Method and system for identifying key environmental elements influencing experience feeling

Abstract

The embodiment of the invention provides a method and a system for identifying key environmental elements influencing experience. The recognition method comprises the following steps: collecting eye movement data of a plurality of testers, and collecting physiological feature data of the testers at the same time; analyzing and processing the eye movement data of each testee to obtain eye movement index data of each testee; determining an ontology experience feeling score of each tester based on the physiological feature data; and performing correlation analysis based on the ontology experience feeling score and the eye movement index data of each tester, and determining key environment elements influencing the experience feeling of the tester. Because the physiological feature data objectively reflects subconscious physiological feature changes when the testee observes the environment scene, the corresponding ontology experience feeling score obtained based on the physiological feature data also relatively objectively represents the feeling of the testee to the environment scene, so that the data in the method for determining the key environment elements in the scheme is more objective; and the corresponding identification result is more accurate.

Description

Technical Field

[0001] The present disclosure relates to the technical field of visual perception evaluation, and in particular to a method and system for identifying key environmental factors that affect the sense of experience. Background Art

[0002] A large amount of scientific research and actual engineering practice has proved that the reasonable layout of environmental elements such as buildings, green vegetation and roads has a great impact on the experience of people entering them, which in turn affects the degree of relaxation and happiness of people entering the corresponding environmental scenes, and affects their behavior.

[0003] Based on the aforementioned research guidelines, methods for determining the tester experience have been proposed in the fields of regional planning and layout, architectural design, and interior layout design, which are used to determine whether the tester has a good experience in a specific planning and design scenario. Furthermore, in order to be able to modify the planning and design based on the tester's experience feedback, the relevant technology proposes a method for identifying key environmental elements based on the tester's experience and the tester's visual focus. In order to determine the environmental factors that affect the experience, it is first necessary to determine the tester's real-time experience in the corresponding environmental scenario. The existing method is to obtain the tester's subjective evaluation of the environmental scene through questionnaires and tester interviews, and then convert the subjective evaluation into a score to obtain the corresponding experience score.

[0004] The aforementioned method of obtaining experience ratings is based on subjective evaluation, which is affected by the subjectivity of the tester and the rational and moderate evaluation ideas. The corresponding rating results have the problem of insufficient objectivity, resulting in poor credibility in the identification of key environmental factors. Summary of the invention

[0005] In order to solve the problem that the existing subjective evaluations obtained based on questionnaires and tester interviews are not credible in identifying key environmental factors, the embodiments of the present disclosure provide a method and system for identifying key environmental factors that affect the user experience.

[0006] In a first aspect, an embodiment of the present disclosure provides a method for identifying key environmental factors that affect user experience, including:

[0007] Collecting eye movement data of multiple testers when they observe the environment scene within a preset time, and simultaneously collecting physiological characteristic data of the testers within the preset time, wherein the physiological characteristic data is physiological data that is correlated with the experience of the testers when observing the environment scene;

[0008] Analyzing and processing the eye movement data of each tester to obtain eye movement index data corresponding to various environmental elements observed by each tester in the environmental scene;

[0009] Determining, based on the physiological characteristic data, a proprioceptive experience score of each test subject when observing the environmental scene;

[0010] Based on the proprioceptive experience scores of each tester and the eye movement index data corresponding to observing various scene elements, a correlation analysis was performed to determine the key environmental factors that affect the tester's experience.

[0011] Optionally, the method further comprises: obtaining baseline physiological characteristic data of each tester in a baseline scenario;

[0012] Determining the proprioceptive experience score of each tester when observing the environmental scene based on the physiological characteristic data includes: taking the baseline physiological characteristic data of each tester as a reference, and determining the proprioceptive experience score when observing the environmental scene based on the corresponding physiological characteristic data.

[0013] Optionally, the collecting of physiological characteristic data of the test subject when observing the environment scene includes:

[0014] The heart rate variability index and / or the skin electrical signal index of the tester when observing the environmental scene are collected, and the heart rate variability index and / or the skin electrical signal index are used as the physiological characteristic data.

[0015] Optionally, when the acquired physiological characteristic data includes more than one indicator, determining the proprioceptive experience score of each tester when observing the environmental scene based on the physiological characteristic data includes:

[0016] Determine the corresponding sub-indicator proprioceptive experience score based on various physiological characteristic parameters of each tester;

[0017] The proprioceptive experience scores of the sub-indicators of each tester are weighted and summed to obtain the proprioceptive experience score when observing the environmental scene.

[0018] Optionally, the method further includes: while collecting eye movement data of multiple testers when observing the environmental scene within a preset time, conducting a subjective questionnaire survey on the environmental scene for each tester to obtain an evaluation score for each survey item, wherein each of the survey items reflects the tester's experience of the environmental scene;

[0019] The subjective experience score is obtained based on the evaluation scores of each survey item;

[0020] The method of performing a correlation analysis based on the proprioceptive experience score of each tester and the eye movement index data corresponding to observing various scene elements to determine the key environmental factors affecting the tester's experience includes: performing a correlation analysis based on the proprioceptive experience score of each tester and the subjective experience score and the eye movement index data corresponding to observing various scene elements to determine the key environmental factors affecting the tester's experience.

[0021] Optionally, the proprioceptive experience scores and the subjective experience scores of each tester are respectively subjected to correlation analysis with eye movement index data corresponding to observing various scene elements to obtain corresponding correlation analysis results, including:

[0022] Based on the proprioceptive experience scores and the subjective experience scores of each tester, correlation analysis is performed with the eye movement index data corresponding to the observation of various scene elements, to determine the eye movement index data with correlation, and to determine the importance ranking and importance coefficient of each environmental element under the various eye movement index data;

[0023] Taking the importance coefficient as the weighting coefficient, weighted average is performed on the ranking order of each environmental factor under various eye movement index data to determine the overall importance score of various environmental factors;

[0024] The key environmental factors affecting the tester's experience are determined according to the overall importance score.

[0025] Optionally, the eye movement data of each tester is analyzed and processed to obtain eye movement index data corresponding to various environmental factors, including:

[0026] Based on the eye movement data of each tester, determine the environmental elements that are focused on at each moment, and count the moments of focusing on the same environmental element to obtain the corresponding attention period of each environmental element;

[0027] Remove the attention time periods whose duration is less than the lower threshold and whose duration is greater than the upper threshold from the attention time periods, to obtain the remaining attention time periods;

[0028] Based on the attention periods corresponding to the various environmental factors, analysis and processing are performed to obtain at least one of the following eye movement indicator data corresponding to the various environmental factors: total fixation time, first fixation time, first fixation duration, and number of fixations.

[0029] Optionally, the method further comprises: obtaining relative projection areas of various environmental elements;

[0030] The analyzing and processing of the eye movement data of each tester to obtain eye movement index data corresponding to various environmental factors also includes:

[0031] The corresponding total gaze time per unit area is calculated based on the total gaze time of various environmental elements and the corresponding relative projection area, and / or the corresponding gaze times per unit area is calculated based on the gaze times of various environmental elements and the corresponding relative projection area.

[0032] Optionally, collecting eye movement data of multiple testers when observing an environmental scene within a preset time period includes:

[0033] A virtual reality display device is used to show the test subject an environmental scene for a preset duration, and the test subject's eye movement data when observing the environmental scene is collected.

[0034] In a second aspect, an embodiment of the present disclosure provides a device for identifying key environmental factors that affect user experience, including:

[0035] A data acquisition unit, used to acquire eye movement data of multiple testers when they observe the environment scene within a preset time period, and simultaneously acquire physiological characteristic data of the testers when they observe the environment scene, wherein the physiological characteristic data is physiological data that is correlated with the experience characteristics of the testers when they observe the environment scene;

[0036] An eye movement data processing unit, used to analyze and process the eye movement data of each tester to obtain eye movement index data corresponding to various environmental elements observed by each tester in the environmental scene;

[0037] A physiological data processing unit, used to determine the proprioceptive experience score of each tester when observing the environmental scene based on the physiological characteristic data;

[0038] The analysis unit is used to perform correlation analysis based on the proprioceptive experience scores of each tester and the eye movement index data corresponding to observing various scene elements, so as to determine the key environmental factors affecting the tester's experience.

[0039] In a third aspect, the present disclosure provides a system for identifying key environmental factors that affect user experience, including:

[0040] Eye movement feature collection equipment, used to collect eye movement data of multiple testers when they observe environmental scenes within a preset time period;

[0041] A physiological characteristic acquisition device is used to obtain physiological characteristic data of the test subject when observing the environmental scene, wherein the physiological characteristic data is physiological data that is correlated with the characteristics of the test subject's experience when observing the environmental scene;

[0042] The data processing device is used to analyze and process the eye movement data of each tester to obtain the eye movement index data corresponding to the various environmental elements observed by each tester in the environmental scene; and determine the proprioceptive experience score of each tester when observing the environmental scene based on the physiological characteristic data; and perform correlation analysis based on the proprioceptive experience score of each tester and the eye movement index data corresponding to observing various scene elements to determine the key environmental factors affecting the tester's experience.

[0043] The embodiment scheme of the present disclosure uses the eye movement data of the tester when observing the environmental scene to determine the proprioceptive experience score, and then uses the proprioceptive experience score and the eye movement index data obtained based on the eye movement data to perform correlation analysis to obtain the key environmental factors that affect the tester's experience. Because the physiological characteristic data objectively reflects the subconscious physiological characteristic changes of the tester when observing the environmental scene, the corresponding proprioceptive experience score obtained based on the physiological characteristic data also relatively objectively represents the tester's feelings about the environmental scene. Compared with the method of determining key environmental factors using subjective questionnaires, the data in the method of determining key environmental factors in this scheme is more objective, and the corresponding recognition results are more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art description. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work, including:

[0046] Figure 1 is a flow chart of a method for identifying key environmental factors affecting user experience provided by an embodiment of the present disclosure;

[0047] Figure 2 is a flow chart of a method for identifying key environmental factors affecting user experience provided by another embodiment of the present disclosure;

[0048] Figure 3 is a schematic diagram of an experimental scenario for implementing a method in some embodiments of the present disclosure;

[0049] Figure 4 are some test scene images used in specific implementations;

[0050] Figure 5 It is a schematic diagram of the structure of the identification system provided by the embodiment of the present disclosure. DETAILED DESCRIPTION

[0051] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0052] The term "including" and its variations used in this document are open inclusions, i.e., "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one other embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions of other terms will be given in the description below. In this document, relational terms such as "first" and "second" are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0053] The disclosed embodiment provides a method for identifying key environmental factors that affect the user experience, which analyzes objective collected data to determine the key environmental factors that affect the user experience.

[0054] Before analyzing the method provided by the embodiment of the present disclosure, the concept of experience is first analyzed. The experience mentioned in the embodiment of the present disclosure is the overall psychological feeling obtained by the tester based on visual observation of the environmental scene when entering a specific environmental scene. The experience represents whether the tester's psychological state is peaceful and stable when entering a specific environmental scene, and whether he has a sense of belonging to the environmental scene; in other words, the experience represents whether the tester has a strong desire to stay in the environmental scene, or whether the tester has a strong desire to leave the environmental scene.

[0055] Before implementing this embodiment, a large number of psychological studies have found that the tester's experience is directly related to the tester's emotional state when in the environmental scene. Therefore, the quality of the tester's experience can be reflected based on the characteristic data that characterizes the tester's emotional state (specifically, the physiological characteristic data that reflects the tester's emotional state), and then the key environmental factors that affect the tester's experience can be identified.

[0056] Figure 1 : is a flow chart of a method for identifying key environmental factors that affect user experience provided by an embodiment of the present disclosure. Figure 1 As shown, the method for identifying key environmental factors affecting user experience provided by the embodiment of the present disclosure includes S110-S140.

[0057] S110: Collecting eye movement data of multiple testers when they observe the environment scene within a preset time period, and simultaneously collecting physiological characteristic data of the testers within the preset time period.

[0058] As analyzed above, the experience discussed in the embodiments of the present disclosure is the overall psychological feeling obtained based on visual observation of the environment scene. Correspondingly, the perceptual information that affects the experience of the tester is the visual information obtained by the tester's glasses observing the environment scene, specifically, the visual information formed after the tester visually observes various environmental elements in the environment scene.

[0059] When observing various environmental elements in the environment scene, the test subject's eyes will change their gaze direction due to subconscious or non-subconscious control, and then focus on a specific environmental element, focus on different parts of a specific environmental element, or switch the focus from one environmental element to another. To achieve the aforementioned focus or switch, the test subject needs to adaptively control the gaze direction of the eyeball, which means adaptively controlling the overall posture of the eyeball.

[0060] Eye movement data is time series data obtained by collecting the movement state and movement characteristics of the tester's eyeballs. Therefore, based on the eye movement data, information about the tester's visual gaze direction can be obtained, and then the environmental factors of the tester's visual gaze can be determined. Based on this, the embodiment of the present disclosure collects the eye movement data of the tester when observing the environmental scene.

[0061] At the same time, in order to enable horizontal comparison and standardized analysis, and to avoid the eye movement data no longer having the significance of representing the environmental factors affecting the tester's proprioceptive experience due to the tester's visual adaptation or the attraction of a specific area of ​​interest, the eye movement data of each tester in the experiment was collected when observing the environmental scene within a preset time. In addition, before the aforementioned preset scene, the tester did not observe the environmental scene visually.

[0062] In a specific implementation, the preset duration is set to 120 seconds to ensure that the tester can fully observe various environmental elements in the environmental scene while observing the environmental scene, and will not only focus on specific environmental elements later because of interest in specific environmental elements.

[0063] In a specific implementation, an eye tracker may be used to record the eye movements of the test subject to obtain eye movement data representing the characteristics of the eye movement trajectory.

[0064] In some solutions, in order to allow the tester to experience the environmental elements in the environment scene in an immersive way, the tester can be placed in a real environment scene and observe the various environmental elements in the environment scene from a specific observation position. For example, if the environment scene is a central square in a city, the tester can observe the central square from the entrance of the central official venue.

[0065] In some other embodiments, the environmental scene is a scene that has not yet been built. In this case, there are only 3D structural design drawings or plane drawings of the environmental scene, but no real scene of the environmental scene. In this case, the 3D structural design drawings or plane drawings can be processed by rendering software to determine the projection image when viewing the environmental scene from a certain angle, and the aforementioned projection image is used as an image displayed to the tester for observing the environmental scene. In some specific implementations, in order to avoid the image of the real environment on the eye movement when the tester observes the aforementioned projection image, a virtual reality display device can be used to display the environmental scene image to the tester, and the eye tracker configured in the virtual reality display device can be used to collect the tester's eye movement data.

[0066] Based on the complexity of the experimental arrangement and the difficulty of data collection, it can be imagined that the use of virtual reality display equipment to display environmental scene images can achieve consistency in the content of the environmental scene observed by each tester, avoiding the problem of changes in the content of the environmental scene caused by changes in weather and lighting characteristics. At the same time, the use of virtual reality display equipment can also realize low-cost repeated sampling experiments, and by limiting the user's eye movement range and body posture range, it makes the subsequent steps of eye movement data processing simpler.

[0067] Of course, in actual operation, the actual environment scene can also be photographed to form a photographic image, and the photographic image can be displayed using the aforementioned virtual reality display device, thereby reducing the test cost and reducing the impact of uncontrollable factors.

[0068] In the embodiment of the present disclosure, while collecting the eye movement data of the test subject when observing the environment scene within the set time, the physiological characteristic data of the test subject in the aforementioned environment scene is also collected. In other words, the physiological characteristic data is the physiological characteristic data of the user within the preset time.

[0069] It should be noted here that the physiological characteristic data collected in the embodiments of the present disclosure are physiological data that are relevant to the experience of the tester when observing the environmental scene, and not all types of physiological data can be used as the physiological characteristic data here.

[0070] Through a large number of preliminary physiological and psychological experimental tests in this embodiment, it is found that the heart rate variability index and the skin electrical signal index are physiological data that are correlated with the user's experience when observing the environment scene. Therefore, these two types of index data can be used as the aforementioned physiological characteristic data, and the corresponding physiological measurement instruments can be used to collect the aforementioned types of physiological characteristic data. In specific implementation, a smart bracelet with corresponding functions can be used to collect the aforementioned physiological characteristic data.

[0071] Here we briefly analyze why the heart rate variability index and skin electrical signal index data are correlated with the user's experience when observing the experimental scene.

[0072] Through physiological analysis, it is found that when the user has a better experience, the parasympathetic nerve activity becomes stronger and the sympathetic nerve activity becomes weaker. When the parasympathetic nerve activity becomes stronger, under the synergistic effect of the parasympathetic and sympathetic nerves, the user's heart is more elastic and adaptable, and has greater variability. Therefore, the heart rate variability index can be used as the aforementioned physiological characteristic data. Similarly, when the user has a better experience, the parasympathetic nerve activity becomes stronger or the sympathetic nerve activity is lower. Under the synergistic effect of the parasympathetic and sympathetic nerves, the user's skin conductance characteristics will also change. Therefore, the skin electrical signal index can be used as the aforementioned physiological characteristic data.

[0073] In a specific implementation, the aforementioned heart rate variability index may include the root mean square difference of successive differences (RMSSD) of heart rate intervals and the percentage of adjacent heart beat interval differences exceeding 50 ms (PN50).

[0074] The method for obtaining the root mean square difference of the heart rate interval is as follows: first, count each normal heartbeat interval in the electrocardiogram distance, then calculate the difference between adjacent heartbeat intervals, and calculate the mean of the square sum of all differences, and finally perform square root processing on the mean of the square sum to obtain the root mean square difference of the heart rate interval. The unit of the root mean square difference of the heart rate interval is usually ms; the higher this value is, the greater the short-term change of the heart rate is, the stronger the parasympathetic nerve activity is, reflecting that the person is in a relaxed and happy state, and has a better experience of the surrounding environment.

[0075] The method for obtaining the percentage of adjacent heartbeat interval differences exceeding 50ms is as follows: first, count each normal heartbeat interval in the electrocardiogram, then calculate the difference between adjacent heartbeat intervals and count the number of times the absolute value of the difference exceeds 50ms, and finally calculate the proportion of the number in all heartbeat intervals, which is the percentage of adjacent heartbeat interval differences exceeding 50ms. The percentage of adjacent heartbeat interval differences exceeding 50ms reflects the short-term heart rate variability index, which is affected by the activity of the parasympathetic nervous system and can reflect the immediate fluctuations in the emotional state and stress level of the tester, and also reflects the tester's experience of the surrounding perceived environment. A higher percentage of adjacent heartbeat interval differences exceeding 50ms indicates strong parasympathetic nerve activity and greater heart variability, which directly reflects that the tester is in a relaxed, happy and quiet emotional state.

[0076] In a specific implementation, the aforementioned skin electrical signal indicators may include skin conductivity level (Skin Conductivity Level, SCL) and skin conductivity response (Skin Conductivity Response, SCR).

[0077] Skin conductance levels can be calculated by measuring the conductivity of the skin over a period of time and averaging the above conductivity values. Lower skin conductance levels indicate lower activity in the pride nerves, which usually corresponds to a relaxed, calm mood.

[0078] Skin conductance response is obtained by recording the baseline conductance value before a specific environmental stimulus and the peak conductance value after the environmental stimulus, and subtracting the peak conductance value from the baseline conductance value. Skin conductance response reflects the instantaneous change in conductivity during a specific stimulus or emotional fluctuation. Because it is event-related, it is usually related to the intensity of the stimulus that causes the emotional fluctuation.

[0079] Lower skin conductance responses indicate that individuals are less responsive to external stimuli and have less emotional fluctuations. Skin conductance responses are lower in calm, relaxed states and in individuals who are insensitive to stimuli.

[0080] The applicant calls attention to the fact that the physiological characteristic data is not limited to the aforementioned root mean square difference of heart rate intervals, the percentage of adjacent heartbeat intervals exceeding 50ms, skin conductance level and skin conductance response. It is more because the existing technical conditions can easily achieve the acquisition of the aforementioned heartbeat data and skin conductivity data, so the aforementioned types of physiological characteristic data are adopted in the disclosed embodiment. In other embodiments, other physiological data can also be adaptively used as the aforementioned physiological characteristic data based on the results obtained by the methods of medical technology, measurement technology and physiological and psychological analysis technology.

[0081] S120: Analyze and process the eye movement data of each tester to obtain eye movement index data corresponding to various environmental elements in the environment scene observed by each tester.

[0082] As analyzed above, the eye movement data reflects the index data of the tester's observation of various environmental elements in the environment scene. Based on the statistical analysis of the eye movement data, the eye movement index data corresponding to various environmental elements can be obtained.

[0083] In a specific implementation, the eye movement indicator data for various environmental factors may include at least one of: total fixation time, first fixation time, first fixation duration, and number of fixations.

[0084] The total fixation time is the total time the test subject fixates on a certain environmental element within the preset time.

[0085] The first fixation time is the time from the start of the test to the first time the test subject fixates on a certain environmental element; the shorter the first fixation time, the easier it is to pay attention to the aforementioned environmental element.

[0086] The first fixation duration refers to the total length of time the subject fixates on a certain environmental element for the first time; the longer the first fixation duration, the more attractive the aforementioned environmental element is to the subject.

[0087] The number of fixations refers to the number of times the test subject looks at a certain environmental element within a preset time.

[0088] In a specific implementation, after obtaining the eye movement data within a preset time period, the gaze direction of the tester at each moment can be determined based on the eye movement data and the benchmark calibration data (the benchmark calibration data is obtained by calibrating the tester's eyes before collecting the eye movement data). Then, based on the element content of the environmental elements corresponding to each gaze direction, the focus environmental elements at each moment are determined. After determining the focus environmental elements at each moment, the computing device can perform statistics based on the data corresponding to the focus environmental elements at each moment to obtain the corresponding eye movement indicator data.

[0089] In the process of executing the above, the eye movement index data corresponding to each environmental element is determined, and the core premise is to determine the environmental element corresponding to each gaze direction. In some specific implementations, the relative relationship between the eye movement measurement device (eye tracker) used to collect the user's eye movement data and the environmental scene (or the rendered picture or real scene picture showing the environmental scene) is determined. Correspondingly, according to the relative relationship determined above, the corresponding environmental element of interest can be determined according to the eye movement data collected by the eye movement measurement device at each moment.

[0090] In some embodiments, the inventors of the present application use a virtual reality display device with an eye movement acquisition device to display a rendered image corresponding to an environmental scene to the user, and determine the position area of ​​each scene element in the environmental scene in the rendered image. Because the eye tracker and the display device in the virtual reality display device are relatively fixed, and the position of each scene element in the rendered image in the display device in the virtual reality display device is determined, the environmental element corresponding to the user's gaze direction can be determined by a simple coordinate transformation. For example, in a specific implementation, the inventors used the built-in software provided by the virtual reality display device to annotate the rendered image and determine the pixel area where each environmental element in the rendered image is located. The virtual reality display device determines the gaze direction corresponding to each environmental element based on the relative position relationship between the aforementioned pixel area, the display device, the tester's eye calibration data, and the eye tracker, and then uses the eye movement data to determine the eye movement indicator data corresponding to each environmental element.

[0091] In some embodiments, corresponding eye movement indicator data may be obtained according to the following S121 - S123 .

[0092] S121: Determine the environmental elements that are focused on at each moment based on the eye movement data of each tester, and count the moments when the same environmental element is focused on to obtain the focus period corresponding to each environmental element.

[0093] Specifically, the environmental factors to be focused on at each moment are determined in S121 based on the eye movement data of each tester using the method determined in the previous text, which will not be repeated here. After obtaining the environmental factors to be focused on at each moment, the environmental factors corresponding to each moment are then arranged in time series, and a sequence of focused environmental factors can be obtained. The aforementioned sequence of environmental factors is sorted, and the moments of focusing on the same environmental factor are counted, and the focus period corresponding to each environmental factor can be obtained.

[0094] S122: removing the attention time periods whose duration is less than the lower threshold and whose duration is greater than the upper threshold from the attention time periods, to obtain the remaining attention time periods.

[0095] Through the previous visual attention analysis mechanism, we found that: (1) users cannot adjust their eyes to observe a certain visual element in a short period of time, that is, they cannot achieve effective fixation. Specifically, it takes about 100ms for users to achieve effective fixation; (2) when users maintain a uniform gaze direction for a long time, it is highly likely that the user is not focusing on a certain content, but is more likely to be not paying attention to the content being fixed, but thinking about other things (or is already in a state of distraction); through statistical analysis, it is found that if the test subject does not change the gaze direction for 5 seconds, he or she is most likely already in a state of distraction.

[0096] As analyzed in the previous paragraph, the eye movement data corresponding to the aforementioned state of being unable to form effective gaze and being in a distracted state cannot reflect the user's perception of environmental elements in the environmental scene. Therefore, it is necessary to remove the aforementioned type of attention period, that is, to remove the period less than the lower threshold time and higher than the upper threshold time to obtain the remaining period.

[0097] S123: Analyze and process the attention periods corresponding to the various environmental factors to obtain at least one of the following eye movement indicator data corresponding to the various environmental factors.

[0098] After obtaining the attention period corresponding to each environmental factor, the attention period can then be statistically analyzed based on the definition and calculation method of each eye movement index data mentioned above to obtain the eye movement index data corresponding to each environmental factor.

[0099] In some embodiments, the eye movement index data may include the total gaze time per unit area and the first gaze duration per unit area in addition to the aforementioned total gaze time, first gaze time, first gaze duration, and number of gazes. Through visual observation experiments, it was found that the length of time the tester focuses on eye elements is correlated with the visual area of ​​the environmental elements in the user's vision. In order to reasonably reflect the tester's attention to each environmental element, the embodiment of the present disclosure introduces the idea of ​​"information density" to calculate the total gaze time per unit area and the first gaze duration per unit area.

[0100] In a specific implementation, the following S124-S125 may be used to calculate the aforementioned total fixation duration per unit area and the first fixation duration per unit area.

[0101] S124: Obtain the relative projection areas of various environmental elements.

[0102] The relative projection area of ​​each environmental element is the projection area of ​​each environmental element in the field of view of the tester. When the viewing scene is an actual scene, the imaging area of ​​each environmental element on the camera at the observation field of view can be counted from the tester's observation position to determine the imaging pixel area of ​​each environmental element, and the aforementioned imaging pixel area is used as the relative projection area. In some other embodiments, when the environmental scene is displayed in a rendered image, the imaging area of ​​each environmental element in the rendered image can be counted, and the statistically obtained area is used as the relative projection area of ​​the corresponding environmental element. In a specific implementation, it is assumed that an environmental element is enclosed by a polygon including N vertices in the rendered image, and the coordinates of the N vertices are (x1, y1), (x2, y2), ..., (x n ,y n ) Relative projection area of ​​the above environmental elements

[0103]

[0104] S125: Calculate the corresponding total gaze duration per unit area based on the total gaze duration and the relative projection area of ​​various environmental elements, and calculate the corresponding number of gazes per unit area based on the number of gazes of various environmental elements and the corresponding relative projection area.

[0105] After obtaining the relative projection areas of the aforementioned environmental elements, the total fixation time per unit area can be obtained by dividing the total fixation time of a certain environmental element by the corresponding relative projection area; similarly, the number of fixations per unit area can be obtained by dividing the number of fixations of a certain environmental element by the relative projection area.

[0106] In S125, the total fixation duration per unit area and the number of fixations per unit area are calculated simultaneously. In other embodiments, only one of the total fixation duration per unit area and the number of fixations per unit area may be calculated.

[0107] S130: Determine the proprioceptive experience score of each tester when observing the environmental scene based on the physiological characteristic data.

[0108] The proprioceptive experience score is a score reflected by physiological characteristic data, which represents the test subject's proprioceptive subconscious experience when observing the environmental scene.

[0109] To determine the proprioceptive experience score of each tester when observing the environmental scene based on the physiological characteristic data, it is necessary to refer to the physiological characteristic data of the tester in the control scene. Accordingly, in order to obtain the proprioceptive experience score in the environmental scene, it is also necessary to collect the baseline physiological characteristic data of the tester when observing the control scene. In the specific implementation, the control environment can be one or more.

[0110] After obtaining the physiological characteristic data in the environmental scene and the control scene, the physiological characteristic data change model obtained based on the physiological experiment and the standard score of the proprioceptive experience of the control environmental scene can be used to calculate and obtain the proprioceptive experience score of the tester when observing the environmental scene. In specific implementation, the aforementioned physiological characteristic data change model may be a linear model or a nonlinear model, which needs to be determined by physiological experiments and psychological experiments based on the labeled scenes.

[0111] In some embodiments, there is only one kind of physiological characteristic data obtained by physiological measurement, and the corresponding sub-indicator proprioceptive experience score can be directly obtained based on the aforementioned physiological characteristic data, and the sub-indicator proprioceptive experience score can be directly used as the proprioceptive experience score for correlation analysis.

[0112] In some other embodiments, at least two types of physiological characteristic data are obtained by performing physiological measurements. In this case, the proprioceptive experience score can be determined by using the following S131-S132.

[0113] S131: Determine corresponding sub-indicator proprioceptive experience scores based on various physiological characteristic parameters of each tester.

[0114] After determining various physiological characteristic parameters, the aforementioned method can be used to determine the corresponding sub-indicator proprioceptive experience scores.

[0115] S132: performing weighted summation of the proprioceptive experience scores of the sub-indicators of each tester to obtain the proprioceptive experience score when observing the environmental scene.

[0116] After obtaining the proprioceptive experience scores of each tester's sub-indicator, the weighted weights of various indicators can be determined based on physiological-psychological experiments, and the proprioceptive experience scores of each sub-indicator are weighted and summed to obtain the proprioceptive experience scores of each tester when observing the environmental scene.

[0117] S140: performing correlation analysis based on the proprioceptive experience scores of each tester and the eye movement index data corresponding to observing various scene elements, and determining key environmental factors that affect the tester's experience.

[0118] After obtaining the proprioceptive experience scores of various testers using the above method, and obtaining the eye movement index data corresponding to various scene elements, mathematical analysis tools can then be used to perform correlation analysis on the aforementioned data to obtain the key environmental factors that affect the tester's experience. In a specific implementation, analysis tools provided by software such as Statistical Product and Service Solutions (SPSS) can be used to process the aforementioned data to obtain the key environmental factors that affect the tester's experience. Considering that the use of mathematical tools such as correlation analysis is not the focus of this solution, and that there are a large number of existing technical solutions that can implement the aforementioned correlation analysis content, the present disclosure embodiment will no longer describe how to perform correlation analysis, and the specific content can refer to the content analysis of the prior art.

[0119] In specific implementation, through correlation analysis, the impact ranking and / or impact degree score of each environmental factor on the test experience can be determined, and then the key environmental factors are determined based on the aforementioned impact ranking degree and impact degree score, as well as the previously determined evaluation rules.

[0120] In specific implementations, when performing correlation analysis, it can be found that there is no correlation analysis between some eye movement indicator data (such as the number of fixations) and the tester's proprioceptive experience score. In this case, the influence ranking and / or influence degree score corresponding to such eye movement indicator data can be excluded.

[0121] In a specific implementation, when there are multiple eye movement index data and proprioceptive experience scores for correlation analysis, the following S141-S143 can be used.

[0122] S141: Correlation analysis is performed based on the proprioceptive experience scores of each tester and various eye movement index data corresponding to observing various scene elements, to determine the eye movement index data with correlation, and to determine the importance ranking and importance coefficient of each environmental element under the various eye movement index data.

[0123] In S141, the proprioceptive experience score and various eye movement index data of the tester are subjected to independent correlation analysis to determine whether the proprioceptive experience score and the eye movement index data are correlated. In the case that the proprioceptive experience score and the eye movement index data are correlated, the correlation coefficient obtained by the correlation analysis can be used as the aforementioned importance coefficient; the correlation ranking of the eye movement index data of each environmental factor under the corresponding correlation is used as the aforementioned importance ranking.

[0124] S142: Taking the importance coefficient as the weighting coefficient, weighted average is performed on the ranking order of each environmental factor under various eye movement index data to determine the overall importance score of various environmental factors.

[0125] In S142, the sorting order of various environmental factors under the corresponding eye movement index is used as the score under the single index, the aforementioned correlation coefficient (specifically the correlation coefficient) is used as the weighting coefficient for weighted averaging, and the weighted score branch of each environmental factor is used as the corresponding overall importance score.

[0126] S143: Determine the key environmental factors that affect the tester's experience based on the overall importance score.

[0127] After determining the overall importance score corresponding to each environmental factor, the aforementioned overall importance score and the predetermined screening rules are screened to obtain the key environmental factors that affect the tester's experience. In a specific implementation, one or more environmental factors that are at the top of the overall importance score can be used as the key environmental factors.

[0128] In the above S131-S132, the overall proprioceptive experience score obtained by weighted summing the tester's sub-indicator proprioceptive experience scores is analyzed with various eye movement indicator data to determine the key environmental factors. In other embodiments, various types of sub-indicator proprioceptive experience scores can also be correlated with eye movement indicator data to obtain correlation indicators and ranking orders, and the corresponding importance rankings and importance coefficients are determined according to methods such as the above S141-S143, and finally the key environmental factors are obtained.

[0129] As analyzed above, the embodiment of the present disclosure uses the eye movement data of the tester when observing the environmental scene to determine the proprioceptive experience score, and then uses the proprioceptive experience score and the eye movement index data obtained based on the eye movement data to perform a correlation analysis to obtain the key environmental factors that affect the tester's experience. Because the physiological characteristic data objectively reflects the subconscious physiological characteristic changes of the tester when observing the environmental scene, the corresponding proprioceptive experience score obtained based on the physiological characteristic data also relatively objectively represents the tester's feelings about the environmental scene. Compared with the method of determining key environmental factors using subjective questionnaires, the data in the method of determining key environmental factors in this scheme is more objective, and the corresponding recognition results are more accurate.

[0130] It is undeniable that although subjective questionnaire surveys may be affected by the tester's rational thinking (moderate thinking), reasonable subjective questionnaire survey results can also reflect the tester's experience to a certain extent, and thus can determine the key environmental factors that affect the user experience. Based on this, in some embodiments of the present disclosure, it is also considered to integrate the survey results obtained from the subjective questionnaire survey into the determination of key environmental factors.

[0131] Figure 2 FIG. 1 is a flow chart of a method for identifying key environmental factors that affect user experience provided by another embodiment of the present disclosure. Figure 2 As shown, in another embodiment of the present disclosure, a method for identifying key environmental factors that affect user experience includes S210-S250.

[0132] S210: Collecting eye movement data of multiple testers when they observe the environmental scene within a preset time, and collecting physiological characteristic data of the testers within the preset time, and conducting a subjective questionnaire survey on the environmental scene for each tester to obtain an evaluation score for each survey item.

[0133] Before executing the solution of the embodiment of the present disclosure, firstly, a subjective feeling questionnaire of the environment scene is prepared according to the identification target of the method. The subjective feeling questionnaire is used to investigate the subjective feelings of the tester when observing the environment scene.

[0134] In a specific implementation, the subjective feelings questionnaire can be in the form of a Likert seven-level scale, wherein the questionnaire questions can include an overall evaluation of the environmental scene and a sub-item evaluation of different elements in the environmental scene. For example, in one embodiment, the subjective feelings involved in the evaluation questions include spatial presence, spatial experience, and spatial intimacy. Among them, the questions corresponding to the sense of spatial presence may include questions such as evaluating "spatial recognition", "ability of scene elements to distract attention", "sense of security", "spatial oppression", and "unity of regional style", and the questions corresponding to the sense of spatial experience may include questions such as evaluating "degree of psychological relaxation", "reducing psychological pressure", "getting rest", and "expectation of spatial exploration". The questions corresponding to the sense of spatial intimacy may include questions such as evaluating "scenes reflect local customs and culture", "individual and environment integration", "stay time" and "spatial attractiveness".

[0135] S220: Analyze and process the eye movement data of each tester to obtain eye movement index data corresponding to various environmental elements in the environment scene observed by each tester.

[0136] S230: Determine the proprioceptive experience score of each tester when observing the environmental scene based on the physiological characteristic data.

[0137] The execution process of the corresponding steps in S210-S230 is the same as that in the previous embodiment, which will not be repeated here. For details, please refer to the previous description.

[0138] S240: Obtain a subjective experience score based on the evaluation score of each survey item.

[0139] In a specific implementation, the evaluation scores of each survey item obtained by conducting the aforementioned supervisory questionnaire on the existing survey questionnaire can be integrated to obtain a subjective experience score. In addition, in some embodiments, some subjective statistical tools in the statistical analysis software can also be used to analyze the scores of each survey item, remove the scoring results of some testers who are not typical, and then summarize the evaluation scores of each survey item according to a predetermined score summarization method to obtain a subjective experience score.

[0140] S250: Based on the proprioceptive experience score and subjective experience score of each tester, correlation analysis is performed with the eye movement index data corresponding to observing various scene elements to determine the key environmental factors of the application tester's experience.

[0141] As analyzed above, the proprioceptive experience score and the subjective experience score reflect the tester's experience of the environmental scene from two aspects, objectively and subjectively respectively. Therefore, in the specific implementation, the proprioceptive experience score and the subjective experience score can be used to perform correlation analysis with the eye movement index data, and the correlation analysis results can be obtained respectively. The key environmental factors that affect the tester's experience can be determined by combining the two analysis results.

[0142] In some embodiments, the following S241 - S243 may be used to determine key environmental factors.

[0143] S241: Based on the proprioceptive experience score and subjective experience score of each tester, correlation analysis is performed with the eye movement index data corresponding to the observation of various scene elements, to determine the eye movement index data with correlation, and to determine the importance ranking and importance coefficient of each environmental element under the various eye movement index data.

[0144] S242: Taking the importance coefficient as the weighting coefficient, weighted average is performed on the ranking order of each environmental factor under various eye movement index data to determine the overall importance score of various environmental factors.

[0145] S243: Determine the key environmental factors that affect the tester's experience based on the overall importance score.

[0146] In the specific implementation, the implementation process of the aforementioned S241-S243 is the same as that of the aforementioned S141-S143, except that the data is processed differently, and the corresponding content will not be analyzed in detail here.

[0147] As analyzed above, in order to reduce the implementation cost of the solution of this embodiment as much as possible, virtual reality equipment, physiological monitoring equipment (smart bracelet) and questionnaire survey are used to implement the above method. Figure 3 Schematic diagram of an experimental scenario for implementing the method in some embodiments of the present disclosure. Figure 3 As shown, the hardware devices used to implement the embodiments of the present disclosure include a head-mounted display 1, a multimodal bracelet 2 and a corresponding bracelet terminal 3, a computing device 4 for processing source data and subsequent data, a questionnaire 5 and a locator for determining the eye movement data of the tester. Figure 4 are some test scene images used in specific implementations. Figure 4After the test scene image shown is processed and labeled with various environmental elements, it is projected onto the head-mounted display for display and observation by the tester, while the multimodal bracelet is collaboratively controlled to collect data, and the tester is asked questions in the questionnaire through language playback, and the tester quickly answers in a short time to obtain the aforementioned eye movement data, physiological characteristic data and survey item scores of the questionnaire. After obtaining the aforementioned data, the computing device processes the data according to the aforementioned method to obtain key environmental elements.

[0148] In addition to providing the aforementioned method for identifying key environmental factors that affect the user experience, the embodiments of the present disclosure also provide a system for identifying key environmental factors that affect the user experience. Figure 5 Schematic diagram of the structure of the system for identifying key environmental factors affecting the user experience provided by the embodiment of the present disclosure. Figure 5 As shown, the recognition system 500 for key environmental factors affecting the user experience includes an eye movement feature acquisition device 501 , a physiological feature acquisition device 502 and a data processing device 503 .

[0149] The eye movement feature collection device 501 is used to collect eye movement data of multiple testers when they observe the environment scene within a preset time period.

[0150] The physiological characteristic acquisition device 502 is used to obtain the physiological characteristic data of the tester when observing the environmental scene, wherein the physiological characteristic data is physiological data that is correlated with the experience characteristics of the tester when observing the environmental scene.

[0151] The data processing device 503 is used to analyze and process the eye movement data of each tester to obtain the eye movement index data corresponding to various environmental elements when each tester observes the environmental scene; and to determine the proprioceptive experience score of each tester when observing the environmental scene based on the physiological characteristic data; and to perform correlation analysis based on the proprioceptive experience score of each tester and the eye movement index data corresponding to observing various scene elements, to determine the key environmental factors that affect the tester's experience.

[0152] In some embodiments, the data processing device 503 uses the baseline physiological characteristic data of each tester as a reference and determines the proprioceptive experience score when observing the environmental scene based on the corresponding physiological characteristic data.

[0153] In some embodiments, the data processing device 503 collects the heart rate variability index and / or the skin electrical signal index of the tester when observing the environmental scene, and uses the heart rate variability index and / or the skin electrical signal index as physiological characteristic data.

[0154] In some embodiments, when the acquired physiological characteristic data includes more than one indicator, the data processing device 503 determines the corresponding sub-indicator proprioceptive experience scores based on the various physiological characteristic parameters of each tester, and weightedly sums the sub-indicator proprioceptive experience scores of each tester to obtain the proprioceptive experience score when observing the environmental scene.

[0155] In some embodiments, while collecting eye movement data of multiple testers when observing environmental scenes within a preset time, a subjective questionnaire survey of the environmental scenes is conducted on each tester to obtain an evaluation score for each survey item, wherein each survey item reflects the tester's experience of the environmental scenes. The data processing device 503 obtains a subjective experience score based on the evaluation score of each survey item, and then performs a correlation analysis based on the proprioceptive experience score and subjective experience score of each tester and the eye movement index data corresponding to observing various scene elements to determine the key environmental elements that affect the tester's experience.

[0156] In some embodiments, the data processing device 503 performs correlation analysis on the eye movement index data corresponding to the observation of various scene elements based on the proprioceptive experience score and subjective experience score of each tester, determines the eye movement index data with correlation, and determines the importance ranking and importance coefficient of each environmental element under the various eye movement index data; uses the importance coefficient as the weighting coefficient, performs weighted average on the ranking order of each environmental element under the various eye movement index data, and determines the overall importance score of the various environmental elements; determines the key environmental elements that affect the tester's experience based on the overall importance score.

[0157] In some embodiments, the data processing device 503 determines the environmental elements that are paid attention to at each moment based on the eye movement data of each tester, and counts the moments of paying attention to the same environmental element to obtain the attention period corresponding to each environmental element; removes the attention periods that are less than the lower threshold duration and greater than the upper threshold duration in the attention period to obtain the remaining attention periods; analyzes and processes the attention periods corresponding to each environmental element to obtain at least one of the following eye movement indicator data corresponding to various environmental elements: total gaze duration, first gaze time, first gaze duration, and number of gazes.

[0158] In some embodiments, the data processing device 503 obtains the relative projection areas of various environmental elements, and calculates the corresponding total gaze time per unit area based on the total gaze time of various environmental elements and the corresponding relative projection areas, and / or calculates the corresponding number of gazes per unit area based on the number of gazes of various environmental elements and the corresponding relative projection areas.

[0159] According to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network, or installed from a storage device, or installed from a ROM. When the computer program is executed by the data processing device 503, the above-mentioned functions defined in the method of the embodiment of the present disclosure are executed.

[0160] It should be noted that the computer-readable medium mentioned above in the present disclosure may be a computer-readable storage medium, a computer-readable signal medium, or any combination of the above two.

[0161] The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0162] The computer-readable medium may be included in the computing device, or may exist independently without being incorporated into the computing device.

[0163] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including but not limited to object-oriented programming languages ​​such as Java, SMalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the tester computer, partially on the tester computer, as a separate software package, partially on the tester computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the tester computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0164] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated system based on hardware that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0165] The units involved in the embodiments described in the present disclosure may be implemented by software or by hardware. The name of the unit does not, in some cases, constitute a limitation on the unit itself. The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0166] The above are only specific embodiments of the present disclosure, so that those skilled in the art can understand or implement the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to these embodiments herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for identifying key environmental factors that affect user experience, characterized in that: include: Collecting eye movement data of multiple testers when they observe the environment scene within a preset time, and simultaneously collecting physiological characteristic data of the testers within the preset time, wherein the physiological characteristic data is physiological data that is correlated with the experience of the testers when observing the environment scene; Analyzing and processing the eye movement data of each tester to obtain eye movement index data corresponding to various environmental elements observed by each tester in the environmental scene; Determining, based on the physiological characteristic data, a proprioceptive experience score of each test subject when observing the environmental scene; Based on the proprioceptive experience scores of each tester and the eye movement index data corresponding to observing various scene elements, a correlation analysis was performed to determine the key environmental factors that affect the tester's experience.

2. The identification method according to claim 1, characterized in that: The method further includes: obtaining baseline physiological characteristic data of each test subject in a baseline scenario; Determining the proprioceptive experience score of each tester when observing the environmental scene based on the physiological characteristic data includes: taking the baseline physiological characteristic data of each tester as a reference, and determining the proprioceptive experience score when observing the environmental scene based on the corresponding physiological characteristic data.

3. The identification method according to claim 1, characterized in that: The collection of the test subject's physiological characteristic data when observing the environment scene includes: The heart rate variability index and / or the skin electrical signal index of the tester when observing the environmental scene are collected, and the heart rate variability index and / or the skin electrical signal index are used as the physiological characteristic data.

4. The identification method according to claim 3, characterized in that: In the case where the acquired physiological characteristic data includes more than one indicator, determining the proprioceptive experience score of each tester when observing the environmental scene based on the physiological characteristic data includes: Determine the corresponding sub-indicator proprioceptive experience score based on various physiological characteristic parameters of each tester; The proprioceptive experience scores of the sub-indicators of each tester are weighted and summed to obtain the proprioceptive experience score when observing the environmental scene.

5. The identification method according to claim 1, characterized in that: The method further comprises: While collecting eye movement data of multiple testers when observing the environmental scene within a preset time, a subjective questionnaire survey on the environmental scene is conducted on each tester to obtain an evaluation score for each survey item, wherein each survey item reflects the tester's experience of the environmental scene; The subjective experience score is obtained based on the evaluation scores of each survey item; The method of performing a correlation analysis based on the proprioceptive experience score of each tester and the eye movement index data corresponding to observing various scene elements to determine the key environmental factors affecting the tester's experience includes: performing a correlation analysis based on the proprioceptive experience score of each tester and the subjective experience score and the eye movement index data corresponding to observing various scene elements to determine the key environmental factors affecting the tester's experience.

6. The identification method according to claim 5, characterized in that: The proprioceptive experience scores and the subjective experience scores of each tester are respectively correlated with the eye movement index data corresponding to observing various scene elements to obtain corresponding correlation analysis results, including: Based on the proprioceptive experience scores and the subjective experience scores of each tester, correlation analysis is performed with the eye movement index data corresponding to the observation of various scene elements, to determine the eye movement index data with correlation, and to determine the importance ranking and importance coefficient of each environmental element under the various eye movement index data; Taking the importance coefficient as the weighting coefficient, weighted average is performed on the ranking order of each environmental factor under various eye movement index data to determine the overall importance score of various environmental factors; The key environmental factors affecting the tester's experience are determined according to the overall importance score.

7. The identification method according to any one of claims 1 to 6, characterized in that: The eye movement data of each tester is analyzed and processed to obtain eye movement index data corresponding to various environmental factors, including: Based on the eye movement data of each tester, determine the environmental elements that are focused on at each moment, and count the moments of focusing on the same environmental element to obtain the corresponding attention period of each environmental element; Remove the attention time periods whose duration is less than the lower threshold and whose duration is greater than the upper threshold from the attention time periods, to obtain the remaining attention time periods; Based on the attention periods corresponding to the various environmental factors, analysis and processing are performed to obtain at least one of the following eye movement indicator data corresponding to the various environmental factors: total fixation time, first fixation time, first fixation duration, and number of fixations.

8. The identification method according to claim 7, characterized in that: The method further comprises: Obtain the relative projection areas of various environmental elements; The analyzing and processing of the eye movement data of each tester to obtain eye movement index data corresponding to various environmental factors also includes: The corresponding total gaze time per unit area is calculated based on the total gaze time of various environmental elements and the corresponding relative projection area, and / or the corresponding first gaze number per unit area is calculated based on the gaze number of various environmental elements and the corresponding relative projection area.

9. The identification method according to any one of claims 1 to 6, characterized in that: The collecting of eye movement data of multiple testers when observing the environment scene within a preset time period includes: A virtual reality display device is used to show the test subject an environmental scene for a preset duration, and the test subject's eye movement data when observing the environmental scene is collected.

10. A system for identifying key environmental factors that affect user experience, characterized in that: include: Eye movement feature collection equipment, used to collect eye movement data of multiple testers when they observe environmental scenes within a preset time period; A physiological characteristic acquisition device is used to obtain physiological characteristic data of the test subject when observing the environmental scene, wherein the physiological characteristic data is physiological data that is correlated with the characteristics of the test subject's experience when observing the environmental scene; The data processing device is used to analyze and process the eye movement data of each tester to obtain the eye movement index data corresponding to the various environmental elements observed by each tester in the environmental scene; and determine the proprioceptive experience score of each tester when observing the environmental scene based on the physiological characteristic data; and perform correlation analysis based on the proprioceptive experience score of each tester and the eye movement index data corresponding to observing various scene elements to determine the key environmental factors affecting the tester's experience.

Images