between the spirit and the body, and on the connection between the human body and mental activity. Based on clinical practice, the Emotional Pulse Method has established a theoretical framework for the impact of emotions on the state of Qi and blood. Other TCM pulse methods can also assess emotions, but these methods are relatively abstract and difficult to quantify.

[0004] Integrating modern science to quantitatively characterize and assess emotional health is a crucial topic. We quantitatively characterize pulse parameters through sensor measurements and mathematical model calculations. Integrating this with traditional Chinese medicine theory, we apply this technology to the quantitative assessment of human emotional patterns and spectrums, facilitating emotional research and management.

[0005] The following are two examples of existing background technology:

[0006] Example 1: Chinese Patent "CN201922151949.2 A Traditional Chinese Medicine Emotional Health Assessment Instrument"

[0007] This patent discloses a TCM emotional health assessment instrument, comprising a main unit and a camera, the main unit and the camera being connected by wires; a mounting assembly, the mounting assembly being mounted on the camera, the mounting assembly comprising a mounting plate, a connecting rod, a mounting box, a support plate, a first adjustment mechanism, and a second adjustment mechanism, the connecting rod being fixedly mounted on one side of the mounting plate, and the mounting box being fixedly mounted on an end of the connecting rod away from the mounting plate. The TCM emotional health assessment instrument provided by this patent can adjust the camera to an appropriate position, enabling the camera to better capture the patient's image and allowing the patient's various behaviors and expressions to be clearly transmitted to the main unit, making the analysis results more accurate and more conducive to the diagnosis of the patient's condition.

[0008] Example 2: Chinese Patent "CN201710592630.6 A Traditional Chinese Medicine Constitution and Emotion Identification and Conditioning System"

[0009] The patent discloses a TCM constitution and emotion identification and conditioning system, comprising: a cabinet, a base, a touch screen; a control panel located on the side of the cabinet; and also comprising: cameras symmetrically distributed above and below the touch screen; an automatic fill light device and a height detection device located above the touch screen and sequentially mounted on the cabinet panel; a speaker, an ID card reader, and a printer located below the touch screen and sequentially mounted on the cabinet panel; a weight detection device and an industrial control host installed on the base; and the industrial control host is provided with an analysis and processing module and an information storage module, wherein the analysis and processing module has a built-in constitution and emotion identification program. The patent is set up for touch-screen operation, which is simple and convenient, improving the user experience. It collects tongue coating and facial images from multiple angles, effectively improving the accuracy of constitution identification and emotion recognition, establishing independent health records for users and providing accurate conditioning plans.

[0010] Because the natural emotions of the human body are complex mixtures of multiple emotions, and the arousal patterns and degrees of individual emotions are obviously individual, the current method based on big data statistical averaging is difficult to meet clinical needs.

[0011] For example, the technical solutions described in Chinese patents "CN201922151949.2: A Traditional Chinese Medicine Emotional Health Assessment Instrument" and "CN201710592630.6: A Traditional Chinese Medicine Constitution and Emotion Identification and Conditioning System" primarily rely on recording facial features with a camera, combined with traditional Chinese medicine facial and tongue diagnosis, to identify emotional patterns. However, these approaches fail to achieve quantitative characterization. Furthermore, this simple identification of emotions is difficult to directly guide adjustment and rehabilitation activities.

[0012] Therefore, the need to conduct personalized quantitative characterization of the subjects' emotional patterns and emotional spectrum has very important practical significance and is also an issue that needs to be urgently addressed. Summary of the Invention

[0013] The main purpose of the present invention is to overcome the defects of the above-mentioned prior art and provide an emotion analysis system based on the pulse wave sequence parameter phase space to solve the problem that the prior art cannot fully and quantitatively characterize the emotional state of the human body.

[0014] An emotion analysis system based on pulse wave order parameter phase space includes: a data acquisition unit for acquiring pulse wave signals from pulse sites; a data preprocessing unit for determining the optimal compression pressure and the order parameters that dominate pulse wave motion; an artificial intelligence training platform for obtaining personalized phase space balance parameters; an order parameter phase space construction unit for obtaining the center point coordinates of each measurement site; and an emotion analysis unit for analyzing different emotion patterns based on the relationship between the center point coordinates of each measurement site and the phase space balance parameters.

[0015] More preferably, the data acquisition unit collects pulse wave signals from six pulse sites, namely, Cun, Guan, and Chi, on the radial arteries at the wrists of the left and right hands.

[0016] More preferably, pressure is gradually increased at each pulse site, and pulse wave pressure data is collected over a period of time.

[0017] More preferably, the data preprocessing unit comprises the following sequence parameters for the dominant pulse wave motion: pulse position, pulse force and pulse rate; the pulse wave pressure data of each pulse site under each pressure segment are periodically segmented to remove baseline drift; the average pulse position, average pulse force and average pulse rate under each pressure segment are calculated respectively, and the pressure corresponding to the maximum pulse force is selected as the optimal pressure by comparing the average pulse force under each pressure segment. The pulse position, pulse force and pulse rate under this pressure segment are respectively the optimal pulse position P of the measurement site. best , optimal pulse F best and optimal pulse rate R best .

[0018] Better yet, the AI training platform can preliminarily divide the population into subcategories based on factors including but not limited to age, gender, physique, personality, and occupation, and learn and train based on the optimal pulse position, optimal pulse strength, and optimal pulse rate, outputting a personalized phase space balance center P. mid , F mid , R mid , and the phase space equilibrium parameter δ F , δ R , δ P ; The phase space equilibrium parameter δ F , δ R , δ P , the value range is 0-1.

[0019] More preferably, the order parameter phase space unit is constructed to obtain the coordinates of the center point of each measurement site, specifically including the order parameter pulse position, pulse force and pulse rate based on the dominant pulse wave movement, to construct the order parameter phase space for emotional analysis; according to the personalized phase space balance center P mid , F mid , R mid To determine the personalized phase space origin (0, 0, 0), thereby realizing the construction of personalized order parameter phase space; further, the coordinates of the center point of each measurement part (P core F core , R core ).

[0020] More preferably, the emotion analysis unit is used to analyze different emotion patterns, specifically including: analysis of emotional stress,

[0021] When Pcore ≤log(1-δ P ), emotional stress means being easily affected by external factors and generating emotions;

[0022] When -logδ P <P core ≤logδ P When the emotional stress level is normal;

[0023] When P core >log(1+δ P ), the emotional stress level is not easily affected by external factors and produces emotions.

[0024] More preferably, the emotion analysis unit is used to analyze different emotion patterns, specifically including: analysis of the degree of emotional outburst,

[0025] When F core ≤log(1-δ F ) when the emotional explosiveness is low after being stimulated and producing emotions;

[0026] When log(1-δ F )<F core ≤log(1+δ F ), the emotional explosiveness is normal after being stimulated and producing emotions;

[0027] When F core >log(1+δ F ) When the emotional explosiveness is high, the emotional explosiveness is strong after being stimulated.

[0028] More preferably, the emotion analysis unit is used to analyze different emotional patterns, specifically including: analysis of emotional mania and depression,

[0029] When R core ≤log(1-δ R ) When the emotional state is irritable, it is easy to suppress the emotions after being stimulated;

[0030] When log(1-δ R )<R core ≤log(1+δ R ) when the emotional mania is low and the tendency to express emotions after being stimulated is not obvious;

[0031] When R core >log(1+δ R ) When the mood is manic and depressed, it is easy to express emotions outwardly after being stimulated.

[0032] More preferably, it further includes a visual output unit for displaying the emotional spectrum of the subject formed by the distances between each measurement part of the individual and the center points of each measurement part.

[0033] Even better, it also includes an emotional database. The emotional model quantitatively depicts the changes in individual emotional patterns by comparing them with historical data, helping users see the fluctuations and evolution patterns of their emotional patterns, and helping health managers to more comprehensively and quantitatively grasp the emotional health status of relevant personnel.

[0034] It also includes an emotion analysis method based on the pulse wave order parameter phase space, which obtains the pulse wave signal of the pulse site; pre-processes the obtained data to determine the order parameter that dominates the pulse wave movement; obtains personalized phase space balance parameters based on the artificial intelligence training platform; obtains the order parameter phase space center point coordinates of each measurement site; and analyzes different emotion patterns based on the relationship between the center point coordinates of each measurement site and the phase space balance parameters.

[0035] More preferably, the acquired data is preprocessed, and the order parameters that dominate the pulse wave movement include: pulse position, pulse force and pulse rate; the pulse wave signal data of the acquired pulse site is periodically segmented to remove baseline drift; the average pulse position, average pulse force and average pulse rate under each section of pressurization pressure are calculated respectively, and by comparing the average pulse force under each section of pressurization pressure, the pressurization pressure corresponding to the maximum pulse force is selected as the optimal pressurization pressure, and the pulse position, pulse force and pulse rate under this pressurization pressure are respectively the optimal pulse position P of the measurement site. best , optimal pulse F best and optimal pulse rate R best .

[0036] Better yet, the AI training platform can preliminarily divide the population into subcategories based on factors including but not limited to age, gender, physique, personality, and occupation, and learn and train based on the optimal pulse position, optimal pulse strength, and optimal pulse rate, outputting a personalized phase space balance center P. mid , F mid , R mid , and the phase space equilibrium parameter δ F , δ R , δ P ; The phase space equilibrium parameter δ F , δ R , δ P , the value range is 0-1.

[0037] Better, obtain the coordinates of the center point of each measurement site, specifically including the order parameters pulse position, pulse force and pulse rate based on the dominant pulse wave movement, and construct the order parameter phase space for emotional analysis; according to the personalized phase space balance center

[0038] P mid , F mid , R midTo determine the personalized phase space origin (0, 0, 0), thereby realizing the construction of personalized order parameter phase space; further, the coordinates of the center point of each measurement part (P core , F core , R core ).

[0039] More preferably, the analysis of different emotional patterns specifically includes: analysis of emotional stress levels,

[0040] When P core ≤log(1-δ P ), emotional stress means being easily affected by external factors and generating emotions;

[0041] When -logδ P <P core ≤logδ P When the emotional stress level is normal;

[0042] When P core >log(1+δ P ), the emotional stress level is not easily affected by external factors and produces emotions.

[0043] More preferably, the analysis of different emotional patterns specifically includes: analysis of emotional burst degree,

[0044] When F core ≤log(1-δ F ) when the emotional explosiveness is low after being stimulated and producing emotions;

[0045] When log(1-δ F )<F core ≤log(1+δ F ), the emotional explosiveness is normal after being stimulated and producing emotions;

[0046] When F core >log(1+δ F ) When the emotional explosiveness is high, the emotional explosiveness is strong after being stimulated.

[0047] More preferably, the analysis of different emotional patterns specifically includes: analysis of emotional mania and depression,

[0048] When R core ≤log(1-δ R ) When the emotional state is irritable, it is easy to suppress the emotions after being stimulated;

[0049] When log(1-δ R )<R core ≤log(1+δ R), the degree of manic-depressive mood is the tendency to express emotions after being stimulated:

[0050] When R core >log(1+δ R ) When the mood is manic and depressed, it is easy to express emotions outwardly after being stimulated.

[0051] More preferably, the distance between each measurement site of the individual and the center point of each measurement site is displayed to form the emotional spectrum of the subject.

[0052] The beneficial effects of the solution of the present invention are as follows:

[0053] 1. Mainly by introducing the concept of "order parameter" in statistical physics into pulse wave research, and by constructing the order parameter phase space of pulse waves, it is possible to distinguish different emotional patterns and quantitatively characterize the emotional spectrum.

[0054] 2. By determining the personalized phase space equilibrium parameters, a personalized order parameter phase space is constructed, and personalized emotion analysis is achieved.

[0055] 3. Based on the artificial intelligence training platform, as the number of user measurements increases, the personalized phase space balance parameters will become more and more accurate, thereby achieving the effect of more and more accurate judgment of individual emotions.

[0056] 4. Compared with the existing technology, the information collection module and analysis module in the technical solution proposed by the present invention are more quantitative and feasible, and can provide users with more comprehensive information on their emotional health, including both emotional patterns, that is, the main emotional components, and emotional expression patterns, that is, whether emotions are easily stimulated and the resulting emotional expression tendencies.

[0057] 5. Based on the emotional database, the present invention can quantitatively characterize the changes in individual emotional patterns by comparing them with historical data, helping users to see the fluctuations and evolution of their emotional patterns. It can also help health managers to more comprehensively, objectively and quantitatively grasp the emotional health status of relevant personnel; this solution can directly connect with personalized health management practices. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] The present application will be further described in the form of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting, and in these embodiments, like numbers represent like structures, wherein:

[0059] Figure 1 Schematic diagram of an emotion analysis system based on pulse wave sequence parameter phase space;

[0060] Figure 2 Schematic diagram of the pulse wave signal of a part of the body under a certain pulse pressure;

[0061] Figure 3 Schematic diagram of the comparison of results before removing baseline drift;

[0062] Figure 4 Schematic diagram of the comparison of results after removing baseline drift;

[0063] Figure 5 Schematic diagram of the phase space distribution of the order parameters of a subject;

[0064] Figure 6 Schematic diagram of the emotional spectrum distribution of a subject. DETAILED DESCRIPTION

[0065] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of the present application. The technical features of each embodiment can be combined with each other to form a practical solution to achieve the purpose of the invention. For ordinary technicians in this field, without paying any creative work, they can also apply this application to other similar scenarios based on these drawings. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0066] It should be understood that the terms "system" and "unit" as used herein are a method for distinguishing between different components, elements, parts, portions, or assemblies at different levels. However, other expressions may be substituted if they achieve the same purpose. Furthermore, a "system" and "unit" may be implemented by software or hardware and may refer to a physical or virtual component having such functionality.

[0067] Flowcharts are used in this application to illustrate the operations performed by the systems according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed precisely in order. Instead, the steps may be processed in reverse order or simultaneously. Furthermore, other operations may be added to these processes, or one or more operations may be removed from these processes. The technical solutions in the various embodiments may be combined to achieve the purpose of the present invention.

[0068] Example 1

[0069] An emotion analysis system based on pulse wave order parameter phase space includes: a data acquisition unit for acquiring pulse wave signals at pulse sites; a data preprocessing unit for determining optimal pressurization pressure and order parameters that dominate pulse wave motion; an artificial intelligence training platform for obtaining personalized phase space balance centers and balance parameters; a construction order parameter phase space unit for obtaining the coordinates of the center points of various measurement sites; and an emotion analysis unit for analyzing different emotion patterns based on the relationship between the coordinates of the center points of various measurement sites and the phase space balance parameters.

[0070] This invention primarily introduces the concept of "order parameters" from statistical physics into pulse wave research. By constructing a pulse wave order parameter phase space, it enables the identification of different emotional patterns. By determining personalized phase space equilibrium parameters, a personalized order parameter phase space is constructed, enabling personalized emotion identification.

[0071] Example 2

[0072] The implementation of the present invention includes a data acquisition unit, a data preprocessing unit, an artificial intelligence training platform, a unit for constructing an order parameter phase space, an emotion analysis unit, a visual output unit, and an emotion database. Figure 1 shown.

[0073] Data acquisition unit

[0074] The data acquisition unit of the present invention includes a pressure sensor, which needs to collect pulse wave signals at six locations, namely, Cun, Guan, and Chi, on the radial arteries at the left and right wrists. Pressure is applied to the six locations, namely, Cun, Guan, and Chi, on the radial arteries at the left and right wrists. For example, the pressure range is 75g-250g, with pressure applied every 25g, and pulse wave pressure data is collected for 10 seconds. The pressure signals of the pulse wave are collected at six locations, namely, Cun, Guan, and Chi, on the radial arteries at the left and right wrists, respectively. The pulse wave data of each measuring location under 8 pressure levels can be obtained, such as Figure 2 As shown, the pulse wave signal of a part of the body is displayed under a pulse pressure of a period of time (10 seconds).

[0075] The pressure range is not limited to 75g-250g, but can be other ranges; it is not limited to pressurizing once every 25g, but can be other pressurizing amplitudes; it is not limited to collecting pressure data for 10 seconds, but can be other time ranges.

[0076] The data acquisition unit can be set up separately or integrated with a pressure increasing device and a pressure sensor. For example, an active pressurized pulse wave collector controlled by a stepper motor includes a pressure increasing device that can actively increase pressure on the pulse site, and also includes a pulse wave signal acquisition device pressure sensor that can collect the pressure signal of the pulse wave.

[0077] Data preprocessing unit

[0078] This application believes that the parameters in the time domain parameters and frequency domain parameters of the pulse wave that can characterize the characteristics of the pulse wave number situation are all order parameters. The three order parameters that dominate the pulse wave motion among the pulse wave order parameters are: pulse position, pulse force and pulse rate. The order parameters of the pulse wave are important parameters that characterize the orderliness of the different dimensions of the pulse wave signal; for the pulse wave system, the order parameters are independent of each other and have clear physical meanings. The following will specifically demonstrate the calculation method of the three order parameters that dominate the pulse wave motion among the pulse wave order parameters: pulse position, pulse force and pulse rate.

[0079] Split cycle

[0080] like Figure 2 As shown in Figure 1, the pulse wave data under each pressure segment is segmented into cycles. The window sliding method is used to determine the starting point of each beat cycle (t start , p start ), and end point (t end , p end ).

[0081] Remove baseline drift

[0082] like Figure 3 As shown, for each cycle of pulse wave data, the baseline drift is removed. The method is that each data point O(t i , p i ) remains unchanged, and the vertical coordinate is reduced by the starting point (t start , p start ) and the end point (t end , p end ) The coordinates of each point after removing the baseline drift are (t′ i , p′ i ):

[0083] t′ i =t i

[0084]

[0085] Calculate the dominant order parameter

[0086] Take the three order parameters that dominate the pulse wave motion: pulse position, pulse force and pulse rate as an example. For the i-th beat cycle, the “pulse position” P i is the pressure value p at the starting point start , "Pulse" F i is the peak value p peak , pulse rate R i The time between the start and end points is calculated as Here, i=1, 2, ..., n, and there are n beat cycles under each compression pressure.

[0087] For the jth section of pressurization pressure, calculate the average pulse position under the pressurization pressure of this section Average pulse strength and average pulse rate

[0088]

[0089]

[0090]

[0091] Wherein, j=1, 2, ..., 8.

[0092] Determine the optimal compression pressure

[0093] By comparing the average pulse force under the pressure of 75g-250g The size of the pulse force is selected The corresponding pressurization pressure is the optimal pressurization pressure, and the pulse position under this pressurization pressure pulse force and pulse rate The best pulse position P for the measurement site is respectively best , optimal pulse F best and optimal pulse rate R best .

[0094] Output personalized phase space equilibrium center and equilibrium parameters

[0095] like Figure 1 As shown in the figure, after data preprocessing, the optimal pulse position, optimal pulse force, and optimal pulse rate are transmitted to the artificial intelligence training platform to output personalized phase space equilibrium parameters. The artificial intelligence training platform includes generative adversarial networks or deep recurrent neural networks.

[0096] The artificial intelligence training platform will make preliminary subcategories of the population based on factors such as the subjects' age, gender, physique, personality and occupation, and conduct learning and training based on health big data to output personalized phase space equilibrium parameters.

[0097] In particular, when the same user is evaluated multiple times, his own data set constitutes a personalized sub-category. Based on the accuracy of the analysis results, the artificial intelligence training platform can output the phase space equilibrium center specifically for that individual.

[0098] P mid , F mid , R mid , and the phase space equilibrium parameter δF , δ R , δ P .

[0099] δ F , δ R , δ P The value range is 0-1, and the specific value is determined according to the parameters learned from the learning set.

[0100] Constructing a personalized order parameter phase space

[0101] Based on the dominant order parameter, the order parameter phase space PFR of emotion analysis is constructed. According to the personalized balance center (P mid , F mid , R mid ) to determine the personalized phase space origin, thereby realizing the construction of personalized order parameter phase space:

[0102] The optimal pulse position of the kth measurement site Optimal pulse strength and optimal pulse rate R best , at this point in phase space is calculated by the following formula:

[0103]

[0104]

[0105]

[0106] Among them, k=1, 2, ..., 6 represent the six measurement parts of left Cun, left Guan, left Chi, right Cun, right Guan, and right Chi respectively.

[0107] Therefore, the equilibrium parameter (P mid , F mid , R mid )’s position in this phase space is the origin of the phase space (0, 0, 0).

[0108] Furthermore, on this basis, the coordinates of the center points of the six measurement parts (P core , F core , R core There are many ways to calculate the center coordinates, such as taking a weighted average of the six corresponding parameters. Let's take the simplest averaging method as an example:

[0109]

[0110]

[0111]

[0112] Among them, k=1, 2, ..., 6 represent the six measurement parts of left Cun, left Guan, left Chi, right Cun, right Guan, and right Chi respectively.

[0113] Emotional Analysis Unit

[0114] Analysis of Emotional Patterns

[0115] According to the equilibrium range of the order parameter phase space, each order parameter can be divided into three modes:

[0116] Emotional stress

[0117] When P core ≤log(1-δ P ), according to Traditional Chinese Medicine theory, emotional stress refers to being easily affected by external factors and generating emotions;

[0118] When -logδ P <P core ≤logδ P According to TCM theory, the emotional stress level is normal;

[0119] When P core >log(1+δ P ), according to the theory of traditional Chinese medicine, emotional stress level means that one is not easily affected by external factors and does not produce emotions.

[0120] Emotional outburst

[0121] When F core ≤log(1-δ F ), according to the theory of traditional Chinese medicine, the degree of emotional explosiveness is the smaller explosive force after being stimulated;

[0122] When log(1-δ F )<F core ≤log(1+δ F ), according to TCM theory, emotional explosiveness refers to the general explosive force after being stimulated;

[0123] When F core >log(1+δ F ), according to the theory of traditional Chinese medicine, the degree of emotional explosiveness is the explosive power after being stimulated.

[0124] Depression

[0125] When R core ≤log(1-δ R ) According to TCM theory, emotional irritability is the tendency to suppress emotions after being stimulated;

[0126] When log(1-δ R )<R core ≤log(1+δR ), according to TCM theory, emotional irritability refers to the tendency to express emotions after being stimulated but not obviously;

[0127] When R core >log(1+δ R ), according to Chinese medicine theory, emotional irritability is the tendency to express emotions outwardly after being stimulated.

[0128] Table 1 Emotional expression pattern of a subject

[0129]

[0130] After the emotion analysis unit determines the subject's emotional pattern, it stores it in the emotion database. Specifically, when the same user undergoes multiple evaluations, their dataset forms a personalized sub-category, which the AI training platform can access. The AI training platform then performs preliminary sub-categorization based on factors such as the subject's age, gender, physical condition, personality, and occupation. Using health big data, the platform learns and trains, outputting personalized phase space equilibrium parameters. Multiple measurement iterations can be performed to obtain personalized phase space equilibrium parameters.

[0131] Emotional portrayal

[0132] Calculate the individual's measurement site and the center point of each measurement site (P core , F core , R core ) between k Here, distance can be calculated using a variety of mathematical methods, such as Euclidean distance, Manhattan distance, Chebyshev distance, Minkowski distance, Mahalanobis distance, angle cosine, Hamming distance, etc. Take Euclidean distance as an example:

[0133]

[0134] According to the theory of the five emotions in traditional Chinese medicine, the left Cun corresponds to joy, the left Guan corresponds to anger, the left Chi corresponds to fear, the right Cun corresponds to sadness, the right Guan corresponds to thinking, and the right Chi corresponds to fear. k Determine the emotional index E corresponding to the emotion k Finally, the emotional spectrum of the subject can be drawn, such as Figure 6 shown.

[0135] Based on the emotional database, the present invention can quantitatively characterize the changes in individual emotional patterns by comparing with historical data, helping users to see the fluctuations and evolution patterns of their emotional patterns. It can also help health managers to more comprehensively and quantitatively grasp the emotional health status of relevant personnel; this solution can directly connect with personalized health management practices.

[0136] This method was used to analyze the emotional patterns of 220 subjects; the results showed that the identification results given by this method were in good agreement with the results of the scale filled out by the subjects, with an accuracy of up to 90%.

[0137] Figure 2-Figure 6 This is the output result of a real measurement case. Figure 2-Figure 4 is the data preprocessing result, Figure 5 The order parameter phase space is constructed to determine the personalized balance parameters based on the artificial training platform. Based on this phase space, the emotional index of each emotional component is measured to form the emotional spectrum distribution as shown in the following figure: Figure 6 shown.

[0138] Compared with the existing technology, the information collection module and analysis module in the technical solution proposed in the present invention are more quantitative and feasible, and can provide users with more comprehensive information on their emotional health, including both emotional patterns, that is, the main emotional components, and emotional expression patterns, that is, whether emotions are easily stimulated and the resulting emotional expression tendencies.

[0139] Furthermore, after multiple measurements, the present invention can quantitatively characterize the changes in individual emotional patterns based on the emotional database by comparing with historical data, helping users to see the fluctuations and evolution of their emotional patterns. It can also help health managers to more comprehensively and quantitatively grasp the emotional health status of relevant personnel and connect with personalized management plans.

[0140] A method for emotion analysis based on the phase space of pulse wave sequence parameters corresponds to the system method. For details, see the system part.

[0141] The beneficial effects that may be brought about by the embodiments of the present application include but are not limited to:

[0142] 1. By introducing the concept of "order parameter" in statistical physics into pulse wave research, the order parameter phase space is constructed to achieve the analysis of different emotional patterns and the quantitative characterization of the emotional spectrum;

[0143] 2. By determining personalized phase space equilibrium parameters, a personalized order parameter phase space is constructed, achieving personalized emotion analysis;

[0144] 3. Based on the AI training platform, as the number of user measurements increases, the personalized phase space equilibrium parameters will become increasingly accurate, thereby achieving an effect of increasingly accurate judgment of individual emotions. This is conducive to clinical promotion and industrial application.

[0145] It should be noted that different embodiments may produce different beneficial effects. In different embodiments, the beneficial effects that may be produced may be any one or a combination of the above, or any other possible beneficial effects.

[0146] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only an example and does not constitute a limitation to the present application.

[0147] In addition, unless explicitly stated in the claims, the order of the processing elements and sequences, the use of alphanumeric characters, or the use of other names described in this application are not intended to limit the order of the processes and methods of this application. Although the above disclosure discusses some of the invention embodiments currently considered useful through various examples, it should be understood that such details are only for illustrative purposes, and the appended claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that are consistent with the spirit and scope of the embodiments of this application.

[0148] Similarly, it should be noted that in order to simplify the description of the present disclosure and thus facilitate understanding of one or more embodiments of the invention, the foregoing description of the embodiments of the present disclosure sometimes combines multiple features into a single embodiment, figure, or description thereof. However, this disclosure method does not mean that the subject matter of the present disclosure requires more features than those mentioned in the claims.

[0149] Finally, it should be understood that the embodiments described in this application are merely illustrative of the principles of the embodiments of this application. Other variations may also fall within the scope of this application. Therefore, by way of example and not limitation, alternative configurations of the embodiments of this application may be considered consistent with the teachings of this application. Accordingly, the embodiments of this application are not limited to the embodiments explicitly introduced and described in this application.

Claims

1. An emotion analysis system based on pulse wave sequence parameter phase space, characterized in that: include: A data acquisition unit, used for acquiring a pulse wave signal at a pulse site; A data pre-processing unit for determining the optimal compression pressure and the sequence parameters of the dominant pulse wave motion; An artificial intelligence training platform is used to obtain personalized phase space balance centers and balance parameters; an order parameter phase space unit is constructed to obtain the center point coordinates of each measurement site; an emotion discrimination unit is used to discriminate different emotion patterns based on the relationship between the center point coordinates of each measurement site and the phase space balance parameters; and the data acquisition unit collects pulse wave signals from six pulse sites, namely, Cun, Guan, and Chi, on the radial arteries at the wrists of both hands; Gradually increase pressure on each pulse site and collect pulse wave pressure data over a period of time; The data preprocessing unit controls the order parameters of the pulse wave motion, including pulse position, pulse force, and pulse rate; performs periodic segmentation on the pulse wave pressure data at each pressure segment of each pulse site to remove baseline drift; calculates the average pulse position, average pulse force, and average pulse rate at each pressure segment, compares the average pulse force at each pressure segment, and selects the pressure corresponding to the maximum pulse force as the optimal pressure. The pulse position, pulse force, and pulse rate at this pressure are the optimal pulse position, optimal pulse force, and optimal pulse rate at the measurement site, respectively; the artificial intelligence training platform performs preliminary subclassification of the population based on factors including but not limited to age, gender, physique, personality, and occupation of the subjects, and performs learning and training based on the optimal pulse position, optimal pulse force, and optimal pulse rate to output a personalized phase space equilibrium center P. mid , F mid , R mid , and the phase space equilibrium parameter δ F , δ R , δ P ; The phase space equilibrium parameter δ F , δ R , δ P , the value range is 0-1; the order parameter phase space unit is used to obtain the coordinates of the center point of each measurement site, specifically including the order parameters pulse position, pulse force and pulse rate based on the dominant pulse wave movement, to construct the order parameter phase space for emotional analysis; according to the personalized phase space balance center P mid , F mid , R mid To determine the personalized phase space origin (0, 0, 0), thereby realizing the construction of personalized order parameter phase space; further, the coordinates of the center point of each measurement part (P core , F core , R core ); also includes a visual output unit that displays the emotional spectrum of the subject composed of the distances between each measurement part of the individual and the center points of each measurement part.

2. The system according to claim 1, wherein: It also includes an emotional database. The emotional model quantitatively depicts the changes in individual emotional patterns by comparing them with historical data, helping the subjects to see the fluctuations and evolution laws of their emotional patterns, and to grasp the emotional health status of the subjects more comprehensively and quantitatively.

3. A method for emotional analysis based on pulse wave sequence parameter phase space, characterized in that: Acquire the pulse wave signal at the pulse site; pre-process the acquired data to determine the order parameter that dominates the pulse wave motion; obtain personalized phase space equilibrium parameters based on the artificial intelligence training platform; Obtain the coordinates of the center point of the order parameter phase space of each measurement site; analyze different emotional patterns according to the position of the center point coordinates of each measurement site and the relationship between the center point coordinates of each measurement site and the phase space balance parameter; preprocess the acquired data, and the order parameters that dominate the pulse wave movement include: pulse position, pulse force and pulse rate; periodically segment the pulse wave signal data of the acquired pulse site to remove baseline drift; calculate the average pulse position, average pulse force and average pulse rate under each section of pressurization pressure, and by comparing the average pulse force under each section of pressurization pressure, select the pressurization pressure corresponding to the maximum pulse force as the optimal pressurization pressure, and the pulse position, pulse force and pulse rate under this pressurization pressure are respectively the optimal pulse position, optimal pulse force and optimal pulse rate of the measurement site; the artificial intelligence training platform performs preliminary subclassification of the population according to the subjects' factors including but not limited to age, gender, physique, personality and occupation, and learns and trains based on the optimal pulse position, optimal pulse force and optimal pulse rate to output a personalized phase space balance center P mid , F mid , R mid , and the phase space equilibrium parameter δ F , δ R , δ P ; The phase space equilibrium parameter δ F , δ R , δ P , the value range is 0-1; obtain the coordinates of the center point of each measurement site, specifically including the order parameters pulse position, pulse force and pulse rate based on the dominant pulse wave movement, and construct the order parameter phase space for emotional analysis; according to the personalized phase space balance center P mid , F mid , R mid To determine the personalized phase space origin (0, 0, 0), thereby realizing the construction of personalized order parameter phase space; further, the coordinates of the center point of each measurement part (P core , F core , R core ); Displays the emotional spectrum of the subject composed of the distance between each measurement site and the center point of each measurement site.

Images