Theme switching method and device, equipment and storage medium

Abstract

The invention discloses a theme switching method and device, equipment and a storage medium, and the scheme can grasp the state of a user in real time through comprehensively collecting the current user behavior feature data, improves the monitoring comprehensiveness and accuracy, provides technical support for rapidly responding to the user state change, and improves the user experience. The early fatigue recognition capability of the system is effectively improved; besides, theme switching can be more intelligently and accurately carried out by combining the current user behavior data and the current equipment performance data, the intelligent degree of theme switching is improved, and the user experience is improved; moreover, by combining the performance data of the current equipment, the theme switching is ensured to be adaptive to the load condition of the equipment, and the fluency of the system and the user experience are further ensured.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence technology, and in particular to a topic switching method, device, equipment and storage medium. Background Art

[0002] At present, modern people have been working, studying and entertaining on digital devices for a long time, and the comfort of the user interface has been paid more and more attention. When users use digital devices for a long time, they usually need to switch themes to adapt to their current needs.

[0003] Currently, when switching themes, it is usually based on a fixed time, manually set by the user, or based on external environmental factors such as light, weather, etc. The existing theme switching method has the problem of low intelligence, which reduces the user experience. Summary of the invention

[0004] The present application aims to at least solve the technical problems existing in the prior art. To this end, the first aspect of the present application proposes a theme switching method, which includes:

[0005] Obtain current user behavior data and current device performance data; where the current user behavior data includes current mouse behavior data, current keyboard behavior data and current screen switching data, and the current device performance data includes current CPU usage data, current memory usage data and current network delay data;

[0006] Based on the current user behavior data, determine the user's current visual fatigue detection result;

[0007] Based on the current equipment performance data, determine the current equipment load status;

[0008] The theme is switched according to the current visual fatigue detection result and the current device load status to generate a switching result.

[0009] In a possible implementation, determining the current visual fatigue detection result of the user based on the current user behavior data includes:

[0010] Perform data preprocessing on the current user behavior data to obtain multi-dimensional feature data;

[0011] Determine the user's overall fatigue index based on multi-dimensional feature data;

[0012] Based on the overall fatigue index and the preset fatigue threshold range, the user's current visual fatigue detection result is determined.

[0013] In a possible implementation, a data preprocessing operation is performed on the current user behavior data to obtain multi-dimensional feature data, including:

[0014] Aggregate the current user behavior data according to the preset time window to obtain aggregated data;

[0015] Perform feature extraction on the aggregated data to obtain current feature data;

[0016] Perform data cleaning and denoising on the current feature data, and segment the processed results according to the preset time period to generate time window feature data;

[0017] The time window feature data is standardized and normalized to generate multi-dimensional feature data.

[0018] In a possible implementation, determining the overall fatigue index of the user based on the multi-dimensional feature data includes:

[0019] For each feature data, based on the feature data and a preset feature threshold value corresponding to the feature data, determine a current visual fatigue state value corresponding to the feature data;

[0020] Based on the current visual fatigue state values ​​and preset weight information, the user's overall fatigue index is calculated.

[0021] In a possible implementation, the preset fatigue threshold interval includes a first threshold interval, a second threshold interval, and a third threshold interval. Based on the overall fatigue index and the preset fatigue threshold interval, determining the current visual fatigue detection result of the user includes:

[0022] If the overall fatigue index is within the first threshold range, it is determined that the current visual fatigue detection result of the user is mild visual fatigue;

[0023] If the overall fatigue index is within the second threshold interval, it is determined that the current visual fatigue detection result of the user is moderate visual fatigue;

[0024] If the overall fatigue index is within the third threshold interval, it is determined that the current visual fatigue detection result of the user is severe visual fatigue.

[0025] In a possible implementation, the theme is switched according to the current visual fatigue detection result and the current device load state, and the switching result is generated, including:

[0026] Determine the current theme switching method based on the current visual fatigue detection result and the current device load status;

[0027] Perform theme switching based on the current theme switching mode and generate a switching result.

[0028] In a possible implementation, based on the current visual fatigue detection result and the current device load state, determining the current theme switching mode includes:

[0029] Based on the current visual fatigue detection result, determine multiple candidate theme switching modes corresponding to the current visual fatigue detection result;

[0030] Based on the current device load state and the preset complexity corresponding to each candidate theme switching mode, a current theme switching mode is determined from multiple candidate theme switching modes.

[0031] The second aspect of the present application provides a theme switching device, which includes:

[0032] The acquisition module is used to acquire the current user behavior data and the current device performance data; wherein the current user behavior data includes the current mouse behavior data, the current keyboard behavior data and the current screen switching data, and the current device performance data includes the current CPU usage data, the current memory usage data and the current network delay data;

[0033] A first determination module, used to determine the user's current visual fatigue detection result based on the current user behavior data;

[0034] A second determination module is used to determine the current equipment load state based on the current equipment performance data;

[0035] The generation module is used to switch themes according to the current visual fatigue detection results and the current device load status, and generate switching results.

[0036] In a possible implementation manner, the first determining module is specifically configured to:

[0037] Perform data preprocessing on the current user behavior data to obtain multi-dimensional feature data;

[0038] Determine the user's overall fatigue index based on multi-dimensional feature data;

[0039] Based on the overall fatigue index and the preset fatigue threshold range, the user's current visual fatigue detection result is determined.

[0040] In a possible implementation manner, the first determining module is further configured to:

[0041] Aggregate the current user behavior data according to the preset time window to obtain aggregated data;

[0042] Perform feature extraction on the aggregated data to obtain current feature data;

[0043] Perform data cleaning and denoising on the current feature data, and segment the processed results according to the preset time period to generate time window feature data;

[0044] The time window feature data is standardized and normalized to generate multi-dimensional feature data.

[0045] In a possible implementation manner, the first determining module is further configured to:

[0046] For each feature data, based on the feature data and a preset feature threshold value corresponding to the feature data, determine a current visual fatigue state value corresponding to the feature data;

[0047] Based on the current visual fatigue state values ​​and preset weight information, the user's overall fatigue index is calculated.

[0048] In a possible implementation manner, the preset fatigue threshold interval includes a first threshold interval, a second threshold interval, and a third threshold interval, and the first determination module is further used to:

[0049] If the overall fatigue index is within the first threshold range, it is determined that the current visual fatigue detection result of the user is mild visual fatigue;

[0050] If the overall fatigue index is within the second threshold interval, it is determined that the current visual fatigue detection result of the user is moderate visual fatigue;

[0051] If the overall fatigue index is within the third threshold interval, it is determined that the current visual fatigue detection result of the user is severe visual fatigue.

[0052] In a possible implementation manner, the generation module is specifically used to:

[0053] Determine the current theme switching method based on the current visual fatigue detection result and the current device load status;

[0054] Perform theme switching based on the current theme switching mode and generate a switching result.

[0055] In a possible implementation manner, the generation module is specifically used to:

[0056] Based on the current visual fatigue detection result, determine multiple candidate theme switching modes corresponding to the current visual fatigue detection result;

[0057] Based on the current device load state and the preset complexity corresponding to each candidate theme switching mode, a current theme switching mode is determined from multiple candidate theme switching modes.

[0058] The third aspect of the present application proposes an electronic device, which includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement the theme switching method described in the first aspect.

[0059] The fourth aspect of the present application proposes a computer-readable storage medium, which stores at least one instruction, at least one program, a code set or an instruction set. The at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by a processor to implement the theme switching method described in the first aspect.

[0060] The embodiments of the present application have the following beneficial effects:

[0061] The theme switching method provided in the embodiment of the present application includes: obtaining current user behavior data and current device performance data, wherein the current user behavior data includes current mouse behavior data, current keyboard behavior data and current screen exchange data, and the current device performance data includes current CPU usage data, current memory occupancy data and current network delay data, determining the user's current visual fatigue detection result based on the current user behavior data, determining the current device load state based on the current device performance data, performing theme switching according to the current visual fatigue detection result and the current device load state, and generating a switching result. This solution can grasp the user's status in real time by comprehensively collecting the current user behavior feature data, improve the comprehensiveness and accuracy of monitoring, provide technical support for rapid response to user status changes, and effectively improve the system's early recognition ability of fatigue; in addition, by combining the current user behavior data and the current device performance data, the theme switching can be performed more intelligently and accurately, which improves the intelligence of the theme switching and improves the user experience; and by combining the current device performance data, it ensures that the theme switching is adapted to the device load status, further ensuring the fluency of the system and the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 A block diagram of a computer device provided in an embodiment of the present application;

[0063] Figure 2 A flowchart of a method for switching themes provided in an embodiment of the present application;

[0064] Figure 3 A flowchart of the steps for determining a user's current visual fatigue detection result provided in an embodiment of the present application;

[0065] Figure 4 A flowchart of the steps for obtaining multi-dimensional feature data provided in an embodiment of the present application;

[0066] Figure 5 A flowchart of the steps for determining the overall fatigue index of a user provided in an embodiment of the present application;

[0067] Figure 6A flow chart of steps for generating a switching result provided in an embodiment of the present application;

[0068] Figure 7 A flowchart of the steps for generating a current theme switching method provided in an embodiment of the present application;

[0069] Figure 8 A structural block diagram of a theme switching device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0070] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0071] Currently, when switching themes, it is usually based on fixed time, manual settings by the user, or based on external environmental factors such as light and weather, but these methods do not fully consider factors such as user visual fatigue and device performance load. Specifically, visual fatigue is a common problem for users after using the device for a long time, especially when reading or browsing for a long time, the degree of eye fatigue will gradually increase, resulting in a decline in user experience. The problem of device performance load is that when the device is processing heavy tasks or running high-load applications, the device may freeze or respond slowly, affecting the user experience. Therefore, the existing theme switching methods have failed to realize a theme optimization system that can intelligently perceive the user status and automatically adjust.

[0072] Based on this, the present application proposes a theme switching method, which includes: obtaining current user behavior data and current device performance data, wherein the current user behavior data includes current mouse behavior data, current keyboard behavior data and current screen exchange data, and the current device performance data includes current CPU usage data, current memory occupancy data and current network delay data, determining the current visual fatigue detection result of the user based on the current user behavior data, determining the current device load state based on the current device performance data, performing theme switching according to the current visual fatigue detection result and the current device load state, and generating a switching result. This solution can grasp the user's status in real time by comprehensively collecting the current user behavior feature data, improve the comprehensiveness and accuracy of monitoring, provide technical support for rapid response to user status changes, and effectively improve the system's early recognition ability of fatigue; in addition, by combining the current user behavior data and the current device performance data, the theme switching can be performed more intelligently and accurately, which improves the intelligence of the theme switching and improves the user experience; and, by combining the current device performance data, it ensures that the theme switching is adapted to the device load status, further ensuring the fluency of the system and the user experience.

[0073] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present disclosure, unless otherwise specified, "multiple" means two or more. In addition, the use of "based on" or "according to" means openness and inclusiveness, because the process, steps, calculations or other actions "based on" or "according to" one or more of the conditions or values ​​may be based on additional conditions or values ​​beyond the described values ​​in practice.

[0074] The theme switching method provided in the present application can be applied to a computer device (electronic device), which can be a server or a terminal, wherein the server can be a single server or a server cluster composed of multiple servers. The embodiments of the present application do not specifically limit this. The terminal can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, and portable wearable devices.

[0075] Take the computer device as a server as an example. Figure 1 A block diagram of a server is shown, such as Figure 1As shown, the server may include a processor and a memory connected via a system bus. The processor of the server is used to provide computing and control capabilities. The memory of the server includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. When the computer program is executed by the processor, a method for switching the subject is implemented.

[0076] Those skilled in the art will understand that Figure 1 The structure shown in the figure is only a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the server to which the solution of the present application is applied. Optionally, the server may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0077] It should be noted that the execution subject of the embodiment of the present application can be a computer device or a theme switching device. The following method embodiment will be described with the computer device as the execution subject.

[0078] Figure 2 A flowchart of a method for switching themes provided in an embodiment of the present application. Figure 2 As shown, the method comprises the following steps:

[0079] Step 202: Obtain current user behavior data and current device performance data.

[0080] Among them, the current user behavior data may include current mouse behavior data, current keyboard behavior data and current screen exchange data. Optionally, the current mouse behavior data can be obtained by monitoring and recording the mouse's dwell time, movement speed, click accuracy, input speed, key interval, scrolling frequency, etc. through the javascript code on the browser side. The current keyboard behavior data and current screen exchange data can also be obtained by monitoring keyboard input and screen changes. The current user behavior data can also be obtained by other means, which is not specifically limited in the embodiments of the present application.

[0081] The current device performance data may include current CPU usage data, current memory occupancy data, and current network delay data. Optionally, the current device performance data may be collected in real time through a preset device load monitoring model, or may be obtained through other methods, which is not specifically limited in the present application embodiment.

[0082] In some optional embodiments, data may be collected once every preset time period to ensure that real-time and continuous current user behavior data and current device performance data are obtained. Optionally, the preset time period may be 5 seconds.

[0083] In some other optional embodiments, the acquired current user behavior data and current device performance data may also be stored in a preset database, and when they are to be used later, they may be directly acquired from the preset database.

[0084] Step 204: Determine the user's current visual fatigue detection result based on the current user behavior data.

[0085] After the current user behavior data is acquired, optionally, the current visual fatigue detection result of the user can be determined directly based on the current user behavior data.

[0086] In some optional embodiments, the current user behavior data may be pre-processed before determining the user's current visual fatigue detection result. Figure 3 As shown, Figure 3 A flowchart of the steps for determining the current visual fatigue detection result of a user provided in an embodiment of the present application includes:

[0087] Step 302: Perform data preprocessing operations on the current user behavior data to obtain multi-dimensional feature data.

[0088] Among them, Figure 4 As shown, Figure 4 A flowchart of the steps of obtaining multi-dimensional feature data provided in an embodiment of the present application includes:

[0089] Step 402: Aggregate the current user behavior data according to a preset time window to obtain aggregated data.

[0090] Step 404: perform feature extraction processing on the aggregated data to obtain current feature data.

[0091] Step 406: perform data cleaning and denoising processing on the current feature data, and segment the processed results according to preset time periods to generate time window feature data.

[0092] Step 408: perform data standardization and normalization processing on the time window feature data to generate multi-dimensional feature data.

[0093] When the current user behavior data is aggregated according to the preset time window to obtain aggregated data, the aggregated data may include key feature data within each preset time window. Optionally, the preset time window may be 5 seconds.

[0094] For example, for the current mouse behavior data in the current user behavior data, the total time the mouse stays in a specific area in each preset time window can be counted to calculate the average movement speed of the mouse. For the current keyboard behavior data, the number of characters entered and the key interval in each preset time window can be calculated. For the current device performance data, the current CPU usage data, current memory occupancy data, current network delay data, etc. in each preset time window can be calculated separately. The data obtained by the above calculations can all be regarded as key feature data.

[0095] Next, feature extraction processing can be performed on the aggregated data to obtain current feature data, where the current feature data is feature data that can reflect user behavior and fatigue status, such as mouse dwell time, mouse movement speed, input speed, scrolling frequency, etc. For example, mouse dwell time refers to the total dwell time on a specific page area or element, movement speed refers to the average movement speed of the mouse within 5 seconds, and key interval refers to the time difference between every two keys.

[0096] Then, the current feature data is cleaned and denoised, and the processed results are segmented according to the preset time period to generate time window feature data. Optionally, when performing data cleaning and denoising, the interquartile range algorithm (IQR) can be used to identify and remove outliers, remove irrelevant outliers and noise data, and ensure that all data for subsequent analysis are of higher quality. The specific implementation process can refer to the existing technology and will not be repeated here.

[0097] In addition, the processed results can be segmented according to a preset time period to generate time window feature data. Optionally, the preset time period can be 5 seconds, so that the processed results can be segmented and analyzed using a rolling window technique, and data features are calculated every 5 seconds to generate time window feature data. For example, the mouse dwell time, input speed, etc. are calculated every 5 seconds to form a time series of time window feature data as input for subsequent analysis and model training.

[0098] Finally, in order to ensure that different features have the same scale and facilitate subsequent analysis and modeling, the time window feature data can be standardized and normalized to generate multidimensional feature data. The specific processing process can refer to the prior art and will not be repeated here. For example, Table 1 is a multidimensional feature data of data standardization and normalization.

[0099] Table 1

[0100]

[0101]

[0102] In this embodiment, by using data cleaning and feature extraction technology, noise data is effectively removed, making the analysis more accurate. In addition, the structured processing of features reduces the computational complexity and improves the efficiency and stability of subsequent processing and analysis, thereby improving the overall processing performance.

[0103] Step 304: Determine the user's overall fatigue index based on the multi-dimensional feature data.

[0104] Among them, Figure 5 As shown, Figure 5 A flowchart of steps for determining the overall fatigue index of a user provided in an embodiment of the present application includes:

[0105] Step 502: for each feature data, based on the feature data and a preset feature threshold value corresponding to the feature data, determine the current visual fatigue state value corresponding to the feature data.

[0106] Step 504: Calculate the user's overall fatigue index based on each current visual fatigue state value and preset weight information.

[0107] The multi-dimensional feature data can be represented as a feature vector F={f1, f2,…, fn}, where f1 to fn represent different feature data respectively, and n represents the number of feature data.

[0108] Thus, for each feature data, based on the feature data and the preset feature threshold corresponding to the feature data, the current visual fatigue state value corresponding to the feature data can be determined. Optionally, in order to cope with individual differences in behavior patterns, a dynamic threshold T can be used. i (t), T i (t) = μ i (t)+k*σ i (t), where μ i (t) and σ i (t) represents the dynamic mean and standard deviation of the feature data, k is an adjustable parameter, and i ranges from 1 to n. In the initial stage, the preset group feature distribution can be used as the basic preset feature threshold, and the real-time data of user behavior can be combined for online learning during operation to continuously adjust the preset feature threshold to adapt to individual characteristics. Through this mechanism, behavioral analysis can dynamically capture changes in user behavior patterns.

[0109] Compare each feature data with the corresponding preset feature threshold T i (t) is compared, so that the current visual fatigue state value corresponding to the feature data can be determined. For example, if the mouse stay time exceeds the corresponding preset feature threshold, it may indicate that the user's current attention is reduced.

[0110] After obtaining the current visual fatigue state value corresponding to each feature data, the user's overall fatigue index can be calculated based on each current visual fatigue state value and preset weight information. Optionally, the user's overall fatigue index F can be calculated using formula (1): i , that is, the user's overall fatigue index F is obtained by weighting and summing the current visual fatigue state values ​​through the preset weight information i .

[0111]

[0112] Among them, ω i To preset weight information, dynamic adjustment can be used to ensure that the analysis can be flexibly adapted to the scenario requirements. i is the current visual fatigue status value.

[0113] In this embodiment, the preset feature threshold designed by the dynamic learning algorithm and the joint analysis of multi-feature data can adapt to individual differences, accurately judge the user's current visual fatigue state, and improve the reliability of the theme switching results and user experience; in addition, by calculating the comprehensive fatigue index, it provides users with a clear basis for fatigue assessment, and supports active intervention to help users adjust their behavior in a timely manner and avoid excessive accumulation of fatigue.

[0114] Step 306: Determine the user's current visual fatigue detection result based on the overall fatigue index and the preset fatigue threshold interval.

[0115] If the overall fatigue index is within the first threshold interval, the user's current visual fatigue detection result is determined to be mild visual fatigue. If the overall fatigue index is within the second threshold interval, the user's current visual fatigue detection result is determined to be moderate visual fatigue. If the overall fatigue index is within the third threshold interval, the user's current visual fatigue detection result is determined to be severe visual fatigue.

[0116] Optionally, the overall fatigue index and the characteristic data of the user's behavior can be combined to comprehensively judge the user's current visual fatigue detection result. i The user is in the first threshold interval, and based on the feature data, it is determined that the user exhibits a slight decrease in attention, such as the feature data and the corresponding preset feature threshold T i (t) differs by a smaller value, then it is determined that the user's current visual fatigue detection result is mild visual fatigue.

[0117] If the overall fatigue index is within the second threshold interval, and it is determined based on the feature data that the user shows obvious signs of fatigue, such as the feature data and the corresponding preset feature threshold T i(t) differs by a larger value. For example, if the user stays on the page for a longer time, the input speed decreases, the error rate increases, etc., it is determined that the user's current visual fatigue detection result is moderate visual fatigue.

[0118] If the overall fatigue index is within the third threshold interval, and the plurality of feature data respectively determine that the user shows obvious signs of fatigue, such as the plurality of feature data and the corresponding preset feature threshold T i (t) differ by a large value, it is determined that the user's current visual fatigue detection result is severe visual fatigue.

[0119] It should be noted that when determining the value with a smaller difference or the value with a larger difference, a difference threshold may be preset for determination.

[0120] Step 206: Determine the current equipment load state based on the current equipment performance data.

[0121] Among them, in order to further improve the accuracy of the evaluation, the device load can be included as an important factor in the fatigue stage evaluation process. The device load monitoring module provides real-time current device performance data, which will be combined with the user's current visual fatigue detection results. For example, when the device is highly loaded, the user's behavior may be more restricted, which will aggravate visual fatigue. Therefore, in some optional embodiments, when the device load exceeds a certain threshold, even if the user's overall fatigue index is low, it can be determined to have entered the fatigue stage.

[0122] In some optional embodiments, due to the differences in fatigue responses among different users, a dynamic threshold adjustment mechanism can be introduced to make the fatigue stage division more personalized. By continuously monitoring the current user behavior data, the fatigue stage evaluation criteria can be gradually learned and adjusted during the long-term use of the user. Specifically, based on the visual fatigue detection results corresponding to the historical user behavior data, the threshold can be gradually optimized using an online learning algorithm to make it more adaptable to the behavior pattern of each user.

[0123] In some optional embodiments, a fatigue detection report for the user can be directly generated based on the current visual fatigue detection results obtained, and a specific decision basis can be provided for intelligent theme adjustment. The report clearly presents the user's current fatigue state (such as mild, moderate or severe fatigue) and the current visual fatigue state value corresponding to each behavioral feature data, including whether the mouse dwell time, click accuracy and other features exceed the preset threshold, thereby forming an intuitive fatigue performance summary.

[0124] Step 208: Switch the theme according to the current visual fatigue detection result and the current device load status, and generate a switching result.

[0125] Among them, Figure 6 As shown, Figure 6 A flowchart of steps for generating a switching result provided in an embodiment of the present application includes:

[0126] Step 602: Determine the current theme switching mode based on the current visual fatigue detection result and the current device load status.

[0127] Step 604: Perform theme switching based on the current theme switching mode and generate a switching result.

[0128] Among them, when switching themes, the current theme switching method can be determined in combination with the current visual fatigue detection results and the current device load status.

[0129] In some optional embodiments, Figure 7 As shown, Figure 7 A flowchart of steps for generating a current theme switching method provided in an embodiment of the present application includes:

[0130] Step 702: Based on the current visual fatigue detection result, determine multiple candidate theme switching methods corresponding to the current visual fatigue detection result.

[0131] Step 704: Based on the current device load state and the preset complexity corresponding to each candidate theme switching mode, determine the current theme switching mode from multiple candidate theme switching modes.

[0132] Among them, based on the current visual fatigue detection result, multiple candidate theme switching methods corresponding to the current visual fatigue detection result can be determined. Exemplarily, if it is determined based on the current visual fatigue detection result that the user is in mild visual fatigue, only a small switching adjustment can be made, and multiple candidate theme switching methods may be to optimize the font style, adjust the background brightness and contrast, etc. If it is determined based on the current visual fatigue detection result that the user is in moderate or severe visual fatigue, multiple candidate theme switching methods may be to switch to low-stimulation themes, such as dark mode or simple mode, optimize the content layout, etc., to reduce the visual burden. Optionally, in the case of severe visual fatigue, a rest suggestion may also pop up to prompt the user to suspend use to protect vision health.

[0133] Next, based on the current device load state and the preset complexity corresponding to each candidate theme switching mode, the current theme switching mode may be determined from a plurality of candidate theme switching modes.

[0134] Optionally, when the current device load state is high, a lightweight adjustment solution can be preferentially adopted, that is, a candidate theme switching method with a lower preset complexity is selected. For example, the color scheme can be changed, non-core functional modules can be hidden, etc., to reduce the demand on device performance.

[0135] Optionally, when the current device load state is relatively low, a more complex dynamic adjustment effect can be performed, that is, a candidate theme switching method with a higher preset complexity is selected, such as gradual switching of themes or real-time optimization of content layout.

[0136] It should be noted that when determining a candidate theme switching mode with a lower preset complexity or a higher preset complexity, a complexity threshold may be preset to determine the mode.

[0137] The present application provides a method for switching themes, which includes: obtaining current user behavior data and current device performance data, wherein the current user behavior data includes current mouse behavior data, current keyboard behavior data and current screen exchange data, and the current device performance data includes current CPU usage data, current memory occupancy data and current network delay data, determining the current visual fatigue detection result of the user based on the current user behavior data, determining the current device load state based on the current device performance data, switching themes according to the current visual fatigue detection result and the current device load state, and generating a switching result. This solution can grasp the user's status in real time by comprehensively collecting the current user behavior feature data, improve the comprehensiveness and accuracy of monitoring, provide technical support for rapid response to user status changes, and effectively improve the system's early recognition ability of fatigue; in addition, by combining the current user behavior data and the current device performance data, the theme switching can be performed more intelligently and accurately, which improves the intelligence of the theme switching and improves the user experience; and by combining the current device performance data, it ensures that the theme switching is adapted to the device load status, further ensuring the fluency of the system and the user experience.

[0138] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0139] Figure 8 A structural block diagram of a theme switching device provided in an embodiment of the present application.

[0140] like Figure 8 As shown, the theme switching device 800 includes:

[0141] The acquisition module 802 is used to obtain the current user behavior data and the current device performance data; wherein the current user behavior data includes the current mouse behavior data, the current keyboard behavior data and the current screen switching data, and the current device performance data includes the current CPU usage data, the current memory occupancy data and the current network delay data.

[0142] The first determination module 804 is used to determine the user's current visual fatigue detection result based on the current user behavior data.

[0143] The second determination module 806 is used to determine the current device load state based on the current device performance data.

[0144] The generation module 808 is used to switch the theme according to the current visual fatigue detection result and the current device load status, and generate a switching result.

[0145] Regarding the device in the above embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment of the method, and will not be described in detail here. Each module in the above theme switching device can be implemented in whole or in part by software, hardware, and a combination thereof. Each of the above modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations of each of the above modules.

[0146] In one embodiment of the present application, a computer device is provided, the computer device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the following steps when executing the computer program:

[0147] Obtain current user behavior data and current device performance data; where the current user behavior data includes current mouse behavior data, current keyboard behavior data and current screen switching data, and the current device performance data includes current CPU usage data, current memory usage data and current network delay data;

[0148] Based on the current user behavior data, determine the user's current visual fatigue detection result;

[0149] Based on the current equipment performance data, determine the current equipment load status;

[0150] The theme is switched according to the current visual fatigue detection result and the current device load status to generate a switching result.

[0151] In one embodiment of the present application, when the processor executes the computer program, the processor further implements the following steps:

[0152] Perform data preprocessing on the current user behavior data to obtain multi-dimensional feature data;

[0153] Determine the user's overall fatigue index based on multi-dimensional feature data;

[0154] Based on the overall fatigue index and the preset fatigue threshold range, the user's current visual fatigue detection result is determined.

[0155] In one embodiment of the present application, when the processor executes the computer program, the processor further implements the following steps:

[0156] Aggregate the current user behavior data according to the preset time window to obtain aggregated data;

[0157] Perform feature extraction on the aggregated data to obtain current feature data;

[0158] Perform data cleaning and denoising on the current feature data, and segment the processed results according to the preset time period to generate time window feature data;

[0159] The time window feature data is standardized and normalized to generate multi-dimensional feature data.

[0160] In one embodiment of the present application, when the processor executes the computer program, the processor further implements the following steps:

[0161] For each feature data, based on the feature data and a preset feature threshold value corresponding to the feature data, determine a current visual fatigue state value corresponding to the feature data;

[0162] Based on the current visual fatigue state values ​​and preset weight information, the user's overall fatigue index is calculated.

[0163] In one embodiment of the present application, when the processor executes the computer program, the processor further implements the following steps:

[0164] If the overall fatigue index is within the first threshold range, it is determined that the current visual fatigue detection result of the user is mild visual fatigue;

[0165] If the overall fatigue index is within the second threshold interval, it is determined that the current visual fatigue detection result of the user is moderate visual fatigue;

[0166] If the overall fatigue index is within the third threshold interval, it is determined that the current visual fatigue detection result of the user is severe visual fatigue.

[0167] In one embodiment of the present application, when the processor executes the computer program, the processor further implements the following steps:

[0168] Determine the current theme switching method based on the current visual fatigue detection result and the current device load status;

[0169] Perform theme switching based on the current theme switching mode and generate a switching result.

[0170] In one embodiment of the present application, when the processor executes the computer program, the processor further implements the following steps:

[0171] Based on the current visual fatigue detection result, determine multiple candidate theme switching modes corresponding to the current visual fatigue detection result;

[0172] Based on the current device load state and the preset complexity corresponding to each candidate theme switching mode, a current theme switching mode is determined from multiple candidate theme switching modes.

[0173] The computer device provided in the embodiment of the present application has similar implementation principles and technical effects to those of the above-mentioned method embodiment, and will not be described in detail here.

[0174] In one embodiment of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0175] Obtain current user behavior data and current device performance data; where the current user behavior data includes current mouse behavior data, current keyboard behavior data and current screen switching data, and the current device performance data includes current CPU usage data, current memory usage data and current network delay data;

[0176] Based on the current user behavior data, determine the user's current visual fatigue detection result;

[0177] Based on the current equipment performance data, determine the current equipment load status;

[0178] The theme is switched according to the current visual fatigue detection result and the current device load status to generate a switching result.

[0179] In one embodiment of the present application, when the computer program is executed by a processor, the following steps are further implemented:

[0180] Perform data preprocessing on the current user behavior data to obtain multi-dimensional feature data;

[0181] Determine the user's overall fatigue index based on multi-dimensional feature data;

[0182] Based on the overall fatigue index and the preset fatigue threshold range, the user's current visual fatigue detection result is determined.

[0183] In one embodiment of the present application, when the computer program is executed by a processor, the following steps are further implemented:

[0184] Aggregate the current user behavior data according to the preset time window to obtain aggregated data;

[0185] Perform feature extraction on the aggregated data to obtain current feature data;

[0186] Perform data cleaning and denoising on the current feature data, and segment the processed results according to the preset time period to generate time window feature data;

[0187] The time window feature data is standardized and normalized to generate multi-dimensional feature data.

[0188] In one embodiment of the present application, when the computer program is executed by a processor, the following steps are further implemented:

[0189] For each feature data, based on the feature data and a preset feature threshold value corresponding to the feature data, determine a current visual fatigue state value corresponding to the feature data;

[0190] Based on the current visual fatigue state values ​​and preset weight information, the user's overall fatigue index is calculated.

[0191] In one embodiment of the present application, when the computer program is executed by a processor, the following steps are further implemented:

[0192] If the overall fatigue index is within the first threshold range, it is determined that the current visual fatigue detection result of the user is mild visual fatigue;

[0193] If the overall fatigue index is within the second threshold interval, it is determined that the current visual fatigue detection result of the user is moderate visual fatigue;

[0194] If the overall fatigue index is within the third threshold interval, it is determined that the current visual fatigue detection result of the user is severe visual fatigue.

[0195] In one embodiment of the present application, when the computer program is executed by a processor, the following steps are further implemented:

[0196] Determine the current theme switching method based on the current visual fatigue detection result and the current device load status;

[0197] Perform theme switching based on the current theme switching mode and generate a switching result.

[0198] In one embodiment of the present application, when the computer program is executed by a processor, the following steps are further implemented:

[0199] Based on the current visual fatigue detection result, determine multiple candidate theme switching modes corresponding to the current visual fatigue detection result;

[0200] Based on the current device load state and the preset complexity corresponding to each candidate theme switching mode, a current theme switching mode is determined from multiple candidate theme switching modes.

[0201] The computer-readable storage medium provided in this embodiment has similar implementation principles and technical effects to those of the above method embodiments, and will not be described in detail here.

[0202] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0203] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0204] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method for switching a theme, characterized in that: The method comprises: Obtain current user behavior data and current device performance data; wherein the current user behavior data includes current mouse behavior data, current keyboard behavior data and current screen switching data, and the current device performance data includes current CPU usage data, current memory occupancy data and current network delay data; Based on the current user behavior data, determine the user's current visual fatigue detection result; Based on the current equipment performance data, determining a current equipment load state; The theme is switched according to the current visual fatigue detection result and the current device load status to generate a switching result.

2. The method according to claim 1, characterized in that The determining, based on the current user behavior data, a current visual fatigue detection result of the user includes: Performing data preprocessing operations on the current user behavior data to obtain multi-dimensional feature data; Determining the overall fatigue index of the user based on the multi-dimensional feature data; Based on the overall fatigue index and the preset fatigue threshold interval, the current visual fatigue detection result of the user is determined.

3. The method according to claim 2, characterized in that The data preprocessing operation is performed on the current user behavior data to obtain multi-dimensional feature data, including: Aggregate the current user behavior data according to a preset time window to obtain aggregated data; Performing feature extraction processing on the aggregated data to obtain current feature data; Performing data cleaning and denoising processing on the current feature data, and segmenting the processed results according to a preset time period to generate time window feature data; The time window feature data is subjected to data standardization and normalization processing to generate the multi-dimensional feature data.

4. The method according to claim 2 or 3, characterized in that: The determining the overall fatigue index of the user based on the multi-dimensional feature data includes: For each of the feature data, based on the feature data and a preset feature threshold value corresponding to the feature data, determine a current visual fatigue state value corresponding to the feature data; Based on each of the current visual fatigue state values ​​and preset weight information, the overall fatigue index of the user is calculated.

5. The method according to claim 2 or 3, characterized in that: The preset fatigue threshold interval includes a first threshold interval, a second threshold interval and a third threshold interval, and the determining the current visual fatigue detection result of the user based on the overall fatigue index and the preset fatigue threshold interval includes: If the overall fatigue index is within the first threshold range, determining that the current visual fatigue detection result of the user is mild visual fatigue; If the overall fatigue index is within the second threshold range, determining that the current visual fatigue detection result of the user is moderate visual fatigue; If the overall fatigue index is within the third threshold interval, it is determined that the current visual fatigue detection result of the user is severe visual fatigue.

6. The method according to any one of claims 1 to 3, characterized in that: The performing theme switching according to the current visual fatigue detection result and the current device load state to generate a switching result includes: Determine a current theme switching mode based on the current visual fatigue detection result and the current device load state; Theme switching is performed based on the current theme switching mode, and the switching result is generated.

7. The method according to claim 6, characterized in that The determining of the current theme switching mode based on the current visual fatigue detection result and the current device load state includes: Based on the current visual fatigue detection result, determining a plurality of candidate theme switching modes corresponding to the current visual fatigue detection result; Based on the current device load state and the preset complexity corresponding to each of the candidate theme switching modes, the current theme switching mode is determined from the multiple candidate theme switching modes.

8. A theme switching device, characterized in that: The device comprises: An acquisition module is used to acquire current user behavior data and current device performance data; wherein the current user behavior data includes current mouse behavior data, current keyboard behavior data and current screen switching data, and the current device performance data includes current CPU usage data, current memory occupancy data and current network delay data; A first determination module, configured to determine a current visual fatigue detection result of a user based on the current user behavior data; A second determination module, configured to determine a current device load state based on the current device performance data; A generation module is used to switch the theme according to the current visual fatigue detection result and the current device load state, and generate a switching result.

9. An electronic device, characterized in that: The electronic device includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement the theme switching method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The storage medium stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement the theme switching method as described in any one of claims 1-7.

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