Intelligent positioning system convenient for adjusting standing posture of patient and method thereof

Abstract

The invention discloses an intelligent positioning system capable of conveniently adjusting the standing posture of a patient and a method thereof, and relates to the technical field of intelligent medical treatment. Comprising the following steps of initial posture evaluation and skeleton modeling, gravity center and supporting point distribution calculation, spine curvature and inclination detection, intelligent laser-assisted posture adjustment, dynamic muscle activation feedback monitoring, pelvis and lower limb alignment correction, posture balance prediction and guidance, upper limb posture and shoulder blade stability correction and real-time adjustment of biological feedback driving. And carrying out long-term attitude optimization and habit remodeling, and carrying out system construction based on the method. According to the intelligent positioning system convenient for adjusting the standing posture of the patient and the method thereof, accurate detection, real-time adjustment and long-term optimization of the standing posture problem of the patient are realized by setting and combining multi-modal data acquisition, a dynamic feedback mechanism and biomechanical analysis. The problems of low static evaluation precision, lack of dynamic feedback and poor long-term effect in the prior art are effectively solved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent medical technology, and in particular to an intelligent positioning system and method for facilitating adjustment of a patient's standing posture. Background Art

[0002] Human standing posture is one of the most important postures in daily life. Bad standing posture not only affects appearance, but also causes long-term damage to the spine, muscles, joints and other parts, leading to chronic pain, bone degeneration and other health problems. Most of the existing standing posture adjustment technologies rely on traditional static observation and subjective evaluation, such as naked eye observation by physical examination doctors, the use of simple measuring tools (such as spirit levels) or relying on patients' self-perception. However, these methods have the limitations of low accuracy, lack of real-time feedback and difficulty in dynamic adjustment, especially when facing complex three-dimensional standing posture problems (such as scoliosis and pelvic tilt), traditional methods are difficult to provide effective guidance. In addition, although some intelligent auxiliary devices have introduced sensors and machine learning technologies, they focus more on data collection and visualization analysis, lack dynamic feedback and personalized correction capabilities, which makes it difficult for patients to adjust and inefficient to form habits.

[0003] In response to the above shortcomings, new technologies such as depth cameras, surface electromyography (EMG) sensors, laser projection and augmented reality (AR) have been developed in recent years, but most of these technologies are used independently and have not yet formed a systematic posture adjustment program. Especially when detecting complex biomechanical parameters such as the three-dimensional curvature of the spine, the distribution of the center of gravity, and the muscle activation pattern, there is a lack of a complete system that can integrate multi-dimensional data, real-time feedback and intuitive guidance. In addition, the existing methods have weak support for patients' long-term habit formation, which can easily lead to the problem of effective short-term correction and unsatisfactory long-term results. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides an intelligent positioning system and method for facilitating adjustment of a patient's standing posture, so as to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions: In a first aspect, an embodiment of the present invention provides an intelligent positioning method for facilitating adjustment of a patient's standing posture, comprising the following steps: S1, initial posture evaluation and skeleton modeling; S2, calculation of center of gravity and support point distribution; S3, spinal curvature and inclination detection; S4, intelligent laser-assisted posture adjustment; S5, dynamic muscle activation feedback monitoring; S6, pelvic and lower limb alignment correction; S7, posture balance prediction and guidance; S8, upper limb posture and scapula stability correction; S9, real-time adjustment driven by biofeedback; S10. Long-term posture optimization and habit reshaping.

[0006] To further optimize the technical solution, in step S1, the overall standing posture data of the patient is collected by a high-precision 3D depth camera or a laser scanner, and a human skeleton model is established; Use multi-view capture technology to determine skeletal joint positions, joint angles, and body posture distribution; Combined with the human anatomy database, a machine learning algorithm is used to infer the stability of the current standing posture and its deviation from the standard standing posture, providing benchmark data for subsequent adjustments.

[0007] To further optimize the technical solution, in step S2, the projection position of the center of gravity on the sole support surface is calculated through the patient's human skeleton model and combined with the sole pressure sensor data, and the uniformity and asymmetry of the sole force when standing are determined.

[0008] To further optimize the technical solution, in step S3, the three-dimensional curvature of the patient's spine is detected through an intelligent posture analysis algorithm, including the physiological curvature in the front-to-back direction including thoracic kyphosis and lumbar lordosis, and scoliosis in the left-right direction.

[0009] To further optimize the technical solution, an intelligent posture analysis model is constructed in the intelligent posture analysis algorithm, based on the spatial curvature distribution of the spine, and multimodal sensor data is introduced for optimization; The intelligent posture analysis model includes a three-dimensional spinal curvature formula, a spinal scoliosis angle formula, and a curvature abnormality index; The three-dimensional curvature formula of the spine is used to describe the curvature of the spine at different positions; The scoliosis angle formula is used to directly reflect whether there is an overall left-right lateral deviation problem in the spine; The curvature abnormality index is used to comprehensively reflect the abnormal distribution of the entire spine.

[0010] To further optimize this technical solution, in the intelligent posture analysis model: Assume that the spine is composed of multiple key points, marked as cervical vertebra C1 to coccygeal vertebra S5, and the three-dimensional coordinates of each key point are collected through sensor data and recorded as ,in Indicates the key point number; Three-dimensional curvature of the spine The formula is as follows: ; in, It is the length parameter of the spine, the cumulative distance from the cervical vertebrae to the coccyx; is the unit tangent vector of the spine, is the first derivative of the tangent vector; is the unit normal vector of the spine, is the first derivative of the normal vector; Represents the magnitude of a vector; The curvature of a standard spine has known normal ranges in specific regions, including the thoracic kyphotic region; The scoliosis angle formula includes: Scoliosis angle Describes the tilt of the spine in the left-right direction and is defined as: ; in, are the transverse and longitudinal coordinates of the cervical vertebrae apex, respectively; are the transverse and longitudinal coordinates of the base of the coccyx; In the bending anomaly index: Defining an anomaly index , which is used to quantify the degree of abnormality in a certain segment of the spine: ; in, is the standard curvature value corresponding to each key point.

[0011] To further optimize the technical solution, in step S4, an intelligent laser projector is arranged in the patient's standing area to project the human skeleton model of the target standing posture onto the patient's body surface in the form of a grid. The patient observes the deviation of the grid line and actively adjusts the body until it is aligned with the projection.

[0012] To further optimize the technical solution, in step S5, the activation pattern of each major muscle group during the patient's posture adjustment is monitored by a surface electromyography (EMG) sensor to determine whether there are compensatory movements or incorrect muscle force patterns.

[0013] To further optimize the technical solution, in steps S6 and S8, the pelvic inclination and rotation are detected through a real-time posture feedback algorithm, and the patient is guided to achieve pelvic alignment by fine-tuning the foot position and leg muscle force, and the patient's upper limb position and scapula stability are monitored, and incorrect shoulder posture is adjusted to avoid the impact of poor standing posture.

[0014] An intelligent positioning system for adjusting the standing posture of a patient is constructed based on the above-mentioned intelligent positioning method for adjusting the standing posture of a patient, and the system includes a data acquisition modeling module, a posture analysis and positioning module, a dynamic calibration guidance module, and a memory enhancement module; Data acquisition and modeling module, used to collect the patient's standing posture data and generate a high-precision human skeleton model to provide a basis for analysis and correction; Posture analysis and positioning module, used to analyze the patient's standing posture data in real time to identify abnormal spinal curvature, center of gravity shift and other posture problems; Dynamic calibration guidance module, used to guide patients to gradually adjust their standing posture to the correct position through intuitive visualization or dynamic prompts; The memory enhancement module is used to help patients form neuromuscular memory of correct standing posture through long-term training and achieve continuous posture optimization.

[0015] In a second aspect, an embodiment of the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program instructions are executed by the processor, the steps of an intelligent positioning system and a method thereof for facilitating adjustment of a patient's standing posture as described in the first aspect of the present invention are implemented.

[0016] In a third aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, the steps of an intelligent positioning system and method thereof for facilitating adjustment of a patient's standing posture as described in the first aspect of the present invention are implemented.

[0017] Compared with the prior art, the present invention provides an intelligent positioning system and method for facilitating adjustment of a patient's standing posture, which has the following beneficial effects: This intelligent positioning system and method for adjusting the patient's standing posture can achieve accurate detection, real-time adjustment and long-term optimization of the patient's standing posture problems by combining multimodal data collection, dynamic feedback mechanism and biomechanical analysis. It effectively solves the problems of low static evaluation accuracy, lack of dynamic feedback and poor long-term effect in the existing technology, and provides patients with an intuitive, scientific and easy-to-operate posture correction solution.

[0018] At the same time, through neuromuscular memory training, it is ensured that patients form habitual muscle memory of correct standing posture during the adjustment process, thereby greatly improving the long-term effect of posture correction and improving health level and quality of life. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 A schematic diagram of a flow chart of an intelligent positioning system method for adjusting a patient's standing posture proposed by the present invention; Figure 2 A schematic diagram of a flow chart of an intelligent posture analysis model in an intelligent positioning method for facilitating adjustment of a patient's standing posture proposed by the present invention; Figure 3 This is a schematic structural diagram of an intelligent positioning system proposed by the present invention for facilitating adjustment of a patient's standing posture. DETAILED DESCRIPTION

[0021] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0022] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0023] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0024] Embodiment 1: Reference Figure 1-2 , which is the first embodiment of the present invention, provides an intelligent positioning method for adjusting the patient's standing posture, comprising the following steps: S1. Initial pose evaluation and skeleton modeling In this embodiment, the overall standing posture data of the patient is collected by a high-precision 3D depth camera or a laser scanner, and a human skeleton model is established; Use multi-view capture technology to determine skeletal joint positions, joint angles, and body posture distribution; Combined with the human anatomy database, a machine learning algorithm is used to infer the stability of the current standing posture and its deviation from the standard standing posture, providing benchmark data for subsequent adjustments.

[0025] Specifically, dynamic modeling through multi-point tracking can identify the patient's natural standing posture in daily life, rather than the "corrected" state after deliberate adjustment. The model also needs to be able to be dynamically updated in real time to adapt to the patient's posture changes during subsequent adjustments.

[0026] S2. Calculation of center of gravity and support point distribution In this embodiment, the projection position of the center of gravity on the sole support surface is calculated through the patient's human skeleton model and combined with the sole pressure sensor data, and the uniformity and asymmetry of the sole force when standing are determined.

[0027] The stability of human standing is highly dependent on whether the center of gravity is within the support surface, especially for patients with posture problems. By capturing the force conditions in different areas of the foot through pressure sensors, it is possible to accurately locate whether the center of gravity projection is offset. In addition, using biomechanical theory to analyze the distribution of support points, such as whether one foot is overweight or the feet are unevenly distributed, can help discover hidden posture problems. These data will be used to guide subsequent adjustments to more scientifically redistribute the center of gravity and foot force.

[0028] S3. Spinal curvature and inclination detection In this embodiment, the three-dimensional curvature of the patient's spine is detected through an intelligent posture analysis algorithm, including the physiological curvature in the anterior-posterior direction including thoracic kyphosis and lumbar lordosis, as well as the scoliosis in the left-right direction.

[0029] Poor standing posture is usually accompanied by abnormal spinal curvature, so detecting the natural shape of the spine is the key to positioning. In this embodiment, non-contact ultrasonic measurement combined with a depth camera is used to achieve accurate modeling. By comparing the standard spinal curvature, abnormal points are identified and their impact on the overall standing posture is calculated. In addition, through the accurate measurement of the inclination angle and rotation angle, it is possible to quickly determine whether the patient has compensatory movements (such as tilt of the shoulders or pelvis), thereby further optimizing the adjustment strategy.

[0030] Furthermore, an intelligent posture analysis model is constructed in the intelligent posture analysis algorithm, based on the spatial curvature distribution of the spine, and multimodal sensor data is introduced for optimization; The intelligent posture analysis model includes a three-dimensional spinal curvature formula, a spinal scoliosis angle formula, and a curvature abnormality index; The three-dimensional curvature formula of the spine is used to describe the curvature of the spine at different positions; The scoliosis angle formula is used to directly reflect whether there is an overall left-right lateral deviation problem in the spine; The curvature abnormality index is used to comprehensively reflect the abnormal distribution of the entire spine.

[0031] In the intelligent posture analysis model: Assume that the spine is composed of multiple key points, marked as cervical vertebra C1 to coccygeal vertebra S5, and the three-dimensional coordinates of each key point are collected through sensor data and recorded as ,in Indicates the key point number; Three-dimensional curvature of the spine The formula is as follows: ; in, It is the length parameter of the spine, the cumulative distance from the cervical vertebrae to the coccyx; is the unit tangent vector of the spine, is the first derivative of the tangent vector; is the unit normal vector of the spine, is the first derivative of the normal vector; Represents the magnitude of a vector; The curvature of a standard spine has known normal ranges in specific regions, including the thoracic kyphotic region; The scoliosis angle formula includes: Scoliosis angle Describes the tilt of the spine in the left-right direction and is defined as: ; in, are the transverse and longitudinal coordinates of the cervical vertebrae apex, respectively; are the transverse and longitudinal coordinates of the base of the coccyx; In the bending anomaly index: Defining an anomaly index , which is used to quantify the degree of abnormality in a certain segment of the spine: ; in, is the standard curvature value corresponding to each key point.

[0032] When used, the model includes: Data collection and model input The three-dimensional coordinates of key points of the spine are obtained through depth cameras and non-contact ultrasound equipment. . Enter these coordinates into the formula to calculate the curvature , roll angle and curvature anomaly index .

[0033] Curvature calculation and deviation analysis Using the curvature formula , local curvatures are calculated at different spinal segments (e.g., cervical, thoracic, and lumbar). The results are compared with the standard spinal curvature range to generate a heat map of deviations for each spinal segment. This segmented analysis allows for quick location of problem areas, such as whether the thoracic spine is excessively kyphotic.

[0034] Tilt detection and motion compensation The roll angle formula , assessing the degree of lateral deviation of the entire spine. If the angle deviation is greater than a preset threshold (such as 5 degrees), the system will mark it as abnormal and give the patient an adjustment prompt, such as "slightly raise the right shoulder."

[0035] Optimization of bending anomaly index By bending anomaly index , quantitatively describes the abnormality of the patient's current standing posture. The system will provide personalized adjustment solutions based on this index. For example, if If the thoracic spine is significantly elevated, the system can advise the patient to adjust the shoulder posture or perform dynamic laser grid correction in this area.

[0036] Dynamic feedback and real-time correction The curvature and inclination angle data calculated by the formula are used to drive the dynamic feedback system. The abnormal area is displayed in real time, and the patient is guided to gradually adjust his standing posture through a visual interface. For example, when the bending abnormality index is reduced to a certain threshold, the patient will receive positive feedback to ensure that the adjustment is up to standard.

[0037] S4, intelligent laser-assisted posture adjustment In this embodiment, an intelligent laser projector is arranged in the patient's standing area, and the human skeleton model of the target standing posture is projected onto the patient's body surface in the form of a grid. The patient observes the deviation of the grid line and actively adjusts the body until it is aligned with the projection.

[0038] In this way, the difficulty of understanding abstract digital feedback is avoided, and the efficiency of patients' participation in posture adjustment is improved. It is especially suitable for small standing posture errors that need to be accurately corrected.

[0039] S5, Dynamic muscle activation feedback monitoring In this embodiment, the activation pattern of each major muscle group during the patient's posture adjustment is monitored by a surface electromyography (EMG) sensor to determine whether there is a compensatory action or an incorrect muscle force pattern.

[0040] Muscle activation feedback is instructive in posture adjustment, because incorrect force patterns may cause other muscles to be overloaded or joint pressure to increase. In this process, the sensor will capture the electrical activity signals of the relevant muscles in real time, and use machine learning algorithms to determine whether the muscle force meets the standard standing posture requirements. If an abnormality is found, the system will issue a prompt to guide the patient to adjust the way the muscle is exerted to avoid incorrect corrections.

[0041] S6, pelvis and lower limb alignment correction In this embodiment, the pelvic tilt and rotation are detected, and the patient is guided to achieve pelvic alignment by fine-tuning the foot position and leg muscle force. The alignment with the hip joint, knee joint and ankle is calculated based on the position data of the pelvis. The patient is guided to change the pressure distribution on the sole of the foot or adjust the hip angle to make the pelvis in a more natural horizontal state. In particular, this adjustment should be made gradually to prevent the patient from discomfort or further problems due to drastic correction.

[0042] S7, Posture Balance Prediction and Guidance In this embodiment, a deep learning model is used to predict the balance changes that may occur after the standing posture is adjusted based on the patient's current skeleton data and center of gravity projection trajectory. A wearable vibration device, such as a feedback device worn on the waist or shoulder, is used to remind the patient to fine-tune the standing position. The strength of the vibration signal is determined by the degree of imbalance to prevent the patient from being in an unstable state for a long time.

[0043] S8. Upper limb posture and scapula stability correction In this embodiment, in steps S6 and S8, the pelvic inclination and rotation are detected through a real-time posture feedback algorithm, and the patient is guided to achieve pelvic alignment by fine-tuning the foot position and leg muscle strength, and the patient's upper limb position and scapula stability are monitored, and incorrect shoulder posture is adjusted to avoid the impact of poor standing posture.

[0044] Adjustment suggestions may include lifting and pulling the shoulders back, while using elastic stretching equipment to assist correction. This method not only improves standing posture, but also reduces the risk of long-term overload of the shoulders.

[0045] S9, biofeedback-driven real-time adjustment In this embodiment, in combination with a real-time feedback interface, the difference between the patient's current standing posture and the target standing posture is displayed, and the patient is dynamically guided to complete the fine adjustment of the standing posture through a graphical interface.

[0046] The differences are dynamically displayed on the screen or wearable device through augmented reality (AR) technology. The patient makes subtle adjustments by comparing the real-time displayed skeleton model with the target standing posture model. At the same time, the system can provide specific adjustment suggestions through color, graphics or text, such as "raise the left shoulder slightly" or "move the chin forward 1cm". This instant feedback allows patients to actively participate in the adjustment process, thereby improving the effect.

[0047] S10. Long-term posture optimization and habit reshaping In this embodiment, by repeating the correction training many times, the patient gradually develops muscle memory of the correct standing posture. The ultimate goal of posture adjustment is to help the patient form a habitual standing posture, rather than relying on external equipment. By repeating the correction process and combining neuromuscular training, the patient's muscles and central nervous system form a memory of the correct standing posture. Wearable devices can be used to monitor the standing posture daily and provide periodic feedback to prevent the recurrence of bad habits.

[0048] Embodiment 2:

[0049] Reference Figure 3 , which is the second embodiment of the present invention, and this embodiment provides an intelligent positioning system that is convenient for adjusting the patient's standing posture. It is constructed based on the intelligent positioning method that is convenient for adjusting the patient's standing posture described in the first embodiment. The system includes a data acquisition modeling module, a posture analysis and positioning module, a dynamic calibration guidance module, and a memory enhancement module.

[0050] The data acquisition and modeling module is used to collect the patient's standing posture data and generate a high-precision human skeleton model to provide a basis for analysis and correction, including: Input devices: Depth cameras and non-contact ultrasound devices are used to capture three-dimensional data of the patient's spine and whole-body posture.

[0051] Data processing: Use multi-view fusion technology to generate an accurate human skeleton model, including bone points, joint positions and key nodes of the spine.

[0052] Modeling algorithm: implement the algorithm interface for spine three-dimensional curvature calculation and inclination angle detection, and input model data.

[0053] Posture analysis and positioning module, used to analyze patient standing posture data in real time, identify abnormal spinal curvature, center of gravity shift and other posture problems, including: Posture analysis: Analyze the patient's standing posture compared to the standard standing posture based on a formulated model.

[0054] Abnormality localization: Generates a heat map of abnormal areas, marking the location of the problem (such as excessive thoracic curvature or pelvic tilt) and the degree (such as mild, moderate, severe).

[0055] Feedback signal generation: pass the detection results to other modules and provide correction solutions.

[0056] The dynamic alignment guidance module is used to guide patients to gradually adjust their standing posture to the correct position through intuitive visual or dynamic prompts, including: Laser grid guidance: Using dynamic laser projection technology, the human skeleton model of the target standing posture is visually projected onto the patient, intuitively guiding the patient to align the standing posture.

[0057] Real-time feedback interface: Combined with AR technology, the comparison between the current posture and the target posture is displayed on the screen or head-mounted device, and the adjustment direction is indicated by color, marking, etc.

[0058] Wearable vibration reminder: Equipped with a vibration device on the waist or shoulder, it triggers vibration reminders of different intensities according to the degree of posture deviation.

[0059] The memory enhancement module is used to help patients form neuromuscular memory of correct standing posture through long-term training and achieve continuous posture optimization, including: Personalized training plan: Based on the initial assessment data (such as curvature anomaly index), a phased training plan is designed.

[0060] Feedback loop mechanism: monitor the patient's adjustment effect in real time and dynamically adjust the training goals and difficulty according to the progress.

[0061] Habit formation assessment: By regularly measuring posture data, the patient's neuromuscular memory is assessed to see if it is solidified, and periodic rewards or prompts are provided.

[0062] Embodiment three:

[0063] This embodiment also provides a computer device, which is suitable for a smart positioning system and method for facilitating adjustment of a patient's standing posture, and includes a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the smart positioning method for facilitating adjustment of a patient's standing posture as proposed in the above embodiment.

[0064] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the intelligent positioning method for facilitating adjustment of the patient's standing posture as proposed in the above embodiment is implemented.

[0065] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covered on the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0066] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0067] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0068] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk case (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0069] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit with a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit with a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0070] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. An intelligent positioning method for facilitating adjustment of a patient's standing posture, characterized in that: The following steps are involved: S1, initial posture evaluation and skeleton modeling; S2, calculation of center of gravity and support point distribution; S3, spinal curvature and inclination detection; S4, intelligent laser-assisted posture adjustment; S5, dynamic muscle activation feedback monitoring; S6, pelvic and lower limb alignment correction; S7, posture balance prediction and guidance; S8, upper limb posture and scapula stability correction; S9, real-time adjustment driven by biofeedback; S10. Long-term posture optimization and habit reshaping.

2. The intelligent positioning method for facilitating adjustment of a patient's standing posture according to claim 1, characterized in that: In the step S1, the overall standing posture data of the patient is collected by a high-precision 3D depth camera or a laser scanner, and a human skeleton model is established; Use multi-view capture technology to determine skeletal joint positions, joint angles, and body posture distribution; Combined with the human anatomy database, a machine learning algorithm is used to infer the stability of the current standing posture and its deviation from the standard standing posture, providing benchmark data for subsequent adjustments.

3. The intelligent positioning method for facilitating adjustment of a patient's standing posture according to claim 1, characterized in that: In step S2, the projection position of the center of gravity on the sole support surface is calculated through the patient's human skeleton model and combined with the sole pressure sensor data, and the uniformity and asymmetry of the sole force when standing are determined.

4. The intelligent positioning method for facilitating adjustment of a patient's standing posture according to claim 1, characterized in that: In step S3, the three-dimensional curvature of the patient's spine is detected by an intelligent posture analysis algorithm, including the physiological curvature in the anterior-posterior direction including thoracic kyphosis and lumbar lordosis, and the scoliosis in the left-right direction.

5. The intelligent positioning method for facilitating adjustment of a patient's standing posture according to claim 4, characterized in that: In the intelligent posture analysis algorithm, an intelligent posture analysis model is constructed based on the spatial curvature distribution of the spine and multimodal sensor data is introduced for optimization; The intelligent posture analysis model includes a three-dimensional spinal curvature formula, a spinal scoliosis angle formula, and a curvature abnormality index; The three-dimensional curvature formula of the spine is used to describe the curvature of the spine at different positions; The scoliosis angle formula is used to directly reflect whether there is an overall left-right lateral deviation problem in the spine; The curvature abnormality index is used to comprehensively reflect the abnormal distribution of the entire spine.

6. The intelligent positioning method for facilitating adjustment of a patient's standing posture according to claim 5, characterized in that: In the intelligent posture analysis model: Assume that the spine is composed of multiple key points, marked as cervical vertebra C1 to coccygeal vertebra S5, and the three-dimensional coordinates of each key point are collected through sensor data and recorded as ,in Indicates the key point number; Three-dimensional curvature of the spine The formula is as follows: ； in, It is the length parameter of the spine, the cumulative distance from the cervical vertebrae to the coccyx; is the unit tangent vector of the spine, is the first derivative of the tangent vector; is the unit normal vector of the spine, is the first derivative of the normal vector; Represents the magnitude of a vector; The curvature of a standard spine has known normal ranges in specific regions, including the thoracic kyphotic region; The scoliosis angle formula includes: Scoliosis angle Describes the tilt of the spine in the left-right direction and is defined as: ； in, are the transverse and longitudinal coordinates of the cervical vertebrae apex, respectively; are the transverse and longitudinal coordinates of the base of the coccyx; In the bend anomaly index: Defining an anomaly index , which is used to quantify the degree of abnormality in a certain segment of the spine: ； in, is the standard curvature value corresponding to each key point.

7. The intelligent positioning method for facilitating adjustment of a patient's standing posture according to claim 1, characterized in that: In step S4, an intelligent laser projector is arranged in the patient's standing area to project the human skeleton model of the target standing posture onto the patient's body surface in the form of a grid. The patient observes the deviation of the grid line and actively adjusts the body until it is aligned with the projection.

8. The intelligent positioning method for facilitating adjustment of a patient's standing posture according to claim 1, characterized in that: In step S5, the activation pattern of each major muscle group during the patient's posture adjustment is monitored by a surface electromyography (EMG) sensor to determine whether there is a compensatory action or an incorrect muscle force pattern.

9. The intelligent positioning method for facilitating adjustment of a patient's standing posture according to claim 1, characterized in that: In steps S6 and S8, the pelvic inclination and rotation are detected through a real-time posture feedback algorithm, and the patient is guided to achieve pelvic alignment by fine-tuning the foot position and leg muscle force. The patient's upper limb position and scapula stability are monitored, and incorrect shoulder posture is adjusted to avoid the impact of a bad standing posture.

10. An intelligent positioning system for facilitating adjustment of a patient's standing posture, constructed based on an intelligent positioning method for facilitating adjustment of a patient's standing posture as claimed in any one of claims 1 to 9, characterized in that: The system includes a data acquisition modeling module, a posture analysis and positioning module, a dynamic calibration guidance module, and a memory enhancement module; Data acquisition and modeling module, used to collect the patient's standing posture data and generate a high-precision human skeleton model to provide a basis for analysis and correction; Posture analysis and positioning module, used to analyze the patient's standing posture data in real time to identify abnormal spinal curvature, center of gravity shift and other posture problems; Dynamic calibration guidance module, used to guide patients to gradually adjust their standing posture to the correct position through intuitive visualization or dynamic prompts; The memory enhancement module is used to help patients form neuromuscular memory of correct standing posture through long-term training and achieve continuous posture optimization.

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