Sitting posture correction method, device and system and seat

Abstract

The invention discloses a sitting posture correction method, device and system and a seat, and belongs to the technical field of health monitoring. The sitting posture correction method comprises the steps of obtaining a sitting posture image of a target object and multiple pressure data on a seat where the target object is located; processing the sitting posture image and the plurality of pressure data to obtain a target sitting posture feature corresponding to the target object; and based on the target sitting posture characteristics, controlling the seat to correct the sitting posture of the target object. According to the sitting posture correction method, the sitting posture of the user is intelligently corrected, the actual requirements of different users can be met, the correction effect and the correction precision are improved, and the use experience of the user is good.

Description

Technical Field

[0001] The present application belongs to the field of health monitoring technology, and in particular relates to a sitting posture correction method, device, system and chair. Background Art

[0002] With the changes in modern office and learning methods, long periods of sitting for work and study have become a common phenomenon. However, bad sitting posture can lead to a variety of health problems, such as scoliosis, lumbar disc herniation, and muscle fatigue. In the related art, there is a method of correcting sitting posture through physical devices such as correction chairs or straps, which cannot intelligently correct the user's sitting posture, and the correction effect and accuracy are poor. Summary of the invention

[0003] The present application aims to solve at least one of the technical problems existing in the related art. To this end, the present application proposes a sitting posture correction method, device, system and chair, which realizes intelligent correction of the user's sitting posture, can meet the actual needs of different users, improves the correction effect and correction accuracy, and provides a good user experience.

[0004] In a first aspect, the present application provides a sitting posture correction method, the method comprising:

[0005] Acquire a sitting posture image of a target object and a plurality of pressure data on a seat where the target object is located;

[0006] Processing the sitting posture image and the plurality of pressure data to obtain a target sitting posture feature corresponding to the target object;

[0007] Based on the target sitting posture feature, the seat is controlled to correct the sitting posture of the target object.

[0008] According to the sitting posture correction method provided in the embodiment of the present application, the user's sitting posture characteristics are analyzed by combining the user's sitting posture image and the pressure data on the seat, and the seat is controlled based on the user's sitting posture characteristics to correct the sitting posture. The user's sitting posture is comprehensively evaluated from two dimensions, visual and mechanical. Sitting posture problems can be identified more accurately, and the user's sitting posture can be corrected intelligently. The actual needs of different users can be met, the correction effect and correction accuracy are improved, and the user experience is better.

[0009] In a sitting posture correction method according to an embodiment of the present application, the processing of the sitting posture image and the plurality of pressure data to obtain a target sitting posture feature corresponding to the target object includes:

[0010] Processing the sitting posture image to obtain a first sitting posture feature corresponding to the target object in the sitting posture image;

[0011] The plurality of pressure data and the first sitting posture feature are processed to obtain a target sitting posture feature corresponding to the target object.

[0012] In a sitting posture correction method according to an embodiment of the present application, the processing of the sitting posture image to obtain a first sitting posture feature corresponding to the target object in the sitting posture image includes:

[0013] Performing feature extraction on the sitting posture image to obtain part features corresponding to each body part of the target object in the sitting posture image;

[0014] The first sitting posture feature is acquired based on difference information between the part feature corresponding to each of the body parts and the standard feature corresponding to the body part.

[0015] In a sitting posture correction method according to an embodiment of the present application, the processing of the plurality of pressure data and the first sitting posture feature to obtain a target sitting posture feature corresponding to the target object includes:

[0016] Processing the plurality of pressure data to obtain at least one area with abnormal pressure corresponding to the seat;

[0017] Based on the correspondence between each of the pressure abnormality regions and the body part of the target object, obtaining a second sitting posture feature corresponding to the target object;

[0018] The first sitting posture feature and the second sitting posture feature are fused to obtain the target sitting posture feature.

[0019] In a sitting posture correction method according to an embodiment of the present application, the processing of the sitting posture image and the plurality of pressure data to obtain a target sitting posture feature corresponding to the target object includes:

[0020] The sitting posture image and the plurality of pressure data are processed by using a machine learning algorithm to obtain the target sitting posture feature.

[0021] A sitting posture correction method according to an embodiment of the present application, controlling the seat based on the target sitting posture feature, comprises:

[0022] Based on the sitting posture characteristics, the parameters of the seat are adjusted, and / or the seat is controlled to output prompt information.

[0023] In a second aspect, the present application provides a sitting posture correction device, the device comprising:

[0024] A first processing module is used to obtain a sitting posture image of a target object and a plurality of pressure data on a seat where the target object is located;

[0025] A second processing module is used to process the sitting posture image and the plurality of pressure data to obtain a target sitting posture feature corresponding to the target object;

[0026] The third processing module is used to control the seat based on the target sitting posture characteristics to correct the sitting posture of the target object.

[0027] According to the sitting posture correction device provided in the embodiment of the present application, the user's sitting posture characteristics are analyzed by combining the user's sitting posture image and the pressure data on the seat, and the seat is controlled based on the user's sitting posture characteristics to correct the sitting posture. The user's sitting posture is comprehensively evaluated from two dimensions, visual and mechanical. Sitting posture problems can be identified more accurately, and the user's sitting posture can be corrected intelligently. The actual needs of different users can be met, the correction effect and correction accuracy are improved, and the user experience is better.

[0028] In a third aspect, the present application provides a sitting posture correction system based on the sitting posture correction method as described in the first aspect, comprising:

[0029] An image sensor, the image sensor being used to capture the sitting posture image of the target object;

[0030] A plurality of pressure sensors, wherein the plurality of pressure sensors are used to collect the plurality of pressure data;

[0031] a data processing device, the data processing device being connected to the image sensor and each of the pressure sensors respectively, and the data processing device being used to obtain the target sitting posture feature based on the sitting posture image and the plurality of pressure data;

[0032] A controller is connected to the data processing device, and is used to control the seat based on the target sitting posture feature.

[0033] According to the sitting posture correction system provided in the embodiment of the present application, the user's sitting posture characteristics are analyzed by combining the user's sitting posture image and the pressure data on the seat, and the seat is controlled based on the user's sitting posture characteristics to correct the sitting posture. The user's sitting posture is comprehensively evaluated from two dimensions, visual and mechanical. Sitting posture problems can be identified more accurately, and the user's sitting posture can be corrected intelligently. The actual needs of different users can be met, the correction effect and correction accuracy are improved, and the user experience is better.

[0034] In a fourth aspect, the present application provides a seat, comprising:

[0035] Chair frame;

[0036] A plurality of pressure sensors, wherein the plurality of pressure sensors are disposed on the chair frame;

[0037] A data processing device, the data processing device is arranged on the chair frame, and the data processing device is respectively connected to each of the pressure sensors;

[0038] A controller is arranged on the chair frame and connected to the data processing device.

[0039] According to the chair provided in the embodiment of the present application, the user's sitting posture characteristics are analyzed by combining the user's sitting posture image and the pressure data on the chair, and the chair is controlled based on the user's sitting posture characteristics to correct the sitting posture. The user's sitting posture is comprehensively evaluated from two dimensions, visual and mechanical. Sitting posture problems can be identified more accurately, and the user's sitting posture can be corrected intelligently. The actual needs of different users can be met, the correction effect and correction accuracy are improved, and the user experience is better.

[0040] In a fifth aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the sitting posture correction method as described in the first aspect above is implemented.

[0041] In a sixth aspect, the present application provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the sitting posture correction method as described in the first aspect above is implemented.

[0042] In a seventh aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the sitting posture correction method as described in the first aspect above.

[0043] The above one or more technical solutions in the embodiments of the present application have at least one of the following technical effects:

[0044] By combining the user's sitting posture image and the pressure data on the seat, the user's sitting posture characteristics are analyzed, and the seat is controlled based on the user's sitting posture characteristics to correct the sitting posture. The user's sitting posture is comprehensively evaluated from both visual and mechanical dimensions, and sitting posture problems can be identified more accurately. The user's sitting posture can be corrected intelligently, which can meet the actual needs of different users, improve the correction effect and accuracy, and provide users with a better experience.

[0045] Furthermore, by processing the sitting posture image and pressure data, the target sitting posture characteristics of the target object are obtained without human intervention, thereby improving the efficiency and convenience of sitting posture assessment.

[0046] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0048] Figure 1 This is one of the flow charts of the sitting posture correction method provided in the embodiment of the present application;

[0049] Figure 2 This is the second flow chart of the sitting posture correction method provided in the embodiment of the present application;

[0050] Figure 3 is a schematic diagram of the structure of a sitting posture correction device provided in an embodiment of the present application;

[0051] Figure 4 is a structural schematic diagram of a sitting posture correction system provided in an embodiment of the present application;

[0052] Figure 5 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of this application.

[0054] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0055] The sitting posture correction method, sitting posture correction device, electronic device and readable storage medium provided in the embodiments of the present application are described in detail below with reference to the accompanying drawings through specific embodiments and their application scenarios.

[0056] Among them, the sitting posture correction method can be applied to a terminal, and can be specifically executed by hardware or software in the terminal.

[0057] The terminal includes, but is not limited to, a portable communication device such as a mobile phone or tablet computer with a touch-sensitive surface (e.g., a touch screen display and / or a touch pad). It should also be understood that in some embodiments, the terminal may not be a portable communication device, but a desktop computer with a touch-sensitive surface (e.g., a touch screen display and / or a touch pad).

[0058] In the following various embodiments, a terminal including a display and a touch-sensitive surface is described. However, it should be understood that the terminal may include one or more other physical user interface devices such as a physical keyboard, a mouse and a joystick.

[0059] The sitting posture correction method provided in the embodiment of the present application may be executed by an electronic device or a functional module or functional entity in the electronic device that can implement the sitting posture correction method. The electronic devices mentioned in the embodiment of the present application include but are not limited to mobile phones, tablet computers, computers, cameras, and wearable devices. The sitting posture correction method provided in the embodiment of the present application is described below using an electronic device as an example of the execution subject.

[0060] like Figure 1 As shown, the sitting posture correction method includes: step 110, step 120 and step 130.

[0061] It should be noted that the sitting posture correction method can be applied to a sitting posture correction system.

[0062] The sitting posture correction system may include an image sensor, a plurality of pressure sensors, a data processing device and a controller.

[0063] The data processing device is connected to the image sensor and each pressure sensor respectively.

[0064] The controller is connected to the data processing device.

[0065] Step 110, obtaining a sitting posture image of the target object and a plurality of pressure data on the seat where the target object is located;

[0066] In this step, the target objects are users who need to use the sitting posture correction system to monitor and correct their sitting posture.

[0067] When the target object is in a sitting state, a sitting image of the target object may be acquired.

[0068] Sitting images can be captured based on an image sensor. The image sensor can be set in front of or to the side of the target object. The setting height of the image sensor can be adjusted based on the height and sitting posture of the target object. For example, the image sensor can be set on a desktop or under a table top and face the target object.

[0069] The image sensor may include a high-definition camera or an infrared sensor, etc.

[0070] A plurality of pressure sensors may be arranged on the seat, and the plurality of pressure sensors may be arranged on the seat cushion, backrest, armrest and other positions of the seat. For example, pressure sensors may be arranged in the waist area, hip area, shoulder area and arm support area respectively.

[0071] Based on the pressure sensor, pressure data can be collected.

[0072] In the actual implementation process, the image sensor and the pressure sensor can collect data based on the same or different data collection frequencies. For example, the image sensor can collect images every one minute, and the pressure sensor can collect pressure data every 30 seconds.

[0073] The collected images and data can be stored on the local device and transmitted to the cloud server through encryption for remote analysis and long-term storage.

[0074] Step 120: Process the sitting posture image and the multiple pressure data to obtain a target sitting posture feature corresponding to the target object;

[0075] In this step, noise data such as abnormal values ​​or repeated values ​​in the multiple pressure data may be removed.

[0076] Key features can be extracted from multiple pressure data, such as pressure distribution uniformity, sitting duration, and body tilt angle.

[0077] By performing statistical analysis on the collected pressure data, the average pressure, maximum pressure and pressure distribution diagram can be calculated.

[0078] Image processing algorithms (such as edge detection, contour extraction, and feature point matching) can be used to identify the body parts of the target object (such as head, shoulders, back, buttocks, and legs, etc.) from the sitting image.

[0079] The part features of each body part, such as position, angle, shape and size, can be extracted.

[0080] Based on the pressure data and the part characteristics, the target sitting posture characteristics of the target object can be obtained.

[0081] By evaluating the target sitting posture characteristics, it can be determined whether the target object has a bad sitting posture, such as hunchback, shrugging shoulders, bending over, and hip deviation.

[0082] Step 130: Based on the target sitting posture characteristics, control the seat to correct the sitting posture of the target object.

[0083] In this step, a correction strategy can be developed based on the evaluation results of the target sitting posture characteristics.

[0084] The correction strategy may include maintaining the current state of the seat unchanged, adjusting parameters such as the seat height, tilt angle, back support, etc., or may include outputting prompt information to guide the user to adjust the sitting posture.

[0085] In the actual implementation process, the correction strategy can be converted into a seat control instruction, and the control instruction is sent to the seat through the control module to adjust the parameters of the seat to correct the sitting posture.

[0086] The seat adjustment effect can be monitored in real time to ensure that the sitting posture is effectively corrected.

[0087] During the correction process, feedback information can be provided to the target object through the user interaction module, such as displaying the correction progress and indicating the adjustment direction.

[0088] After the correction is completed, a prompt message indicating that the sitting posture correction is successful can be sent to the target object.

[0089] According to the sitting posture correction method provided in the embodiment of the present application, the user's sitting posture characteristics are analyzed by combining the user's sitting posture image and the pressure data on the seat, and the seat is controlled based on the user's sitting posture characteristics to correct the sitting posture. The user's sitting posture is comprehensively evaluated from two dimensions, visual and mechanical. Sitting posture problems can be identified more accurately, and the user's sitting posture can be corrected intelligently. The actual needs of different users can be met, the correction effect and correction accuracy are improved, and the user experience is better.

[0090] In some embodiments, step 120 may include:

[0091] Processing the sitting posture image to obtain a first sitting posture feature corresponding to the target object in the sitting posture image;

[0092] The plurality of pressure data and the first sitting posture feature are processed to obtain a target sitting posture feature corresponding to the target object.

[0093] In this embodiment, the sitting posture image may be preprocessed, including denoising, grayscale conversion, binarization, and the like.

[0094] Image segmentation can then be performed to separate the target object (such as a human body) from the background, and image processing algorithms (such as edge detection or contour detection, etc.) can be used to extract the contours and key points of the target object (such as a human body) in the sitting image.

[0095] Based on the extracted contours and key points, the first sitting posture feature of the target object can be calculated.

[0096] The relative positions and angles between the key points can be calculated to obtain the first sitting posture feature.

[0097] The first sitting posture characteristics may include the tilt angle of the body, the height difference of the shoulders, and the contact area between the buttocks and the ground.

[0098] Pressure features can be extracted based on multiple pressure data, such as the center of gravity of the pressure distribution and the pressure values ​​in different areas.

[0099] The first sitting posture feature and the extracted pressure feature may be fused, for example, by weighted averaging or a machine learning algorithm (such as a support vector machine or a neural network).

[0100] Based on the results of the fusion processing, the target sitting posture features of the target object can be obtained.

[0101] In some embodiments, processing the sitting posture image to obtain the first sitting posture feature corresponding to the target object in the sitting posture image may include:

[0102] Perform feature extraction on the sitting posture image to obtain part features corresponding to each body part of the target object in the sitting posture image;

[0103] Based on the difference information between the part features corresponding to each body part and the standard features corresponding to the body part, a first sitting posture feature is obtained.

[0104] In this embodiment, a machine learning or deep learning algorithm, such as a convolutional neural network (CNN), may be used to segment the sitting image into body parts and extract the part features of each part.

[0105] Body parts may include the head, shoulders, torso, arms, and legs, among others.

[0106] It can determine whether the head is tilted or whether the head is looking down at the phone by identifying features such as head outline, eye position and mouth state.

[0107] By analyzing the inclination angle of the shoulder line, you can determine whether there are problems such as hunching and hunching.

[0108] By identifying the spinal curve and chest and abdominal contours, etc., it is possible to assess whether the sitting posture is upright.

[0109] By analyzing the position and posture of the arms, it is possible to determine whether there are movements such as arm support and crossing.

[0110] By identifying the position of the knees and the angle of the legs, etc., it is possible to determine whether the legs are relaxed or crossed.

[0111] The standard sitting posture characteristics may be determined based on average characteristic values ​​statistically derived from a large number of healthy sitting posture samples, or standard values ​​may be set based on professional medical or ergonomic recommendations.

[0112] Calculates the difference between actual and standard sitting posture characteristics, such as excessive head tilt, unequal shoulder heights, or abnormal spinal curves.

[0113] Based on the difference information, the first sitting posture feature of the target object can be comprehensively derived. The first sitting posture feature can be quantitative (such as the head tilt angle and the spinal curvature, etc.) or qualitative (such as whether the shoulders are shrugged or whether the back is hunched, etc.).

[0114] For example, in the sitting image, the target object's head is obviously tilted and his eyes are fixed on the mobile phone screen. Through feature extraction and comparison, it can be concluded that the first sitting posture feature is "head tilted, looking down at the phone".

[0115] The target object has different shoulder heights in the sitting image, and the spine curve is S-shaped, so the first sitting posture feature can be derived as "shrugging shoulders and hunching back".

[0116] The target subject sits upright, with the head, shoulders, torso, arms and legs all meeting standard sitting posture characteristics. The first sitting posture characteristic can be described as "sitting upright".

[0117] In some embodiments, processing the plurality of pressure data and the first sitting posture feature to obtain the target sitting posture feature corresponding to the target object may include:

[0118] Processing the multiple pressure data to obtain at least one area with abnormal pressure corresponding to the seat;

[0119] Based on the correspondence between each area with abnormal pressure and a body part of the target object, a second sitting posture feature corresponding to the target object is obtained;

[0120] The first sitting posture feature and the second sitting posture feature are integrated to obtain the target sitting posture feature.

[0121] In this embodiment, a plurality of pressure data may be converted into a pressure distribution diagram to intuitively display the pressure distribution on the seat surface.

[0122] In the pressure distribution diagram, at least one area with abnormal pressure can be identified. These areas usually show excessively high or low pressure values, which are significantly different from the pressure distribution in a normal sitting position.

[0123] The pressure threshold can be set according to the pressure distribution range in a normal sitting posture.

[0124] By comparing the actual pressure distribution with the threshold, areas of abnormal pressure can be identified.

[0125] The correspondence between each area of ​​abnormal pressure and the body part of the target object can be obtained through ergonomic research and experimental data.

[0126] Based on the location and shape of the abnormal pressure area, the corresponding body part (such as the hips, waist, and back, etc.) can be inferred.

[0127] By analyzing the difference in pressure distribution between the abnormal pressure area and the normal sitting posture, the second sitting posture characteristics of the target object (such as hip deviation, suspended waist and insufficient back support, etc.) can be extracted.

[0128] The first sitting posture characteristics (such as head tilt, shrugging and hunching, etc.) can be matched with the second sitting posture characteristics (such as hip offset and waist hanging, etc.) to find out the commonalities and differences.

[0129] According to the matching results, the sitting posture of the target object is comprehensively evaluated to obtain a target sitting posture feature, which can be a comprehensive score, a list containing multiple sitting posture problems, or a sitting posture analysis report.

[0130] For example, when the target subject sits on the seat, the pressure distribution diagram shows that the pressure on the left side of the buttocks is too high, while the pressure on the right side is low. At the same time, the first sitting posture feature shows that the target subject has a shoulder shrug problem. By fusing the two features, it can be concluded that the target sitting posture feature is "hip offset and shoulder shrug".

[0131] The target object appears to be upright in the sitting posture image, but the pressure distribution diagram shows that the pressure in the waist area is relatively low, indicating that the waist is suspended. Combined with the first sitting posture feature (no obvious abnormality), it can be concluded that the target sitting posture feature is "insufficient waist support."

[0132] In some embodiments, processing the sitting posture image and the plurality of pressure data to obtain the target sitting posture feature corresponding to the target object may include:

[0133] A machine learning algorithm is used to process the sitting posture image and multiple pressure data to obtain the target sitting posture features.

[0134] In this embodiment, image data containing the target object's sitting posture may be collected. These images may be static pictures or video frames and cover different sitting posture scenes.

[0135] The pressure data generated by the target object in a sitting position can be collected from the pressure sensor built into the seat, which can include pressure distribution information at multiple time points.

[0136] The image data and pressure data of the sitting posture can be used as training samples of the machine learning model to train the machine learning model. During the training process, the model will learn the mapping relationship between the sitting posture image and pressure data and the sitting posture features.

[0137] You can choose an appropriate machine learning algorithm, such as support vector machine (SVM), random forest or neural network, based on the complexity of the problem, the characteristics of the data and user needs.

[0138] The performance of the model can be evaluated through methods such as cross-validation or leave-one-out. If the model performance is poor, the model parameters can be adjusted or other algorithms can be tried.

[0139] The sitting posture images and pressure data collected in real time are input into the trained machine learning model, and the model can predict the target sitting posture characteristics of the target object based on the input data.

[0140] According to the sitting posture correction method provided in the embodiment of the present application, the target sitting posture characteristics of the target object are obtained by processing the sitting posture image and pressure data without manual intervention, thereby improving the efficiency and convenience of sitting posture assessment.

[0141] In some embodiments, step 130 may include:

[0142] Based on the sitting posture characteristics, the seat parameters are adjusted, and / or the seat is controlled to output prompt information.

[0143] In this embodiment, the parameters of the seat may include seat height, footrest height, seat tilt angle, backrest support strength, armrest height and armrest angle, etc.

[0144] For example, if it is detected that the user's feet are not flat on the ground or the knees are excessively bent, the seat height can be automatically adjusted to ensure that the user's feet can be placed comfortably on the ground while maintaining a natural bend in the knees.

[0145] If it is detected that the user's spine is too curved or the head is tilted forward too much, the tilt angle of the seat can be adjusted to adjust the user's spine and back support.

[0146] By adjusting the backrest support strength, you can ensure that the user's back is properly supported and reduce fatigue in the waist and back.

[0147] The armrest height is the vertical distance between the chair armrest and the seat surface. By adjusting the armrest height, you can ensure that the user's arms are properly supported and reduce the pressure on the shoulders and neck. The height of the armrest can be adjusted to match the height of the desktop.

[0148] The armrest angle refers to the inclination of the chair armrest relative to the seat surface. By adjusting the armrest angle, the user's sitting posture can be further improved to ensure that both arms are comfortably supported.

[0149] When it is detected that the user maintains a bad sitting posture, the chair can send a prompt message through the built-in speaker or lighting system to remind the user to adjust the sitting posture.

[0150] The prompt information may include voice prompts (such as "Please adjust your sitting posture and keep your spine straight"), text displays (for example, can be displayed on the user's mobile terminal) or flashing lights, etc.

[0151] The sitting posture correction device provided by the present application is described below. The sitting posture correction device described below and the sitting posture correction method described above can be referenced to each other.

[0152] The sitting posture correction method provided in the embodiment of the present application can be performed by a sitting posture correction device. In the embodiment of the present application, the sitting posture correction device performing the sitting posture correction method is taken as an example to illustrate the sitting posture correction device provided in the embodiment of the present application.

[0153] The embodiment of the present application also provides a sitting posture correction device.

[0154] like Figure 3 As shown, the sitting posture correction device includes: a first processing module 310, a second processing module 320 and a third processing module 330.

[0155] A first processing module 310 is used to obtain a sitting posture image of a target object and a plurality of pressure data on a seat where the target object is located;

[0156] The second processing module 320 is used to process the sitting posture image and the multiple pressure data to obtain the target sitting posture feature corresponding to the target object;

[0157] The third processing module 330 is used to control the seat based on the target sitting posture feature to correct the sitting posture of the target object.

[0158] According to the sitting posture correction device provided in the embodiment of the present application, the user's sitting posture characteristics are analyzed by combining the user's sitting posture image and the pressure data on the seat, and the seat is controlled based on the user's sitting posture characteristics to correct the sitting posture. The user's sitting posture is comprehensively evaluated from two dimensions, visual and mechanical. Sitting posture problems can be identified more accurately, and the user's sitting posture can be corrected intelligently. The actual needs of different users can be met, the correction effect and correction accuracy are improved, and the user experience is better.

[0159] In some embodiments, the second processing module 320 may also be used to:

[0160] Processing the sitting posture image to obtain a first sitting posture feature corresponding to the target object in the sitting posture image;

[0161] The plurality of pressure data and the first sitting posture feature are processed to obtain a target sitting posture feature corresponding to the target object.

[0162] In some embodiments, the second processing module 320 may also be used to:

[0163] Perform feature extraction on the sitting posture image to obtain part features corresponding to each body part of the target object in the sitting posture image;

[0164] Based on the difference information between the part features corresponding to each body part and the standard features corresponding to the body part, a first sitting posture feature is obtained.

[0165] In some embodiments, the second processing module 320 may also be used to:

[0166] Processing the multiple pressure data to obtain at least one area with abnormal pressure corresponding to the seat;

[0167] Based on the correspondence between each area with abnormal pressure and a body part of the target object, a second sitting posture feature corresponding to the target object is obtained;

[0168] The first sitting posture feature and the second sitting posture feature are integrated to obtain the target sitting posture feature.

[0169] In some embodiments, the second processing module 320 may also be used to:

[0170] A machine learning algorithm is used to process the sitting posture image and multiple pressure data to obtain the target sitting posture features.

[0171] In some embodiments, the third processing module 330 may also be used to:

[0172] Based on the sitting posture characteristics, the seat parameters are adjusted, and / or the seat is controlled to output prompt information.

[0173] The sitting posture correction device in the embodiment of the present application can be an electronic device, or a component in the electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal, or other devices other than a terminal. Exemplarily, the electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, a vehicle-mounted electronic device, a mobile Internet device (Mobile Internet Device, MID), an augmented reality (augmented reality, AR) / virtual reality (virtual reality, VR) device, a robot, a wearable device, an ultra-mobile personal computer (ultra-mobile personal computer, UMPC), a netbook or a personal digital assistant (personal digital assistant, PDA), etc., and can also be a server, a network attached storage (Network Attached Storage, NAS), a personal computer (personal computer, PC), a television (television, TV), a teller machine or a self-service machine, etc., which is not specifically limited in the embodiment of the present application.

[0174] The sitting posture correction device in the embodiment of the present application may be a device having an operating system. The operating system may be an Android operating system, an IOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0175] The sitting posture correction device provided in the embodiment of the present application can achieve Figure 1 to Figure 2 To avoid repetition, the various processes implemented by the method embodiment are not described here.

[0176] In some embodiments, the present application also provides a chair, comprising: a chair frame, a plurality of pressure sensors, a data processing device and a controller.

[0177] In this embodiment, a plurality of pressure sensors are disposed on the chair frame, for example, they may be distributed on the seat cushion, backrest, armrests, etc.

[0178] In this application, the pressure sensor is designed to be light and comfortable and easy to integrate into the seat and backrest.

[0179] The data processing device is arranged on the chair frame, and the data processing device is respectively connected to each pressure sensor for communication.

[0180] The controller is arranged on the chair frame and is connected with the data processing device.

[0181] The above-mentioned seats may be in the form of ordinary seats, sofas, children's chairs, gaming chairs, etc.

[0182] In some embodiments, the seat can be connected to an external health monitoring device so that the health monitoring device can output a more comprehensive health management plan.

[0183] According to the chair provided in the embodiment of the present application, the user's sitting posture characteristics are analyzed by combining the user's sitting posture image and the pressure data on the chair, and the chair is controlled based on the user's sitting posture characteristics to correct the sitting posture. The user's sitting posture is comprehensively evaluated from two dimensions, visual and mechanical. Sitting posture problems can be identified more accurately, and the user's sitting posture can be corrected intelligently. The actual needs of different users can be met, the correction effect and correction accuracy are improved, and the user experience is better.

[0184] like Figure 4 As shown, in some embodiments, the present application also provides a sitting posture correction system 400, including an image sensor 410, a plurality of pressure sensors 420, a data processing device 430 and a controller 440.

[0185] In this embodiment, the image sensor 410 is used to capture a sitting image of the target object.

[0186] The plurality of pressure sensors 420 are used to collect a plurality of pressure data.

[0187] The data processing device 430 is connected to the image sensor 410 and each pressure sensor 420 respectively, and the data processing device 430 is used to obtain the target sitting posture characteristics based on the sitting posture image and multiple pressure data.

[0188] The controller 440 is connected to the data processing device 430 , for example, via a high-speed data bus, and the controller 440 is used to control the seat based on the target sitting posture characteristics.

[0189] In some embodiments, the sitting posture correction system may further include a display device.

[0190] In this embodiment, the display device may be connected to the controller 440 to display prompt information.

[0191] For example, the display device may be an indicator light (such as an LED, etc.) or a voice broadcast device, etc.

[0192] The controller 440 can output control instructions, and the display device can output prompt information based on the control instructions. For example, the indicator light can be controlled to change color or flash, or the voice broadcast device can be controlled to broadcast a prompt voice to remind the user to correct the sitting posture.

[0193] The prompt information may also include a correction animation, etc. For example, the correction animation may be displayed on a display screen connected to the seat.

[0194] In the present application, prompt information is output to correct the user's sitting posture, making the correction process more intuitive and easy to operate, thereby improving the user experience.

[0195] According to the sitting posture correction system 400 provided in the embodiment of the present application, the user's sitting posture characteristics are analyzed by combining the user's sitting posture image and the pressure data on the seat, and the seat is controlled based on the user's sitting posture characteristics to correct the sitting posture. The user's sitting posture is comprehensively evaluated from two dimensions, visual and mechanical. Sitting posture problems can be identified more accurately, and the user's sitting posture can be corrected intelligently. The actual needs of different users can be met, the correction effect and correction accuracy are improved, and the user experience is better.

[0196] In some embodiments, Figure 5 As shown, the embodiment of the present application also provides an electronic device 500, including a processor 501, a memory 502, and a computer program stored in the memory 502 and executable on the processor 501. When the program is executed by the processor 501, each process of the above-mentioned sitting posture correction method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be described here.

[0197] It should be noted that the electronic devices in the embodiments of the present application include the mobile electronic devices and non-mobile electronic devices mentioned above.

[0198] On the other hand, the present application also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the various processes of the above-mentioned sitting posture correction method embodiment and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0199] On the other hand, the present application also provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, it is implemented to perform the various processes of the above-mentioned sitting posture correction method embodiment and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0200] On the other hand, an embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned sitting posture correction method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0201] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0202] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0203] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, by hardware. Based on this understanding, the above technical solution can be essentially or in other words, the part that contributes to the relevant technology can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiment.

[0204] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A sitting posture correction method, characterized in that: include: Acquire a sitting posture image of a target object and a plurality of pressure data on a seat where the target object is located; Processing the sitting posture image and the plurality of pressure data to obtain a target sitting posture feature corresponding to the target object; Based on the target sitting posture feature, the seat is controlled to correct the sitting posture of the target object.

2. The sitting posture correction method according to claim 1, characterized in that: The processing of the sitting posture image and the plurality of pressure data to obtain a target sitting posture feature corresponding to the target object includes: Processing the sitting posture image to obtain a first sitting posture feature corresponding to the target object in the sitting posture image; The plurality of pressure data and the first sitting posture feature are processed to obtain a target sitting posture feature corresponding to the target object.

3. The sitting posture correction method according to claim 2, characterized in that: The processing of the sitting posture image to obtain a first sitting posture feature corresponding to the target object in the sitting posture image includes: Performing feature extraction on the sitting posture image to obtain part features corresponding to each body part of the target object in the sitting posture image; The first sitting posture feature is acquired based on difference information between the part feature corresponding to each of the body parts and the standard feature corresponding to the body part.

4. The sitting posture correction method according to claim 2, characterized in that: The processing of the plurality of pressure data and the first sitting posture feature to obtain the target sitting posture feature corresponding to the target object includes: Processing the plurality of pressure data to obtain at least one area with abnormal pressure corresponding to the seat; Based on the correspondence between each of the pressure abnormality regions and the body part of the target object, obtaining a second sitting posture feature corresponding to the target object; The first sitting posture feature and the second sitting posture feature are fused to obtain the target sitting posture feature.

5. The sitting posture correction method according to any one of claims 1 to 4, characterized in that: The processing of the sitting posture image and the plurality of pressure data to obtain a target sitting posture feature corresponding to the target object includes: The sitting posture image and the plurality of pressure data are processed by using a machine learning algorithm to obtain the target sitting posture feature.

6. The sitting posture correction method according to any one of claims 1 to 4, characterized in that: The controlling the seat based on the target sitting posture feature comprises: Based on the sitting posture characteristics, the parameters of the seat are adjusted, and / or the seat is controlled to output prompt information.

7. A sitting posture correction device, characterized in that: include: A first processing module is used to obtain a sitting posture image of a target object and a plurality of pressure data on a seat where the target object is located; A second processing module is used to process the sitting posture image and the plurality of pressure data to obtain a target sitting posture feature corresponding to the target object; The third processing module is used to control the seat based on the target sitting posture characteristics to correct the sitting posture of the target object.

8. A sitting posture correction system based on the sitting posture correction method according to any one of claims 1 to 6, characterized in that: include: An image sensor, the image sensor being used to capture the sitting posture image of the target object; A plurality of pressure sensors, wherein the plurality of pressure sensors are used to collect the plurality of pressure data; a data processing device, the data processing device being connected to the image sensor and each of the pressure sensors respectively, and the data processing device being used to obtain the target sitting posture feature based on the sitting posture image and the plurality of pressure data; A controller is connected to the data processing device, and is used to control the seat based on the target sitting posture feature.

9. A seat, characterized in that: include: Chair frame; A plurality of pressure sensors, wherein the plurality of pressure sensors are disposed on the chair frame; A data processing device, the data processing device is arranged on the chair frame, and the data processing device is respectively connected to each of the pressure sensors; A controller is arranged on the chair frame and connected to the data processing device.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the sitting posture correction method as described in any one of claims 1-6 is implemented.

11. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the sitting posture correction method as described in any one of claims 1 to 6 is implemented.

12. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the sitting posture correction method as described in any one of claims 1 to 6 is implemented.

Images