Intelligent training system for treating scoliosis

Abstract

The invention discloses an intelligent training system for treating scoliosis. A posture sensing module in the system is used for collecting first three-dimensional position data of a preset key point of a spine, collecting inclination angle and rotation angle data of a pelvis and collecting second three-dimensional position data of a scapula; a main controller in the system is used for fitting the first three-dimensional position data to construct an actual curve of the spine, determining a lateral bending angle of the spine according to the actual curve, and judging the inclination degree of the inclination angle relative to a preset human body sagittal plane; judging the right-handed rotation degree of the rotation angle data relative to a preset vertical axis; calculating according to the second three-dimensional position data to obtain a motion track of the shoulder blade, and determining a deviation degree of the motion track; and finally, determining the scoliosis degree of the spine based on the scoliosis angle, the inclination degree, the dextrorotation degree and the deviation degree. The scoliosis degree detection accuracy is effectively improved by implementing the scoliosis degree detection method and the scoliosis degree detection device.

Description

Technical Field

[0001] The present invention relates to the field of medical devices, and in particular to an intelligent training system for treating scoliosis. Background Art

[0002] Scoliosis is a common spinal deformity disease that has a serious impact on the patient's physical health and quality of life. Early accurate diagnosis and effective treatment intervention are essential to control the progression of the disease.

[0003] In the prior art, most monitoring methods can only focus on parameters of a single dimension. For example, some devices only focus on collecting the angle information of the spine, and preliminarily judge the morphological changes of the spine through simple angle measurements. However, the health of the spine is a complex whole, and relying solely on a single angle data is far from sufficient to fully and accurately reflect the actual condition of the spine. This current situation of only being able to monitor a single parameter has led to the lack of multi-dimensional data fusion capabilities in the intelligent training system used to treat scoliosis in the prior art, which cannot accurately assess the degree of scoliosis of the spine, resulting in poor training results. Summary of the invention

[0004] The present invention provides an intelligent training system for treating scoliosis. The system effectively solves the problem of the prior art that scoliosis detection is performed only from a single dimension. The system determines the degree of scoliosis of the patient's spine by comprehensively considering the scoliosis angle of the patient's spine, the degree of inclination of the patient's pelvis, the degree of right rotation of the patient's pelvis, and the degree of deviation of the patient's scapula running trajectory, thereby significantly improving the accuracy and effectiveness of scoliosis detection.

[0005] An embodiment of the present invention provides an intelligent training system for treating scoliosis, comprising: a posture sensing module and a main controller; The posture sensing module is used to collect first three-dimensional position data of preset key points of the spine; collect inclination angle and rotation angle data of the pelvis; collect second three-dimensional position data of the shoulder blade; and send the first three-dimensional position data, the inclination angle, the rotation angle data and the second three-dimensional position data to the main controller; The main controller is used to fit the first three-dimensional position data according to a preset spline curve fitting algorithm, construct an actual curve of the spine, and compare the actual curve with a preset standard curve to determine the scoliosis angle of the spine; judge the degree of inclination of the inclination angle relative to a preset human sagittal plane according to a preset forward tilt angle standard interval; judge the degree of right rotation of the rotation angle data relative to a preset vertical axis according to a preset right rotation standard interval; calculate the movement trajectory of the scapula according to the second three-dimensional position data, and determine the degree of deviation of the movement trajectory based on the preset standard movement trajectory; determine the degree of scoliosis of the spine according to the scoliosis angle, the degree of inclination, the degree of right rotation, the degree of deviation and a preset first weight distribution relationship.

[0006] Furthermore, the intelligent training system for treating scoliosis further includes: a pressure sensing module; The pressure sensing module is used to collect pressure distribution data borne by a preset human body support part and send the pressure distribution data to the main controller; The main controller is also used to generate a pressure distribution thermodynamic map based on a preset thermodynamic map drawing function and the pressure distribution data, and determine the pressure state of the human body support part according to the pressure distribution thermodynamic map; and obtain the corrected scoliosis degree of the spine according to the scoliosis angle, the inclination degree, the right rotation degree, the deviation degree, the pressure state and a preset second weight distribution relationship.

[0007] Furthermore, the human body support part includes the spine and the sole of the foot; the pressure distribution data includes first pressure distribution data for reflecting the stress condition of the spine and second pressure distribution data for reflecting the stress condition of the sole of the foot; The step of generating a pressure distribution thermodynamic map based on a preset thermodynamic map drawing function and the pressure distribution data, and determining the pressure state of the supporting part of the human body according to the pressure distribution thermodynamic map, comprises: generating a first pressure distribution thermodynamic map according to the first pressure distribution data and the thermodynamic map drawing function; Determining the compression state of the spine according to the pressure distribution on both sides of the spine in the first pressure distribution thermodynamic map; generating a second pressure distribution thermodynamic map according to the second pressure distribution data and the thermodynamic map drawing function; The pressure state of the sole is determined according to a first ratio between the pressure value of the outer side of the sole and the pressure value of the entire sole in the second pressure distribution thermogram and a second ratio between the pressure value of the forefoot and the pressure value of the entire sole in the second pressure distribution thermogram.

[0008] Further, the posture sensing module includes a main sensor, an auxiliary sensor and a reference sensor; The main sensor is used to collect first three-dimensional position data of preset key points of the spine and send the first three-dimensional position data to the main controller; The auxiliary sensor is used to collect the inclination angle and rotation angle data of the pelvis, and send the inclination angle and the rotation angle data to the main controller; The reference sensor is used to collect the second three-dimensional position data of the scapula and send the second three-dimensional position data to the main controller.

[0009] Furthermore, the intelligent training system for treating scoliosis further includes: an electromyographic acquisition module and a therapeutic device; The electromyography acquisition module is used to collect surface electromyography signals of the erector spinae muscles on both sides of the spine and send the surface electromyography signals to the main controller; The main controller is also used to determine the muscle state of the erector spinae muscle based on the surface electromyographic signal; determine the target training mode of the therapeutic device based on the degree of scoliosis and the muscle state, so that the therapeutic device works according to the target training mode; wherein the target training mode includes: normal movement mode, relaxation recovery mode and intensive correction mode.

[0010] Furthermore, the muscle state of the erector spinae muscle includes a muscle activity state and a muscle fatigue state; Determining the muscle state of the erector spinae muscle according to the surface electromyographic signal includes: Determine whether the RMS values ​​of the surface electromyography signals in the preset time period are all greater than the preset threshold value, If yes, it is determined that the muscle activity state of the erector spinae muscle in the preset time period is in a contraction state, On the contrary, it is determined that the muscle activity state of the erector spinae muscle in the preset time period is in a relaxed state; Determine whether the difference between the average median frequency value of the surface electromyography signal in the preset time period and the preset initial median frequency value is greater than a preset fatigue threshold, If yes, it is determined that the muscle fatigue state of the erector spinae muscle in the preset time period is in a fatigue state, On the contrary, it is determined that the muscle fatigue state of the erector spinae muscle in the preset time period is not in a fatigue state.

[0011] Furthermore, the intelligent training system for treating scoliosis further includes: a human-machine interface server and a human-machine interface client; The human-machine interface server is used to obtain the personalized setting parameters transmitted by the human-machine interface client; generate a personalized adjustment instruction according to the personalized setting parameters, and transmit the personalized adjustment instruction to the main controller; wherein the personalized setting parameters include light color, light flashing frequency, vibration mode to be switched, training mode to be switched, and decibel size of the prompt audio; The main controller is further used to parse the personalized adjustment instruction to obtain the type of the multimodal auxiliary module to be driven and the corresponding personalized setting parameters; and drive the corresponding multimodal auxiliary module to operate according to the type of the multimodal auxiliary module to be driven and the corresponding personalized setting parameters; wherein the types of the multimodal auxiliary modules include vibration modules, light auxiliary modules and sound auxiliary modules.

[0012] Furthermore, the therapeutic apparatus comprises: a vibration module; The vibration module is used to, after determining the target training mode, perform vibration output according to the initial vibration mode matched by the target training mode; and, according to the personalized adjustment instruction, adjust the vibration mode that requires vibration output; wherein the vibration mode includes a constant pressure mode, a pulse mode, a gradual change mode and a wave mode.

[0013] Furthermore, the therapeutic apparatus further comprises: a light-assisted module; The light auxiliary module is used to emit light according to the initial light mode matched by the target training mode after determining the target training mode; and adjust the light color or light flashing frequency of the initial light mode according to the personalized adjustment instruction; wherein each of the initial light modes includes a light color and a light flashing frequency.

[0014] Furthermore, the therapeutic apparatus further comprises: a sound auxiliary module; The sound auxiliary module is used to emit a prompt audio that matches the preset time point when it is recognized that the set duration of the target training mode reaches the preset time point; and adjust the decibel level of the prompt audio according to the personalized adjustment instruction.

[0015] The following beneficial effects are achieved by implementing the present invention: The present invention provides an intelligent training system for treating scoliosis, the system comprising a posture sensing module, a pressure sensing module, an electromyographic acquisition module, a main controller and a therapeutic device; The posture sensing module is used to collect the first three-dimensional position data of the preset key points of the spine; collect the inclination angle and rotation angle data of the pelvis; collect the second three-dimensional position data of the scapula; thus, by detecting the relevant data of the human spine, pelvis and scapula, a multi-dimensional data basis is provided for the subsequent analysis of the scoliosis degree of the spine, which effectively solves the problem that the existing technology only detects scoliosis from a single dimension; The main controller is used to fit the first three-dimensional position data according to a preset spline curve fitting algorithm, construct the actual curve of the spine, and compare the actual curve with the preset standard curve to determine the scoliosis angle of the spine; judge the degree of inclination of the inclination angle relative to the preset human sagittal plane according to the preset forward tilt angle standard interval; judge the degree of right rotation of the rotation angle data relative to the preset vertical axis according to the preset right rotation standard interval; calculate the movement trajectory of the scapula according to the second three-dimensional position data, and determine the degree of deviation of the movement trajectory based on the preset standard movement trajectory; determine the degree of scoliosis of the spine according to the scoliosis angle, the degree of inclination, the degree of right rotation, the degree of deviation and a preset first weight distribution relationship; thus, the main controller determines the degree of scoliosis of the patient's spine by comprehensively considering the scoliosis angle of the patient's spine, the degree of inclination of the patient's pelvis, the degree of right rotation of the patient's pelvis and the degree of deviation of the patient's scapula running trajectory, thereby significantly improving the accuracy and effectiveness of scoliosis detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solution of the present application, the drawings required for use in the implementation manner will be briefly introduced below. Obviously, the drawings described below are only some implementation manners of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0017] Figure 1 is a first structural schematic diagram of an intelligent training system for treating scoliosis provided in a certain embodiment of the present application; Figure 2 is a second structural schematic diagram of an intelligent training system for treating scoliosis provided by a certain embodiment of the present application; Figure 3 is a third structural schematic diagram of an intelligent training system for treating scoliosis provided by a certain embodiment of the present application; Figure 4 is a fourth structural schematic diagram of an intelligent training system for treating scoliosis provided by a certain embodiment of the present application; Figure 5 This is the fifth structural schematic diagram of the intelligent training system for treating scoliosis provided in a certain embodiment of the present application.

[0018] Description of reference numerals: Posture sensor module 1 Main sensor 1-1 Auxiliary sensor 1-2 Reference sensor 1-3 Main controller 2 Pressure sensor module 3 Myoelectric acquisition module 4 Therapeutic device 5 Vibration module 5-1 Light auxiliary module 5-2 Sound auxiliary module 5-3 Human-machine interface server 6 Human-machine interface client 7 DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" in the specification and claims of this application and the above-mentioned figure descriptions and any variations thereof are intended to cover non-exclusive inclusions.

[0021] In the description of the embodiments of the present application, the technical terms "first", "second", etc. are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number, specific order or primary and secondary relationship of the indicated technical features. In the description of the embodiments of the present application, the meaning of "multiple" is more than two, unless otherwise clearly and specifically defined.

[0022] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0023] In the description of the embodiments of the present application, the term "and / or" is only a description of the association relationship of the associated objects, indicating that there may be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0024] In the description of the embodiments of the present application, the term "multiple" refers to more than two (including two). Similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).

[0025] In the description of the embodiments of the present application, unless otherwise clearly specified and limited, technical terms such as "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, and it can be the internal connection of two elements or the interaction relationship between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the embodiments of the present application can be understood according to the specific circumstances.

[0026] See also Figure 1 , is an intelligent training system for treating scoliosis provided by an embodiment of the present invention, comprising: a posture sensing module 1 and a main controller 2; The posture sensing module 1 is used to collect the first three-dimensional position data of the preset key points of the spine; collect the inclination angle and rotation angle data of the pelvis; collect the second three-dimensional position data of the shoulder blade; and send the first three-dimensional position data, the inclination angle, the rotation angle data and the second three-dimensional position data to the main controller; The main controller 2 is used to fit the first three-dimensional position data according to a preset spline curve fitting algorithm, construct an actual curve of the spine, and compare the actual curve with a preset standard curve to determine the scoliosis angle of the spine; judge the degree of inclination of the inclination angle relative to a preset human sagittal plane according to a preset forward tilt angle standard interval; judge the degree of right rotation of the rotation angle data relative to a preset vertical axis according to a preset right rotation standard interval; calculate the motion trajectory of the scapula according to the second three-dimensional position data, and determine the degree of deviation of the motion trajectory based on a preset standard motion trajectory; determine the degree of scoliosis of the spine according to the scoliosis angle, the degree of inclination, the degree of right rotation, the degree of deviation and a preset first weight distribution relationship; Schematically, the posture sensing module 1 measures the posture data of preset key points of the patient's spine, measures the tilt state of the patient's pelvis, measures the rotation angle data of the patient's pelvis, and measures the second three-dimensional position data of the patient's shoulder blade; See also Figure 2 , in a preferred embodiment, the posture sensing module 1 includes a main sensor 1-1, an auxiliary sensor 1-2 and a reference sensor 1-3; The main sensor 1-1 is used to collect first three-dimensional position data of preset key points of the spine, and send the first three-dimensional position data to the main controller 2; The auxiliary sensor 1-2 is used to collect the inclination angle and rotation angle data of the pelvis, and send the inclination angle and the rotation angle data to the main controller 2; The reference sensor 1-3 is used to collect the second three-dimensional position data of the shoulder blade and send the second three-dimensional position data to the main controller 2; Schematically, by dividing the posture sensing module 1 into a main sensor 1-1, an auxiliary sensor 1-2 and a reference sensor 1-3, when data of a specific part of the patient needs to be recollected, only the corresponding sensor needs to be enabled without affecting the normal operation of other sensors.

[0027] Specifically, the preset key points of the spine are selected from the T1-L5 spinal key points of the human body; it should be noted that the T1-L5 spinal key points are common knowledge in human anatomy and related medical and rehabilitation fields, and their specific positions are well known to technicians in this field, so the specific positions of the T1-L5 spinal key points will not be elaborated here.

[0028] Schematically, the first three-dimensional position data is fitted by a preset spline curve fitting algorithm to construct the actual curve of the spine, and the actual curve is compared with a preset standard curve to determine the scoliosis angle of the spine; specifically, assuming that the first three-dimensional position data of the T1-L5 spine key points collected are (x T1 ,y T1 , z T1 )、(x T2 ,y T2 , z T2 )、(x T3 ,y T3 , z T3 ),...,(x L5 ,y L5 , z L5 ); Then, the main controller 2 performs curve fitting according to the preset spline curve fitting algorithm and the first three-dimensional position data corresponding to each of the T1-L5 spine key points, so as to construct the actual curve of the patient's spine; it should be noted that the spline curve fitting algorithm can be a cubic spline curve fitting algorithm, which constructs a series of cubic polynomial functions to ensure that the first-order derivative and the second-order derivative of the curve at each point are continuous while ensuring that the curve passes through all data points, so that the fitted curve is smoother and can more accurately reflect the actual shape of the spine; Then, the actual curve obtained by fitting is compared with the preset standard curve (which is an ideal projection line of the human spine on the coronal plane. The standard curve is obtained based on the statistical analysis of the spinal data of a large number of healthy people and represents the ideal shape and position relationship that the normal human spine should present on the coronal plane). After the two curves are projected onto the coronal plane, the vertebrae at the upper and lower ends of the scoliosis of the actual curve are found, and perpendicular lines are drawn to the upper and lower end plates of the two vertebrae respectively, and the angle between the two perpendicular lines is calculated, thereby calculating the scoliosis angle of the spine.

[0029] Schematically, according to a preset standard range of the forward tilt angle, the degree of tilt of the tilt angle relative to a preset human body sagittal plane is determined; It should be noted that the preset human sagittal plane is perpendicular to the ground and perpendicular to the coronal plane. On the sagittal plane, the structural relationship of the human body in the front-back direction can be clearly observed, such as the physiological curvature of the spine, the shape of the vertebral body, etc. The sagittal plane can accurately determine the posture changes such as the forward and backward tilt of the spine, providing an important basis for diagnosing spinal diseases; in this embodiment, when describing the pelvic forward tilt angle, it is measured by the degree of inclination of the pelvis relative to the human sagittal plane; Specifically, the normal range of the pelvic tilt angle for adults is between 5° and 10°. Therefore, in this embodiment, the standard tilt angle interval is also set to 5°-10°; when the tilt angle is between 10° and 15°, the tilt degree is determined to be mild pelvic tilt; when the tilt angle is between 15° and 20°, the tilt degree is determined to be moderate tilt; when the tilt angle is greater than 20°, the tilt degree is determined to be severe tilt.

[0030] Indicatively, according to a preset right-hand standard interval, the right-hand degree of the rotation angle data relative to a preset vertical axis is determined; It should be noted that the vertical axis is an imaginary axis that is perpendicular to the ground, runs through the upper and lower parts of the human body, and extends from the top of the head to the soles of the feet. In an anatomical posture, the human body performs rotational movement around the vertical axis, such as the left and right rotation of the spine. For example, when twisting the waist, the spine will perform rotational movement around the vertical axis. Specifically, in the initial state of the patient standing naturally, the pelvic markers are positioned. Then, the patient is asked to perform a simple twisting movement, and the posture sensing module 1 collects the rotation angle data of the patient's pelvis relative to the initial position, and the right rotation angle of the pelvis relative to the vertical axis finally measured is the rotation angle data; From the statistical analysis of the data, it can be obtained that in the daily activities of normal healthy adult people, the rotation range of the pelvis in a normal state is usually 0°-3°. Therefore, in the present embodiment, the standard interval of the right rotation angle is also set to 0°-3°; then the collected rotation angle data is compared with the preset right rotation standard interval; when the rotation angle data is between 0°-3°, the right rotation degree is determined to be within the normal range; when the rotation angle data is 3°-6°, the right rotation degree is determined to be a mild right rotation abnormality; when the rotation angle data is 6°-9°, the right rotation degree is determined to be a moderate right rotation abnormality; when the rotation angle data is greater than 9°, the right rotation degree is determined to be a severe right rotation abnormality.

[0031] Schematically, the motion trajectory of the scapula is calculated according to the second three-dimensional position data, and the degree of deviation of the motion trajectory is determined based on a preset standard motion trajectory; Specifically, several key marking points are selected on the patient's scapula, and the marking points include the acromion, the inferior angle of the scapula, etc., which are not limited here; it should be noted that the setting of the above-mentioned marking points should fully consider the stretching trend of the joints or muscles when the patient performs shoulder training movements, and setting the marking points according to the above-mentioned stretching trend can effectively improve the accuracy of the subsequent fitting motion trajectory and the calculation of the trajectory overlap; Then, the patient is asked to perform a set of specific shoulder training movements (such as raising the arm forward). During the training process, the posture sensing module 1 is used to record the second three-dimensional position data of the marking point during the training process, and the preset interpolation algorithm is used to fit these discrete second three-dimensional position data to obtain a motion trajectory representing the scapula; Schematically, the fitted motion trajectory is compared with the pre-set standard motion trajectory, and the degree of deviation is determined according to the degree of overlap; Specifically, the curvature of the fitted motion trajectory and the standard motion trajectory at each marked point is calculated. Since the curvature can reflect the degree of bending of the motion trajectory, if the curvatures of the two trajectories at the same position are similar, it means that their shapes are similar near the key point. In this embodiment, the overall similarity of the trajectory shapes is evaluated by calculating the absolute value of the difference in the curvature of each marked point between the motion trajectory and the standard motion trajectory, and summing and averaging the curvatures of all marked points to obtain the coincidence R, and a coincidence threshold R1 is preset (wherein R1 is a preset mild deviation threshold, which can be determined based on a large amount of experimental data and clinical experience). If R≤R1, the degree of deviation is determined to be mild; if R1≤R≤R2 (wherein R2 is a preset moderate deviation threshold, which can be determined based on a large amount of experimental data and clinical experience), the degree of deviation is determined to be moderate; if R≥R2, the degree of deviation is determined to be severe.

[0032] Schematically, the degree of scoliosis of the spine is determined according to the scoliosis angle, the inclination degree, the right rotation degree, the deviation degree and a preset first weight distribution relationship; Specifically, assuming that the scoliosis angle of the current patient's spine is 12°, the score corresponding to the scoliosis angle parameter is set to 12; assuming that the inclination of the current patient's pelvis is mild, the inclination of the patient is quantified as a value of 1 (when the inclination is mild forward tilt, it is quantified as a value of 1, when the inclination is moderate forward tilt, it is quantified as a value of 2, and when the inclination is severe forward tilt, it is quantified as a value of 3); assuming that the right rotation of the current patient's pelvis is moderate right rotation abnormality, the right rotation of the patient is quantified as a value of 2 (when the right rotation is mild right rotation abnormality, it is quantified as a value of 1, when the right rotation is moderate right rotation abnormality, it is quantified as a value of 2, and when the right rotation is severe right rotation abnormality, it is quantified as a value of 3); assuming that the deviation of the current patient's scapula is mild deviation, the deviation of the patient is quantified as a value of 1 (when the deviation is mild deviation, it is quantified as a value of 1, when the deviation is moderate deviation, it is quantified as a value of 2, and when the deviation is severe deviation, it is quantified as a value of 3); Assume that the first weight distribution relationship is: the side bending angle is given a weight of w1=0.4, the tilt degree is given a weight of w2=0.2, the right rotation degree is given a weight of w3=0.2, and the deviation degree is given a weight of w4=0.2; The scoliosis angle, the tilt degree, the right rotation degree, and the deviation degree are multiplied by the corresponding weights to calculate a comprehensive score of the current patient's scoliosis degree: S=12*0.4+1*0.2+2*0.2+1*0.2=5.6; The degree of scoliosis of the patient's spine is determined based on the corresponding relationship between the comprehensive score and the preset value. Specifically, 0-3 points indicate mild scoliosis, 3-6 points indicate moderate scoliosis, and 6-10 points indicate severe scoliosis. Since the patient's comprehensive score is 5.6, it is determined that the degree of scoliosis of the patient's spine is in a moderate scoliosis state.

[0033] See also Figure 3 In a preferred embodiment, the intelligent training system for treating scoliosis further comprises: Pressure sensing module 3; The pressure sensing module 3 is used to collect the pressure distribution data of the preset supporting part of the human body and send the pressure distribution data to the main controller 2; The main controller 2 is further used to generate a pressure distribution thermodynamic map based on a preset thermodynamic map drawing function and the pressure distribution data, and determine the pressure state of the supporting part of the human body according to the pressure distribution thermodynamic map; and obtain a corrected scoliosis degree of the spine according to the scoliosis angle, the inclination degree, the right rotation degree, the deviation degree, the pressure state and a preset second weight distribution relationship; In a preferred embodiment, the human body supporting part includes a spine and a sole; the pressure distribution data includes first pressure distribution data for reflecting the stress condition of the spine and second pressure distribution data for reflecting the stress condition of the sole; the method of generating a pressure distribution thermogram based on a preset thermogram drawing function and the pressure distribution data, and determining the pressure state of the human body supporting part according to the pressure distribution thermogram includes: generating a first pressure distribution thermodynamic map according to the first pressure distribution data and the thermodynamic map drawing function; Determining the compression state of the spine according to the pressure distribution on both sides of the spine in the first pressure distribution thermodynamic map; generating a second pressure distribution thermodynamic map according to the second pressure distribution data and the thermodynamic map drawing function; Determining the pressure state of the sole according to a first ratio between the pressure value of the lateral side of the sole and the pressure value of the entire sole in the second pressure distribution thermogram and a second ratio between the pressure value of the forefoot and the pressure value of the entire sole in the second pressure distribution thermogram; Schematically, the pressure distribution data of the preset patient's body support part is collected through the pressure sensing module 3; It should be noted that the setting of the human body support part can be adjusted according to actual conditions. In this embodiment, in order to more accurately obtain pressure data related to the health status of the spine, so as to provide more reliable data support for the subsequent judgment of the degree of scoliosis and the formulation of training programs, the human body support part is set to the spine and the sole of the foot; the sensor type of the pressure sensing module 3 is a thin film pressure sensor array; the thin film pressure sensor array has the characteristics of being light and sensitive, and can accurately collect pressure distribution data, providing a reliable basis for subsequent analysis; Specifically, in the deployment scheme based on the patient's spine, this embodiment is deployed on both sides of the patient's spine T1-L5 spinal key points; Specifically, in the deployment scheme based on the sole of the patient's foot, (1) sensors are arranged at the center and edge of the heel respectively; (2) because the forefoot is an important part of the human body that exerts force when walking and running, especially the metatarsal head area is subject to greater pressure, so sensors are arranged under each metatarsal head to accurately measure the pressure of various parts of the forefoot; (3) sensors are arranged in sequence from the heel to the forefoot along the lateral edge of the sole; because the lateral side of the sole plays a certain supporting and stabilizing role during walking and exercise, the change in pressure in this area can reflect the tendency of the foot to evert or invert, and thus reflect the potential impact on the spinal posture; (4) because the arch of the foot has elasticity and buffering effect, the pressure is relatively small and the distribution is more complex, so a thin film pressure sensor array is arranged on the inner, outer and middle parts of the arch of the foot; Specifically, the first pressure distribution data is processed using a preset thermal map drawing function to generate a first pressure distribution thermal map; Identify the symmetry of the pressure distribution on both sides of the spine in the first pressure distribution thermodynamic map. If the pressure distribution on both sides is basically symmetrical and the color depth is similar, it means that the spine is relatively evenly compressed and there is no obvious uneven force. If the color difference on both sides is greater than a preset color difference threshold (the color difference threshold is determined through a large amount of clinical data and experimental research, and is determined by collecting a large amount of spinal pressure distribution thermodynamic map data of healthy people and patients with spinal diseases in advance), it is determined that the spine has uneven force. Specifically, the second pressure distribution data is processed using the heat map drawing function to generate a second pressure distribution heat map. In the second pressure distribution heat map, a first ratio between the pressure value on the outside of the sole and the pressure value on the entire sole is calculated, that is, the pressure values ​​collected by all the thin film pressure sensor arrays on the outside of the sole are summed, and then divided by the sum of the pressure values ​​collected by all the thin film pressure sensor arrays on the entire sole, to obtain the first ratio; Similarly, the second ratio between the pressure value of the forefoot and the pressure value of the entire sole is calculated, that is, the pressure values ​​collected by all the thin film pressure sensor arrays of the forefoot (including the metatarsal head area) are summed, and then divided by the sum of the pressure values ​​collected by all the thin film pressure sensor arrays of the entire sole to obtain the second ratio; determining whether the first proportion is within a preset first normal range (the first normal range refers to a normal balance range between the pressure on the outside of the sole of a healthy person and the pressure on the entire sole of the foot, and the range is determined by collecting a large number of plantar pressure distribution thermogram data of healthy people and patients with spinal diseases in advance), and if so, it means that the pressure on the sole of the patient is relatively uniform; If the first ratio exceeds the first normal range, it means that the pressure on the outer side of the sole is too much, and there is a tendency for the foot to evert; If the second ratio exceeds a preset second normal range (the second normal range refers to the normal balance range between the pressure on the forefoot and the pressure on the entire sole of the foot in healthy people, and this range is determined by collecting a large number of plantar pressure distribution thermogram data from healthy people and patients with spinal diseases in advance), it indicates that the forefoot is under excessive pressure.

[0034] Schematically, in order to better improve the accuracy of the scoliosis degree, the corrected scoliosis degree of the spine is obtained according to the scoliosis angle, the inclination degree, the right rotation degree, the deviation degree, the compression state and the preset second weight distribution relationship; Specifically, when it is determined that the patient's spine is in a state of uneven force, the compression state of the spine is quantified as a number 3, otherwise it is quantified as a number 0; Similarly, when it is determined that the first proportion of the patient exceeds the first normal range and the second proportion exceeds the preset second normal range, the pressure state of the sole is quantified as a number 5; when it is determined that the first proportion of the patient exceeds the first normal range and the second proportion is within the preset second normal range, the pressure state of the sole is quantified as a number 3; when it is determined that the first proportion of the patient is within the first normal range and the second proportion exceeds the preset second normal range, the pressure state of the sole is quantified as a number 3; otherwise, the pressure state of the sole is quantified as a number 0; Then, the values ​​obtained after quantifying the pressure state of the sole of the foot and the pressure state of the spine are used as the quantified values ​​of the pressure state.

[0035] Assume that the second weight distribution relationship is: the side bending angle is given a weight of w1=0.4, the tilt degree is given a weight of w2=0.15, the right rotation degree is given a weight of w3=0.15, the deviation degree is given a weight of w4=0.2, and the compression state is given a weight of w5=0.1; Assuming that the compression state score of the patient's spine is 3, the compression state score of the patient's sole is 3, and the compression state score of the patient is 6; the scoliosis angle, the inclination degree, the right rotation degree, the deviation degree, the compression state of the spine, and the compression state of the sole are multiplied by the corresponding weights respectively to calculate the comprehensive score of the current patient's scoliosis degree: S=12*0.4+1*0.15+2*0.15+1*0.2+6*0.1=6.05; The degree of scoliosis of the patient's spine is determined based on the corresponding relationship between the comprehensive score and the preset setting; specifically, 0-3 points indicate mild scoliosis, 3-6 points indicate moderate scoliosis, and 6-10 points indicate severe scoliosis. Since the patient's comprehensive score is 6.05, it is determined that the degree of scoliosis of the patient's spine is in a severe scoliosis state.

[0036] See also Figure 4 In a preferred embodiment, the intelligent training system for treating scoliosis further comprises: Myoelectric acquisition module 4 and therapeutic device 5; The electromyography acquisition module 4 is used to collect surface electromyography signals of the erector spinae muscles on both sides of the spine and send the surface electromyography signals to the main controller 2; The main controller 2 is also used to determine the muscle state of the erector spinae muscle based on the surface electromyographic signal; determine the target training mode of the therapeutic device 5 based on the degree of scoliosis and the muscle state, so that the therapeutic device 5 works according to the target training mode; wherein the target training mode includes: normal movement mode, relaxation recovery mode and intensive correction mode.

[0037] In a preferred embodiment, the muscle state of the erector spinae muscle includes a muscle activity state and a muscle fatigue state; and determining the muscle state of the erector spinae muscle according to the surface electromyography signal includes: Determine whether the RMS values ​​of the surface electromyography signals in the preset time period are all greater than the preset threshold value, If yes, it is determined that the muscle activity state of the erector spinae muscle in the preset time period is in a contraction state, On the contrary, it is determined that the muscle activity state of the erector spinae muscle in the preset time period is in a relaxed state; Determine whether the difference between the average median frequency value of the surface electromyography signal in the preset time period and the preset initial median frequency value is greater than a preset fatigue threshold, If yes, it is determined that the muscle fatigue state of the erector spinae muscle in the preset time period is in a fatigue state, On the contrary, it is determined that the muscle fatigue state of the erector spinae muscle in the preset time period is not in a fatigue state; Specifically, at the beginning of training, the electromyographic acquisition module 4 acquires the surface electromyographic signal of the erector spinae muscle, assuming that the initial median frequency value of the patient's left erector spinae muscle is 90 Hz, and the initial median frequency value of the right erector spinae muscle is 92 Hz. At the same time, through a large number of experiments and clinical studies, it has been determined that the preset threshold for judging the muscle activity state is 15 μV, and the preset fatigue threshold for judging the muscle fatigue state is 12 Hz; Assume that the preset time period lasts for 15 seconds; then within the preset time period of 15 seconds, the main controller 2 monitors the RMS value of the surface electromyographic signal of the left erector spinae muscle in real time; it is found that the RMS values ​​fluctuate between 8-12μV, which are all less than the preset threshold value of 15μV, then, it is determined that the muscle activity state of the left erector spinae muscle is in a relaxed state within these 15 seconds; the main controller 2 calculates the median frequency value of the surface electromyographic signal of the left erector spinae muscle within the preset time period to be 88Hz on average, and the difference with the initial median frequency value of 90Hz is 2Hz, which is less than the preset fatigue threshold value of 12Hz, so it is determined that the muscle fatigue state of the left erector spinae muscle is not in a fatigue state within these 15 seconds.

[0038] Similarly, the RMS value of the surface electromyographic signal of the erector spinae muscle on the right side is between 20-25 μV in these 15 seconds, which is greater than the preset threshold value of 15 μV. Therefore, it is determined that the muscle activity state of the erector spinae muscle on the right side is in a contraction state in these 15 seconds. The median frequency value of the surface electromyographic signal of the erector spinae muscle on the right side in the preset period is 91 Hz on average, and the difference from the initial median frequency value of 92 Hz is 1 Hz, which is less than the preset fatigue threshold value of 12 Hz. Therefore, it is determined that the muscle fatigue state of the erector spinae muscle on the right side is not in a fatigue state in these 15 seconds.

[0039] Specifically, when the patient's spinal scoliosis is mild, the erector spinae muscle activity state in N preset time periods shows regular and coordinated contraction and relaxation (that is, the RMS value of the surface electromyographic signal has normal fluctuations in different time periods and will not be continuously at too high or too low levels), and the erector spinae muscle is not in a fatigue state (the erector spinae muscle has good endurance and recovery ability and can withstand exercise of a certain intensity), the main controller 2 will select the normal exercise mode; in the normal exercise mode, the therapeutic device 5 can provide moderate stimulation to simulate the normal activity of the muscles around the spine during daily exercise, help patients further strengthen the stability of the spine and muscle strength, maintain the normal physiological function of the spine, and prevent the scoliosis from worsening.

[0040] When the patient needs rest and recovery after a period of training, the relaxation recovery mode is not limited to a specific range of scoliosis degree, and is applicable to patients with mild, moderate or severe scoliosis under certain circumstances. However, the erector spinae muscles may be in a state of continuous contraction during N preset time periods, and the erector spinae muscles are in a state of fatigue. At this time, the metabolic products of the muscles accumulate, and the muscle strength and endurance decrease, requiring relaxation and recovery. Regardless of the degree of scoliosis of the patient, the main controller 2 will select the relaxation recovery mode at this time. In the relaxation recovery mode, the therapeutic device 5 will use a gentle stimulation method, such as a vibration mode in a pulse mode, to help relax the erector spinae muscles.

[0041] When the patient's spinal scoliosis is moderate or severe, and within N preset time periods, the RMS value of the surface electromyographic signal of the erector spinae muscle on one side is continuously higher than the preset threshold, while the other side is continuously lower than the threshold, and the erector spinae muscle is not always in a fatigue state within the N preset time periods, the main controller 2 will select the enhanced correction mode; in the enhanced correction mode, the therapeutic device 5 will provide more targeted and more intense stimulation, by adjusting the contraction and relaxation of the erector spinae muscles on both sides of the spine, correcting the imbalance of muscle strength, gradually improving the scoliosis of the spine, and promoting the spine to return to its normal shape and function.

[0042] See also Figure 5 In a preferred embodiment, the intelligent training system for treating scoliosis further comprises: A human-machine interface server 6 and a human-machine interface client 7; The human-machine interface server 6 is used to obtain the personalized setting parameters transmitted by the human-machine interface client 7; generate personalized adjustment instructions according to the personalized setting parameters, and transmit the personalized adjustment instructions to the main controller 2; wherein the personalized setting parameters include light color, light flashing frequency, vibration mode to be switched, training mode to be switched, and decibel size of the prompt audio; The main controller 2 is further used to parse the personalized adjustment instruction to obtain the type of the multimodal auxiliary module to be driven and the corresponding personalized setting parameters; and according to the type of the multimodal auxiliary module to be driven and the corresponding personalized setting parameters, drive the corresponding multimodal auxiliary module to operate; wherein the type of the multimodal auxiliary module includes a vibration module 5-1, a light auxiliary module 5-2 and a sound auxiliary module 5-3; Specifically, the patient or medical staff operates on the human-machine interface client 7 and personalizes the training-related parameters according to their own needs and feelings. For example, the patient feels that the current vibration mode is too strong and wants to switch to a softer mode; or feels that the light color is too dazzling and wants to adjust it to a more comfortable color; or hopes to change the decibel level of the prompt audio according to his or her hearing condition; the human-machine interface client 7 packages these parameters set by the user, namely the light color, light flashing frequency, the vibration mode to be switched, the training mode to be switched, and the decibel level of the prompt audio, into the personalized adjustment instruction, and transmits it to the human-machine interface server 6; the human-machine interface server 6 parses the personalized adjustment instruction after receiving it, and generates the corresponding personalized adjustment instruction according to the personalized setting parameters obtained after the analysis, wherein the personalized adjustment instruction contains information about various aspects that the user wants to adjust, for example, if the light color is to be adjusted to blue, the operation that the light auxiliary module needs to perform and the new color parameters will be clearly indicated in the personalized adjustment instruction; after generating the instruction, the human-machine interface server 6 transmits it to the main controller 2; Specifically, if the instruction contains a vibration mode that needs to be switched, the main controller 2 will send the new vibration mode parameters to the vibration module 5-1, driving it to vibrate output according to the new mode; for example, to switch the vibration mode from constant pressure mode to wave mode, the main controller 2 will transmit parameters such as the new vibration intensity change law to the vibration module 5-1; when it is necessary to adjust the lighting related parameters, the main controller 2 sends instructions to the light auxiliary module 5-2 to change the light color and light flashing frequency according to the personalized setting parameters; for the adjustment of the decibel size of the prompt audio, the main controller 2 will send the new decibel value to the sound auxiliary module 5-3, driving it to emit the prompt audio according to the new volume requirement.

[0043] In a preferred embodiment, the therapeutic device 5 comprises: a vibration module 5-1; The vibration module 5-1 is used to, after determining the target training mode, perform vibration output according to the initial vibration mode matched by the target training mode; and adjust the vibration mode required for vibration output according to the personalized adjustment instruction; wherein the vibration mode includes a constant pressure mode, a pulse mode, a gradual change mode and a wave mode; Specifically, in the initial case, the initial vibration mode matched by the normal motion mode is the constant pressure mode. In the constant pressure mode, the vibration module 5-1 will output vibrations at a constant pressure and frequency; the intensity, frequency and duration of the vibrations will remain relatively stable for a period of time without large fluctuations; the initial vibration mode matched by the enhanced correction mode is the pulse mode. In the pulse mode, the vibration module 5-1 will output vibrations in the form of intermittent pulses, with a certain interval between each pulse, and the intensity and frequency of the pulses can be adjusted as needed. This mode can provide strong and short-term stimulation, and produce obvious contraction and relaxation effects on muscles; the initial vibration mode matched by the relaxation recovery mode is the wave mode. In the wave mode, the vibration intensity of the vibration module 5-1 will show a periodic change similar to a wave, and will gradually increase and decrease regularly.

[0044] In a preferred embodiment, the therapeutic apparatus 5 further includes: a light auxiliary module 5-2; The light auxiliary module 5-2 is used to emit light according to the initial light mode matched by the target training mode after determining the target training mode; and adjust the light color or light flashing frequency of the initial light mode according to the personalized adjustment instruction; wherein each of the initial light modes includes a light color and a light flashing frequency; Specifically, in the initial situation, the initial light color matched by the normal exercise mode is green, and the light flashing frequency is medium-low frequency (1-2 times / second); the initial light color matched by the relaxation recovery mode is blue, and the light flashing frequency is low frequency (0.5-1 times / second); the initial light color matched by the enhanced correction mode is red, and the light flashing frequency is medium-low frequency (3-5 times / second).

[0045] In a preferred embodiment, the therapeutic apparatus 5 further includes: a sound auxiliary module 5-3; The sound auxiliary module 5-3 is used to emit a prompt audio matching the preset time point when recognizing that the set duration of the target training mode reaches the preset time point; and adjust the decibel level of the prompt audio according to the personalized adjustment instruction; Specifically, it is assumed that the patient is using the therapeutic apparatus 5 for scoliosis rehabilitation training, the target training mode is the intensive correction mode, the set duration is 30 minutes, and every 15 minutes is a preset time point; Then, 15 minutes into the training, a simple music melody will be played with the volume set at 60 decibels. 30 minutes into the training, a continuous beeping sound will be emitted with the volume set at 70 decibels, marking the end of this intensive correction mode training.

[0046] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. An intelligent training system for treating scoliosis, characterized in that: include: Attitude sensor module and main controller; The posture sensing module is used to collect first three-dimensional position data of preset key points of the spine; Collect the tilt angle and rotation angle data of the pelvis; Collecting second three-dimensional position data of the shoulder blade; sending the first three-dimensional position data, the tilt angle, the rotation angle data and the second three-dimensional position data to the main controller; The main controller is used to fit the first three-dimensional position data according to a preset spline curve fitting algorithm to construct an actual curve of the spine, and compare the actual curve with a preset standard curve to determine the scoliosis angle of the spine; and determine the degree of inclination of the inclination angle relative to a preset human sagittal plane according to a preset forward inclination angle standard range; According to a preset right-handed standard interval, determining the right-handed degree of the rotation angle data relative to a preset vertical axis; calculating a motion trajectory of the scapula according to the second three-dimensional position data, and determining a degree of deviation of the motion trajectory based on a preset standard motion trajectory; The degree of scoliosis of the spine is determined according to the scoliosis angle, the inclination degree, the right rotation degree, the deviation degree and a preset first weight distribution relationship.

2. The intelligent training system for treating scoliosis according to claim 1, characterized in that: Also includes: Pressure sensing module; The pressure sensing module is used to collect pressure distribution data borne by a preset human body support part and send the pressure distribution data to the main controller; The main controller is also used to generate a pressure distribution thermodynamic map based on a preset thermodynamic map drawing function and the pressure distribution data, and determine the pressure state of the human body support part according to the pressure distribution thermodynamic map; and obtain the corrected scoliosis degree of the spine according to the scoliosis angle, the inclination degree, the right rotation degree, the deviation degree, the pressure state and a preset second weight distribution relationship.

3. The intelligent training system for treating scoliosis according to claim 2, characterized in that: The human body support part includes the spine and the sole of the foot; the pressure distribution data includes first pressure distribution data for reflecting the stress condition of the spine and second pressure distribution data for reflecting the stress condition of the sole of the foot; The step of generating a pressure distribution thermodynamic map based on a preset thermodynamic map drawing function and the pressure distribution data, and determining the pressure state of the supporting part of the human body according to the pressure distribution thermodynamic map, comprises: generating a first pressure distribution thermodynamic map according to the first pressure distribution data and the thermodynamic map drawing function; Determining the compression state of the spine according to the pressure distribution on both sides of the spine in the first pressure distribution thermodynamic map; generating a second pressure distribution thermodynamic map according to the second pressure distribution data and the thermodynamic map drawing function; The pressure state of the sole is determined according to a first ratio between the pressure value of the outer side of the sole and the pressure value of the entire sole in the second pressure distribution thermogram and a second ratio between the pressure value of the forefoot and the pressure value of the entire sole in the second pressure distribution thermogram.

4. The intelligent training system for treating scoliosis according to claim 1, characterized in that: The posture sensing module includes a main sensor, an auxiliary sensor and a reference sensor; The main sensor is used to collect first three-dimensional position data of preset key points of the spine and send the first three-dimensional position data to the main controller; The auxiliary sensor is used to collect the inclination angle and rotation angle data of the pelvis, and send the inclination angle and the rotation angle data to the main controller; The reference sensor is used to collect the second three-dimensional position data of the scapula and send the second three-dimensional position data to the main controller.

5. The intelligent training system for treating scoliosis according to claim 1, characterized in that: Also includes: Myoelectric acquisition module and therapeutic device; The electromyography acquisition module is used to collect surface electromyography signals of the erector spinae muscles on both sides of the spine and send the surface electromyography signals to the main controller; The main controller is also used to determine the muscle state of the erector spinae muscle based on the surface electromyographic signal; determine the target training mode of the therapeutic device based on the degree of scoliosis and the muscle state, so that the therapeutic device works according to the target training mode; wherein the target training mode includes: normal movement mode, relaxation recovery mode and intensive correction mode.

6. The intelligent training system for treating scoliosis according to claim 5, characterized in that: The muscle state of the erector spinae muscle includes a muscle activity state and a muscle fatigue state; Determining the muscle state of the erector spinae muscle according to the surface electromyographic signal includes: Determine whether the RMS values ​​of the surface electromyography signals in the preset time period are all greater than the preset threshold value, If yes, it is determined that the muscle activity state of the erector spinae muscle in the preset time period is in a contraction state, On the contrary, it is determined that the muscle activity state of the erector spinae muscle in the preset time period is in a relaxed state; Determine whether the difference between the average median frequency value of the surface electromyography signal in the preset time period and the preset initial median frequency value is greater than a preset fatigue threshold, If yes, it is determined that the muscle fatigue state of the erector spinae muscle in the preset time period is in a fatigue state, On the contrary, it is determined that the muscle fatigue state of the erector spinae muscle in the preset time period is not in a fatigue state.

7. The intelligent training system for treating scoliosis according to claim 6, characterized in that: Also includes: Human-machine interface server and human-machine interface client; The human-machine interface server is used to obtain the personalized setting parameters transmitted by the human-machine interface client; Generate a personalized adjustment instruction according to the personalized setting parameters, and transmit the personalized adjustment instruction to the main controller; wherein the personalized setting parameters include light color, light flashing frequency, vibration mode to be switched, training mode to be switched, and decibel size of prompt audio; The main controller is further used to parse the personalized adjustment instruction to obtain the type of the multimodal auxiliary module to be driven and the corresponding personalized setting parameters; and drive the corresponding multimodal auxiliary module to operate according to the type of the multimodal auxiliary module to be driven and the corresponding personalized setting parameters; wherein the types of the multimodal auxiliary modules include vibration modules, light auxiliary modules and sound auxiliary modules.

8. The intelligent training system for treating scoliosis according to claim 7, characterized in that: The therapeutic device comprises: a vibration module; The vibration module is used to, after determining the target training mode, perform vibration output according to the initial vibration mode matched by the target training mode; and, according to the personalized adjustment instruction, adjust the vibration mode that requires vibration output; wherein the vibration mode includes a constant pressure mode, a pulse mode, a gradual change mode and a wave mode.

9. The intelligent training system for treating scoliosis according to claim 7, characterized in that: The therapeutic apparatus further comprises: a light auxiliary module; The light auxiliary module is used to emit light according to the initial light mode matched by the target training mode after determining the target training mode; and adjust the light color or light flashing frequency of the initial light mode according to the personalized adjustment instruction; wherein each of the initial light modes includes a light color and a light flashing frequency.

10. The intelligent training system for treating scoliosis according to claim 7, characterized in that: The therapeutic apparatus further comprises: a sound auxiliary module; The sound auxiliary module is used to emit a prompt audio that matches the preset time point when it is recognized that the set duration of the target training mode reaches the preset time point; and adjust the decibel level of the prompt audio according to the personalized adjustment instruction.

Images