A cervical vertebra rehabilitation system based on virtual reality

Abstract

The present invention relates to a cervical vertebra rehabilitation system based on virtual reality, comprising a virtual reality display module, a cervical vertebra motion detection module, a central processing module, a rehabilitation training control module and a data recording and analysis module. The virtual reality display module provides an immersive rehabilitation environment for patients through a head-mounted display device, and the cervical vertebra motion detection module captures the patient's cervical vertebra motion data in real time through an accelerometer, a gyroscope and a magnetometer. The central processing module fuses multidimensional data through a Kalman filter algorithm, accurately estimates the patient's cervical vertebra posture, and synchronizes its movements to a virtual environment. The rehabilitation training control module dynamically adjusts the training content according to the patient's actual rehabilitation progress, provides a personalized rehabilitation plan, and enhances interactivity and fun. The data recording and analysis module records the patient's training data in real time and generates a rehabilitation report to help doctors conduct scientific evaluations.

Description

Technical Field

[0001] The present invention relates to the technical field of cervical vertebra rehabilitation, and in particular to a cervical vertebra rehabilitation system based on virtual reality. Background Art

[0002] With the change of modern lifestyle, the incidence of cervical spine related diseases has increased year by year. Many people suffer from cervical spine strain, cervical spondylosis and other problems due to long-term use of electronic devices, long-term sitting or improper posture (such as looking down at mobile phones and computers for a long time). Cervical spine diseases not only affect the quality of life, but may also cause severe nerve and blood vessel compression, and even affect the movement and sensory function of the limbs. Especially for office workers, students and some athletes, cervical spine problems have become a common health risk.

[0003] 1. Limitations of traditional cervical spine rehabilitation methods:

[0004] At present, common cervical rehabilitation training mainly relies on physical therapy and traditional rehabilitation equipment, such as cervical traction device, manual massage, acupuncture and physical therapy, etc. Although these traditional therapies can relieve cervical discomfort and promote cervical function recovery to a certain extent, they have the following obvious limitations:

[0005] Lack of initiative and interaction: Traditional rehabilitation methods usually require patients to passively accept treatment, and the initiative in rehabilitation training is poor. For example, when a physical therapist manually operates the patient's neck or uses fixed rehabilitation equipment for traction, the patient can only passively cooperate and lacks interaction with the treatment process.

[0006] Lack of interest and low patient compliance: As the traditional rehabilitation training process is monotonous and boring, patients often find it difficult to persist for a long time, which leads to a reduction in the rehabilitation effect. Especially for patients who need long-term rehabilitation training, low compliance becomes a prominent obstacle in the rehabilitation process.

[0007] Difficulty in personalized training: Traditional rehabilitation equipment is difficult to adjust the intensity and content of training in real time according to the rehabilitation progress and actual situation of each patient. The training content of patients is usually fixed, and personalized training design cannot be carried out for different patients' cervical spine dysfunction, thus affecting the rehabilitation effect.

[0008] Lack of data recording and real-time feedback: In traditional rehabilitation training, the patient's training data (such as cervical spine range of motion, rotation angle, etc.) cannot be recorded and analyzed in real time, and rehabilitation progress is difficult to quantify. In addition, it is difficult for patients to obtain timely feedback during training to correct incorrect movements or postures.

[0009] 2. Application of virtual reality technology in rehabilitation:

[0010] In recent years, the development of virtual reality (VR) technology has brought new breakthroughs in medical rehabilitation. VR technology can create an immersive and interactive virtual environment, allowing patients to perform various rehabilitation training in virtual scenes. Compared with traditional rehabilitation methods, VR technology has significant advantages in the following aspects:

[0011] Enhanced immersive experience and interactivity: By wearing a head-mounted display, patients can enter a realistic virtual environment for training. The diversity and interactivity of virtual reality scenes can effectively improve patients' sense of participation and initiative. Patients can interact with the virtual world through neck movements, enhancing the fun of rehabilitation training.

[0012] Personalization and dynamic adjustment: The virtual reality system can dynamically adjust the difficulty and content of the training tasks according to the cervical spine rehabilitation status of each patient, and realize a personalized rehabilitation plan. For example, the system can automatically adjust the training target according to the patient's actual cervical spine range of motion to ensure the pertinence and effectiveness of rehabilitation training.

[0013] Real-time feedback and accurate data recording: Through the cervical spine motion detection module (such as accelerometer, gyroscope, magnetometer, etc.), the system can monitor the patient's neck movement in real time and provide multi-modal feedback (such as visual, auditory, etc.) to help patients adjust incorrect postures in time. At the same time, the virtual reality system can record detailed data for each training session, including the rotation angle, range of motion, training time, etc. of the cervical spine, so that doctors can quantitatively evaluate the patient's rehabilitation progress.

[0014] Remote rehabilitation and cloud monitoring: Combined with the Internet and cloud computing technology, the virtual reality rehabilitation system can also realize remote rehabilitation. Patients can perform rehabilitation training at home, while doctors can monitor the patient's training data in real time through the cloud and adjust the training plan remotely according to the progress of rehabilitation. This greatly expands the flexibility of rehabilitation training, especially for patients with inconvenient transportation or limited mobility, remote rehabilitation has become an important solution.

[0015] 3. Technical requirements for cervical spine rehabilitation system based on virtual reality:

[0016] Although virtual reality technology has shown great potential in the field of rehabilitation, existing virtual reality rehabilitation systems are mostly used for rehabilitation training of limbs and gait, and systems for cervical spine rehabilitation are still relatively scarce. At the same time, some key technical requirements in the design of cervical spine rehabilitation systems also need to be improved and enhanced:

[0017] Accurately capture cervical spine movements: Every subtle movement in cervical spine rehabilitation training (such as rotation, flexion, and backward bending) is crucial to the rehabilitation effect. Therefore, the system must be able to detect the multi-dimensional motion data of the cervical spine (such as angular velocity, acceleration, and azimuth change) in real time through high-precision sensors, and ensure the accuracy and real-time nature of these data.

[0018] Automatic generation of personalized rehabilitation plans: The cervical spine problems of different patients vary greatly. How to intelligently generate personalized rehabilitation training plans based on each patient's rehabilitation status and training progress is a technical challenge that the existing system needs to solve.

[0019] Intelligent analysis and evaluation of rehabilitation data: The system needs to have strong data processing and analysis capabilities, be able to conduct in-depth analysis of the patient's rehabilitation training data, provide accurate rehabilitation progress assessment reports, and help doctors formulate and adjust rehabilitation plans.

[0020] Further improvement of immersion and interactivity: The effect of rehabilitation training is closely related to the patient's sense of participation. The virtual reality system needs to design a variety of training scenarios and interactive tasks to improve the patient's participation and compliance by enhancing immersion and fun.

[0021] 4. Deficiencies of existing technologies:

[0022] Existing virtual reality rehabilitation equipment is mostly used for the recovery of limb functions, and less focused on the rehabilitation of the cervical spine. Existing virtual reality systems for cervical spine rehabilitation still have the following shortcomings:

[0023] Lack of accurate data collection and posture estimation for the cervical spine: The current system is not comprehensive enough in capturing the fine movements of the cervical spine, and lacks high-precision multi-dimensional data fusion and real-time posture estimation technology.

[0024] Lack of intelligent adjustment of personalized rehabilitation training: The existing system is unable to adjust the training content according to the patient's real-time status, resulting in a lack of targetedness and personalization in rehabilitation training.

[0025] Lack of patient compliance: Due to the lack of interactivity and fun in rehabilitation training, patients often find it difficult to persist in rehabilitation training for a long time, which affects the final rehabilitation effect.

[0026] To this end, we designed a cervical spine rehabilitation system based on virtual reality to solve the above problems. Summary of the invention

[0027] The purpose of the present invention is to provide a cervical vertebra rehabilitation system based on virtual reality to address the deficiencies of the prior art and to solve the problems raised in the background technology.

[0028] To achieve the above object, the present invention provides the following technical solution: a cervical vertebra rehabilitation system based on virtual reality, comprising:

[0029] Virtual reality display module: used to display the virtual rehabilitation training environment;

[0030] Cervical vertebra motion detection module: includes at least one inertial sensor, which is used to detect the motion data of the patient's neck, including angle, acceleration, and rotation speed parameters;

[0031] Central processing module: used to receive and process the motion data obtained by the cervical vertebra motion detection module, and calculate the patient's cervical vertebra motion state through a preset algorithm;

[0032] Rehabilitation training control module: adjusts the rehabilitation training content in the virtual reality environment based on the analysis results of the central processing module and provides real-time feedback to patients;

[0033] Data recording and analysis module: used to record the patient's training data and generate rehabilitation assessment reports.

[0034] As a preferred technical solution of the present invention, the virtual reality display module includes a head-mounted display, and the head-mounted display works in conjunction with the cervical vertebrae motion detection module to achieve synchronous presentation of the patient's motion in a virtual reality environment.

[0035] As a preferred technical solution of the present invention, the cervical vertebra movement detection module includes:

[0036] Accelerometer module: used to detect the linear acceleration of the patient's neck:

[0037]

[0038] in , and They are the acceleration components of the accelerometer in the X, Y, and Z directions respectively. The pitch angle of the patient's cervical spine is calculated by the following formula: and roll angle

[0039]

[0040] in, is the pitch angle of the patient’s cervical spine;

[0041]

[0042] in, is the roll angle of the patient’s cervical spine;

[0043] Gyroscope module: used to detect the angular velocity of the patient's neck ,in Represents the components of angular velocity in three directions, and the rotation angle is obtained by integrating the angular velocity over time , the formula is:

[0044]

[0045] in, For the patient's neck at all times The rotation angle of For the gyroscope at time The angular velocity of is the rotation angle at the initial moment;

[0046] Magnetometer module: used to detect the position of the patient's neck relative to the earth's magnetic field ,in , , is the magnetic field component of the magnetometer in the X, Y, and Z directions. The heading angle is calculated by the following formula

[0047]

[0048] in, is the heading angle of the patient's cervical spine.

[0049] As a preferred technical solution of the present invention, the central processing module fuses the data from the accelerometer, gyroscope and magnetometer through the Kalman filter algorithm to obtain the patient's cervical spine posture estimation. The state update formula of the Kalman filter is:

[0050]

[0051] in: It is the current moment The state estimate of , including attitude information, pitch angle, roll angle and heading angle;

[0052] are the measurements of the accelerometer, gyroscope, and magnetometer;

[0053] Is the measurement matrix: used to map the state vector to the observation space;

[0054] is the Kalman gain: used to dynamically adjust the weight between the measurement value and the state estimate.

[0055] As a preferred technical solution of the present invention, the rehabilitation training control module dynamically adjusts the training content according to the range of motion of the cervical spine, and its adjustment algorithm includes the following steps:

[0056] Setting a target cervical range of motion

[0057] According to the actual range of motion of the cervical spine , determine whether the goal is achieved:

[0058] like , then the training difficulty is increased;

[0059] like , then maintain or reduce the training difficulty;

[0060] The training difficulty adjustment formula is:

[0061]

[0062] in, is the updated training difficulty, is the training difficulty of the previous stage, is the actual cervical spine motion range, Target cervical range of motion.

[0063] As a preferred technical solution of the present invention, the data recording and analysis module can generate a real-time rehabilitation report, which includes the following contents:

[0064] The time curve of the patient's cervical spine range of motion;

[0065] Changes in angular velocity and acceleration of cervical spine movements;

[0066] Historical records and trend analysis of training difficulty;

[0067] Quantitative assessment score of rehabilitation progress.

[0068] As a preferred technical solution of the present invention, the quantitative assessment score of rehabilitation progress is based on the following formula:

[0069]

[0070] in, is the rehabilitation assessment score, and are the actual and target cervical range of motion, and are the actual and target training time, and is the weight coefficient.

[0071] As a preferred technical solution of the present invention, the virtual reality rehabilitation environment provides a variety of rehabilitation training modes, including but not limited to:

[0072] Static target tracking module: patients track static targets in virtual reality by turning their necks;

[0073] Dynamic obstacle avoidance module: patients avoid moving obstacles in virtual reality through neck movements;

[0074] Scene interaction module: Patients perform various interactive tasks in virtual scenes through neck movements.

[0075] As a preferred technical solution of the present invention, the task feedback in the virtual reality environment is carried out in multiple forms such as vision, hearing and touch. The control algorithm of the task feedback mechanism is:

[0076]

[0077] in, is the feedback strength, , and are the quantified strengths of visual, auditory and tactile feedback, respectively. , , is the weight coefficient of the task feedback mechanism.

[0078] As a preferred technical solution of the present invention, the device also includes:

[0079] Remote monitoring module: used to upload the patient's training data to the cloud for doctors to conduct remote diagnosis and rehabilitation guidance;

[0080] The personalized training generation module automatically adjusts the training plan according to the patient's cervical spine rehabilitation progress and real-time motion data to recommend personalized rehabilitation training plans. The personalized training generation module dynamically generates training tasks that are suitable for the patient's current rehabilitation status by analyzing the patient's historical data and target data.

[0081] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention can detect the multi-dimensional motion data of the patient's cervical spine in real time, including information such as rotation angle, linear acceleration and azimuth, by integrating high-precision sensors such as accelerometers, gyroscopes and magnetometers. By fusing the multi-sensor data through the Kalman filter algorithm, the system can accurately estimate the posture of the patient's cervical spine and ensure accurate synchronization of the patient's actual movements in the virtual reality training environment. This technology effectively solves the problem of inaccurate capture of subtle cervical spine movements in the prior art, and greatly improves the accuracy and effectiveness of rehabilitation training.

[0082] The system of the present invention can dynamically adjust the difficulty and content of training in real time according to the patient's cervical spine rehabilitation progress. The system analyzes the patient's cervical spine range of motion, angular velocity, reaction speed and other data to intelligently generate a personalized rehabilitation training program to ensure the pertinence and adaptability of the rehabilitation task. This function greatly improves the flexibility of the rehabilitation process and solves the problem that the existing system is difficult to adjust training according to the individual needs of patients, thereby improving the effect of rehabilitation training.

[0083] Through virtual reality technology, the system provides patients with an immersive rehabilitation environment and designs a variety of interactive tasks (such as dynamic object tracking, obstacle avoidance, balance maintenance, etc.), which greatly enhances the fun and interactivity of rehabilitation training. Patients can not only actively participate in rehabilitation training, but also obtain training results through real-time visual and auditory feedback. This highly immersive and interactive training experience effectively improves patient compliance, solves the problem of poor patient compliance in traditional rehabilitation methods, helps patients persist in rehabilitation training for a longer period of time, and improves the final rehabilitation effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] Figure 1 This is a structural block diagram of a virtual reality-based cervical vertebra rehabilitation system proposed by the present invention. DETAILED DESCRIPTION

[0085] 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.

[0086] The following is combined with Figure 1 With reference to the accompanying drawings and a number of embodiments, specific embodiments of the present invention are described in detail.

[0087] The present invention provides a cervical vertebra rehabilitation system based on virtual reality, which helps patients to perform cervical vertebra rehabilitation training through the coordinated work of a virtual reality display module, a cervical vertebra motion detection module, a central processing module and a data recording module. The implementation of the system is described in detail below.

[0088] Example 1: Overall system architecture:

[0089] The virtual reality-based cervical vertebra rehabilitation system of the present invention consists of the following main modules:

[0090] Virtual reality display module: A head-mounted virtual reality display (such as a VR headset) is used to provide patients with an immersive virtual rehabilitation environment. By wearing the device, patients can enter the virtual scene and interact with it. The VR headset has built-in visual, auditory, and tactile feedback structures.

[0091] Cervical spine motion detection module: includes accelerometer, gyroscope and magnetometer, which can capture the patient's cervical spine motion in real time and obtain three-dimensional motion data including linear acceleration, angular velocity and orientation.

[0092] Central processing module: processes the cervical spine motion data collected by the sensor, fuses the data through the Kalman filter algorithm, estimates the patient's cervical spine posture (including pitch angle, roll angle and heading angle) in real time, and maps the patient's movements into the virtual reality environment.

[0093] Data recording and analysis module: records the patient's training process, including data such as movement amplitude and frequency, generates rehabilitation reports and provides data support for doctors.

[0094] Specific implementation methods of the virtual reality display module: Head-mounted display device: The virtual reality display module is mainly implemented through a head-mounted display (VR headset).

[0095] Patients wear the device to enter a virtual rehabilitation environment. The virtual scene can include static target tracking, dynamic obstacle avoidance, virtual object interaction and other modes according to different rehabilitation needs.

[0096] Virtual scene generation: Virtual reality scenes are generated through 3D rendering technology, and the patient's neck movement controls the viewing angle and interactive actions. For example, there can be multiple dynamic obstacles in the virtual scene, and the patient needs to turn his head to avoid collision, or need to track the position of virtual objects.

[0097] Real-time feedback: When the patient makes any action in the virtual reality scene, the virtual environment will give real-time feedback.

[0098] Feedback methods include:

[0099] Visual feedback: Patients can see their head movements in the virtual scene, such as target movement, obstacle avoidance, etc.

[0100] Auditory feedback: When the patient completes a task or reaches a specified training goal, the system will provide feedback through sound effects to enhance the training effect.

[0101] Specific implementation of the cervical vertebra motion detection module: Sensor layout: The cervical vertebra motion detection module includes accelerometers, gyroscopes and magnetometers, which can be integrated into a head-mounted display device or a sensor device worn on the neck. They collect real-time movement data of the patient's head and neck, including:

[0102] Accelerometer: Detects the linear acceleration of the neck and is used to calculate the tilt angle of the head.

[0103] Gyroscope: detects the angular velocity of the neck, mainly used to obtain the rotation angle of the head.

[0104] Magnetometer: Provides a directional reference related to the Earth's magnetic field, mainly used to correct the accumulated drift of the rotation angle to ensure the accuracy of the directional data.

[0105] Data acquisition and fusion: The accelerometer data is used to calculate the pitch angle of the cervical spine using the following formula: and roll angle

[0106]

[0107] in, is the pitch angle.

[0108]

[0109] in, is the roll angle.

[0110] The gyroscope data is used to calculate the rotation angle through the integral formula

[0111]

[0112] in, The angular velocity provided by the gyroscope.

[0113] Magnetometer is used to calculate heading angle , the formula is:

[0114]

[0115] in, is the heading angle.

[0116] Specific implementation of the central processing module: Data fusion: The central processing module fuses the data of the accelerometer, gyroscope and magnetometer through the Kalman filter algorithm. Since the data of a single sensor may have noise or drift problems, the Kalman filter can provide more accurate cervical spine posture estimation by dynamically adjusting the data weights of different sensors. The state update formula of the Kalman filter is:

[0117]

[0118] in, is the current state estimation, including the patient's cervical spine posture information, is the sensor data, is the Kalman gain is the measurement matrix.

[0119] Motion mapping in virtual reality: Based on the posture information calculated by the Kalman filter, the central processing module will synchronously map the patient's neck movement into the virtual reality environment. Every angle change will be reflected in the virtual scene in real time, such as changes in perspective or movement of the character.

[0120] Specific implementation of the rehabilitation training control module: Dynamically adjust the training difficulty: The rehabilitation training control module can dynamically adjust the training content according to the patient's actual cervical spine range of motion. The module uses the following formula to adjust the training difficulty:

[0121]

[0122] in, is the updated training difficulty, is the training difficulty of the previous stage, is the patient's current range of motion of the cervical spine, The target range of motion of the cervical spine is 1. When the patient reaches the target range of motion, the training difficulty automatically increases, otherwise it decreases.

[0123] Training task generation: The rehabilitation training module automatically generates training tasks based on the patient's rehabilitation progress and cervical spine range of motion, such as:

[0124] Static target tracking: Patients track a virtual target by turning their neck to improve rotational flexibility of the neck.

[0125] Dynamic obstacle avoidance: Obstacles are set up in the virtual scene, and the patient avoids the obstacles by turning his head, improving the reaction ability and range of motion of the neck.

[0126] Specific implementation methods of the data recording and analysis module: Training data recording: The data recording module will automatically record every movement of the patient in rehabilitation training, including range of motion, angular velocity, number of training sessions and duration, etc.

[0127] Rehabilitation progress assessment: The system generates a rehabilitation report based on the patient's historical data, including the following:

[0128] Changing trends of cervical spine range of motion.

[0129] Record of adjustments to training difficulty.

[0130] Quantitative score of rehabilitation effect. The score is calculated by the following formula:

[0131]

[0132] in, Score the recovery. and is the scoring weight, is the actual training time, is the target time.

[0133] Specific implementation methods of remote monitoring and personalized training modules: Remote monitoring: The system also includes a remote monitoring module, where doctors can view patients' training data in real time through the cloud platform and provide diagnosis and guidance.

[0134] Personalized training generation: The personalized training module automatically adjusts the training plan according to the patient's rehabilitation progress and generates targeted rehabilitation plans to ensure that the training difficulty and content match the patient's actual recovery status.

[0135] Embodiment 2: Based on Embodiment 1, cervical vertebra range of motion training based on virtual reality:

[0136] In this embodiment, the system is used to improve the range of motion of the patient's cervical spine, especially for rehabilitation training of cervical spine rotation flexibility.

[0137] Implementation steps:

[0138] Virtual reality scene setting: The system generates a virtual outdoor scene, such as a forest, grassland, etc. In the scene, multiple static and dynamic virtual objects (such as flying birds, balloons, etc.) are set up. These objects are outside the patient's field of vision and need to be observed and tracked by rotating the neck.

[0139] Motion detection and mapping: The patient wears a head-mounted display, and the system detects the rotation angle of the neck through the cervical spine motion detection module (including accelerometer, gyroscope and magnetometer), and maps the actual movement to virtual reality in real time. For example, when the patient turns his head to the right, the system will synchronously change the perspective so that he can see the virtual object on the right.

[0140] Training goals and feedback: The training goal is to track the positions of all virtual objects by turning the neck. The system will provide real-time feedback based on the patient's head rotation angle and tracking effect, such as visual prompts or sound effects, to remind the patient whether the goal has been achieved.

[0141] Training data recording: During the training process, the system will record the patient's cervical spine range of motion (maximum rotation angle), angular velocity, completion time and other data. These data can help doctors analyze the patient's progress.

[0142] Effect: This training mode is mainly used to improve the patient's cervical rotation range of motion, enhance cervical flexibility and reaction speed.

[0143] Embodiment 3: Based on Embodiment 1, cervical spine extension training based on virtual reality:

[0144] This embodiment is used to train the patient's cervical spine extension ability, especially for the rehabilitation training of neck flexion and backward extension.

[0145] Implementation steps:

[0146] Virtual scene generation: The system generates a virtual street scene with multiple virtual objects (such as virtual vehicles or obstacles) approaching the patient. The patient needs to avoid these obstacles by extending the neck (flexing forward and leaning back).

[0147] Motion detection and posture estimation: The patient wears a head-mounted display device, and the cervical motion detection module collects the angle data of the neck flexion and backward in real time. Through the accelerometer and gyroscope, the system can calculate the patient's pitch angle and correspond it to the tasks in the virtual scene. For example, when the patient flexes his neck forward, the system calculates the pitch angle through the accelerometer and makes corresponding movements in the virtual scene.

[0148] Dynamic tasks and feedback: The speed and frequency of virtual obstacles will gradually increase, and patients need to react quickly and avoid obstacles by extending their necks. The system adjusts the difficulty of the task in real time based on the patient's success rate and movement accuracy, and provides visual or audio feedback.

[0149] Training data and evaluation: After each training session, the system will record the patient's pitch angle change range, reaction time, task completion rate and other data, and generate a detailed rehabilitation progress report to help doctors evaluate the training effect.

[0150] Effect: This training mode can effectively enhance the patient's cervical flexion and backward movement ability, and improve the stretchability and flexibility of the neck.

[0151] Embodiment 4: Based on Embodiment 1, cervical vertebra stability training based on virtual reality:

[0152] This embodiment is suitable for restoring cervical stability of patients, especially for patients with neck discomfort, to help them improve their control and endurance.

[0153] Implementation steps: Virtual scene design: The system generates a virtual balance scene, such as a suspended virtual platform, and the patient needs to stabilize the neck posture to maintain the balance of the virtual object. In the scene, the patient's field of vision will be disturbed by external disturbances (such as wind blowing, platform shaking), and the patient needs to restore the stability of the field of vision through fine-tuning of the neck.

[0154] Cervical motion detection and mapping: The system monitors the patient's neck movements in real time through the cervical motion detection module. The gyroscope detects the patient's angular velocity, and the central processing module processes this data through the Kalman filter algorithm, calculates the posture changes of the cervical spine, and adjusts the balance state of the virtual platform.

[0155] Training goals and feedback: The training goal is to maintain the balance of the virtual object by keeping the cervical spine stable. The system will prompt the patient through visual or sound effects whether the virtual platform has been successfully stabilized, and provide feedback based on the patient's neck adjustment movements. For example, when the patient's neck posture exceeds the stable range, the virtual object will deviate from the balanced state.

[0156] Data analysis: The system records the patient's cervical spine posture changes, stabilization time, and disturbance recovery speed during training, and generates a rehabilitation report to help doctors evaluate the control and endurance of the cervical spine.

[0157] Effect: This training mode helps to improve the patient's cervical stability and enhance neck control. It is suitable for patients after cervical surgery or with chronic cervical diseases.

[0158] Embodiment 5: Based on Embodiment 1, comprehensive cervical vertebra rehabilitation training based on virtual reality:

[0159] This embodiment is suitable for comprehensive cervical rehabilitation training, combining multiple functions of cervical range of motion, stretching and stability training.

[0160] Implementation steps: Virtual scene design: The system designs a complex virtual environment, and the scene includes multiple tasks, such as tracking objects, avoiding obstacles, maintaining posture stability, etc. Patients need to complete these tasks through different movements of the cervical spine.

[0161] Motion detection and feedback: The system uses the cervical motion detection module to monitor the patient's various cervical spine movements in real time, including rotation, flexion, backward movement, and tilt. The central processing module calculates the patient's cervical spine posture by fusing sensor data and maps these postures with tasks in the virtual scene in real time.

[0162] Personalized training plan: According to the patient's rehabilitation needs, the system can automatically generate a personalized training plan. For example:

[0163] For patients with limited cervical spine range of motion, the system prioritizes rotation and tilt tasks.

[0164] For patients with insufficient cervical spine stability, the system provides more balance tasks.

[0165] Training evaluation and feedback: The system provides instant feedback based on the patient's performance in the virtual scene and records detailed training data (such as cervical spine angle, movement completion rate, task completion time, etc.). These data will be used to generate rehabilitation progress reports for doctors' reference.

[0166] Effect: This embodiment combines multiple rehabilitation functions, is suitable for patients at different rehabilitation stages, and can comprehensively improve the flexibility, control, and endurance of the cervical spine.

[0167] Example 6: Based on Example 1, remote virtual reality cervical vertebra rehabilitation training:

[0168] This embodiment is aimed at remote rehabilitation training scenarios, and doctors can provide rehabilitation guidance to patients through a remote monitoring system.

[0169] Implementation steps: Patient-side equipment: The patient wears a head-mounted display at home and connects to the remote rehabilitation system via the Internet. The system collects the patient's real-time motion data through the cervical spine motion detection module and uploads it to the cloud platform.

[0170] Remote monitoring and training guidance: Doctors can view the patient's training data and cervical spine movement performance in real time through the remote monitoring module, and adjust the training plan for the patient based on this data. For example, doctors can modify the training tasks in the virtual scene in real time during the patient's rehabilitation process to increase or decrease the difficulty.

[0171] Data synchronization and feedback: All training data (such as cervical spine range of motion, task completion status) will be synchronized to the cloud in real time for doctors and patients to view together. Patients will also receive instant feedback from the system during training to improve training results.

[0172] Effect: Remote rehabilitation training enables patients to receive effective rehabilitation training at home. Doctors can adjust patients’ training plans in a timely manner through remote monitoring to ensure the effectiveness and continuity of rehabilitation.

[0173] The contents not described in detail in this specification belong to the prior art known to professional and technical personnel in the field. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A cervical vertebra rehabilitation system based on virtual reality, characterized in that: include: Virtual reality display module: used to display the virtual rehabilitation training environment; Cervical vertebra motion detection module: comprising at least one inertial sensor, wherein the inertial sensor is used to detect the motion data of the patient's neck, including angle, acceleration and rotation speed parameters; The inertial sensor includes an accelerometer module, a gyroscope module and a magnetometer module, and the cervical vertebra motion detection module includes: Accelerometer module: used to detect the linear acceleration of the patient's neck; a(t)=[a x ,a y ,a z ] where a x 、a y and a z are the acceleration components of the accelerometer in the X, Y, and Z directions respectively. The pitch angle α(t) and roll angle β(t) of the patient's cervical spine are calculated by the following formula: Where α(t) is the pitch angle of the patient’s cervical spine; Where β(t) is the roll angle of the patient’s cervical spine; Gyroscope module: used to detect the angular velocity ω(t) of the patient's neck, where ω(t) = [ω x ,ω y ,ω z ] represents the components of angular velocity in three directions. The rotation angle θ(t) is obtained by integrating the angular velocity over time. The formula is: Among them, θ(t) is the rotation angle of the patient's neck at time t, ω(t) is the angular velocity of the gyroscope at time t, and θ(t0) is the rotation angle at the initial time; Magnetometer module: used to detect the position data of the patient's neck relative to the earth's magnetic field m(t) = [m x , m y , m z ], where m x 、m y 、m z is the magnetic field component of the magnetometer in the X, Y, and Z directions. The heading angle γ(t) is calculated by the following formula: Where, Y(t) is the heading angle of the patient’s cervical spine; Central processing module: used to receive and process the motion data obtained by the cervical motion detection module, and calculate the patient's cervical motion state through a preset algorithm; the central processing module fuses the data from the accelerometer, gyroscope and magnetometer through the Kalman filter algorithm to obtain the patient's cervical posture estimation. The state update formula of the Kalman filter is: in: is the state estimate at the current time k, including the pitch angle, roll angle and heading angle of the attitude information; z k are the measurements of the accelerometer, gyroscope, and magnetometer; H is the measurement matrix: used to map the state vector to the observation space; Kk is the Kalman gain: used to dynamically adjust the weight between the measurement value and the state estimation; Rehabilitation training control module: adjusts the rehabilitation training content in the virtual reality environment based on the analysis results of the central processing module and provides real-time feedback to the patient; the rehabilitation training control module dynamically adjusts the training content according to the range of motion of the cervical spine, and its adjustment algorithm includes the following steps: Set target cervical range of motion R target ; According to the actual detected cervical vertebrae motion range R actual , determine whether the goal is achieved: If R actual ≥R target , then increase the difficulty of training; If R actual <R target , then maintain or reduce the training difficulty; The training difficulty adjustment formula is: Among them, D new is the updated training difficulty, D old is the training difficulty of the previous stage, R actual is the actual cervical spine motion range, R target The target cervical range of motion; Data recording and analysis module: used to record the patient's training data and generate rehabilitation assessment reports.

2. A cervical vertebra rehabilitation system based on virtual reality according to claim 1, characterized in that: The virtual reality display module includes a head-mounted display, and the head-mounted display works in conjunction with the cervical vertebrae motion detection module to achieve synchronous presentation of the patient's motion in a virtual reality environment.

3. The virtual reality-based cervical vertebra rehabilitation system according to claim 1, characterized in that: The data recording and analysis module is capable of generating a real-time rehabilitation report, which includes the following: The time curve of the patient's cervical spine range of motion; Changes in angular velocity and acceleration of cervical spine movements; Historical records and trend analysis of training difficulty; Quantitative assessment score of rehabilitation progress.

4. The virtual reality-based cervical vertebra rehabilitation system according to claim 3, characterized in that: The quantitative assessment score of rehabilitation progress is based on the following formula: Among them, S is the rehabilitation assessment score, R actual and R target are the actual and target cervical range of motion, T actual and T target are the actual and target training times respectively, and α and β are weight coefficients.

5. The virtual reality-based cervical vertebra rehabilitation system according to claim 1, characterized in that: The virtual reality rehabilitation environment provides a variety of rehabilitation training modes, including but not limited to: Static target tracking module: patients track static targets in virtual reality by turning their necks; Dynamic obstacle avoidance module: patients avoid moving obstacles in virtual reality through neck movements; Scene interaction module: Patients perform various interactive tasks in virtual scenes through neck movements.

6. The virtual reality-based cervical vertebra rehabilitation system according to claim 2, characterized in that: The task feedback in the virtual reality environment is carried out in multiple forms such as vision, hearing and touch. The control algorithm of the task feedback is: F feedback =w1V visual +w2A audio +w3T tactile Among them, F feedback is the feedback strength, V visual , A audio and T tactile are the quantitative strengths of visual, auditory and tactile feedback respectively, and w1, w2, w3 are the weight coefficients of task feedback.

7. The virtual reality-based cervical vertebra rehabilitation system according to claim 1, characterized in that: The system further comprises: Remote monitoring module: used to upload the patient’s training data to the cloud; Personalized training generation module: automatically adjusts the training plan according to the patient's cervical spine rehabilitation progress and real-time motion data to recommend personalized rehabilitation training plans. The personalized training generation module dynamically generates training tasks that are suitable for the patient's current rehabilitation status by analyzing the patient's historical data and target data.

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