Intelligent psychological diagnosis robot, equipment and storage medium

Abstract

The invention relates to the technical field of artificial intelligence, in particular to a psychological intelligent diagnosis robot, equipment and a storage medium. Comprising a robot position adjustment module, an environment detection and analysis module, a physiological data acquisition module, a physiological data analysis module, a behavior data acquisition module, a behavior data analysis module, a psychological test module, a symptom evaluation module and a management database. The system obtains the influence coefficient of the current diagnosis environment on the patient according to the environmental factor analysis of the diagnosis environment, obtains the influence degree of the psychological state on the physiological reaction according to the physiological index analysis of the patient, and obtains the body relaxation degree of the patient through the behavior data analysis of the patient. The emotion recovery degree of the patient is obtained through voice recording and the emotion test scale, the psychological health condition of the patient is comprehensively analyzed, the corresponding suggestion scheme is provided, the psychological health condition of the patient can be comprehensively mastered, and more accurate psychological health service is achieved.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to a psychological intelligence diagnosis robot, device and storage medium. Background Art

[0002] With the development of society and the accelerated pace of people's lives, mental health issues are receiving increasing attention. Traditional psychological diagnosis methods may have problems such as low efficiency and limited resources. Against this background, psychological intelligent diagnostic robots have come into being. On the one hand, the continuous advancement of artificial intelligence technology has provided technical support for the development of psychological intelligent diagnostic robots, enabling them to better understand and analyze users' language and behavioral performance. On the other hand, people's emphasis on mental health and their demand for personalized and immediate psychological services have also promoted the research and development of psychological intelligent diagnostic robots, which can break through the limitations of time and space and provide users with preliminary diagnosis and suggestions at any time.

[0003] For example, the existing Chinese patent with publication number CN117216230A discloses an AI psychologist dialogue interaction processing method, system, terminal and medium. The scheme obtains the first dialogue text input by the user; analyzes and processes the first dialogue text to obtain the first user tag; constructs a user tag set according to the first user tag; encodes the first dialogue text to generate a text code; obtains the user's state sequence; uses a pre-trained state transition model to analyze and process the user tag set, state sequence and text code to determine the target state node from a pre-built finite state machine model; uses the finite state machine model to generate feedback text based on the target state node, and returns the feedback text to the user; obtains the second dialogue text input by the user after receiving the feedback text to perform the next round of interaction processing. This application can improve the accuracy and security of the AI ​​psychologist system dialogue.

[0004] A Chinese patent with publication number CN117216228B discloses a psychological companion robot and its interaction method, which conducts in-depth analysis of each input text during each interaction to count the user's interaction satisfaction and interaction optimization demand, and accordingly confirms the adaptation position sorting and update frequency of the reply text in the interaction language library, effectively solving the problem that the fixed reply update frequency is difficult to adjust according to the specific needs of each user, ensuring the interaction quality and interaction effect of the psychological companion robot, improving the interaction accuracy of the psychological companion robot, and realizing personalized customization of user interaction optimization.

[0005] However, the above patent has the following problems: 1. The solution currently mainly performs intent analysis and key information extraction based on the user's text conversation input, and does not involve voice interaction. It may have certain limitations in understanding user input, and also limits its application in certain scenarios.

[0006] Second, the plan does not involve analyzing the psychological state of users before and after consultation, which may reduce the effectiveness of psychological counseling. This is because it is impossible to comprehensively compare and grasp the changing process of users’ psychological states, making it difficult to accurately evaluate the progress and effectiveness of counseling. It is also not conducive to timely adjusting counseling strategies and directions based on dynamic changes in users’ psychological states, which may affect the in-depth understanding and effective resolution of users’ problems. Summary of the invention

[0007] In order to overcome the shortcomings of the background technology, the embodiments of the present invention provide a psychological intelligent diagnosis robot, device and storage medium, which can effectively solve the problems involved in the above-mentioned background technology.

[0008] The purpose of the present invention can be achieved through the following technical solutions: The first aspect of the present invention provides a psychological intelligent diagnostic robot, including: a robot position adjustment module, which is used to obtain the patient's sitting height and the number of distance intervals between the diagnostic robot and the patient, and adjust the screen height and screen inclination of the diagnostic robot accordingly.

[0009] The environmental detection and analysis module is used to detect the environmental factors of the diagnostic environment and analyze the impact coefficient of the current diagnostic environment on the patient. The environmental factors include the suitability of light at the patient's location, the impact of environmental noise, the suitability of environmental temperature, and the suitability of environmental humidity.

[0010] The physiological data acquisition module is used to obtain the patient's physiological indicators, including the heart rate difference of the patient in each time period group, the systolic pressure difference, diastolic pressure difference, and skin electrical response difference of the patient's blood pressure at each time point.

[0011] The physiological data analysis module is used to analyze the patient's physiological indicators to obtain the degree of influence of the psychological state on the physiological response.

[0012] The behavior data acquisition module is used to obtain the patient's concentration level and the uniformity of the speed at which the patient performs action tasks.

[0013] The behavioral data analysis module is used to analyze the patient's concentration level and the uniformity of the speed at which the patient performs the action task to obtain the degree of neural relaxation corresponding to the patient's attention and the degree of neural relaxation corresponding to the uniformity of the speed at which the patient performs the action task, thereby obtaining the patient's physical relaxation level.

[0014] The psychological test module is used to obtain the patient's pre-diagnosis tone, the emotional score corresponding to the tone in each time period, and the patient's emotional scale score before and after diagnosis through voice recording and emotional test scale, and then analyze the patient's emotional recovery degree.

[0015] The symptom assessment module is used to comprehensively analyze the patient's mental health level, and then analyze the patient's mental health condition and provide corresponding recommendations for the patient's mental health condition.

[0016] The management database is used to store the suitable light intensity range for the human body, the emotion classification model and the score of each emotion classification.

[0017] Preferably, in the first step, the screen height of the diagnostic robot is measured, and at the same time, the sitting height of the patient is measured after the patient sits down.

[0018] In the second step, the screen height of the diagnostic robot is subtracted from the sitting height of the patient to obtain a corresponding adjustment value of the screen height of the diagnostic robot, and the screen height of the diagnostic robot is adjusted accordingly.

[0019] The third step is to measure the distance between the diagnostic robot and the patient, divide the distance into several intervals according to the set distance, and count the number of distance intervals between the diagnostic robot and the patient.

[0020] The fourth step is to set a tilt angle standard for the unit distance interval, recorded as the unit distance interval adjustment angle, and superimpose the unit distance interval adjustment angles according to the number of distance intervals between the robot and the diagnosed patient to obtain the screen tilt adjustment value of the diagnostic robot, and use this to adjust the screen tilt of the diagnostic robot.

[0021] Preferably, the specific analysis method of the environmental detection and analysis module is as follows: in the first step, a number of position points are selected around the patient's position, recorded as each position point of the patient's position, and a light meter is used to measure each position point of the patient's position to obtain the light intensity of each position point of the patient's position, and the light intensity of the patient's position is obtained by taking the average value, which is recorded as , read the suitable light intensity range for human body from the management database, extract the maximum and minimum values ​​corresponding to the suitable light intensity range for human body, and record them as the maximum suitable light intensity , Minimum suitable light intensity , substituting it into the formula Get the appropriate lighting level for the patient's location .

[0022] The second step is to select several time points with equal time intervals during the diagnosis process, record them as time points, measure the noise value in the environment at each time point with a noise meter, and calculate the average value to obtain the environmental noise value of the diagnosis process, and compare it with the preset maximum allowable environmental noise value to obtain the degree of environmental noise impact. .

[0023] The third step is to detect the ambient temperature and humidity at each time point using a thermometer and a hygrometer. The ambient temperature suitability and ambient humidity suitability are analyzed according to the method of analyzing the light suitability of the patient's location, and are recorded as .

[0024] The fourth step is to analyze the impact coefficient of the current diagnostic environment on the patient. The formula is: ,in They respectively represent the weight factors of the set light suitability, environmental noise impact, environmental temperature suitability, and environmental humidity suitability.

[0025] Preferably, the specific analysis method of the influence of the psychological state on the physiological response is as follows: the first step is to divide the diagnosis process into a number of unit time periods according to the set time length, recorded as each detection time period, and measure the patient's heart rate within the unit time length before diagnosis, recorded as , and after the diagnosis begins, the patient's heart rate is measured in each detection time period, and the heart rate difference of each detection time period of the patient is obtained by subtracting the heart rate of each detection time period from the heart rate of the previous detection time period, which is recorded as , Indicates The number of the detection time period, .

[0026] The second step is to test the systolic and diastolic blood pressure of the patient before diagnosis, recorded as , respectively monitor the systolic and diastolic blood pressure of the patient at each time point, recorded as , , Indicates The number of the time point, , through the formula , Get the systolic pressure difference and diastolic pressure difference of the patient's blood pressure at each time point , , Respectively represent the patient The systolic and diastolic blood pressure at each time point.

[0027] The third step is to clean the skin of the patient's test area and place the two electrodes of the skin electrical test instrument on the cleaned skin to test the patient's skin electrical response value before diagnosis, which is recorded as At the same time, the skin electrical response value of the patient at each time point is tested after the diagnosis begins, recorded as , and by the formula Get the difference of the patient's skin electrical response at each time point .

[0028] The fourth step is to read the heart rate difference of the patients in each time period. , the systolic blood pressure difference at each time point , diastolic pressure difference , Skin galvanic response difference , substituting it into the formula Get the degree of influence of psychological state on physiological response ,in Respectively represent the weight factors of the set heart rate, blood pressure, and skin galvanic response value, Indicates the number of time period groups, Indicates the number of time periods.

[0029] Preferably, the specific analysis method of the behavior data acquisition module is as follows: in the first step, during the diagnosis process, the eye movement trajectory of the patient is tracked by an eye tracker to generate the patient's eye movement trajectory, the robot screen is recorded as the gaze area, and the length of time the patient's gaze stays in the gaze area is read from the patient's eye movement trajectory and recorded as , divide the unit time period into fixed time periods, obtain the number of blinks of the patient in each unit time period, and divide the number of blinks of the patient in each unit time period by the length of the unit time period to obtain the blink frequency of the patient in each unit time period, recorded as , Indicates The number of the unit time period, , substituting it into the formula Get the patient's concentration level , They represent the preset reference values ​​of the duration of gaze stay and blink frequency. They represent the weight factors of the set gaze dwell time and blink frequency respectively. Indicates the number of unit time periods.

[0030] The second step is to issue a specified action task to the patient at each time point during the diagnosis process, recorded as the action task at each time point, and obtain the duration of the patient's action task at each time point, recorded as At the same time, the motion capture device is used to obtain the movement path of the marked points of each body part of the patient at each time point, and the movement distance is recorded as , Indicates The number of the body part landmarks, , through the formula Get the speed of the patient's action task at each time point , substituting it into the formula Get the uniformity of the speed at which the patient performs the action task , Indicates the number of time periods.

[0031] Preferably, the specific analysis method of the behavior data analysis module is: reading the patient's concentration level respectively , the uniformity of the speed at which patients perform motor tasks , substituting it into the formula Get the patient's level of physical relaxation , They represent the weight factors of the preset concentration level and the uniformity of the speed of executing the action task respectively.

[0032] Preferably, the specific analysis method of the psychological test module is: before the patient is diagnosed, a fixed-length voice recording is performed on the patient, and the fixed-length voice is divided into time periods after the diagnosis, and the patient's voice in each time period is recorded, which are respectively recorded as the patient's voice before diagnosis and the voice in each time period, and the patient's voice before diagnosis and the voice in each time period are denoised, and the patient's tone is extracted therefrom, which are recorded as the patient's tone before diagnosis and the tone in each time period, and the emotion classification model and each emotion classification score are extracted from the management database, and the patient's tone before diagnosis and the tone in each time period are compared with them to obtain the emotion classification corresponding to the patient's tone before diagnosis and the tone in each time period, and then the emotion score corresponding to the patient's tone before diagnosis and the tone in each time period is matched, which is recorded as , Indicates The number of the time period, At the same time, the patient was tested before and after diagnosis using the emotional test scale, and the emotional scale scores of the patient before and after diagnosis were recorded as , substituting it into the formula Get the patient's emotional recovery level ,in By formula get, Indicates The emotional score corresponding to the tone of voice in each time period, Indicates the number of time periods, They respectively represent the emotional score corresponding to the set tone and the weight factor of the emotional scale score.

[0033] Preferably, the specific analysis method of the symptom assessment module is: respectively reading the influence coefficient of the current diagnostic environment on the patient , the degree of influence of psychological state on physiological response , the patient's degree of physical relaxation , the patient's emotional recovery , substituting it into the formula Get the patient's mental health level , They respectively represent the influence coefficient of the current diagnostic environment on the patient, the influence of the psychological state on the physiological reaction, the patient's physical relaxation degree, and the weight factors of the emotional recovery degree. The patient's mental health degree is compared with the mental health conditions corresponding to the preset mental health degree ranges to obtain the patient's mental health condition, feedback is given and a corresponding suggestion plan for the patient's mental health condition is provided to the patient.

[0034] A second aspect of the present invention provides an electronic device, characterized in that the device includes a processor, a memory and a communication bus, and the memory stores a computer-readable program that can be executed by the processor.

[0035] The communication bus realizes the connection and communication between the processor and the memory.

[0036] When the processor executes the computer-readable program, the steps of a psychological intelligent diagnosis robot as described in the present invention are implemented.

[0037] The third aspect of the present invention provides a storage medium, characterized in that: the storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement steps in a psychological intelligent diagnostic robot.

[0038] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention improves the user experience of patients by adjusting the screen height and screen inclination of the diagnostic robot, allowing patients to view the information on the screen more comfortably and reduce fatigue and discomfort caused by uncomfortable viewing posture.

[0039] 2. The present invention obtains the influence coefficient of the current diagnostic environment on the patient based on the environmental factor analysis of the diagnostic environment, which can more comprehensively understand the specific influence of the diagnostic environment on the patient and reduce adverse effects.

[0040] 3. The present invention obtains the degree of influence of psychological state on physiological response based on the patient's physiological indicators, which can provide a deeper understanding of the relationship between the patient's body and mind, and help to diagnose the disease and assess health status more accurately.

[0041] Fourth, by analyzing the patient's degree of physical relaxation, the present invention can more intuitively understand the patient's neural and physical reactions in different states, so as to adjust the treatment or intervention strategy in a timely manner.

[0042] 5. By analyzing the patient's emotional recovery degree, the present invention can more objectively and comprehensively understand the patient's emotional changes before and after diagnosis, and can promptly detect subtle fluctuations in the patient's emotions.

[0043] 6. The present invention obtains the patient's mental health level through comprehensive analysis, and then analyzes the patient's mental health condition and provides corresponding suggestions for the patient's mental health condition, which is conducive to long-term monitoring and tracking of the patient's mental health, timely adjustment of the plan, and ensuring that the patient can continue to receive effective help. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0045] Figure 1 This is a system module connection diagram of the present invention.

[0046] Figure 2 This is a flow chart of the robot position adjustment module.

[0047] Figure 3 The figure is a schematic diagram of an embodiment of an application device in an example of the present invention. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] See also Figure 1 As shown, a psychological intelligent diagnostic robot includes a robot position adjustment module, an environmental detection and analysis module, a physiological data acquisition module, a physiological data analysis module, a behavioral data acquisition module, a behavioral data analysis module, a psychological testing module, a symptom assessment module, and a management database.

[0050] The management database is connected to the robot position adjustment module, the environmental detection and analysis module, the physiological data analysis module, the behavioral data analysis module, the psychological testing module, and the symptom assessment module; the symptom assessment module is connected to the environmental detection and analysis module, the physiological data analysis module, the behavioral data analysis module, and the psychological testing module; the physiological data acquisition module is connected to the physiological data analysis module; and the behavioral data acquisition module is connected to the behavioral data analysis module.

[0051] The robot position adjustment module is used to obtain the patient's sitting height and the number of distance intervals between the diagnostic robot and the patient, and adjust the screen height and screen inclination of the diagnostic robot accordingly.

[0052] See also Figure 2 As shown, the specific analysis method of the robot position adjustment module is: the first step is to measure the screen height of the diagnostic robot, and at the same time measure the sitting height of the patient after the patient sits down; ensure that the patient does not need to excessively raise or lower his head when watching the diagnostic robot screen, reduce neck discomfort, and improve the comfort of the overall medical experience.

[0053] The second step is to subtract the screen height of the diagnostic robot from the sitting height of the patient to obtain the corresponding adjustment value of the screen height of the diagnostic robot, and adjust the screen height of the diagnostic robot accordingly; by precisely adjusting the screen height, it can ensure that every patient can view the screen at the most comfortable and ergonomic angle and obtain the best visual experience.

[0054] The third step is to measure the distance between the diagnostic robot and the patient, divide the distance into several intervals according to the set distance, and count the number of distance intervals between the diagnostic robot and the patient; clarifying the distance interval between the robot and the patient will help to more accurately design the interaction method and content to meet the needs at different distances.

[0055] The fourth step is to set a tilt angle standard for the unit distance interval, recorded as the unit distance interval adjustment angle, and superimpose the unit distance interval adjustment angle according to the number of distance intervals between the robot and the diagnosed patient to obtain the screen tilt adjustment value of the diagnostic robot, and adjust the screen tilt of the diagnostic robot accordingly; it can flexibly adapt to various distances between the patient and the robot and provide a better user experience. The appropriate screen tilt helps patients to better view and operate, and improves the convenience and accuracy of interaction.

[0056] The environmental detection and analysis module is used to detect the environmental factors of the diagnostic environment and analyze the impact coefficient of the current diagnostic environment on the patient. The environmental factors include the suitability of light at the patient's location, the impact of environmental noise, the suitability of environmental temperature, and the suitability of environmental humidity.

[0057] The specific analysis method of the environmental detection and analysis module is as follows: the first step is to select a number of position points around the patient's position, record them as the patient's position points, use a light meter to measure the light intensity of each position point at the patient's position, and obtain the light intensity of the patient's position by taking the average value, which is recorded as , read the suitable light intensity range for human body from the management database, extract the maximum and minimum values ​​corresponding to the suitable light intensity range for human body, and record them as the maximum suitable light intensity , Minimum suitable light intensity , substituting it into the formula Get the appropriate lighting level for the patient's location ; The suitability can be assessed based on the actual lighting conditions at the specific patient location, and a suitable lighting environment may have a positive impact on the patient's mood and recovery.

[0058] The second step is to select several time points with equal time intervals during the diagnosis process, record them as time points, measure the noise value in the environment at each time point with a noise meter, and calculate the average value to obtain the environmental noise value of the diagnosis process, and compare it with the preset maximum allowable environmental noise value to obtain the degree of environmental noise impact. ; It can accurately grasp the overall condition of environmental noise during the diagnosis process. Appropriate environmental noise can help patients communicate and cooperate with doctors better and improve the accuracy of diagnosis.

[0059] It should be noted that the specific analysis method of the degree of influence of the environmental noise is: read the environmental noise value of the diagnosis process, recorded as , read the maximum allowable environmental noise value from the management database and record it as , substituting it into the formula Get the degree of environmental noise impact .

[0060] The third step is to detect the ambient temperature and humidity at each time point using a thermometer and a hygrometer. The ambient temperature suitability and ambient humidity suitability are analyzed according to the method of analyzing the light suitability of the patient's location, and are recorded as ; Appropriate temperature and humidity can enhance the patient's comfort in the environment and is beneficial to their physical and mental state.

[0061] The fourth step is to analyze the impact coefficient of the current diagnostic environment on the patient. The formula is: ,in They respectively represent the weight factors of the set lighting suitability, environmental noise impact, environmental temperature suitability, and environmental humidity suitability; ensuring that the diagnostic environment better meets patient needs and improves patient comfort and satisfaction.

[0062] It should be noted that, in a specific embodiment, It can be set to 0.2. It can be set to 0.3. It can be set to 0.3. It can be set to 0.2. The suitability of lighting may be relatively less important, but its suitability may also affect the patient's comfort and mood to a certain extent. The impact of environmental noise is more important. Excessive noise may interfere with the communication between patients and medical staff and affect the patient's mood and rest. The suitability of ambient temperature has a greater impact on the patient's physical sensation and comfort. Too high or too low temperature may make the patient uncomfortable. The suitability of ambient humidity will also affect the patient's feelings, but it may be slightly less than the relative temperature. Therefore, the weights corresponding to the impact of environmental noise and the suitability of ambient temperature are higher.

[0063] The physiological data acquisition module is used to obtain the patient's physiological indicators, including the heart rate difference of the patient in each time period group, the systolic pressure difference, diastolic pressure difference, and skin electrical response difference of the patient's blood pressure at each time point.

[0064] The physiological data analysis module is used to analyze the patient's physiological indicators to obtain the degree of influence of the psychological state on the physiological response.

[0065] The specific analysis method of the influence of the psychological state on the physiological response is as follows: the first step is to divide the diagnosis process into several unit time periods according to the set time length, recorded as each detection time period, and measure the patient's heart rate within the unit time length before diagnosis, recorded as , and after the diagnosis begins, the patient's heart rate is measured in each detection time period, and the heart rate difference of each detection time period of the patient is obtained by subtracting the heart rate of each detection time period from the heart rate of the previous detection time period, which is recorded as , Indicates The number of the detection time period, ; Segmenting the diagnostic process can more accurately observe changes in the patient's heart rate in different time periods, promptly detect adverse reactions that may occur in the patient due to the diagnostic process, and ensure patient safety.

[0066] The second step is to test the systolic and diastolic blood pressure of the patient before diagnosis, recorded as , respectively monitor the systolic and diastolic blood pressure of the patient at each time point, recorded as , , Indicates The number of the time point, , through the formula , Get the systolic pressure difference and diastolic pressure difference of the patient's blood pressure at each time point , , Respectively represent the patient The systolic and diastolic blood pressure at different time points can be used to know in more detail the specific changes in the patient's blood pressure before and after diagnosis and at different time points, and to quickly detect abnormal fluctuations in blood pressure so that timely intervention measures can be taken.

[0067] The third step is to clean the skin of the patient's test area and place the two electrodes of the skin electrical test instrument on the cleaned skin to test the patient's skin electrical response value before diagnosis, which is recorded as At the same time, the skin electrical response value of the patient at each time point is tested after the diagnosis begins, recorded as , and by the formula Get the difference of the patient's skin electrical response at each time point ; Changes in skin electrical response may reflect changes in certain diseases or physiological states and help with diagnosis.

[0068] The fourth step is to read the heart rate difference of the patients in each time period. , the systolic blood pressure difference at each time point , diastolic pressure difference , Skin galvanic response difference , substituting it into the formula Get the degree of influence of psychological state on physiological response ,in Respectively represent the weight factors of the set heart rate, blood pressure, and skin galvanic response value, Indicates the number of time period groups, Indicates the number of time periods; can continuously monitor the changes in the impact of the patient's psychological state on physiology in different time periods, adjust the treatment plan in time, and comprehensively consider multiple physiological indicators such as heart rate, blood pressure, and skin electrical response to fully understand the patient's physiological state.

[0069] It should be noted that, in a specific embodiment, It can be set to 0.4. It can be set to 0.3. It can be set to 0.3. Heart rate is a relatively sensitive indicator. Changes in psychological state often cause heart rate changes more quickly. Blood pressure is relatively affected by many factors, but psychological state also has a certain effect on it. The skin electrical response value can better reflect the psychological tension and other states. Therefore, the weight corresponding to the heart rate is slightly higher, and the weights corresponding to blood pressure and skin electrical response values ​​are equal.

[0070] The behavior data acquisition module is used to obtain the patient's concentration level and the uniformity of the speed at which the patient performs action tasks.

[0071] The specific analysis method of the behavior data acquisition module is as follows: In the first step, the eye movement trajectory of the patient is tracked by an eye tracker during the diagnosis process to generate the patient's eye movement trajectory, the robot screen is recorded as the gaze area, and the length of time the patient's gaze stays in the gaze area is read from the patient's eye movement trajectory and recorded as , divide the unit time period into fixed time periods, obtain the number of blinks of the patient in each unit time period, and divide the number of blinks of the patient in each unit time period by the length of the unit time period to obtain the blink frequency of the patient in each unit time period, recorded as , Indicates The number of the unit time period, , substituting it into the formula Get the patient's concentration level , They represent the preset reference values ​​of the duration of gaze stay and blink frequency. They represent the weight factors of the set gaze dwell time and blink frequency respectively. Indicates the number of unit time periods; it is carried out in real time during the diagnosis process and can promptly detect dynamic changes in the patient's attention.

[0072] It should be noted that, in a specific embodiment, It can be set to 0.6. It can be set to 0.4. The duration of gaze can largely reflect the patient's concentration level. When the patient's attention is more focused, their eyes tend to stay on a specific target or area for a longer time because they are concentrating on observing, thinking or processing relevant information. A longer gaze duration usually means that the patient devotes more cognitive resources to the current focus. The blinking frequency can also reflect the attention level to a certain extent. When the attention is focused, the blinking frequency may be relatively low because the patient is more focused on the object of attention and rarely performs subconscious actions such as blinking. However, the blinking frequency is also affected by many other factors, such as eye fatigue, physiological state, etc. It does not depend entirely on attention. Its indicativeness is relatively not as clear and direct as the gaze duration. Therefore, the corresponding weight of the gaze duration is higher.

[0073] The second step is to issue a specified action task to the patient at each time point during the diagnosis process, recorded as the action task at each time point, and obtain the duration of the patient's action task at each time point, recorded as At the same time, the motion capture device is used to obtain the movement path of the marked points of each body part of the patient at each time point, and the movement distance is recorded as , Indicates The number of the body part landmarks, , through the formula Get the speed of the patient's action task at each time point , substituting it into the formula Get the uniformity of the speed at which the patient performs the action task , Indicates the number of time periods; helps to more accurately judge the patient's physical function, coordination ability and other aspects, and provides a strong basis for disease diagnosis.

[0074] It should be noted that the specific analysis method for the duration of the patient's action task at each time point is: select the midpoint of the body part that needs to be moved in the action task at each time point for position marking, record it as the body part marking point of the action task at each time point, use the motion capture sensor to record the start time and end time of the patient's action task at each time point, and obtain the duration of the patient's action task at each time point by subtracting the start time and end time of the patient's action task at each time point, which is recorded as .

[0075] The behavioral data analysis module is used to analyze the patient's concentration level and the uniformity of the speed at which the patient performs the action task to obtain the degree of neural relaxation corresponding to the patient's attention and the degree of neural relaxation corresponding to the uniformity of the speed at which the patient performs the action task, thereby obtaining the patient's physical relaxation level.

[0076] The specific analysis method of the behavior data analysis module is: reading the patient's concentration level respectively , the uniformity of the speed at which patients perform motor tasks , substituting it into the formula Get the patient's level of physical relaxation , They respectively represent the weight factors of the preset concentration level and the uniformity of the speed of executing the action task; the degree of neural relaxation is evaluated by comprehensively considering the concentration level and the uniformity of the speed of executing the action task, which is more comprehensive and can provide a basis for the formulation and adjustment of the rehabilitation training plan according to the patient's physical relaxation level.

[0077] It should be noted that, in a specific embodiment, It can be set to 0.5. It can be set to 0.5. The degree of concentration can reflect the patient's cognitive state and psychological concentration ability. If the attention is difficult to concentrate or overly distracted, it may indicate the presence of psychological conditions such as attention deficit, anxiety, and excessive stress. This has a certain reference value for diagnosing certain psychological disorders or evaluating psychological functions. The uniformity of the speed of executing action tasks can also provide clues. Uneven speed may imply emotional instability, inner tension, weak self-control, etc., which is helpful for diagnosing emotion-related psychological problems or understanding the individual's psychological stability. Therefore, the weights corresponding to the degree of concentration and the uniformity of the speed of executing action tasks are equal.

[0078] The psychological test module is used to obtain the patient's pre-diagnosis tone, the emotional score corresponding to the tone in each time period, and the patient's emotional scale score before and after diagnosis through voice recording and emotional test scale, and then analyze the patient's emotional recovery degree.

[0079] The specific analysis method of the psychological test module is as follows: before the patient is diagnosed, a fixed-length voice recording is performed on the patient, and the fixed-length voice is divided into time periods after the diagnosis, and the patient's voice in each time period is recorded, which are respectively recorded as the patient's voice before diagnosis and the voice in each time period, and the patient's voice before diagnosis and the voice in each time period are denoised, and the patient's tone is extracted therefrom, which are recorded as the patient's tone before diagnosis and the tone in each time period, and the emotion classification model and each emotion classification score are extracted from the management database, and the patient's tone before diagnosis and the tone in each time period are compared with them to obtain the emotion classification corresponding to the patient's tone before diagnosis and the tone in each time period, and then the emotion score corresponding to the patient's tone before diagnosis and the tone in each time period is matched, which is recorded as , Indicates The number of the time period, At the same time, the patient was tested before and after diagnosis using the emotional test scale, and the emotional scale scores of the patient before and after diagnosis were recorded as , substituting it into the formula Get the patient's emotional recovery level ,in By formula get, Indicates The emotional score corresponding to the tone of voice in each time period, Indicates the number of time periods, They respectively represent the emotion score corresponding to the set tone and the weight factor of the emotion scale score; through voice recording and analysis, we can more comprehensively grasp the emotional state of patients at different stages. With the help of emotion classification models and scoring, the emotion assessment is more objective and accurate, and more targeted intervention measures can be formulated according to the specific emotional characteristics and changes of patients.

[0080] It should be noted that, in a specific embodiment, It can be set to 0.4. It can be set to 0.6. Although intonation can reflect emotions to a certain extent, it is relatively simple and superficial, and may be affected by some other temporary factors, such as the physical condition at the time, environmental sounds, etc., and different people may have different ways and understandings of expressing emotions through intonation. The emotional scale score is usually scientifically designed and verified, and can more comprehensively and systematically evaluate the various emotional dimensions and states of patients, cover more extensive and in-depth information, and assess the degree of emotional recovery more accurately and reliably. Therefore, the emotional scale score has a higher weight.

[0081] It should be noted that the specific analysis method of the patient's pre-diagnosis intonation and the intonation of each time period is as follows: the first step is to read the patient's pre-diagnosis voice and the voice in each time period after noise reduction, and convert its analog voice signal into a digital signal, which is recorded as the patient's pre-diagnosis voice signal and the voice signal in each time period.

[0082] In the second step, the speech signal of the patient before diagnosis and the speech signal of each time period are divided into several time frames of equal length, and each time frame is subjected to fast Fourier transform to obtain its spectrum, which is recorded as the spectrum of each time frame of the speech signal of the patient before diagnosis and the spectrum of each time frame of the speech signal of each time period.

[0083] The third step is to extract the main frequency from the spectrum of each time frame of the patient's speech signal before diagnosis and the spectrum of each time frame of the speech signal in each time period, and compare the main frequency fluctuations in adjacent time frames of the patient's speech signal before diagnosis and the speech signal in each time period, and judge the rising, falling or stable fluctuation state of the tone based on it, and record it as the patient's tone state before diagnosis and the tone state in each time period.

[0084] It should be noted that, in a specific embodiment, a specified speech is recorded as the specified speech, and its analog speech signal is converted into a digital signal and then framed and recorded as each time frame of the speech signal. A fast Fourier transform is performed on a certain time frame of the speech signal to obtain the spectrum of the speech signal in the time frame, which is recorded as the first time frame spectrum of the speech signal. The main frequency is extracted from it and it is found that its main frequency is concentrated at 500Hz. The main frequency of the second time frame of the speech signal is obtained according to the method of analyzing the main frequency of the first time frame of the speech signal, and it is found that its main frequency becomes 600Hz, which indicates that the frequency increases, and it is inferred that the tone is on an upward trend. Then, the main frequency of the third time frame of the speech signal drops back to 450Hz, which shows that the tone has dropped again. In summary, it can be determined that the tone in this speech signal first rises and then falls. The fluctuation of the tone, that is, the specified speech tone state, first rises and then falls.

[0085] The symptom assessment module is used to comprehensively analyze the patient's mental health level, and then analyze the patient's mental health condition and provide corresponding recommendations for the patient's mental health condition.

[0086] The specific analysis method of the symptom assessment module is: respectively reading the influence coefficient of the current diagnostic environment on the patient , the degree of influence of psychological state on physiological response , the patient's degree of physical relaxation , the patient's emotional recovery , substituting it into the formula Get the patient's mental health level , They respectively represent the influence coefficient of the set current diagnostic environment on the patient, the influence of the psychological state on the physiological reaction, the patient's physical relaxation degree, and the weight factors of the emotional recovery degree. The patient's mental health degree is compared with the mental health conditions corresponding to the preset mental health degree ranges to obtain the patient's mental health condition, feedback is given and the patient is provided with a corresponding suggestion plan for the patient's mental health condition; the mental health degree is calculated according to the specific conditions of different patients, which is more targeted and convenient to provide appropriate suggestion plans based on the mental health condition to guide subsequent treatment and rehabilitation.

[0087] It should be noted that, in a specific embodiment, It can be set to 0.2. It can be set to 0.3. It can be set to 0.2. It can be set to 0.3. Although the diagnostic environment will have a certain impact on the patient, the patient's own psychological and physiological conditions are more critical. The psychological state is closely related to the physiological reaction. A bad psychological state often causes obvious physiological reactions, which have a greater impact on mental health. Whether the body is relaxed or not can reflect the psychological state to a certain extent, but it is not the most core factor. The emotional state is an important manifestation of mental health, and good emotional recovery is crucial to mental health. Therefore, the degree of influence of the psychological state on the physiological reaction and the degree of emotional recovery have higher corresponding weights.

[0088] The management database is used to store the suitable light intensity range for the human body, the emotion classification model and the score of each emotion classification.

[0089] A second aspect of the present invention provides an electronic device, characterized in that the device includes a processor, a memory and a communication bus, and the memory stores a computer-readable program that can be executed by the processor.

[0090] The communication bus realizes the connection and communication between the processor and the memory.

[0091] When the processor executes the computer-readable program, the steps of the psychological intelligent diagnosis robot described in the present invention are implemented.

[0092] See also Figure 3 As shown, the third aspect of the present invention provides a storage medium, characterized in that: the storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement steps in a psychological intelligent diagnostic robot.

[0093] The present invention adjusts the screen height and screen inclination of the diagnostic robot by detecting the patient's sitting height and the number of distance intervals between the diagnostic robot and the patient, obtains the influence coefficient of the current diagnostic environment on the patient according to the environmental factors of the diagnostic environment, obtains the degree of influence of the psychological state on the physiological reaction according to the physiological indicators of the patient, obtains the patient's physical relaxation degree through patient behavior data analysis, obtains the patient's emotional recovery degree through voice recording and emotional test scales, and then comprehensively analyzes the patient's mental health condition and provides corresponding suggestions, which helps to fully grasp the patient's mental health condition and achieve more accurate mental health services.

[0094] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations on the present invention. A person skilled in the art may make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention and they are still covered by the protection scope of the present invention.

Claims

1. A psychological intelligent diagnostic robot, characterized in that: The system specifically includes the following modules: The robot position adjustment module is used to obtain the patient's sitting height and the number of distance intervals between the diagnostic robot and the patient, and adjust the screen height and screen inclination of the diagnostic robot accordingly; The environmental detection and analysis module is used to detect the environmental factors of the diagnostic environment and analyze the influence coefficient of the current diagnostic environment on the patient. The environmental factors include the suitability of light at the patient's location, the influence of environmental noise, the suitability of environmental temperature, and the suitability of environmental humidity. The physiological data acquisition module is used to obtain the patient's physiological indicators, including the heart rate difference of the patient in each time period group, the systolic pressure difference, diastolic pressure difference, and skin electrical response difference of the patient's blood pressure at each time point; A physiological data analysis module is used to analyze the patient's physiological indicators to determine the degree of influence of the psychological state on the physiological response; The behavioral data acquisition module is used to obtain the patient's concentration level and the uniformity of the speed at which the patient performs the action task; The behavior data analysis module is used to analyze the patient's concentration level and the uniformity of the speed at which the patient performs the action task to obtain the degree of neural relaxation corresponding to the patient's attention and the degree of neural relaxation corresponding to the uniformity of the speed at which the patient performs the action task, thereby obtaining the patient's physical relaxation level; The psychological test module is used to obtain the patient's pre-diagnosis tone, the emotional score corresponding to the tone in each time period, and the patient's emotional scale score before and after diagnosis through voice recording and emotional test scale, and then analyze the patient's emotional recovery degree; Symptom assessment module, which is used to comprehensively analyze the patient's mental health level, and then analyze the patient's mental health condition and provide corresponding suggestions for the patient's mental health condition; The management database is used to store the suitable light intensity range for the human body, the emotion classification model and the score of each emotion classification.

2. A psychological intelligent diagnostic robot according to claim 1, characterized in that: The specific analysis method of the robot position adjustment module is as follows: the first step is to measure the screen height of the diagnostic robot and at the same time measure the sitting height of the patient after the patient sits down; The second step is to obtain a corresponding adjustment value of the screen height of the diagnostic robot by subtracting the screen height of the diagnostic robot from the sitting height of the patient, and adjust the screen height of the diagnostic robot accordingly; The third step is to measure the distance between the diagnostic robot and the patient, divide the distance into several intervals according to the set distance, and count the number of distance intervals between the diagnostic robot and the patient; The fourth step is to set a tilt angle standard for the unit distance interval, recorded as the unit distance interval adjustment angle, and superimpose the unit distance interval adjustment angles according to the number of distance intervals between the robot and the diagnosed patient to obtain the screen tilt adjustment value of the diagnostic robot, and use this to adjust the screen tilt of the diagnostic robot.

3. A psychological intelligent diagnostic robot according to claim 1, characterized in that: The specific analysis method of the environmental detection and analysis module is as follows: the first step is to select a number of position points around the patient's position, record them as the patient's position points, use a light meter to measure the light intensity of each position point at the patient's position, and obtain the light intensity of the patient's position by taking the average value, which is recorded as , read the suitable light intensity range for human body from the management database, extract the maximum and minimum values ​​corresponding to the suitable light intensity range for human body, and record them as the maximum suitable light intensity , Minimum suitable light intensity , substituting it into the formula Get the appropriate lighting level for the patient's location ; The second step is to select several time points with equal time intervals during the diagnosis process, record them as time points, measure the noise value in the environment at each time point with a noise meter, and calculate the average value to obtain the environmental noise value of the diagnosis process, and compare it with the preset maximum allowable environmental noise value to obtain the degree of environmental noise impact. ; The third step is to detect the ambient temperature and humidity at each time point using a thermometer and a hygrometer. The ambient temperature suitability and ambient humidity suitability are analyzed according to the method of analyzing the light suitability of the patient's location, and are recorded as ; The fourth step is to analyze the impact coefficient of the current diagnostic environment on the patient. The formula is: ,in They respectively represent the weight factors of the set light suitability, environmental noise impact, environmental temperature suitability, and environmental humidity suitability.

4. A psychological intelligent diagnostic robot according to claim 3, characterized in that: The specific analysis method of the influence of the psychological state on the physiological response is as follows: the first step is to divide the diagnosis process into several unit time periods according to the set time length, recorded as each detection time period, and measure the patient's heart rate within the unit time length before diagnosis, recorded as , and after the diagnosis begins, the patient's heart rate is measured in each detection time period, and the heart rate difference of each detection time period of the patient is obtained by subtracting the heart rate of each detection time period from the heart rate of the previous detection time period, which is recorded as , Indicates The number of the detection time period, ; The second step is to test the systolic and diastolic blood pressure of the patient before diagnosis, recorded as , respectively monitor the systolic and diastolic blood pressure of the patient at each time point, recorded as , , Indicates The number of the time point, , through the formula , Get the systolic pressure difference and diastolic pressure difference of the patient's blood pressure at each time point , , Respectively represent the patient Systolic and diastolic blood pressure at each time point; The third step is to clean the skin of the patient's test area and place the two electrodes of the skin electrical test instrument on the cleaned skin to test the patient's skin electrical response value before diagnosis, which is recorded as At the same time, the skin electrical response value of the patient at each time point is tested after the diagnosis begins, recorded as , and by the formula Get the difference of the patient's skin electrical response at each time point ; The fourth step is to read the heart rate difference of the patients in each time period. , the systolic blood pressure difference at each time point , diastolic pressure difference , Skin galvanic response difference , substituting it into the formula Get the degree of influence of psychological state on physiological response ,in Respectively represent the weight factors of the set heart rate, blood pressure, and skin galvanic response value, Indicates the number of time period groups, Indicates the number of time periods.

5. A psychological intelligent diagnostic robot according to claim 4, characterized in that: The specific analysis method of the behavior data acquisition module is as follows: In the first step, the eye movement trajectory of the patient is tracked by an eye tracker during the diagnosis process to generate the patient's eye movement trajectory, the robot screen is recorded as the gaze area, and the length of time the patient's gaze stays in the gaze area is read from the patient's eye movement trajectory and recorded as , divide the unit time period into fixed time periods, obtain the number of blinks of the patient in each unit time period, and divide the number of blinks of the patient in each unit time period by the length of the unit time period to obtain the blink frequency of the patient in each unit time period, recorded as , Indicates The number of the unit time period, , substituting it into the formula Get the patient's concentration level , They represent the preset reference values ​​of the duration of gaze stay and blink frequency. They represent the weight factors of the set gaze dwell time and blink frequency respectively. Indicates the number of unit time periods; The second step is to issue a specified action task to the patient at each time point during the diagnosis process, recorded as the action task at each time point, and obtain the duration of the patient's action task at each time point, recorded as At the same time, the motion capture device is used to obtain the movement path of the marked points of each body part of the patient at each time point, and the movement distance is recorded as , Indicates The number of the body part landmarks, , through the formula Get the speed of the patient's action task at each time point , substituting it into the formula Get the uniformity of the speed at which the patient performs the action task , Indicates the number of time periods.

6. A psychological intelligent diagnostic robot according to claim 4, characterized in that: The specific analysis method of the behavior data analysis module is: reading the patient's concentration level respectively , the uniformity of the speed at which patients perform motor tasks , substituting it into the formula Get the patient's level of physical relaxation , They represent the weight factors of the preset concentration level and the uniformity of the speed of executing the action task respectively.

7. A psychological intelligent diagnostic robot according to claim 6, characterized in that: The specific analysis method of the psychological test module is as follows: before the patient is diagnosed, a fixed-length voice recording is performed on the patient, and the fixed-length voice is divided into time periods after the diagnosis, and the patient's voice in each time period is recorded, which are respectively recorded as the patient's voice before diagnosis and the voice in each time period, and the patient's voice before diagnosis and the voice in each time period are denoised, and the patient's tone is extracted therefrom, which are recorded as the patient's tone before diagnosis and the tone in each time period, and the emotion classification model and each emotion classification score are extracted from the management database, and the patient's tone before diagnosis and the tone in each time period are compared with them to obtain the emotion classification corresponding to the patient's tone before diagnosis and the tone in each time period, and then the emotion score corresponding to the patient's tone before diagnosis and the tone in each time period is matched, which is recorded as , Indicates The number of the time period, At the same time, the patient was tested before and after diagnosis using the emotional test scale, and the emotional scale scores of the patient before and after diagnosis were recorded as , substituting it into the formula Get the patient's emotional recovery level ,in By formula get, Indicates The emotional score corresponding to the tone of voice in each time period, Indicates the number of time periods, They respectively represent the emotional score corresponding to the set tone and the weight factor of the emotional scale score.

8. A psychological intelligent diagnostic robot according to claim 7, characterized in that: The specific analysis method of the symptom assessment module is: respectively reading the influence coefficient of the current diagnostic environment on the patient , the degree of influence of psychological state on physiological response , the patient's degree of physical relaxation , the patient's emotional recovery , substituting it into the formula Get the patient's mental health level , They respectively represent the influence coefficient of the current diagnostic environment on the patient, the influence of the psychological state on the physiological reaction, the patient's physical relaxation degree, and the weight factors of the emotional recovery degree. The patient's mental health degree is compared with the mental health conditions corresponding to the preset mental health degree ranges to obtain the patient's mental health condition, feedback is given and a corresponding suggestion plan for the patient's mental health condition is provided to the patient.

9. A psychological intelligence diagnostic device, characterized in that: The device includes a processor, a memory and a communication bus, wherein the memory stores a computer-readable program executable by the processor; The communication bus realizes the connection and communication between the processor and the memory; When the processor executes the computer-readable program, the steps of a psychological intelligent diagnostic robot as described in any one of claims 1-8 are implemented.

10. A storage medium, characterized in that: The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps in a psychological intelligent diagnostic robot as described in any one of claims 1-8.

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