A social interaction platform for the elderly based on virtual reality

Abstract

The present invention relates to the field of virtual reality technology, and more specifically to a virtual reality-based social interaction platform for seniors, comprising a user management unit, a virtual scene creation unit, a real-time interaction unit, a multi-dimensional social ecology adaptation unit, and a context-driven social game unit. The user management unit is used for user registration, personal information management, and social account maintenance; the virtual scene creation unit allows users to customize virtual scenes as needed; the real-time interaction unit provides voice, video, and text chat functions; the multi-dimensional social ecology adaptation unit constructs a user's social ecology map; and the context-driven social game unit designs a series of social games based on the user's current context. This invention enhances the platform's flexibility and applicability, making it more immersive and engaging. The scene saving and sharing functions also increase interactive communication between users.

Description

Technical Field

[0001] The present invention relates to the field of virtual reality technology, and in particular to a social interaction platform for elderly people based on virtual reality. Background Art

[0002] With the acceleration of the aging process of the global population, the social needs and mental health problems of the elderly are becoming increasingly prominent. Traditional social methods are limited by factors such as geographical location, physical function and shrinking social circles, and are unable to meet the elderly's growing social interaction needs. The development of virtual reality technology has provided a new social channel for the elderly. With the help of immersive virtual environments, the elderly can break through the limitations of time and space, interact with family, friends and new partners, enrich their social life, and improve their quality of life and sense of happiness. However, how to make full use of virtual reality technology to create a social interaction platform that meets the needs of the elderly is still an urgent problem to be solved. Existing virtual reality social platforms are mostly designed for young users and lack attention to the special needs of elderly users, especially in terms of personalized services, emotional care and health considerations.

[0003] Current virtual reality social platforms have the following shortcomings in meeting the special needs of the elderly. First, they lack personalized user management functions and are unable to provide customized services based on the interests, social habits and health status of elderly users, resulting in a poor user experience. Second, the creation and interaction methods of virtual scenes are single, which cannot allow elderly users to fully participate and immerse themselves in them. Third, existing platforms lack the ability to adapt to multi-dimensional social ecosystems and cannot intelligently identify users' social circles, interest preferences and emotional states, resulting in inaccurate recommended social activities and friends. In addition, there is a lack of context-driven social games, and the game content cannot be dynamically adjusted according to the user's current context, which reduces user participation and satisfaction.

[0004] In response to the above-mentioned deficiencies in the existing technologies, the present invention aims to provide a social interaction platform for the elderly based on virtual reality, aiming to promote the social participation of the elderly group, improve their mental health level, and make up for the deficiencies of the existing technologies in personalized services, emotional care and interactive richness. Summary of the Invention

[0005] The present invention provides a social interaction platform for elderly people based on virtual reality.

[0006] The social interaction platform for the elderly based on virtual reality includes a user management unit, a virtual scene creation unit, a real-time interaction unit, a multi-dimensional social ecological adaptation unit, and a situation-driven social game unit, among which;

[0007] The user management unit is used for user registration, personal information management and social account maintenance, and records the user's interests, social habits and health status;

[0008] The virtual scene creation unit allows users to customize virtual scenes according to their needs, including parks and cafes, and supports users to upload personal photos and videos to generate personalized scenes;

[0009] The real-time interactive unit provides voice, video and text chat functions, and integrates gesture recognition technology to enhance the naturalness of interaction between users;

[0010] The multi-dimensional social ecological adaptation unit constructs a user's social ecological map, identifies the user's social circle, interests, activity preferences, and emotional state, and provides personalized social suggestions and activity organization, specifically including:

[0011] Social circle identification: By analyzing the user's social network and interaction history, the system identifies the user's social circle and intelligently recommends activities that the user is interested in or friends to connect with, thereby enhancing the user's social connection;

[0012] Interest and activity preference analysis: Analyze users' interests and activity preferences based on their participation in activities, comments, and browsing history, and dynamically adjust recommendation strategies to adapt to changes in user interests;

[0013] Emotional state monitoring: By analyzing users' behavioral data (such as chat records and activity participation) and physiological data (such as heart rate changes and voice emotion analysis) on the platform, the system assesses the user's current emotional state and adjusts the user's activity content and social suggestions;

[0014] The context-driven social game unit designs a series of social games based on the user's current context, and dynamically adjusts game rules and goals in combination with the user's social ecological map to increase fun and participation.

[0015] Optionally, the user management unit includes:

[0016] User registration: register new users through the personal information form filled out by the user;

[0017] Personal information management: Store and update basic user information, including name, age, gender, and contact information, and allow users to modify their personal information at any time;

[0018] Social account maintenance: provides user social account binding and management functions, allowing users to associate third-party social platform accounts (such as WeChat, QQ, etc.) with this platform to achieve cross-platform social interaction;

[0019] Interest and social habit records: automatically record users' interests, hobbies and social habits through questionnaires and behavior analysis;

[0020] Health status record: allows users to voluntarily fill in health-related information (such as chronic diseases, physical conditions, etc.) and update it regularly.

[0021] Optionally, the virtual scene creation unit includes:

[0022] Scene template selection: used to provide a variety of preset virtual scene templates, users can choose different types of scenes according to their needs, including parks and cafes;

[0023] Scene customization: allows users to make detailed adjustments based on the selected scene template, including the scene's color, layout, and element settings;

[0024] Media upload: supports users to upload personal photos and videos and embed their own photos and videos into virtual scenes;

[0025] Scene saving and sharing: Allows users to save the created personalized virtual scenes to their personal accounts and provides sharing functions.

[0026] Optionally, the real-time interaction unit includes:

[0027] Voice chat: Provides voice call function, supporting users to conduct real-time voice communication in virtual scenes;

[0028] Video chat: allows users to interact face-to-face via video calls and supports multi-user video conferencing capabilities;

[0029] Text chat: Provides instant messaging and receiving functions, allowing users to send text messages while making voice or video calls;

[0030] Gesture recognition: Integrates gesture recognition technology to identify users' gestures in virtual scenes, allowing users to interact through natural gestures, including waving and giving likes.

[0031] Optionally, the social circle identification includes:

[0032] Social network analysis: By analyzing the user's social network structure and interaction history, we can identify the strength of relationships between users and other users and build the user's social graph;

[0033] Interest matching: Based on the user's social network analysis results and combined with the user's interest preferences (such as activity participation records, browsing history, etc.), intelligently recommend social activities or friends that the user is interested in;

[0034] Social recommendation: Combining the user's social graph and interest matching results, using collaborative filtering algorithms to recommend potential social activities and friends based on the user's interaction relationship and interest similarity with other users in their social circle.

[0035] Optionally, the interest and activity preference analysis includes:

[0036] Interest extraction: Based on the user's participation in activities, evaluations, and browsing history data, the user's interest in different types of activities is extracted, and the user's interest score for each type of activity is calculated using a weighted average algorithm;

[0037] Preference analysis: Combining users' browsing history and interest scores, we identify changing trends in user preferences for activity types and use a time decay factor to weight historical activities to reflect the dynamic changes in user interests.

[0038] Dynamic recommendation adjustment: Based on the dynamic preference values ​​obtained from preference analysis, the recommendation strategy is adjusted in real time, including:

[0039] Real-time monitoring of user preference values: Continuously receive dynamic preference values ​​P(u,c,t) from preference analysis;

[0040] Calculate and sort the recommendation weights: Calculate the recommendation weight W(c) for each activity category c based on the preference value of each activity category, and sort the calculated weights W(c);

[0041] Recommended content update: Dynamically update recommended content based on the ranking results of weight W(c). The higher the weight W(c) of activity category c, the more likely it is to recommend activities in that category to users, thereby adapting to changes in user interests in real time.

[0042] Optionally, the emotional state monitoring includes:

[0043] Behavioral data analysis: By analyzing the user's behavioral data on the platform (chat records, activity participation frequency and activeness), the user's emotional characteristics are extracted through natural language processing (NLP) technology, and the user's emotional characteristics are analyzed using the emotional scoring algorithm to generate a behavioral emotional score E. b (u);

[0044] Physiological data analysis: Extract voice emotion scores and heart rate emotion scores through the user's physiological data (such as heart rate, voice emotion analysis), and calculate the physiological emotion score E through a weighted algorithm p (u);

[0045] Calculation of comprehensive emotional score: The behavioral emotional score E is calculated by weighted average. b (u) and physiological emotion score E p(u) to generate the user's current comprehensive emotional state score E(u).

[0046] Optionally, the context-driven social game unit includes:

[0047] Context recognition: Analyzes the user's current context in real time, including emotional state, location (e.g., at home or outdoors), time, and social activity, and generates a context description based on the user's social ecosystem.

[0048] Dynamic game adjustment: Based on the user context description provided by context recognition, the game rules, difficulty, interaction methods and goals are adjusted to suit the user's current context.

[0049] Optionally, the context recognition includes:

[0050] Emotional state analysis: real-time acquisition of the user's current comprehensive emotional state score E(u);

[0051] Location environment analysis: Identify the user's geographic location (e.g., at home, outdoors, etc.) through positioning data, and score the user based on their activity range and location category to generate a location environment score L(u);

[0052] Social activity analysis: Calculate the user's social activity score A(u) based on the user's recent interaction frequency and intensity;

[0053] Context description generation: The user's emotional state score E(u), location environment score L(u), time T(u) and social activity score A(u) are integrated to generate the user's context description C(u).

[0054] Optionally, the dynamic adjustment of the game includes:

[0055] Rule adjustment: When the situation description C(u) is higher than the rule threshold T1, the game's interactive links and task complexity are increased; when the situation description C(u) is lower than the rule threshold T1, the game's interactive links and task complexity are reduced;

[0056] Difficulty adjustment: When the situation description C(u) is higher than the difficulty threshold T2, the game difficulty is increased (for example, shortening the task time, raising the task standard); when the situation description C(u) is lower than the difficulty threshold T2, the game difficulty is reduced;

[0057] Interaction mode adjustment: When the situation description C(u) is higher than the interaction threshold T3, a multi-person interaction mode is recommended. When the situation description C(u) is lower than the interaction threshold T3, a single-person or low-interaction mode is provided.

[0058] Goal adjustment: When the situation description C(u) is higher than the target threshold T4, increase the challenge of the game goal. When the situation description C(u) is lower than the target threshold T4, choose a casual game goal.

[0059] Beneficial effects of the present invention:

[0060] The present invention provides comprehensive social support and personalized experience through five units: user management, virtual scene creation, real-time interaction, multi-dimensional social ecological adaptation, and context-driven social games. The user management unit not only supports user registration, information update, and social account management, but also provides safer and more thoughtful social activity recommendations by recording users' interests and health status, thereby enhancing the flexibility and applicability of the platform. Virtual scene creation allows users to customize social scenes according to their needs, making the platform more immersive and attractive. At the same time, the scene saving and sharing functions increase interactive communication between users.

[0061] The present invention further enhances the user's social experience through the real-time interactive unit and the multi-dimensional social ecological adaptation unit through rich interactive methods and intelligent recommendation mechanisms. The real-time interactive unit provides a variety of communication methods such as voice, video, text chat and gesture recognition, allowing elderly users to express their emotions in a natural way and reducing barriers to technology use. The multi-dimensional social ecological adaptation unit accurately recommends activities and friends that users may be interested in through functions such as social circle identification, interest and activity preference analysis, and emotional state monitoring, ensuring that the recommended content meets the user's personalized needs. This intelligent recommendation mechanism effectively enhances the connection between users and improves the platform's interactivity and user satisfaction.

[0062] The present invention, through real-time context recognition and dynamic adjustment, enables the game rules, difficulty, interaction methods and goals to flexibly adapt to factors such as the user's emotional state, social activity, location environment and time, providing users with a social game experience that fits the current context. This personalized dynamic adjustment method not only enhances the fun and sense of participation in the game, allowing users to obtain a suitable interactive experience regardless of the context, but also promotes users' social participation on the platform, improves users' mental health and social vitality, and helps to build a rich social network and high-quality social life for the elderly. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0064] Figure 1Schematic diagram of platform functional units according to an embodiment of the present invention;

[0065] Figure 2 Schematic diagram of a multi-dimensional social ecological adaptation unit according to an embodiment of the present invention. DETAILED DESCRIPTION

[0066] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments. It is also noted that, to provide a more detailed description, the following embodiments are best and preferred embodiments, and those skilled in the art may employ alternative methods for implementing certain known technologies. Furthermore, the accompanying drawings are intended only to provide a more detailed description of the embodiments and are not intended to limit the present invention.

[0067] It should be noted that references in the specification to "one embodiment," "an embodiment," "an exemplary embodiment," "some embodiments," etc. indicate that the described embodiments may include specific features, structures, or characteristics, but not every embodiment necessarily includes such specific features, structures, or characteristics. In addition, when specific features, structures, or characteristics are described in conjunction with an embodiment, it is within the knowledge of persons skilled in the relevant art to implement such features, structures, or characteristics in conjunction with other embodiments (whether or not explicitly described).

[0068] In general, terms can be understood, at least in part, from their use in context. For example, depending at least in part on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending at least in part on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0069] like Figure 1-Figure 2 As shown, the social interaction platform for the elderly based on virtual reality includes a user management unit, a virtual scene creation unit, a real-time interaction unit, a multi-dimensional social ecological adaptation unit, and a situation-driven social game unit, wherein;

[0070] The user management unit is used for user registration, personal information management, and social account maintenance, and records users' interests, social habits, and health status;

[0071] The virtual scene creation unit allows users to customize virtual scenes according to their needs, including parks and cafes, and supports users to upload personal photos and videos to generate personalized scenes;

[0072] The real-time interactive unit provides voice, video and text chat functions, and integrates gesture recognition technology to enhance the naturalness of interaction between users;

[0073] The multi-dimensional social ecological adaptation unit builds a user's social ecological map, identifies the user's social circle, interests, activity preferences, and emotional state, and provides personalized social suggestions and activity organization, including:

[0074] Social circle identification: By analyzing the user's social network and interaction history, the system identifies the user's social circle and intelligently recommends activities that the user is interested in or friends to connect with, thereby enhancing the user's social connection;

[0075] Interest and activity preference analysis: Analyze users' interests and activity preferences based on their participation in activities, comments, and browsing history, and dynamically adjust recommendation strategies to adapt to changes in user interests;

[0076] Emotional state monitoring: By analyzing users' behavioral data (such as chat records and activity participation) and physiological data (such as heart rate changes and voice emotion analysis) on the platform, the system assesses the user's current emotional state and adjusts the user's activity content and social suggestions to improve user engagement and satisfaction.

[0077] The context-driven social game unit designs a series of social games based on the user's current context. By combining the user's social ecosystem, it dynamically adjusts the game rules and goals to increase fun and participation.

[0078] Through the above content, personalized and immersive social experience can be provided for elderly users, which not only enhances the connection and interactivity between users, but also optimizes the participation and satisfaction of social activities through intelligent recommendations and emotional monitoring, and promotes the social participation and mental health of the elderly group.

[0079] The user management unit includes:

[0080] User registration: Register new users through the personal information form filled out by the user to ensure the uniqueness and validity of the user identity;

[0081] Personal information management: Store and update basic user information, including name, age, gender, and contact information, and allow users to modify their personal information at any time to maintain information accuracy;

[0082] Social account maintenance: provides user social account binding and management functions, allowing users to associate third-party social platform accounts (such as WeChat, QQ, etc.) with this platform to achieve cross-platform social interaction;

[0083] Interest and social habit records: automatically record users' interests, hobbies and social habits through questionnaires and behavior analysis;

[0084] Health status record: Allow users to voluntarily fill in health-related information (such as chronic diseases, physical conditions, etc.) and update it regularly so that the platform can take users' health status into consideration when recommending social activities;

[0085] Through the above content, a safe and convenient social platform is provided for elderly users. It not only supports users to update basic information and bind social accounts in real time, enhancing the flexibility of social interaction, but also realizes personalized social activity recommendations through interest records and health status monitoring. This comprehensive management function enables elderly users to participate in social activities more easily, improves their social experience and satisfaction, and thus promotes more active social participation and mental health.

[0086] The virtual scene creation unit includes:

[0087] Scene template selection: used to provide a variety of preset virtual scene templates, users can choose different types of scenes according to their needs, including parks and cafes;

[0088] Scene customization: allows users to make detailed adjustments based on the selected scene template, including the scene's color, layout, and element settings to meet their personalized needs;

[0089] Media upload: allows users to upload personal photos and videos and embed them into virtual scenes, making them more personalized and realistic.

[0090] Scene saving and sharing: Allow users to save the personalized virtual scenes they create to their personal accounts, and provide sharing functions so that users can share their own scenes with other users to promote social interaction;

[0091] Through the above content, elderly users can easily create a virtual environment that suits their personal preferences according to their own needs. This function not only enhances the user's sense of participation and immersion, but also allows users to create a more real and warm social atmosphere by uploading personal photos and videos. In addition, the scene saving and sharing functions encourage interaction and communication between users, making social activities more colorful, thereby promoting social connections and mental health of the elderly group. This personalized virtual scene experience provides users with a more attractive and fun way to socialize.

[0092] The live interactive sessions include:

[0093] Voice chat: Provides voice call function, supporting users to conduct real-time voice communication in virtual scenes, ensuring smooth and clear communication;

[0094] Video chat: Allows users to interact face-to-face through video calls, enhancing social intimacy and participation, and supports multi-user video conferencing capabilities;

[0095] Text chat: Provides instant messaging and receiving functions, allowing users to send text messages while making voice or video calls, facilitating information sharing and interaction.

[0096] Gesture recognition: Integrates gesture recognition technology to identify user gestures in virtual scenes, allowing users to interact through natural gestures, including waving and giving “likes”, thereby enhancing the naturalness of interaction and emotional expression between users.

[0097] Through the above content, diverse communication methods are created for elderly users, and the flexibility and convenience of social interaction are enhanced. The integrated gesture recognition technology further enhances the naturalness of interaction, allowing users to express emotions and reactions in an intuitive way, reducing barriers to technology use. This diversified interaction method not only makes communication more vivid and cordial, but also encourages users to actively participate in social activities, improves the quality and satisfaction of social experience, and promotes the mental health and social connections of the elderly.

[0098] Social circle identification includes:

[0099] Social network analysis: By analyzing the user's social network structure and interaction history, we can identify the strength of the relationship between the user and other users and construct the user's social graph, which can be expressed as:

[0100]

[0101] Among them, S(u,v) represents the strength of the social relationship between user u and user v, w i is the weight of the i-th interaction, t i is the duration or frequency of the i-th interaction, and n is the total number of interactions;

[0102] Interest matching: Based on the user's social network analysis results and combined with the user's interest preferences (such as activity participation records, browsing history, etc.), intelligently recommend social activities or friends that the user is interested in;

[0103] Social recommendation: Combining the user's social graph and interest matching results, using collaborative filtering algorithms to recommend potential social activities and friends based on the user's interaction relationship with other users in their social circle and the similarity of interests, expressed as:

[0104] R(u,a)=∑ v∈N(u) (S(u,v)·I(v,a));

[0105] Where R(u,a) is the user u's interest recommendation for activity a, N(u) is the user u's social circle, S(u,v) is the relationship strength between user u and user v in the social circle, and I(v,a) is the user v's interest preference for activity a.

[0106] Through the above content, activities and possible friends that users are interested in can be intelligently recommended, which not only improves the accuracy and relevance of the recommendations, but also enhances the social connections between users, allowing elderly users to more naturally discover activities and people that match their interests and social circles. This intelligent social recommendation mechanism effectively promotes the social participation of elderly users, improves the interactivity and user satisfaction of the platform, and helps the elderly build a richer social network.

[0107] Interest and activity preference analysis includes:

[0108] Interest extraction: Based on the user's participation in activities, evaluations, and browsing history data, the user's interest in different types of activities is extracted, and the user's interest score for each type of activity is calculated using a weighted average algorithm, expressed as:

[0109]

[0110] Among them, I(u,c) represents the interest score of user u for activity category c, r i is the user's evaluation of the i-th activity (such as rating or feedback), k i is the weight of the i-th activity (determined based on factors such as the frequency and duration of activity participation), and q is the number of activities in which the user participates;

[0111] Preference analysis: Combine the user's historical browsing history and interest scores to identify the changing trends in the user's preference for activity types. Use the time decay factor to weight historical activities to reflect the dynamic changes in user interests, expressed as:

[0112] P(u,c,t)=I(u,c)·e -λt ;

[0113] Where P(u,c,t) represents the preference value of user u for activity category c at time t, and λ is the time decay coefficient, which is used to reduce the weight of past activities.

[0114] Dynamic recommendation adjustment: Based on the dynamic preference values ​​obtained from preference analysis, the recommendation strategy is adjusted in real time, including:

[0115] Real-time monitoring of user preference values: Continuously receive dynamic preference values ​​P(u,c,t) from preference analysis;

[0116] Calculate the recommendation weight and sort: Calculate the recommendation weight W(c) of each activity category c according to the preference value of each activity category, and sort the calculated weight W(c). The weight W(c) is expressed as:

[0117]

[0118] Among them, W(c) is the weight ratio of activity category c in the current recommendation strategy, c ′ is any activity category in the activity category set C, C is the set of all recommended activity categories, P(u,c ′ ,t) is the interest intensity or preference of user u for category c′ at time t. The higher the preference value, the greater the user’s interest in the category at that time point;

[0119] Recommended content update: Dynamically update recommended content based on the ranking results of weight W(c). The higher the weight W(c) of activity category c, the more likely it is to recommend activities in that category to users, thus adapting to changes in user interests in real time.

[0120] Through the above content, a weighted analysis of the user's participation activities, evaluations and browsing history is performed, and the preference value is dynamically adjusted in combination with the time decay factor, thereby achieving real-time tracking and updating of user interests. It can accurately identify the changing trends of user interests and dynamically adjust the weight and ranking of recommended content to ensure that the recommendation results always meet the user's current interests. This personalized and dynamic recommendation mechanism not only enhances user participation and satisfaction, but also makes the recommendations of social platforms more targeted and flexible, providing users with an interactive experience that is more in line with their needs.

[0121] Emotional state monitoring includes:

[0122] Behavioral data analysis: By analyzing the user's behavioral data on the platform (chat records, activity participation frequency and activeness), the user's emotional characteristics are extracted through natural language processing (NLP) technology, and the user's emotional characteristics are analyzed using the emotional scoring algorithm to generate a behavioral emotional score E. b (u), expressed as:

[0123]

[0124] Among them, E b (u) represents the behavioral sentiment score of user u, which is used to reflect the overall emotional state of the user through platform behavior, s j is the sentiment score of the user’s j-th behavior data, f j is the importance weight of the jth behavior data, and m is the total number of user behavior data;

[0125] Sentiment scoresj The sentiment score is directly calculated through the sentiment analysis model. The sentiment score range is set to [-1, 1], where -1 represents negative sentiment, 1 represents positive sentiment, and 0 represents neutral sentiment, which is expressed as:

[0126] s j =SentimentScore(Data j );

[0127] Among them, SentimentScore is the sentiment analysis model (such as a dictionary or classifier) ​​for the j-th behavior data Data j Sentiment ratings;

[0128] Importance weight of behavioral data f j The weight is measured by the frequency of behavioral data, expressed as:

[0129]

[0130] Among them, F j is the frequency of the user's j-th behavior (e.g., number of chats, number of activities participated in, etc.), is the total frequency of all user behaviors, used to normalize the weight;

[0131] Physiological data analysis: Extract voice emotion scores and heart rate emotion scores through the user's physiological data (such as heart rate, voice emotion analysis), and calculate the physiological emotion score E through a weighted algorithm p (u), expressed as:

[0132] E p (u) = a·H(u) + b·V(u);

[0133] Where H(u) represents the heart rate emotion score of user u, V(u) represents the user's voice emotion score, and a and b are weighting coefficients;

[0134] The heart rate emotion score H(u) is calculated based on heart rate variability (HRV) and is expressed as:

[0135]

[0136] Among them, H(u) is the heart rate emotion score of user u, ranging from [-1,1], indicating the change from negative emotion to positive emotion, HRV is the user's current heart rate variability (fluctuation of heartbeat intervals), HRV min and HRV max are the minimum and maximum values ​​of heart rate variability, respectively;

[0137] The speech emotion score V(u) is calculated by the speech emotion analysis model and is expressed as:

[0138]

[0139] Among them, V(u) is the speech emotion score of user u, ranging from [-1,1], indicating the intensity of emotion from negative to positive, v k is the sentiment score of the kth speech segment, which is output by the speech sentiment analysis model and has a value between [-1, 1]. k is the importance weight of the k-th speech segment;

[0140] Calculation of comprehensive emotional score: The behavioral emotional score E is calculated by weighted average. b (u) and physiological emotion score E p (u) to generate the user's current comprehensive emotional state score E(u), which is expressed as:

[0141] E(u)=α·E b (u)+β·E p (u);

[0142] Among them, α and β are the weight coefficients of behavioral data and physiological data;

[0143] Through the above content, it is possible to accurately capture the user's emotional fluctuations, combine natural language processing and physiological signal processing technology, and quantify the user's emotional score. Through these emotional data, the platform can dynamically adjust social suggestions and activity content to ensure that the recommended interactions meet the user's current emotional needs. This personalized emotional monitoring and real-time adjustment mechanism not only improves the user's experience satisfaction, but also strengthens the user's emotional support, helping elderly users maintain a positive mental state and social vitality.

[0144] Context-driven social game units include:

[0145] Context recognition: Analyzes the user's current context in real time, including emotional state, location (e.g., at home or outdoors), time, and social activity, and generates a context description based on the user's social ecosystem.

[0146] Dynamic game adjustment: Based on the user context description provided by context recognition, the game rules, difficulty, interaction methods and goals are adjusted to suit the user's current context;

[0147] Through the above content, the gaming experience can be flexibly adapted according to the user's current situation (such as emotional state, location, time and social activity), providing users with personalized social interaction options, so that users can obtain the social gaming experience that best suits their needs in different situations. Whether it is a relaxing leisure moment or an active social occasion, they can enjoy a game mode that fits the situation. This not only enhances the fun and sense of participation in the game, but also enhances the depth of interaction between users and others, making elderly users more willing to participate in social activities, thereby enhancing the overall attractiveness of the platform and user satisfaction.

[0148] Context recognition includes:

[0149] Emotional state analysis: real-time acquisition of the user's current comprehensive emotional state score E(u);

[0150] Location environment analysis: Identify the user's geographic location environment (such as at home, outdoors, etc.) through positioning data, and score the user based on their activity range and location category to generate a location environment score L(u), which is expressed as:

[0151]

[0152] Among them, Dist(u,p home ) represents the user's current location and home location p home The distance, D max The preset maximum distance threshold is used to normalize the distance to the range of [0, 1]. The value closer to the home location is higher, which is suitable for identifying the user in the home situation.

[0153] Social activity analysis: Based on the user's recent interaction frequency and intensity, the user's social activity score A(u) is calculated, expressed as:

[0154]

[0155] Among them, S(u,v i ) represents user u and user v in his social circle i The interaction intensity is , l is the total number of friends in the user’s social circle;

[0156] Context description generation: The user's emotional state score E(u), location environment score L(u), time T(u), and social activity score A(u) are integrated to generate the user's context description C(u), which can be expressed as:

[0157] C(u)=w1·E(u)+w2·L(u)+w3·A(u)+w4·T(u);

[0158] Among them, w1, w2, w3, and w4 are the weight coefficients of each score;

[0159] Through the above content, it can flexibly adapt to the needs of different users and scenarios, making the situation description more in line with the user's actual situation, and dynamically reflecting the different degrees of influence of various factors on the situation, thereby providing accurate situational information for the platform, helping the system to recommend social content and interactive activities that best suit the user's current situation in real time, thereby enhancing the user's sense of participation and the level of personalization of the social experience.

[0160] Game dynamic adjustments include:

[0161] Rule adjustment: When the situation description C(u) is higher than the rule threshold T1, the game's interactive links and task complexity are increased to make the game more challenging. When the situation description C(u) is lower than the rule threshold T1, the game's interactive links and task complexity are reduced to reduce the user's participation pressure.

[0162] Difficulty adjustment: When the situation description C(u) is higher than the difficulty threshold T2, the game difficulty is increased (for example, by shortening the task time or raising the task standard) to match the user's high activity level. When the situation description C(u) is lower than the difficulty threshold T2, the game difficulty is reduced to make it easier to complete and adapt to the user's relaxed situation.

[0163] Interaction mode adjustment: When the context description C(u) is higher than the interaction threshold T3, a multi-person interaction mode is recommended. When the context description C(u) is lower than the interaction threshold T3, a single-person or low-interaction mode is provided to reduce the user's social pressure.

[0164] Goal adjustment: When the situation description C(u) is higher than the target threshold T4, the game goal is made more challenging. When the situation description C(u) is lower than the target threshold T4, a casual game goal is selected to enhance user participation and fun.

[0165] Rule threshold T1 is based on the user's historical average context description value To set, expressed as:

[0166]

[0167] in, is the average value of the user's historical context description, σ C(u) is the standard deviation of the user context description, k1 is the adjustment factor (1.0 or 1.5) used to control the sensitivity of the threshold;

[0168] The difficulty threshold T2 is set based on the user's current activity quantile, expressed as:

[0169] T2=Q 75 (C(u))+k2·σ A(u) ;

[0170] Among them, Q75 (C(u)) represents the 75th percentile of the user context description, indicating a higher level of activity, σ A(u) is the standard deviation of the user's social activity score, and k2 is the adjustment factor (0.5 or 1.0);

[0171] The interaction threshold T3 is set based on the average interaction frequency of the user's current social circle and is expressed as:

[0172]

[0173] in, represents the average interaction frequency between the user and all friends in the social circle, σ S(u,v) is the standard deviation of the frequency of interaction between users and friends, and k3 is the adjustment coefficient;

[0174] The target threshold T4 is set based on the user's emotional state distribution and is expressed as:

[0175]

[0176] in, is the historical average of the user's emotional state score, σ E(u) is the standard deviation of the user's emotional state score, k4 is the adjustment coefficient used to control the sensitivity of target setting;

[0177] Through the above content, the gaming experience can be accurately optimized in real time according to the user's current situation. This dynamic adjustment method allows the game rules, difficulty, interaction methods and goals to flexibly adapt to the user's emotional state, social activity, location environment and time factors, so that users can obtain a social gaming experience that meets their needs regardless of the situation they are in, thereby enhancing the fun and sense of participation in the game. At the same time, this personalized dynamic adjustment effectively enhances user satisfaction and promotes users to participate more actively in social interactions.

[0178] The present invention encompasses any alternatives, modifications, equivalents, and solutions that fall within the spirit and scope of the present invention. To provide a thorough understanding of the present invention, specific details are described in detail below in connection with the preferred embodiments of the present invention, but those skilled in the art will be able to fully understand the present invention without these detailed descriptions. Furthermore, to avoid unnecessary confusion regarding the essence of the present invention, well-known methods, processes, procedures, components, and circuits have not been described in detail.

[0179] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A social interaction platform for the elderly based on virtual reality, characterized by: It includes user management unit, virtual scene creation unit, real-time interaction unit, multi-dimensional social ecological adaptation unit and context-driven social game unit, among which; The user management unit is used for user registration, personal information management and social account maintenance, and records the user's interests, social habits and health status; The virtual scene creation unit allows users to customize virtual scenes according to their needs, including parks and cafes, and supports users to upload personal photos and videos to generate personalized scenes; The real-time interactive unit provides voice, video and text chat functions, and integrates gesture recognition technology to enhance the naturalness of interaction between users; The multi-dimensional social ecological adaptation unit constructs a user's social ecological map, identifies the user's social circle, interests, activity preferences, and emotional state, and provides personalized social suggestions and activity organization, specifically including: Social circle identification: By analyzing the user's social network and interaction history, the system identifies the user's social circle and intelligently recommends activities that the user is interested in or friends to connect with, thereby enhancing the user's social connection; Interest and activity preference analysis: Analyze users' interests and activity preferences based on their participation in activities, comments, and browsing history, and dynamically adjust recommendation strategies to adapt to changes in user interests; Emotional state monitoring: By analyzing the user's behavioral data on the platform, the user's current emotional state is assessed and the user's activity content and social suggestions are adjusted; The context-driven social game unit designs a series of social games based on the user's current context and dynamically adjusts game rules and goals based on the user's social ecosystem to increase fun and participation. The interest and activity preference analysis includes: Interest extraction: Based on the user's participation in activities, evaluations, and browsing history data, the user's interest in different types of activities is extracted, and the user's interest score for each type of activity is calculated using a weighted average algorithm; Preference analysis: Combining users' browsing history and interest scores, we identify changing trends in user preferences for activity types and use a time decay factor to weight historical activities to reflect the dynamic changes in user interests. Dynamic recommendation adjustment: Based on the dynamic preference values ​​obtained from preference analysis, the recommendation strategy is adjusted in real time, including: Real-time monitoring of user preference values: Continuously receive dynamic preference values ​​P(u,c,t) from preference analysis; Calculate and sort the recommendation weights: Calculate the recommendation weight W(c) for each activity category c based on the preference value of each activity category, and sort the calculated weights W(c); Recommended content update: Dynamically update recommended content based on the ranking results of weight W(c). The higher the weight W(c) of activity category c, the more likely it is to recommend activities in that category to users, thereby adapting to changes in user interests in real time.

2. The virtual reality-based social interaction platform for the elderly according to claim 1, characterized in that: The user management unit includes: User registration: register new users through the personal information form filled out by the user; Personal information management: Store and update basic user information, including name, age, gender, and contact information, and allow users to modify their personal information at any time; Social account maintenance: Provides user social account binding and management functions, allowing users to link third-party social platform accounts with this platform; Interest and social habit records: automatically record users' interests, hobbies and social habits through questionnaires and behavior analysis; Health status record: Allow users to voluntarily fill in health-related information and update it regularly.

3. The virtual reality-based social interaction platform for the elderly according to claim 1, characterized in that: The virtual scene creation unit includes: Scene template selection: used to provide a variety of preset virtual scene templates, users can choose different types of scenes according to their needs, including parks and cafes; Scene customization: allows users to make detailed adjustments based on the selected scene template, including the scene's color, layout, and element settings; Media upload: supports users to upload personal photos and videos and embed their own photos and videos into virtual scenes; Scene saving and sharing: Allows users to save the created personalized virtual scenes to their personal accounts and provides sharing functions.

4. The virtual reality-based social interaction platform for the elderly according to claim 1, characterized in that: The real-time interactive unit includes: Voice chat: Provides voice call function, supporting users to conduct real-time voice communication in virtual scenes; Video chat: allows users to interact face-to-face via video calls and supports multi-user video conferencing capabilities; Text chat: Provides instant messaging and receiving functions, allowing users to send text messages while making voice or video calls; Gesture recognition: Integrates gesture recognition technology to identify users' gestures in virtual scenes, allowing users to interact through natural gestures, including waving and giving likes.

5. The virtual reality-based social interaction platform for the elderly according to claim 1, characterized in that: The social circle identification includes: Social network analysis: By analyzing the user's social network structure and interaction history, we can identify the strength of relationships between users and other users and build the user's social graph; Interest matching: Based on the user's social network analysis results and combined with the user's interest preferences, intelligently recommend social activities or friends that the user is interested in; Social recommendation: Combining the user's social graph and interest matching results, using collaborative filtering algorithms to recommend potential social activities and friends based on the user's interaction relationship and interest similarity with other users in their social circle.

6. The virtual reality-based social interaction platform for the elderly according to claim 5, characterized in that: The emotional state monitoring includes: Behavioral data analysis: By analyzing the user's behavioral data on the platform, extracting the user's emotional characteristics through natural language processing technology, and using the emotional scoring algorithm to perform sentiment analysis on the user's emotional characteristics, a behavioral emotion score E is generated. b (u); Physiological data analysis: Extract the voice emotion score and heart rate emotion score through the user's physiological data, and calculate the physiological emotion score E through a weighted algorithm p (u); Calculation of comprehensive emotional score: The behavioral emotional score E is calculated by weighted average. b (u) and physiological emotion score E p (u) to generate the user's current comprehensive emotional state score E(u).

7. The virtual reality-based social interaction platform for the elderly according to claim 6, characterized in that: The context-driven social game unit includes: Context recognition: Real-time analysis of the user's current context, including emotional state, location, time, and social activity, and generates a context description based on the user's social ecosystem. Dynamic game adjustment: Based on the user context description provided by context recognition, the game rules, difficulty, interaction methods and goals are adjusted to suit the user's current context.

8. The virtual reality-based social interaction platform for the elderly according to claim 7, characterized in that: The context recognition includes: Emotional state analysis: real-time acquisition of the user's current comprehensive emotional state score E(u); Location environment analysis: Identify the user's geographic location environment through positioning data, and score the user based on their activity range and location category to generate a location environment score L(u); Social activity analysis: Calculate the user's social activity score A(u) based on the user's recent interaction frequency and intensity; Context description generation: The user's emotional state score E(u), location environment score L(u), time T(u) and social activity score A(u) are integrated to generate the user's context description C(u).

9. The virtual reality-based social interaction platform for the elderly according to claim 8, characterized in that: The dynamic adjustment of the game includes: Rule adjustment: When the situation description C(u) is higher than the rule threshold T1, the game's interactive links and task complexity are increased; when the situation description C(u) is lower than the rule threshold T1, the game's interactive links and task complexity are reduced; Difficulty adjustment: When the situation description C(u) is higher than the difficulty threshold T2, the game difficulty increases; when the situation description C(u) is lower than the difficulty threshold T2, the game difficulty decreases; Interaction mode adjustment: When the situation description C(u) is higher than the interaction threshold T3, a multi-person interaction mode is recommended. When the situation description C(u) is lower than the interaction threshold T3, a single-person or low-interaction mode is provided. Goal adjustment: When the situation description C(u) is higher than the target threshold T4, increase the challenge of the game goal. When the situation description C(u) is lower than the target threshold T4, choose a casual game goal.

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