Sofa-based assisted motion method and apparatus, electronic device, and storage medium

Abstract

The embodiment of the application discloses a sofa-based auxiliary movement method and device, electronic equipment and storage medium, which are applied to a sofa. The armrest area and the backrest area of the sofa are provided with a mechanical arm. The end of the mechanical arm is provided with a fixing device. The fixing device is used for fixing the legs or hands of a user. The armrest area of the sofa is provided with a joint detection device. The method comprises the following steps: acquiring data collected by the joint detection device to obtain a joint detection result of the user. The joint detection result is used for indicating the joint injury condition of the user. Corresponding instructions are generated according to the joint detection result. The mechanical arm is controlled to drive the legs or hands of the user to move according to the instructions. According to the embodiment of the application, the sofa can assist the user in movement according to the joint injury condition, and the effect and efficiency of rehabilitation are improved.

Description

Technical Field

[0001] This application relates to the field of sofa technology, and more particularly to a sofa-based auxiliary movement method, device, electronic device, and storage medium. Background Technology

[0002] In modern society, the number of people suffering from joint injuries is constantly increasing due to various reasons, including accidents, sports injuries, and chronic diseases. These joint problems cause numerous inconveniences in daily life, especially severely limiting independent movement. For this group, there is an urgent need for a safe and effective assistive exercise method to help them engage in appropriate physical activity and promote joint rehabilitation. Currently, rehabilitation equipment and assistive tools mainly focus on professional medical devices and fitness equipment, while developing assistive movement functions for common household furniture such as sofas is a key technical problem that urgently needs to be solved. Summary of the Invention

[0003] This application discloses a sofa-based assistive movement method, device, electronic device, and storage medium. It can assist movement based on the user's joint injury condition. Compared with traditional rehabilitation equipment, the sofa reduces pressure and discomfort on the joints during movement, lowers the risk of pain and secondary injury, thereby improving the effectiveness and efficiency of rehabilitation.

[0004] The first aspect of this application discloses a sofa-based assisted movement method applied to a sofa. The sofa has robotic arms installed in its armrest and backrest areas, with a fixing device at the end of each robotic arm for securing a user's legs or hands. A joint detection device is installed in the armrest area of ​​the sofa. The method includes:

[0005] The joint detection device collects data to obtain the user's joint detection results, which are used to indicate the user's joint damage status.

[0006] Generate corresponding instructions based on the joint detection results;

[0007] The instructions control the robotic arm to move the user's legs or hands.

[0008] As an optional implementation, in a first aspect of this embodiment, obtaining the data collected by the joint detection device to obtain the user's joint detection results includes:

[0009] The data collected by the joint detection device is input into the algorithm model to obtain the user's joint detection results. The data collected by the joint detection device includes data collected by the camera and sensors.

[0010] As an optional implementation, in the first aspect of this embodiment, generating corresponding instructions based on the joint detection results includes:

[0011] Based on the user's joint injury condition, instructions are generated to control the movement mode of the robotic arm corresponding to the joint injury condition. The robotic arm movement mode includes active movement mode, assisted movement mode and passive movement mode.

[0012] The robotic arm has pre-stored parameters corresponding to different motion modes, and the parameters include at least the angle, amplitude, and speed of the robotic arm's flexion and extension.

[0013] As an optional implementation, in a first aspect of this embodiment, the instruction to generate a motion mode for the control robotic arm corresponding to the user's joint injury includes:

[0014] If the user's joint is detected to be in a level one injury, the movement mode of the robotic arm is controlled to be active movement mode;

[0015] If a user's joint is detected to have a level two injury, the movement mode of the robotic arm is controlled to be an assisted movement mode.

[0016] If a user's joint is detected to have a level 3 injury, the movement mode of the robotic arm is controlled to be a passive movement mode.

[0017] The corresponding operation is performed according to the movement pattern of the robotic arm.

[0018] As an optional implementation, in the first aspect of this embodiment, performing the corresponding operation according to the motion mode of the robotic arm includes:

[0019] The motion trajectory of the robotic arm is planned according to the motion pattern of the robotic arm, and the motion trajectory is used to indicate the joint movement path of the user.

[0020] The parameters corresponding to the motion mode are adjusted according to the motion mode of the robotic arm.

[0021] As an optional implementation, in a first aspect of this embodiment, controlling the robotic arm to move the user's legs or hands according to the instructions includes:

[0022] Obtain the user's physiological index data during exercise;

[0023] The movement mode of the robotic arm is adjusted in real time based on the physiological index data.

[0024] As an optional implementation, in the first aspect of this embodiment, the method further includes:

[0025] When an abnormality in the user's physiological indicators is detected during exercise, an emergency mode is activated. The emergency mode includes an alarm function and an emergency stop function.

[0026] A second aspect of this application discloses a sofa-based assistive movement device, the device comprising:

[0027] The data acquisition module is used to acquire data collected by the joint detection device and obtain the user's joint detection results, which are used to indicate the user's joint damage status.

[0028] The instruction control module is used to generate corresponding instructions based on the joint detection results, and control the robotic arm to move the user's legs or hands according to the instructions.

[0029] A third aspect of this application discloses an electronic device, including a memory and a processor. The memory stores a computer program, and when the computer program is executed by the processor, the processor performs the method described above.

[0030] The fourth aspect of this application discloses a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described above.

[0031] Compared with related technologies, the embodiments of this application have at least the following beneficial effects:

[0032] The sofa can acquire data from joint detection devices, obtain the user's joint detection results, and generate corresponding instructions based on these results to control a robotic arm to move the user's legs or hands. Compared to traditional rehabilitation equipment, the sofa can assist movement based on the user's joint injury condition, reduce pressure and discomfort on the joints during movement, lower the risk of pain and secondary injury, and thus improve the effectiveness and efficiency of rehabilitation. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0034] Figure 1 This is an application scenario diagram of a sofa-based assisted movement method in one embodiment;

[0035] Figure 2 This is a flowchart illustrating a sofa-based assisted movement method in one embodiment;

[0036] Figure 3 This is a structural schematic diagram of a sofa in one embodiment;

[0037] Figure 4 This is a schematic diagram of a sofa-based assisted motion monitoring process in one embodiment;

[0038] Figure 5 This is a block diagram of a sofa-based assistive motion device in one embodiment;

[0039] Figure 6 This is a structural block diagram of an electronic device in one embodiment. Detailed Implementation

[0040] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0041] To facilitate a clear description of the technical solutions in the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish identical or similar items with essentially the same function and effect. For example, "first instruction" and "second instruction" are used to distinguish different user instructions and do not limit their order. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and the terms "first" and "second" are not necessarily different.

[0042] It should be noted that, in this application, the words "exemplarily" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "exemplarily" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of words such as "exemplarily" or "for example" is intended to present the relevant concepts in a specific manner.

[0043] Furthermore, "at least one" refers to one or more, while "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, and c can mean: a, or b, or c, or a and b, or a and c, or b and c, or a, b, and c, where a, b, and c can be single or multiple.

[0044] Furthermore, the terms "comprising" and "having," and any variations thereof, in the embodiments and drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the steps or units listed, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0045] With the increasing aging of the global population, more and more elderly people are facing health problems such as joint diseases and muscle atrophy, requiring rehabilitation training to maintain physical function. In addition, modern lifestyles and work habits have led to a continuous increase in the incidence of sports injuries. For example, people who sit for long periods and lack exercise are prone to muscle strains and joint sprains when suddenly engaging in strenuous exercise. For these patients with joint injuries, timely and effective rehabilitation training is crucial. However, traditional rehabilitation equipment is usually large and heavy, making it inconvenient to carry and move, which is a significant limitation for patients who need to perform rehabilitation training at home. Moreover, traditional rehabilitation equipment often uses standardized designs, making it difficult to meet the personalized needs of different users. Sofas, as a common type of furniture, are usually placed in homes and offices, offering high portability and accessibility. However, the development of motion-assisting functions for common household furniture such as sofas remains a key technological problem that urgently needs to be solved.

[0046] This application discloses a sofa-based assisted movement method, device, electronic device, and storage medium. Compared with traditional rehabilitation equipment, the sofa can assist movement according to the user's joint injury condition, reduce pressure and discomfort on the joints during movement, lower the risk of pain and secondary injury, thereby improving the effectiveness and efficiency of rehabilitation. Detailed descriptions follow.

[0047] Please see Figure 1 , Figure 1This is an application scenario diagram of a sofa-based assisted motion method in one embodiment, such as... Figure 1 As shown, the application scenario may include a joint detection device 10, a sofa 20, and a robotic arm 30. The joint detection device 10 may be installed in the armrest area of ​​the sofa 20 or in the area of ​​the sofa where the legs are placed. The robotic arm 30 may be installed in the armrest area and backrest area of ​​the sofa 20. The joint detection device 10 establishes a communication connection with the sofa 20, and the sofa 20 establishes a communication connection with the robotic arm 30.

[0048] In this embodiment, the joint detection device 10 includes a camera 101 and sensors 102. The camera 101 is used to capture the user's body posture and movements on the sofa. It can capture the position of the joints, movement trajectory, and overall posture changes of the body. By analyzing the captured images, the range of motion of the user's joints can be accurately determined. In addition, the image data collected by the camera 101 can be combined with image recognition technology to evaluate the appearance of the joints. If swelling, deformation, or abnormal color appears in the joint area, it indicates that the user's joint is damaged. The sensor 102 may include, but is not limited to, pressure sensors, gyroscope sensors, and electromyography sensors, used to monitor leg movements and force input, thereby obtaining the stability and coordination of leg movements through monitoring data analysis. In this application scenario, different types of sensors can be distributed in different locations to better detect the user's joint status and determine the extent of damage. In some embodiments, pressure sensors are mainly distributed in the parts of the sofa that come into contact with the user's body, such as the seat surface, backrest, and armrests. These locations can directly sense the weight and pressure distribution of the user's body, thereby inferring the amount of pressure borne by different joints. For example, pressure sensors on the seat surface can detect the pressure of the user's buttocks and thighs on the sofa, reflecting the stress on the hip and knee joints; pressure sensors on the backrest can sense the pressure when the user's back contacts the sofa, which helps to analyze the condition of the spinal joints. When the joints are damaged, the pressure distribution may be abnormal, providing a reference for judging the condition of joint damage.

[0049] In some embodiments, gyroscope sensors can sense the rotation angle and angular velocity of joints. For joints requiring rotational movement, such as the shoulder and hip joints, gyroscope sensors can accurately detect their motion state and determine whether damage exists. For example, gyroscope sensors can be integrated into the armrest area of ​​a sofa to detect the rotation angle and angular velocity of the user's arm joints, determining the motion state of the shoulder and elbow joints. Electromyography (EMG) sensors, on the other hand, can detect the electrical activity of muscles. When a joint is damaged, the electrical activity of the surrounding muscles also changes. By analyzing EMG signals, the contraction state and fatigue level of muscles can be understood, indirectly reflecting the health status of the joint. EMG sensors can be placed in locations with close contact with the user's muscles. For example, an adjustable EMG sensor band can be installed on the armrest of a sofa. When using the sofa, the user can place their arm on the armrest, bringing the EMG sensor close to the arm muscles. This allows for the detection of the electrical activity of the arm muscles, and further analysis of the state of the muscles around the elbow and shoulder joints, providing a basis for determining the extent of damage to these joints.

[0050] The sofa 20 may include, but is not limited to, a processor, a communication module, a display screen, a speaker, and a microphone. The processor of the sofa 20 can process and analyze the data collected by the joint detection device 10 to obtain the user's joint detection results, and generate corresponding instructions based on the joint detection results to control the state of the robotic arm. It can also adjust the movement mode of the robotic arm in real time based on the user's physiological index data during movement. The functionality of the processor is not limited in this embodiment.

[0051] The communication module of sofa 20 can receive data collected by joint detection device 10 and send generated control commands to robotic arm 30. The communication module may include a wireless communication module and a wired communication module. The wireless communication module may include, but is not limited to, Bluetooth Low Energy (BLE) modules, Wireless Fidelity (Wi-Fi) modules, cellular modules, Low Power Wide Area Network (LPWAN) modules, ZigBee modules, etc. Cellular modules may include, but are not limited to, 4G and 5G technologies. The wired communication module may include, but is not limited to, wired interfaces such as RS485 (Recommended Standard 485) and Ethernet interfaces.

[0052] The display screen shows the user's joint detection results and can also be used to set and adjust various parameters of the sofa 20 and robotic arm 30, as well as display the system's operation interface and status information. Users can personalize the functions of the sofa 20 through the display screen, such as adjusting the movement force of the robotic arm 30 and selecting different joint detection points. Simultaneously, the display screen can also show the real-time working status of the sofa 20, such as whether the joint detection device 10 is operating normally and the current status of the robotic arm 30, allowing users to easily monitor the sofa's usage.

[0053] The speaker of sofa 20 can be used to play audio data such as music and sound prompts. For example, when the user starts using sofa 20, the speaker can play a welcome message and instructions; during assisted exercise, the speaker can remind the user of precautions, exercise progress, and goals, and can also play soft, soothing music to help the user relax. The microphone of sofa 20 can be used to collect the user's audio data. For example, the user can issue voice commands to sofa 20 through the microphone to adjust the intensity of the robotic arm 30's movement or select a specific exercise mode. The user can also control the start and stop of the robotic arm through voice commands.

[0054] The robotic arm 30 includes a main body and a fixing device mounted at the end of the robotic arm 30 for securing the user's legs or hands. The main body of the robotic arm 30 consists of a series of connectors, links, and actuators. The connectors allow the robotic arm to rotate and move in multiple degrees of freedom. These connectors can employ different driving methods, such as motor-driven, hydraulic-driven, or pneumatic-driven, with common actuators including motors, hydraulic pumps, and pneumatic motors. The fixing device can be a flexible gripper or hold for securing the user's body parts, such as arms or legs. The fixing device can also be equipped with sensors to detect the user's physiological indicators, such as blood pressure and heart rate sensors, to monitor the user's blood pressure, heart rate, and other physiological indicators in real time during movement.

[0055] The sofa 20 acquires data collected by the joint detection device 10 to obtain the user's joint detection results. The joint detection results are used to indicate the user's joint damage. The sofa 20 generates corresponding instructions based on the joint detection results and controls the robotic arm 30 to move the user's legs or hands according to the instructions.

[0056] Please see Figure 2 , Figure 2 This is a flowchart illustrating a sofa-based assisted motion method in one embodiment. This method can be applied to, for example... Figure 1 Sofa 20 in the application scenario shown, such as Figure 2 As shown, the method may include the following steps:

[0057] Step 201: Obtain the data collected by the joint detection device to obtain the user's joint detection results, which are used to indicate the user's joint damage status.

[0058] In some embodiments, data collected by the joint detection device can be input into an algorithm model, such as a neural network model, to obtain the user's joint detection results. The data collected by the joint detection device includes data collected by a camera and sensors. The sofa can perform noise reduction, enhancement, and cropping on the images captured by the camera. For example, it can remove noise points from the image, enhance the contrast and brightness of the image, and crop the image area containing the joints to improve image quality and highlight key information. It can also perform calibration and filtering on the sensor data to remove noise and outliers. Sensors may include pressure sensors, gyroscope sensors, electromyography (EMG) sensors, etc. These sensors can be installed in the armrest area of ​​the sofa or integrated into the area of ​​wearable devices that contact the joints, such as smart knee braces, wristbands, and sports watches.

[0059] In this embodiment, the degree of joint damage can be obtained by acquiring different feature data from sensors and cameras. This feature data can be fused, for example, using weighted averaging or feature stitching, to obtain a feature data vector. This feature data vector is then input into a preset algorithm model to obtain the degree of joint damage. In practice, the sofa can fuse multi-source data from pressure sensors, gyroscopes, electromyography (EMG) sensors, and cameras. Weighted averaging and feature stitching methods can be used to integrate different types of data into a unified feature vector for processing by the algorithm model. For example, the pressure value detected by the pressure sensor, the motion angle measured by the gyroscope, the muscle electrical activity signal acquired by the EMG sensor, and the joint image features captured by the camera can be fused. Key features can then be extracted from the fused data, including statistical features of the sensor data such as mean, variance, and peak value, texture features of the image, and spatiotemporal features of joint movement. For example, frequency features of muscle activity can be extracted from EMG sensor data, shape and contour features of the joint can be extracted from camera images, and angular velocity and acceleration features of joint movement can be extracted from gyroscope sensor data. The algorithm model is then trained using a large amount of labeled joint state data, allowing it to learn the relationship between different features and joint states. The trained model can then predict the user's joint state based on newly input sensor data and camera images, determining whether damage exists and the degree and type of damage. For example, deep learning algorithms, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), can automatically classify the fused features to determine whether the joint is normal, has mild, moderate, or severe damage.

[0060] Step 202: Generate corresponding instructions based on the joint detection results.

[0061] In this embodiment, the sofa generates instructions for controlling the movement mode of the robotic arm according to the user's joint injury condition. The robotic arm movement mode includes an active movement mode, an assisted movement mode, and a passive movement mode. For example, if the user's joint is detected to be in a level one injury, the robotic arm is controlled in an active movement mode; if the user's joint is detected to be in a level two injury, the robotic arm is controlled in an assisted movement mode; and if the user's joint is detected to be in a level three injury, the robotic arm is controlled in a passive movement mode.

[0062] In some embodiments, when the sofa detects a Grade 1 injury to a user's joint, indicating that the injury is minor or nonexistent and the user has strong voluntary movement ability, the sofa controls the robotic arm to enter active movement mode. In this mode, the robotic arm primarily plays an assistive and guiding role, allowing the user to perform voluntary movements more easily. For example, when the user performs arm extension exercises, the robotic arm follows the user's movements, providing slight resistance or assistance to help the user better exercise muscles and restore joint function. Active movement mode can fully mobilize the user's own muscle strength and motivation, promote blood circulation and synovial fluid flow, and accelerate the rehabilitation process.

[0063] If the sofa determines that the user's joint is at level two, it means the joint damage is moderate and the user's ability to move independently is somewhat limited. In this case, the robotic arm enters assisted movement mode. In assisted movement mode, the robotic arm provides a greater degree of assistance to help the user complete some more difficult movements. For example, when the user lifts their leg, the robotic arm provides a certain upward push to reduce the burden on the user's leg muscles, while guiding the user's joint to move correctly. Assisted movement mode can help users perform moderate exercise when their own strength is insufficient, preventing muscle atrophy and joint stiffness caused by prolonged inactivity.

[0064] When the sofa detects a grade three injury to a user's joint, it indicates that the injury is very severe, and the user has almost lost the ability to move independently. At this point, the robotic arm enters passive motion mode. In passive motion mode, the robotic arm completely controls the movement, and the user does not need to exert any effort. The robotic arm will slowly and rhythmically move the user's joints according to a preset program and parameters. For example, the robotic arm can gently lift the user's arm and then lower it, repeating this process to maintain the flexibility of the user's joints.

[0065] Step 203: Control the robotic arm to move the user's legs or hands according to the instructions.

[0066] In this embodiment, after determining the user's joint injury, the sofa generates corresponding control commands and sends them to the robotic arm via a communication module. Upon receiving the commands, the robotic arm adjusts its movement mode and parameters to adapt to the user's joint injury. As an optional implementation, the user, aware of the extent of their joint injury, can choose the robotic arm's movement mode independently. For example, they can send control commands to the sofa or robotic arm via a control panel (display screen) on the sofa, control buttons on a remote control, or an application on an electronic device.

[0067] After the robotic arm's end effector secures the user's hand or leg, it activates a motion mode based on received commands, enabling the user's joints to move, such as extending, bending, and rotating. In some embodiments, robotic arms can be installed on the armrests and backrest of the sofa, using multiple robotic arms to simultaneously provide motion assistance to different joints or body parts of the user. For example, one robotic arm assists the user's leg movements, while another assists the user's hand movements. Multiple robotic arms can be coordinated through a collaborative control algorithm to ensure their movements cooperate without conflict. For instance, when the user performs a full-body exercise, the leg and hand robotic arms can synchronize according to the user's rhythm and intensity, or adjust the motion state of each robotic arm according to the user's needs.

[0068] In other embodiments, users can wear virtual reality devices to enter a specially designed virtual environment for rehabilitation training. The sofa and robotic arm can communicate with the virtual reality device via wireless communication methods such as Bluetooth and Wi-Fi, without specific limitations. The sofa can send detected joint injuries to the virtual reality device, which can then adjust the difficulty of training in the virtual environment based on this information. Furthermore, the sofa can generate control commands based on the user's movements and joint status in the virtual environment to control the robotic arm's movement mode. For example, when a user is performing mountain climbing training in the virtual environment, if the joint detection device detects increased fatigue or injury in the user's leg joints, the sofa can adjust the command to switch the robotic arm from active movement mode to assisted movement mode.

[0069] Using the above embodiments, the sofa can acquire data collected by the joint detection device, obtain the user's joint detection results, and generate corresponding instructions based on the joint detection results to control the robotic arm to move the user's legs or hands. Compared with traditional rehabilitation equipment, the sofa can assist in movement according to the user's joint injury condition, reduce pressure and discomfort on the joints during the user's movement, reduce pain and the risk of secondary injury, thereby improving the effectiveness and efficiency of rehabilitation.

[0070] Please see Figure 3 , Figure 3 This is a schematic diagram of the sofa structure in one embodiment. When the sofa detects user use, the camera and sensors in the joint detection device will automatically activate to detect the user's joint damage. The sofa can then broadcast voice prompts to the user via a speaker. After acquiring the user's joint detection results, the sofa can generate instructions to control the robotic arm's movement mode according to the user's joint damage condition. For example, if the user's joint is detected as having a level one injury, the robotic arm's movement mode is active; if the user's joint is detected as having a level two injury, the robotic arm's movement mode is assisted; and if the user's joint is detected as having a level three injury, the robotic arm's movement mode is passive. Specific implementation details are not elaborated here. It should be noted that once the robotic arm's movement mode is determined, the sofa performs corresponding operations based on the movement mode. For example, it plans the robotic arm's movement trajectory based on the movement mode, and the movement trajectory is used to indicate the user's joint movement path. Furthermore, the robotic arm pre-stores parameters corresponding to different movement modes, including at least the angle, amplitude, and speed of the robotic arm's flexion and extension. The sofa will adjust the parameters corresponding to the movement mode based on the robotic arm's movement mode.

[0071] In some embodiments, the sofa can determine the start and end points of the joint movement path based on the current position of the joint and the desired target position, thereby planning the motion trajectory of the robotic arm. For example, for elbow joint injuries, the start point could be the maximum degree of joint flexion, and the end point could be the straightened position. The purpose of planning the robotic arm's motion trajectory is to ensure that the motion trajectory is within the safe range of motion of the joint, avoiding secondary injuries caused by overextension or flexion. The flexion and extension angles, amplitudes, and speeds of the robotic arm can correspond to its movement mode and the user's joint injury condition. For example, if the user's joint is in a grade I injury, the corresponding robotic arm movement mode is active movement mode, where the flexion and extension angles and amplitudes can be set to 80%-90% of the normal joint range of motion, and the movement speed can be set to 80%-90% of the normal speed. The movement speed can be determined based on the number of times the robotic arm can repeatedly perform flexion and extension movements within a specific time. If the user's joint is in a grade II injury, the user's joint range of motion may be somewhat limited, and the corresponding robotic arm movement mode is assisted movement mode, where the flexion and extension angles and amplitudes can be set to 70%-80% of the normal joint range of motion, and the movement speed can be set to 70%-80% of the normal speed. If the user's joint is in a grade III injury, the corresponding robotic arm movement mode is passive movement mode, where the flexion and extension angles and amplitudes can be set to 60%-70% of the normal joint range of motion, and the movement speed can be set to 60%-70% of the normal speed.

[0072] Using the above embodiments, the sofa can plan a specific motion trajectory according to the movement pattern of the robotic arm, and control the flexion and extension angle, amplitude, and speed of the robotic arm, so that it is within a safe range according to the user's joint injury, which can better meet the user's specific needs and improve the effect of rehabilitation or exercise.

[0073] In one embodiment, the sofa includes a motion monitoring system to monitor for any abnormalities that may occur during the user's movement, such as... Figure 4 As shown, Figure 4 This is a schematic diagram of a sofa-based assisted motion monitoring process in one embodiment. During the process of the robotic arm moving the user's hand or leg, the motion monitoring system acquires and monitors the user's physiological index data in real time, and adjusts the movement mode of the robotic arm in real time based on the physiological index data.

[0074] In some embodiments, the motion monitoring system can acquire physiological data of the user during the movement driven by the robotic arm through various sensors, such as heart rate sensors, blood pressure sensors, blood oxygen saturation sensors, and electromyography sensors. These sensors can be arranged on the wearable device or on the fixing device of the robotic arm. The wearable device and the robotic arm can establish a communication connection with the sofa, enabling the motion monitoring system to acquire and monitor the user's physiological data in real time. The physiological data can reflect the user's physical load and tolerance during exercise. If the system detects an upward trend in the user's heart rate, blood pressure, or other physiological indicators, or if the user experiences discomfort such as muscle fatigue or pain, the motion monitoring system can promptly adjust the robotic arm's movement mode, trajectory, and parameters to reduce the intensity and speed of the movement. Alternatively, it can play voice prompts to the user, asking if they want to stop exercising, and perform corresponding operations based on the user's feedback to ensure user safety.

[0075] In this embodiment, when the exercise monitoring system detects abnormal physiological data during exercise, an emergency mode is activated. The emergency mode includes an alarm function and an emergency stop function. As an optional implementation, the emergency mode is triggered when the exercise monitoring system detects that the user's physiological data exceeds the normal threshold range. For example, for heart rate, values ​​above a specific value (e.g., 150 beats per minute) or below a specific value (e.g., 40 beats per minute) can be set as abnormal; for blood pressure, systolic blood pressure above 180 mmHg or diastolic blood pressure above 110 mmHg can be set as abnormal; for blood oxygen saturation, values ​​below a specific value (e.g., 90%) can be set as abnormal, etc. The exercise monitoring system continuously monitors various physiological data during user exercise and updates the data at a certain frequency (e.g., once per second or higher) to promptly detect abnormalities. Furthermore, the exercise monitoring system can combine multiple physiological data for comprehensive judgment to improve accuracy.

[0076] In some embodiments, when the motion monitoring system detects abnormal physiological data of the user, the system immediately triggers an alarm function. Alarm methods may include sound alarms, light alarms, and vibration alarms. Sound alarms may involve the sofa emitting a loud beep or a voice prompt through its speakers; light alarms may involve a flashing red light or an indicator light of a specific color; vibration alarms may involve a vibration signal emitted by a device in contact with the user. Additionally, the sofa can automatically send information about abnormal physiological data to relevant personnel so that timely rescue actions can be taken. Besides the alarm function, the system will also activate an emergency stop function to immediately halt the movement of the robotic arm. This prevents further injury to the user, especially when the user is experiencing abnormal physical conditions, avoiding further strain on their body. The stop function can be implemented through software control, such as sending a stop command to the robotic arm via a terminal device, or through hardware devices, such as an emergency stop button or switch on the sofa's armrest area, or by voice control to stop the robotic arm's movement.

[0077] Using the above embodiments, the motion monitoring system can acquire and monitor the user's physiological index data in real time, and adjust the movement mode of the robotic arm or trigger the activation of the emergency mode based on the physiological index data, thereby ensuring the safety of the exercise process, improving the effectiveness of the exercise, and optimizing the user experience.

[0078] In some embodiments, the sofa can also record detailed information such as the time, type of exercise (specific movement pattern for legs or hands), and intensity of each assisted exercise session. Simultaneously, it records joint data collected by the joint detection device before and after each exercise session. Data analysis algorithms are used to comprehensively analyze the stored historical exercise data and joint detection results, for example, to plot the user's joint recovery curve and visually display the trend of joint condition changes over a period of time on a screen. Furthermore, by comparing exercise data and joint conditions at different time points, the sofa evaluates the effectiveness of the assisted exercise method and can adjust the exercise plan for the user in a timely manner.

[0079] Based on the foregoing embodiments, this application provides a sofa-based auxiliary movement device. The device includes various modules and units included in each module, which can be implemented by a processor; of course, it can also be implemented by specific logic circuits. In the implementation process, the processor can be a central processing unit (CPU), microprocessor (MPU), digital signal processor (DSP), or field programmable gate array (FPGA), etc.

[0080] Please see Figure 5 , Figure 5 This is a block diagram of a sofa-based assistive motion device in one embodiment, such as... Figure 5 As shown, the sofa-based assistive motion device 500 may include a data acquisition module 510 and a command control module 520.

[0081] The data acquisition module 510 is used to acquire data collected by the joint detection device to obtain the user's joint detection results, which are used to indicate the user's joint damage status.

[0082] The instruction control module 520 is used to generate corresponding instructions based on the joint detection results, and control the robotic arm to move the user's legs or hands according to the instructions.

[0083] In some embodiments, the data acquisition module 510 is further configured to:

[0084] The data collected by the joint detection device is input into the algorithm model to obtain the user's joint detection results. The data collected by the joint detection device includes data collected by the camera and sensors; and...

[0085] Obtain the user's physiological index data during exercise.

[0086] In some embodiments, the instruction control module 520 is further configured to:

[0087] Based on the user's joint injury condition, instructions are generated to control the movement mode of the robotic arm corresponding to the joint injury condition. The robotic arm movement mode includes active movement mode, assisted movement mode and passive movement mode.

[0088] If the user's joint is detected to be in a level one injury, the movement mode of the robotic arm is controlled to be active movement mode;

[0089] If a user's joint is detected to have a level two injury, the movement mode of the robotic arm is controlled to be an assisted movement mode.

[0090] If a user's joint is detected to have a level 3 injury, the movement mode of the robotic arm is controlled to be a passive movement mode.

[0091] In some embodiments, the instruction control module 520 is further configured to:

[0092] The motion trajectory of the robotic arm is planned according to the motion pattern of the robotic arm, and the motion trajectory is used to indicate the joint movement path of the user.

[0093] Adjust the parameters corresponding to the motion mode according to the motion mode of the robotic arm;

[0094] The movement mode of the robotic arm is adjusted in real time based on the physiological index data.

[0095] When an abnormality in the user's physiological indicators is detected during exercise, an emergency mode is activated. The emergency mode includes an alarm function and an emergency stop function.

[0096] In this embodiment, the sofa can acquire data collected by the joint detection device, obtain the user's joint detection results, and generate corresponding instructions based on the joint detection results to control the robotic arm to move the user's legs or hands. Compared with traditional rehabilitation equipment, the sofa can assist in movement according to the user's joint injury condition, reduce pressure and discomfort on the joints during the user's movement, reduce the risk of pain and secondary injury, thereby improving the effectiveness and efficiency of rehabilitation.

[0097] Figure 6 This is a structural block diagram of an electronic device in one embodiment. For example... Figure 6 As shown, the terminal electronic device 600 may include: a memory 610 storing executable program code and a processor 620 coupled to the memory 610.

[0098] Specifically, the processor 620 calls the executable program code stored in the memory 610 to execute any of the spatial interaction control methods disclosed in the embodiments of this application. Those skilled in the art will understand that... Figure 6 The electronic device structure shown does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0099] The processor 620 is the control center of the electronic device. It connects various parts of the electronic device via various interfaces and lines. By running or executing software programs and / or modules stored in the memory 610, and by calling data stored in the memory 610, it performs various functions and processes data, thereby providing overall monitoring of the electronic device. Optionally, the processor 620 may include one or more processing units; preferably, the processor 620 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 620.

[0100] The memory 610 can be used to store software programs and modules. The processor 620 executes various functional applications and data processing of the electronic device by running the software programs and modules stored in the memory 610. The memory 610 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function, etc.; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 610 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0101] This application discloses a computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the methods described in the above embodiments.

[0102] This application discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program can be executed by a processor to implement the methods described in the above embodiments.

[0103] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, ROM, etc.

[0104] Any references to memory, storage, databases, or other media used herein may include non-volatile and / or volatile memory. Suitable non-volatile memory may include ROM, Programmable ROM (PROM), Erasable PROM (EPROM), Electrically Erasable PROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM), which is used as an external cache. By way of illustration and not limitation, RAM may take many forms, such as Static RAM (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDR SDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchlink DRAM (SLDRAM), Rambus DRAM (RDRAM), and Direct Rambus DRAM (DRDRAM).

[0105] It should be understood that the phrase "one embodiment" or "an embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Those skilled in the art should also recognize that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application. It should be noted that "multiple" in this application includes "two or more".

[0106] In the various embodiments of this application, it should be understood that the sequence number of each process does not necessarily imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0107] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they can be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0108] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0109] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0110] The foregoing has provided a detailed description of a sofa-based assisted movement method, device, electronic device, and storage medium disclosed in the embodiments of this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the embodiments above are merely for the purpose of helping to understand the method and its core ideas. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A sofa-based assisted movement method, characterized in that, An application is made to a sofa, wherein robotic arms are installed in the armrest and backrest areas, and a fixing device is installed at the end of the robotic arm for fixing a user's legs or hands. A joint detection device is installed in the armrest area of ​​the sofa. The method includes: The data collected by the joint detection device is input into the algorithm model to obtain the user's joint detection results. The data collected by the joint detection device includes data collected by the camera and sensors. The joint detection results are used to indicate the user's joint damage status. If the user's joint is detected to be in a level one injury, the movement mode of the robotic arm is controlled to be active movement mode; When a user's joint is detected to have a level two injury, the movement mode of the robotic arm is controlled to be an assisted movement mode; the degree of joint damage corresponding to the level two injury is greater than the degree of joint damage corresponding to the level one injury. When a user's joint is detected to have a level 3 injury, the movement mode of the robotic arm is controlled to be a passive movement mode; the degree of joint damage corresponding to the level 3 injury is greater than the degree of joint damage corresponding to the level 2 injury. The motion trajectory of the robotic arm is planned according to the motion pattern of the robotic arm, and the motion trajectory is used to indicate the joint movement path of the user. The operating parameters are adjusted according to the motion mode of the robotic arm; the robotic arm has pre-stored operating parameters corresponding to different motion modes, and the operating parameters include at least the flexion and extension angle, amplitude, and speed of the robotic arm. The robotic arm is controlled to move the user's legs or hands.

2. The method according to claim 1, characterized in that, Controlling the robotic arm to move the user's legs or hands includes: Obtain the user's physiological index data during exercise; The movement mode of the robotic arm is adjusted in real time based on the physiological index data.

3. The method according to claim 2, characterized in that, The method further includes: When an abnormality in the user's physiological indicators is detected during exercise, an emergency mode is activated. The emergency mode includes an alarm function and an emergency stop function.

4. A sofa-based assistive movement device, characterized in that, Applied to a sofa, the sofa has robotic arms installed in the armrest and backrest areas, and a fixing device is installed at the end of the robotic arm for fixing the user's legs or hands. The armrest area of ​​the sofa is equipped with a joint detection device. The sofa-based assistive movement device includes: The data acquisition module is used to input the data collected by the joint detection device into the algorithm model to obtain the joint detection results of the user. The data collected by the joint detection device includes data collected by the camera and sensors. The joint detection results are used to indicate the joint damage status of the user. The data acquisition module is further configured to: control the robotic arm's movement mode to active movement mode when a user's joint is detected to be at level one; control the robotic arm's movement mode to assisted movement mode when a user's joint is detected to be at level two; wherein the degree of joint damage corresponding to level two injury is greater than the degree of joint damage corresponding to level one injury; and control the robotic arm's movement mode to passive movement mode when a user's joint is detected to be at level three; wherein the degree of joint damage corresponding to level three injury is greater than the degree of joint damage corresponding to level two injury. The instruction control module is used to plan the motion trajectory of the robotic arm according to the motion mode of the robotic arm, and the motion trajectory is used to indicate the joint movement path of the user; adjust the operation parameters according to the motion mode of the robotic arm; the robotic arm has pre-stored operation parameters corresponding to different motion modes, and the operation parameters include at least the flexion and extension angle, amplitude, and speed of the robotic arm; The instruction control module is also used to control the robotic arm to move the user's legs or hands.

5. An electronic device, characterized in that, The method includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor causes the processor to perform the method as described in any one of claims 1 to 3.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 3.

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