Physical training system based on virtual reality

Abstract

The invention relates to the technical field of physical training, and particularly discloses a physical training system based on virtual reality, comprising: a virtual reality environment generation module for creating and presenting a virtual physical training scene; the high-precision motion capture device is used for capturing motion posture data of the user in the virtual reality environment in real time; the biomechanical analysis software module is used for receiving and analyzing the motion posture data; through the virtual reality environment generation module, diversification and vividness of a training environment are realized, and the module can quickly construct a virtual scene meeting requirements according to training requirements of a user, so that the user seems to be in a real competition or training environment, and the user experience is improved. The immersive training experience can greatly improve the participation degree and the training enthusiasm of the user, meanwhile, the training effect can be improved, in addition, the virtual reality environment can simulate different weather, illumination and other conditions, the training scene is further enriched, and the practicability and pertinence of training are enhanced.

Description

Technical Field

[0001] The invention belongs to the technical field of sports training, and in particular relates to a sports training system based on virtual reality. Background Art

[0002] With the rapid development of science and technology, the field of sports training has also ushered in technological innovation. In recent years, virtual reality technology has shown great application potential in the field of sports training with its unique immersive experience. Through VR technology, trainees can be placed in a realistic virtual environment and simulate real competition or training scenes, thereby improving training results. This technology not only greatly enriches training methods, but also provides the possibility for the formulation of personalized training plans.

[0003] However, although the existing sports training system based on virtual reality has improved the fun and interactivity of training to a certain extent, the existing system is still rough in biomechanical analysis. It is unable to accurately capture and analyze the trainee's movement posture data in the virtual environment, and thus cannot comprehensively evaluate the trainee's muscle activation pattern, movement efficiency and potential injury risk. This defect limits the further improvement of training effect and also makes the formulation of personalized training plans lack scientific basis. For example, in track and field training, key indicators such as step frequency, step length, take-off angle and landing posture are crucial to training effect, but the existing system is often unable to accurately measure and analyze these indicators, which makes it difficult for trainees to discover their own technical movement defects and cannot get targeted improvement suggestions. Therefore, staff are needed to improve them. Summary of the invention

[0004] The purpose of the present invention is to provide a sports training system based on virtual reality to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A sports training system based on virtual reality, comprising:

[0007] A virtual reality environment generation module for creating and presenting virtual sports training scenes;

[0008] A high-precision motion capture device, used to capture the user's motion posture data in the virtual reality environment in real time;

[0009] A biomechanical analysis software module, connected to a high-precision motion capture device, for receiving and analyzing the motion posture data, further analyzing the user's muscle activation pattern, and evaluating the user's motion efficiency and potential injury risk;

[0010] The real-time feedback module is connected to the biomechanical analysis software module to intuitively display the analysis results to the user through a virtual reality interface and provide instant adjustment suggestions to optimize the user's technical movements and reduce the risk of injury.

[0011] Preferably, the high-precision motion capture device includes at least one wearable sensor, which is configured on a key part of the user's body to capture fine movement details.

[0012] Preferably, the biomechanical analysis software module includes:

[0013] The data preprocessing unit is used to execute the following formula to clean and calibrate the motion posture data to improve the accuracy of the analysis:

[0014]

[0015] Among them, P clean (t) is the motion posture data after preprocessing, d i (t) is the raw data of the i-th sensor, w i is the weight coefficient, f filter (·) is the information filtering function, μ i is the mean value, g normalize (t) is the normalization function;

[0016] The motion pattern recognition unit is used to recognize the user's motion pattern and compare it with the standard motion pattern library to evaluate the user's action standardization. The recognition process uses the following formula to calculate the matching degree:

[0017]

[0018] Among them, S match (t) is the matching degree, M(t) is the user motion pattern feature vector, M standard (t) is the standard motion pattern feature vector, T is the training time, λ is the adjustment coefficient, and MSE is the mean square error;

[0019] The muscle activation pattern analysis unit uses the following formula to analyze the activity intensity and coordination of the user's muscles based on the motion posture data:

[0020]

[0021] Among them, A activation (t) is the degree of muscle activation, a j (t) is the activation intensity of the jth muscle, h exp (·) is an exponential function, b j (t) is the activation threshold of the jth muscle, c j is a constant.

[0022] Preferably, the real-time feedback module includes:

[0023] A visual feedback unit, which is used to overlay analysis results and suggestions in the virtual reality interface, such as correction diagrams for movement postures and heat maps for muscle activation;

[0024] The voice prompt unit is used to provide users with instant adjustment suggestions through voice commands to enhance the interactivity of the user experience.

[0025] Preferably, the system further comprises a personalized training plan generation module, which automatically generates a personalized training plan based on the user's biomechanical data, training history and goals, and works in conjunction with the real-time feedback module to dynamically adjust the training difficulty and focus. When generating a personalized training plan, the user's potential risk of injury is considered, and the risk is evaluated by the following formula:

[0026]

[0027] Among them, R injury (t) is the risk of injury, P stress (s) is the stress level, A asym (s) is asymmetric, P recovery (s) is the recovery level, and α, β, and γ are weight coefficients.

[0028] Preferably, the system further includes a remote coaching module, which allows the remote coach to observe the user's training situation in real time through a virtual reality interface and provide remote guidance and feedback. The remote coach can provide feedback based on the user's comprehensive training effect, which is evaluated by the following formula:

[0029]

[0030] Among them, E training (t) is the training effect, P target (s) is the target training performance, P actual (s) is the actual training performance.

[0031] Preferably, the system supports simultaneous multi-user training, allowing users to conduct team training and competitive games in a virtual environment while each receiving personalized biomechanical analysis and feedback.

[0032] Preferably, the system also includes a data synchronization and storage module for synchronizing the user's training data and analysis results to a cloud server to achieve cross-device access and historical data analysis.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] (1) The training environment can be diversified and realistic through the virtual reality environment generation module. The module can quickly build a virtual scene that meets the requirements according to the user's training needs, making the user feel as if they are in a real competition or training environment. The immersive training experience can greatly enhance the user's participation and training enthusiasm, and also help improve the training effect. In addition, the virtual reality environment can also simulate different weather, lighting and other conditions to further enrich the training scene and enhance the practicality and pertinence of the training.

[0035] (2) Through the high-precision motion capture device, the user's movement posture is accurately captured. The accuracy helps to ensure the accuracy and reliability of subsequent analysis. At the same time, the device can also capture subtle changes in the user's movement process, providing a more detailed basis for training adjustments. Combined with the data provided by the high-precision motion capture device, the biomechanical analysis software module can deeply analyze the user's muscle activation pattern, movement efficiency and other key indicators. The analysis capability helps to timely discover and correct improper aspects of the user's movement process, thereby reducing the risk of injury. At the same time, the module can also tailor a training plan for the user based on the user's biomechanical characteristics, further improving the training effect.

[0036] (3) Through the real-time feedback module, users can instantly understand their training status, including the correctness of movement posture and the balance of muscle activation. Instant feedback helps users to adjust training strategies in a timely manner and optimize technical movements, thereby improving training effects. At the same time, the intuitive feedback form also helps to enhance the interactivity of the user experience. Combined with the user's biomechanical data and training history, the personalized training plan generation module can tailor a training plan for the user. The personalized training plan is more in line with the user's actual situation and needs, which helps to improve the pertinence and effectiveness of the training. At the same time, the module can also dynamically adjust the training difficulty and focus according to the user's training progress and feedback to ensure the continuous improvement of the training effect. Through the remote coaching guidance module, users can enjoy professional remote guidance and feedback. The remote guidance method is not restricted by time and space, which helps users to obtain professional training suggestions anytime and anywhere. At the same time, the remote coach can also provide personalized training suggestions based on the user's comprehensive training effect to help users better improve their skill level. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0038] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0039] Embodiment 1:

[0040] See also Figure 1 As shown, a sports training system based on virtual reality comprises:

[0041] A virtual reality environment generation module for creating and presenting virtual sports training scenes;

[0042] High-precision motion capture device, used to capture the user's motion posture data in real time in a virtual reality environment;

[0043] Biomechanical analysis software module, connected to the high-precision motion capture device, is used to receive and analyze motion posture data, further analyze the user's muscle activation pattern, and evaluate the user's movement efficiency and potential injury risk;

[0044] The real-time feedback module is connected to the biomechanical analysis software module to intuitively display the analysis results to the user through a virtual reality interface and provide instant adjustment suggestions to optimize the user's technical movements and reduce the risk of injury.

[0045] The high-precision motion capture device includes at least one wearable sensor, which is configured on key parts of the user's body to capture fine movement details.

[0046] Biomechanical analysis software modules include:

[0047] The data preprocessing unit is used to clean and calibrate the motion posture data to improve the accuracy of the analysis:

[0048]

[0049] Among them, P clean (t) is the motion posture data after preprocessing, d i (t) is the raw data of the i-th sensor, w i is the weight coefficient, f filter (·) is the information filtering function, μ i is the mean value, g normalize (t) is the normalization function;

[0050] Range explanation: P cleanThe value range of (t) is [0,1], which indicates the ratio of the preprocessed data to its possible range. The higher the value, the better the data quality.

[0051] The motion pattern recognition unit is used to recognize the user's motion pattern and compare it with the standard motion pattern library to evaluate the user's action standardization. The recognition process uses the following formula to calculate the matching degree:

[0052]

[0053] Among them, S match (t) is the matching degree, M(t) is the user motion pattern feature vector, M standard (t) is the standard motion pattern feature vector, T is the training time, λ is the adjustment coefficient, and MSE is the mean square error;

[0054] Range explanation: S match The value range of (t) is [0,1], and the higher the value, the more the user's movement pattern matches the standard movement pattern;

[0055] The muscle activation pattern analysis unit uses the following formula to analyze the activity intensity and coordination of the user's muscles based on the motion posture data:

[0056]

[0057] Among them, A activation (t) is the degree of muscle activation, a j (t) is the activation intensity of the jth muscle, h exp (·) is an exponential function, b j (t) is the activation threshold of the jth muscle, c j is a constant;

[0058] Range explanation: A activation The value range of (t) is [0,+∞), and the higher the value, the higher the muscle activation.

[0059] The real-time feedback module includes:

[0060] A visual feedback unit, which is used to overlay analysis results and suggestions in the virtual reality interface, such as correction diagrams for movement postures and heat maps for muscle activation;

[0061] The voice prompt unit is used to provide users with instant adjustment suggestions through voice commands to enhance the interactivity of the user experience.

[0062] The system also includes a personalized training plan generation module, which automatically generates a personalized training plan based on the user's biomechanical data, training history and goals, and works with the real-time feedback module to dynamically adjust the training difficulty and focus. When generating a personalized training plan, the user's potential risk of injury is considered, which is evaluated by the following formula:

[0063]

[0064] Among them, R injury (t) is the risk of injury, P stress (s) is the stress level, A asym (s) is asymmetric, P recovery (s) is the recovery level, α, β, γ are weight coefficients;

[0065] Range explanation: R injury The value range of (t) is [0,+∞), and the higher the value, the greater the potential risk of injury to the user.

[0066] The system also includes a remote coaching module, which allows the remote coach to observe the user's training status in real time through the virtual reality interface and provide remote guidance and feedback. The remote coach can provide feedback based on the user's comprehensive training effect, which is evaluated by the following formula:

[0067]

[0068] Among them, E training (t) is the training effect, P target (s) is the target training performance, P actual (s) is actual training performance;

[0069] Range explanation: E training The value range of (t) is [-∞,1]. The higher the value, the better the user's training effect. A value close to 1 indicates that the target performance is reached or exceeded, and a negative value indicates that the training effect is far below the target.

[0070] The system supports simultaneous multi-user training, allowing users to conduct team training and competitive games in a virtual environment while each receiving personalized biomechanical analysis and feedback.

[0071] The system also includes a data synchronization and storage module, which is used to synchronize the user's training data and analysis results to the cloud server to achieve cross-device access and historical data analysis.

[0072] Embodiment 2:

[0073] See also Figure 1As shown in the figure, the virtual reality environment generation module creates a realistic basketball court scene, including details such as court boundaries, baskets, and spectator seats, making the user feel as if they are in a real basketball game.

[0074] The high-precision motion capture device includes wearable sensors installed on key parts of the user's body (such as wrists, ankles, knees, waist, etc.). These sensors can capture the user's motion posture data in a virtual reality environment in real time, such as shooting posture, dribbling rhythm, moving pace, etc.

[0075] The biomechanical analysis software module receives motion posture data from a high-precision motion capture device and performs in-depth analysis. The data preprocessing unit cleans and calibrates the data to improve the accuracy of the analysis. The motion pattern recognition unit identifies the user's motion pattern and compares it with the standard basketball motion pattern library to evaluate the user's motion standardization. The muscle activation pattern analysis unit analyzes the activity intensity and coordination of the user's muscles to evaluate the user's motion efficiency and potential injury risk.

[0076] The real-time feedback module provides instant feedback to users through the virtual reality interface based on the analysis results of the biomechanical analysis software module. The visual feedback unit overlays the analysis results and suggestions in the virtual reality interface, such as correction diagrams for shooting postures and heat maps for muscle activation. The voice prompt unit provides users with instant adjustment suggestions through voice commands, such as "Please adjust your shooting posture and keep your arms straight", etc., to enhance the interactivity of the user experience.

[0077] In addition, the system also includes a personalized training plan generation module, which automatically generates a personalized basketball training plan based on the user's biomechanical data, training history and goals, and works with the real-time feedback module to dynamically adjust the difficulty and focus of training. When generating a personalized training plan, the module also considers the user's potential risk of injury to ensure the safety and effectiveness of the training.

[0078] Embodiment three:

[0079] See also Figure 1 As shown in FIG. 1 , the virtual reality environment generation module creates a training scene containing a variety of track and field events, such as a running track, a long jump sand pit, a throwing area, etc. Users can choose different track and field events for training according to their own training needs.

[0080] High-precision motion capture devices also include wearable sensors installed on key parts of the user's body. These sensors can capture the user's motion posture data in a virtual reality environment in real time, such as running posture, jumping height, throwing angle, etc.

[0081] The biomechanical analysis software module receives motion posture data from a high-precision motion capture device and performs in-depth analysis. Similar to the basketball training system, this module includes a data preprocessing unit, a motion pattern recognition unit, and a muscle activation pattern analysis unit to evaluate the user's motion standardization, motion efficiency, and potential injury risk.

[0082] The real-time feedback module provides instant feedback to users through a virtual reality interface based on the analysis results of the biomechanical analysis software module. Unlike the basketball training system, the visual feedback unit of the track and field training system will display more specific analysis results and suggestions related to track and field events, such as the adjustment of the cadence and step length when running, the take-off angle and landing posture when jumping, etc. The voice prompt unit will also provide corresponding adjustment suggestions based on the characteristics of the track and field events.

[0083] In addition, the system also supports a remote coaching module, which allows remote coaches to observe the user's training status in real time through a virtual reality interface and provide remote guidance and feedback. The remote coach can provide personalized training suggestions based on the user's comprehensive training results to help users better improve their track and field skills.

[0084] Virtual reality technology provides users with realistic training scenarios and instant biomechanical analysis feedback, helping them optimize technical movements and reduce injury risks; at the same time, the personalized training plan generation module and remote coaching guidance module further improve training effects and user experience.

[0085] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A sports training system based on virtual reality, characterized in that: include: A virtual reality environment generation module for creating and presenting virtual sports training scenes; A high-precision motion capture device, used to capture the user's motion posture data in the virtual reality environment in real time; A biomechanical analysis software module, connected to a high-precision motion capture device, for receiving and analyzing the motion posture data, further analyzing the user's muscle activation pattern, and evaluating the user's motion efficiency and potential injury risk; The real-time feedback module is connected to the biomechanical analysis software module to intuitively display the analysis results to the user through a virtual reality interface and provide instant adjustment suggestions to optimize the user's technical movements and reduce the risk of injury.

2. A sports training system based on virtual reality according to claim 1, characterized in that: The high-precision motion capture device includes at least one wearable sensor, which is configured on a key part of the user's body to capture fine motion details.

3. A sports training system based on virtual reality according to claim 1, characterized in that: The biomechanical analysis software module includes: The data preprocessing unit is used to execute the following formula to clean and calibrate the motion posture data to improve the accuracy of the analysis: Among them, P clean (t) is the pre-processed motion posture data, d i (t) is the raw data of the i-th sensor, w i is the weight coefficient, f filter (·) is the information filtering function, μ i is the mean value, g normalize (t) is the normalization function; The motion pattern recognition unit is used to recognize the user's motion pattern and compare it with the standard motion pattern library to evaluate the user's action standardization. The recognition process uses the following formula to calculate the matching degree: Among them, S match (t) is the matching degree, M(t) is the user motion pattern feature vector, M standard (t) is the standard motion pattern feature vector, T is the training time, λ is the adjustment coefficient, and MSE is the mean square error; The muscle activation pattern analysis unit uses the following formula to analyze the activity intensity and coordination of the user's muscles based on the motion posture data: Among them, A activation (t) is the degree of muscle activation, a j (t) is the activation intensity of the jth muscle, h exp (·) is an exponential function, b j (t) is the activation threshold of the jth muscle, c j is a constant.

4. A sports training system based on virtual reality according to claim 1, characterized in that: The real-time feedback module comprises: A visual feedback unit, which is used to overlay analysis results and suggestions in the virtual reality interface, such as correction diagrams for movement postures and heat maps for muscle activation; The voice prompt unit is used to provide users with instant adjustment suggestions through voice commands to enhance the interactivity of the user experience.

5. A sports training system based on virtual reality according to claim 1, characterized in that: The system also includes a personalized training plan generation module, which automatically generates a personalized training plan based on the user's biomechanical data, training history and goals, and works in conjunction with the real-time feedback module to dynamically adjust the training difficulty and focus. When generating a personalized training plan, the user's potential risk of injury is considered, which is evaluated by the following formula: Among them, R injury (t) is the risk of injury, P stress (s) is the stress level, A asym (s) is asymmetric, P recovery (s) is the recovery level, and α, β, and γ are weight coefficients.

6. A sports training system based on virtual reality according to claim 1, characterized in that: The system also includes a remote coaching module, which allows the remote coach to observe the user's training status in real time through the virtual reality interface and provide remote guidance and feedback. The remote coach can provide feedback based on the user's comprehensive training effect, which is evaluated by the following formula: Among them, E training (t) is the training effect, P target (s) is the target training performance, P actual (s) is the actual training performance.

7. A sports training system based on virtual reality according to claim 1, characterized in that: The system supports simultaneous multi-user training, allowing users to conduct team training and competitive games in a virtual environment while each receiving personalized biomechanical analysis and feedback.

8. A sports training system based on virtual reality according to claim 1, characterized in that: The system also includes a data synchronization and storage module for synchronizing the user's training data and analysis results to a cloud server to achieve cross-device access and historical data analysis.

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