CN120131004A - A self-aligning knee joint testing and training system and method - Google Patents

A self-aligning knee joint testing and training system and method Download PDF

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Publication number
CN120131004A
CN120131004A CN202510323273.8A CN202510323273A CN120131004A CN 120131004 A CN120131004 A CN 120131004A CN 202510323273 A CN202510323273 A CN 202510323273A CN 120131004 A CN120131004 A CN 120131004A
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knee joint
user
torque
data processing
processing module
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CN120131004B (en
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孙根基
何文涛
李明鹤
陈竟成
占礼葵
王俊
孙少明
雷子豪
竺艺楠
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Anhui Xiaohe Intelligent Technology Co ltd
Hefei Institute Of Technology Innovation Engineering
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Anhui Xiaohe Intelligent Technology Co ltd
Hefei Institute Of Technology Innovation Engineering
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    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Measuring devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
    • A61B5/1121—Determining geometric values, e.g. centre of rotation or angular range of movement
    • A—HUMAN NECESSITIES
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
    • A61H1/00—Apparatus for passive exercising; Vibrating apparatus; Chiropractic devices, e.g. body impacting devices, external devices for briefly extending or aligning unbroken bones
    • A61H1/02—Stretching or bending or torsioning apparatus for exercising
    • A61H1/0237—Stretching or bending or torsioning apparatus for exercising for the lower limbs
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
    • A61H1/00—Apparatus for passive exercising; Vibrating apparatus; Chiropractic devices, e.g. body impacting devices, external devices for briefly extending or aligning unbroken bones
    • A61H1/02—Stretching or bending or torsioning apparatus for exercising
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    • A61H1/024—Knee
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
    • A61H2201/00—Characteristics of apparatus not provided for in the preceding codes
    • A61H2201/01—Constructive details
    • A61H2201/0119—Support for the device
    • A61H2201/0138—Support for the device incorporated in furniture
    • A61H2201/0149—Seat or chair
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
    • A61H2201/00—Characteristics of apparatus not provided for in the preceding codes
    • A61H2201/12—Driving means
    • A61H2201/1207—Driving means with electric or magnetic drive
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
    • A61H2201/00—Characteristics of apparatus not provided for in the preceding codes
    • A61H2201/16—Physical interface with patient
    • A61H2201/1602—Physical interface with patient kind of interface, e.g. head rest, knee support or lumbar support
    • A61H2201/164—Feet or leg, e.g. pedal
    • A61H2201/1642—Holding means therefor
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
    • A61H2201/00—Characteristics of apparatus not provided for in the preceding codes
    • A61H2201/16—Physical interface with patient
    • A61H2201/1657—Movement of interface, i.e. force application means
    • A61H2201/1664—Movement of interface, i.e. force application means linear
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
    • A61H2201/00—Characteristics of apparatus not provided for in the preceding codes
    • A61H2201/50—Control means thereof
    • A61H2201/5007—Control means thereof computer controlled
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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Abstract

The invention provides a self-centering knee joint training system and method, comprising a rotating shaft alignment mechanism, a moment output mechanism, a moment measuring mechanism, a bending and stretching mechanism and a data processing module which are arranged on a seat, wherein the rotating shaft alignment mechanism comprises a linear guide rail, the moment output mechanism comprises a motor and a harmonic reducer, the moment measuring mechanism comprises a potentiometer and a static torque sensor which are arranged in the motor, and the bending and stretching mechanism comprises a guide rail bracket, a linear bearing, an optical axis which is connected with the linear bearing in a sliding manner and a shank binding belt which is arranged on the optical axis and used for fixing the shank of a user. The invention automatically aligns the rotation axis of the equipment with the rotation axis of the knee joint through the rotation center of the dynamic adjustment device in a passive mode, eliminates measurement errors caused by rotation axis deviation, simultaneously provides a testing method and two training methods, realizes the integration of measurement and training, and can meet the requirements of various users.

Description

Self-centering knee joint training system and method
Technical Field
The invention relates to the technical field of intelligent medical rehabilitation devices, in particular to a self-centering knee joint training system and method.
Background
Knee joints are important parts of human bodies, play a role in bearing weight and transmitting load, often cause knee joint dyskinesia caused by injury diseases such as meniscus injury, ligament strain or fracture, tendinitis and the like, and generally promote knee joint muscle strength recovery by cooperation of surgical treatment and postoperative rehabilitation training. The human knee joint allows the femur and tibia to have relatively large motion amplitudes in two degrees of freedom, flexion-extension and axial rotation, and can be anatomically approximated as a hinge structure with one degree of rotational freedom.
In recent years, with the development of sports medicine and rehabilitation technology, knee joint training systems have been widely used in the fields of medical rehabilitation and sports training. However, the conventional knee joint training devices still have a plurality of limitations in design and function, and are mainly characterized in that most of the conventional knee joint training devices are designed by adopting a fixed rotation axis, and cannot be dynamically adjusted according to the actual rotation axis of the knee joint of a user. Because the knee joint is in the motion of stretching, the relative motion of femur and tibia leads to the rotation axis to change constantly, and this kind of fixed design can lead to equipment and knee joint's actual motion mismatch, and then produces measuring error, influences training and recovered effect. Accurate measurement of knee moment is critical to assessing knee function, developing rehabilitation programs and optimizing training protocols. However, the existing equipment is difficult to realize high-precision moment measurement due to the problems of misalignment of a rotating shaft, unreasonable arrangement of sensors and the like, and limits the application of the equipment in clinic and scientific research.
Disclosure of Invention
The invention aims to provide a self-centering knee joint training system and a self-centering knee joint training method, which aim to solve the defects in the prior art.
In order to achieve the above purpose, the invention adopts the following technical scheme:
A self-centering knee joint training system comprises a seat, thigh binding bands, a rotation shaft alignment mechanism, a moment output mechanism, a moment measuring mechanism, a bending and stretching mechanism and a data processing module, wherein the thigh binding bands are arranged on the seat and used for fixing thighs of a user, the rotation shaft alignment mechanism, the moment output mechanism, the moment measuring mechanism, the bending and stretching mechanism and the data processing module are arranged on the seat, the rotation shaft alignment mechanism comprises linear guide rails which are arranged on the left side and the right side of the seat in parallel, the moment output mechanism comprises a motor which is connected with the linear guide rails in a sliding mode and a harmonic reducer which is connected with a motor shaft of the motor in a coaxial mode, the motor shaft of the motor is perpendicular to the linear guide rails, the motor dynamically adjusts output moment through a PID controller, the moment measuring mechanism comprises a potentiometer which is arranged in the motor and used for detecting bending and stretching angles of the knee joint of the user, the static torque sensor is connected with the harmonic reducer in a coaxial mode, the bending and stretching mechanism comprises a guide rail bracket connected with the static torque sensor, a linear bearing which is arranged on the guide rail bracket, one end of the linear bearing is arranged in the linear bearing and the other end of the linear bearing is connected with the linear bearing in a coaxial mode, the harmonic reducer which is arranged on the other end of the linear bearing and is coaxial with a motor shaft of the motor shaft, the motor shaft is perpendicular to the motor shaft, the motor is used for dynamically adjusting output moment through a PID controller, the PID controller can be embedded into a fuzzy control algorithm based on a mechanical model, and can be used for measuring and can be used for outputting a mechanical control algorithm based on a fuzzy control algorithm, and a mechanical model.
The system comprises a data processing module, a data interaction module, a power module, a biomechanical model, a reverse kinetic model, a muscle-skeleton model, a fatigue monitoring algorithm and a reinforcement learning algorithm, wherein the data processing module is used for processing information, transmitting the information to the user, and providing circuit protection.
The linear guide rail comprises a circular rail fixedly connected with the outer side face of the seat and a sliding block sleeved on the circular rail, the motor is in sliding connection with the sliding block through a frame, a Hall sensor is arranged on the frame and used as an emergency stop switch of the motor, and the Hall sensor can send a motor stall command to the PID controller when the surrounding magnetic flux density reaches a preset threshold value.
Further, the guide rail bracket is provided with a permanent magnet which can be matched with the Hall sensor for the emergency stop control of the motor.
The self-centering knee joint training method is realized based on the self-centering knee joint training system, and comprises a constant-speed movement knee joint moment measuring method, and specifically comprises the following steps of:
S1, a user is positioned on a seat, the thigh is fixed with the seat through thigh binding bands, and the shank is fixed with an optical axis through shank binding bands;
S2, a user selects a corresponding preset execution program for measuring the moment of the knee joint in constant-speed motion through a user interaction module;
S3, starting a motor, driving an optical axis to perform simple pendulum motion at a preset angular velocity through a harmonic reducer, driving a user' S lower leg to bend and stretch and driving the optical axis to slide and stretch on a linear bearing, and simultaneously enabling a moment output measurement module to slide on a circular rail under the traction action of the lower leg stretching action, so that a rotation axis of the moment output measurement module is always aligned with a rotation axis of a knee joint of the user;
s4, detecting the knee joint bending and stretching angle of the user in real time through a potentiometer, transmitting the knee joint bending and stretching angle to a data processing module, and collecting the lower limb parameters of the user in real time through the data processing module;
the lower limb parameters comprise the mass, the length, the moment of inertia and the centroid position of thighs, calves and feet of the user;
S5, controlling the output torque of the torque output module by the data processing module based on the inverse dynamics model and combining with a fuzzy PID control algorithm;
the inverse kinetic model can calculate the moment required for the knee joint based on the following formula (1) according to the motion state of the knee joint of the user:
in the formula (1), tau represents moment required by knee joint, M (q) is mass matrix, and represents inertial characteristic of the system; Represents the matrix of Coriolis force and centrifugal force, the G (q) gravity matrix, q represents the knee joint flexion and extension angle; Represents knee joint angular velocity; representing knee joint angular acceleration, said AndRespectively obtaining through the first-order derivative and the second-order derivative of q;
S6, detecting moment data of the knee joint of the user in real time through a static torque sensor and transmitting the moment data to a data processing module;
and S7, receiving moment data of the knee joint of the user through a data processing module, processing and analyzing the moment data to generate a moment measurement report, and simultaneously displaying and interacting the data through a user interaction module.
Further, the training method also comprises a rehabilitation training method for the knee joint injury patient, and specifically comprises the following steps:
S1, a user is positioned on a seat, the thigh is fixed with the seat through thigh binding bands, and the shank is fixed with an optical axis through shank binding bands;
s2, a user selects a corresponding preset execution program of rehabilitation training of the knee joint injury patient through a user interaction module;
S3, starting a motor, driving an optical axis to perform simple pendulum motion at a preset angular velocity through a harmonic reducer, driving a user' S lower leg to bend and stretch and driving the optical axis to slide and stretch on a linear bearing, and simultaneously enabling a moment output measurement module to slide on a circular rail under the traction action of the lower leg stretching action, so that a rotation axis of the moment output measurement module is always aligned with a rotation axis of a knee joint of the user;
s4, detecting the knee joint bending and stretching angle of the user in real time through a potentiometer, transmitting the knee joint bending and stretching angle to a data processing module, and collecting the lower limb parameters of the user in real time through the data processing module;
S5, controlling the output torque of the torque output module by the data processing module based on the biomechanical model and combining with a fuzzy PID control algorithm;
The biomechanical model is capable of calculating the moment required for the knee joint based on the following equation (2) from the kinematic and mechanical properties of the user's knee joint:
τ=τinertial+τcoriolis+τgravity (2);
Wherein:
τgravity=mglsinθ (5);
in the formulas (2) - (5), τ represents the moment required by the knee joint, τ inertoal represents the inertial force caused by the knee joint angular acceleration, τ coriolis represents the coriolis force and centrifugal force caused by the knee joint angle, τ gravity represents the moment caused by gravity, and θ represents the knee joint flexion and extension angle; Represents knee joint angular velocity; Representing angular acceleration, said AndThe method comprises the steps of respectively obtaining through first-order derivative and second-order derivative of theta, wherein I represents moment of inertia; representing the matrix of Coriolis force and centrifugal force, l representing the distance from the centroid to the axis of rotation, m representing the mass, g representing the acceleration of gravity;
s6, acquiring motion state data of the knee joint of the user in real time through a data processing module, and optimizing the output torque of the torque output module according to a reward mechanism based on a reinforcement learning algorithm;
The rewarding mechanism is constructed based on a reinforcement learning algorithm, and adopts an Actor-Criti method to evaluate the current motion state of the user by combining a strategy function and a cost function, wherein the strategy function and the cost function are respectively represented by the following formulas (6) and (7):
V(s)←V(s)+α[r+γV(s′)-V(s)] (7);
Wherein:
In the formulas (6) - (10), θ represents a parameter of a policy function, J (θ) represents an objective function of a policy, α represents a learning rate, s represents a current state, s ' represents a next state, a represents an action taken in the state s, a ' represents an action taken in the state s ', V(s) represents a value of the state s, V (s ') represents a value of the state s ', Q (s, a) represents a value of the action a taken in the state s, and Q (s ', a ') represents a value of the action a ' taken in the state s '; r represents current rewards, gamma represents discount factors for balancing the current rewards and future rewards, and the value range of gamma is more than or equal to 0 and less than or equal to 10 and less than or equal to 1; R+gamma V (s') -V(s) represent dominant functions and represent the merits of the current actions; Representing an objective function updated by adopting a strategy gradient;
S7, detecting moment data of the knee joint of the user in real time through a static torque sensor and transmitting the moment data to a data processing module;
and S8, receiving moment data of the knee joint of the user through a data processing module, processing and analyzing the moment data to generate a rehabilitation strategy, and simultaneously displaying and interacting data through a user interaction module.
Further, the training method further comprises a leg muscle training method, and specifically comprises the following steps:
S1, a user is positioned on a seat, the thigh is fixed with the seat through thigh binding bands, and the shank is fixed with an optical axis through shank binding bands;
S2, a user selects a corresponding preset execution program of leg muscle training through a user interaction module;
S3, starting a motor, driving an optical axis to perform simple pendulum motion at a preset angular velocity through a harmonic reducer, driving a user' S lower leg to bend and stretch and driving the optical axis to slide and stretch on a linear bearing, and simultaneously enabling a moment output measurement module to slide on a circular rail under the traction action of the lower leg stretching action, so that a rotation axis of the moment output measurement module is always aligned with a rotation axis of a knee joint of the user;
s4, detecting the knee joint bending and stretching angle of the user in real time through a potentiometer, transmitting the knee joint bending and stretching angle to a data processing module, and collecting the lower limb parameters of the user in real time through the data processing module;
S5, controlling the output torque of the torque output module by the data processing module based on the biomechanical model and combining with a fuzzy PID control algorithm;
S6, detecting moment data of the knee joint of the user in real time through a static torque sensor, transmitting the moment data to a data processing module, analyzing the moment data through the data processing module based on a muscle-bone model and a fatigue monitoring algorithm, and judging the fatigue degree of the muscle of the user;
the data processing module is used for judging the motion state by analyzing the change trend of signal characteristics based on the moment, angle and angular velocity data of the knee joint of the user based on a muscle-bone model combined fatigue monitoring algorithm, wherein the signal characteristics comprise the maximum moment, average moment, angle change range and angular velocity change value of the knee joint;
S7, optimizing the output torque of the torque output module according to the fatigue degree of the user muscle, and gradually reducing the torque output after training for a certain period of time;
and S8, displaying related data in real time in the whole training process through a user interaction module, and generating training suggestions after the training is finished.
Further, the output torque of the torque output module is controlled by the fuzzy PID control algorithm and is represented by the following formula (11):
In the formula (11), u (t) represents control output, e (t) represents an error between a target torque and an actual torque, d represents differentiation, t represents time, and K p、Ki、Kd is a proportional, integral and differential coefficient respectively.
According to the technical scheme, the rotation center of the dynamic adjusting device in a passive mode is utilized to enable the rotation axis of equipment to be automatically aligned with the rotation axis of a knee joint, measurement errors caused by rotation axis deviation are eliminated, a testing method and two training methods are provided, in the testing method, the accuracy of moment measurement is remarkably improved through a fuzzy PID control algorithm by establishing a self-centering function of a reverse dynamic model, in the two training methods, dynamic adjustment of a training scheme is achieved in rehabilitation training through a biomechanical model in combination with a fuzzy PID control algorithm, a reinforcement learning algorithm and a fatigue monitoring algorithm, rehabilitation effect is improved, dynamic adjustment of training strength and real-time detection of muscle fatigue degree are achieved in muscle training, scientific training suggestion is provided, measurement and training integration is achieved, and requirements of various users can be met.
Drawings
FIG. 1 is a schematic diagram of the overall structure of the self-centering knee joint training system of the present invention;
FIG. 2 is a schematic diagram of a portion of a self-centering knee joint training system of the present invention;
FIG. 3 is a schematic view of a portion of the self-centering knee joint training system of the present invention;
FIG. 4 is a schematic view of a portion of the self-centering knee joint training system of the present invention;
FIG. 5 is a schematic view of a portion of the self-centering knee joint training system of the present invention;
FIG. 6 is a schematic diagram of the mechanics principle of the self-centering knee joint training system of the present invention;
FIG. 7 is a schematic diagram of the mechanics principle of the self-centering knee joint training system of the present invention;
FIG. 8 is a flow chart of the steps of the self-centering knee training method of the present invention;
FIG. 9 is a table of K p fuzzy rules;
FIG. 10 is a table of K i fuzzy rules;
FIG. 11 is a table of K d fuzzy rules;
The device comprises a linear guide rail 1, a motor 2, a harmonic reducer 3, a static torque sensor 4, a guide rail bracket 5, a linear bearing 6, a linear bearing 7, an optical axis 8, a shank binding belt 9, a user interaction module 10, a circular rail 11, a sliding block 12, a rack 13, a Hall sensor 14 and a permanent magnet.
Detailed Description
A preferred embodiment of the present invention will be described in detail with reference to the accompanying drawings.
The self-centering knee joint training system shown in the figures 1-3 comprises a seat, thigh binding bands, a rotating shaft alignment mechanism, a moment output mechanism, a moment measuring mechanism, a bending and stretching mechanism and a data processing module, wherein the thigh binding bands are arranged on the seat and used for fixing thighs of a user, the rotating shaft alignment mechanism, the moment output mechanism, the moment measuring mechanism, the bending and stretching mechanism and the data processing module are arranged on the seat, the rotating shaft alignment mechanism comprises linear guide rails 1 which are arranged on the left side and the right side of the seat in parallel, the moment output mechanism comprises a motor 2 which is connected with the linear guide rails 1 in a sliding mode and a harmonic reducer 3 which is connected with a motor shaft of the motor 2 in a coaxial mode, the motor shaft of the motor 2 is perpendicular to the linear guide rails 1, the motor 2 dynamically adjusts output moment through a PID controller, the moment measuring mechanism comprises a potentiometer which is arranged in the motor 2 and used for detecting bending and stretching angles of the knee joints of the user, a static torque sensor 4 which is connected with the harmonic reducer 3 in a coaxial mode and is used for measuring the knee joint moment of the user, the bending and stretching mechanism comprises a guide rail bracket 5 which is connected with the static torque sensor 4, two linear bearings 6 which are arranged on the guide rail bracket 5, one end of the linear bearings 6 are respectively arranged in the linear bearings 6, one end of each end of which is connected with the linear bearings 6 and the other end of the two lower leg bearings 7 can be fixed on the small leg binding bands 8.
The data processing module in the preferred embodiment adopts an embedded processor, can control the output torque of the torque output mechanism based on a biomechanical model or an inverse kinetic model in combination with a fuzzy PID control algorithm, and can process and analyze the data detected by the torque measuring mechanism based on a machine learning algorithm.
The biomechanical model according to the preferred embodiment is a model describing the motion and mechanical characteristics of a human body under the mechanical action by a mathematical equation, and the inverse kinetic model is a mathematical model deriving the force or moment required by the system by the known motion state.
The self-centering knee joint training system further comprises a user interaction module and a power module, wherein the user interaction module is connected with an external interface of the data processing module and comprises an industrial control screen and a loudspeaker for information transmission and user interaction, the power module is used for supplying power to the system and providing circuit protection, and the data processing module is provided with corresponding execution programs according to measurement or training requirements of a user and is provided with a biomechanical model, a reverse kinetic model, a muscle-bone model, a fatigue monitoring algorithm and a reinforcement learning algorithm.
As shown in fig. 4 and 5, the linear guide rail 1 comprises two circular rails 10 fixedly connected with the outer side surface of the seat and a sliding block 11 sleeved on the two circular rails, specifically, the motor 2 is slidably connected with the sliding block 11 through a frame 12, a hall sensor 13 is arranged on the frame 12 as a sudden stop switch of the motor 2, a motor 2 stopping command can be sent to the PID controller when the magnetic flux density around the sensor reaches a preset threshold value, and a permanent magnet 14 is correspondingly arranged on the guide rail bracket 4 and can be matched with the hall sensor for controlling the sudden stop of the motor 2.
The hall sensor 13 according to the preferred embodiment is a hall effect based magnetic sensor, which can control the on-off state of the switch by using the change of the magnetic field, and when the magnetic object approaches the hall sensor as described in the preferred embodiment, the magnetic flux density around the hall sensor 13 changes, thereby causing the generation of a hall voltage, and the voltage signal can be used to control the on-off state of the switch.
In a specific use, a user can select a corresponding preset execution program through the user interaction module 9 according to measurement or training requirements, as shown in fig. 6 and 7, after the motor 2 is started, the optical axis 7 is driven by the harmonic reducer 3 to perform single pendulum motion at a preset angular velocity, the user's lower leg is driven to bend and stretch, the optical axis 7 is driven to slide and stretch on the linear bearing 6, and meanwhile, the moment output measurement module slides on the circular rail 10 under the traction action of the lower leg stretching action, so that the rotation axis of the moment output measurement module is always aligned with the rotation axis of the knee joint.
The self-centering knee joint training method shown in fig. 8 can perform constant velocity motion knee joint moment measurement, rehabilitation training of a knee joint injury user, and muscle training of the leg based on the self-centering knee joint training system.
First embodiment, constant velocity motion knee moment measurement
The method specifically comprises the following steps:
S1, a user is positioned on a seat, the thigh is fixed with the seat through thigh binding bands, and the shank is fixed with an optical axis through shank binding bands;
S2, a user selects a corresponding preset execution program for measuring the moment of the knee joint in constant-speed motion through a user interaction module;
S3, starting a motor, driving an optical axis to perform simple pendulum motion at a preset angular velocity through a harmonic reducer, driving a user' S lower leg to bend and stretch and driving the optical axis to slide and stretch on a linear bearing, and simultaneously enabling a moment output measurement module to slide on a circular rail under the traction action of the lower leg stretching action, so that a rotation axis of the moment output measurement module is always aligned with a rotation axis of a knee joint of the user;
s4, detecting the knee joint bending and stretching angle of the user in real time through a potentiometer, transmitting the knee joint bending and stretching angle to a data processing module, and collecting the lower limb parameters of the user in real time through the data processing module;
the lower limb parameters comprise the mass, the length, the moment of inertia and the centroid position of thighs, calves and feet of the user;
S5, controlling the output torque of the torque output module by the data processing module based on the inverse dynamics model and combining with a fuzzy PID control algorithm;
In the step, the inverse dynamic model simplifies the knee joint into a single-degree-of-freedom hinge structure, the femur and the tibia are connected through the knee joint, the lower limb is simplified into a rigid body connecting rod system comprising a thigh, a shank and a foot, and the knee joint moment is obtained by inputting the knee joint angle, the knee joint angular velocity and the knee joint angular acceleration and performing kinematic analysis. The inverse kinetic model can calculate the moment required for the knee joint based on the following formula (1) according to the motion state of the knee joint of the user:
in the formula (1), tau represents moment required by knee joint, M (q) is mass matrix, and represents inertial characteristic of the system; Represents the matrix of Coriolis force and centrifugal force, the G (q) gravity matrix, q represents the knee joint flexion and extension angle; Represents knee joint angular velocity; representing knee joint angular acceleration, said AndDerived from the first and second derivatives of q, respectively.
S6, detecting moment data of the knee joint of the user in real time through a static torque sensor and transmitting the moment data to a data processing module;
and S7, receiving moment data of the knee joint of the user through a data processing module, processing and analyzing the moment data to generate a moment measurement report, and simultaneously displaying and interacting the data through a user interaction module.
Second embodiment rehabilitation training for knee joint injury user
The method specifically comprises the following steps:
S1, a user is positioned on a seat, the thigh is fixed with the seat through thigh binding bands, and the shank is fixed with an optical axis through shank binding bands;
s2, a user selects a corresponding preset execution program of rehabilitation training of the knee joint injury patient through a user interaction module;
S3, starting a motor, driving an optical axis to perform simple pendulum motion at a preset angular velocity through a harmonic reducer, driving a user' S lower leg to bend and stretch and driving the optical axis to slide and stretch on a linear bearing, and simultaneously enabling a moment output measurement module to slide on a circular rail under the traction action of the lower leg stretching action, so that a rotation axis of the moment output measurement module is always aligned with a rotation axis of a knee joint of the user;
s4, detecting the knee joint bending and stretching angle of the user in real time through a potentiometer, transmitting the knee joint bending and stretching angle to a data processing module, and collecting the lower limb parameters of the user in real time through the data processing module;
S5, controlling the output torque of the torque output module by the data processing module based on the biomechanical model and combining with a fuzzy PID control algorithm;
specifically, the biomechanical model is capable of calculating the moment required for the knee joint based on the following equation (2) according to the kinematic and mechanical characteristics of the user knee joint:
τ=τinertial+τcoriolis+τgravity (2);
Wherein:
τgravity=mglsinθ (5);
In the formulas (2) - (5), τ represents the moment required by the knee joint, τ inertial represents the inertial force caused by the knee joint angular acceleration, τ coriolis represents the coriolis force and centrifugal force caused by the knee joint angle, τ gravity represents the moment caused by gravity, and θ represents the knee joint flexion and extension angle; Represents knee joint angular velocity; Representing angular acceleration, said AndThe method comprises the steps of respectively obtaining through first-order derivative and second-order derivative of theta, wherein I represents moment of inertia; representing the matrix of Coriolis force and centrifugal force, l representing the distance from the centroid to the axis of rotation, m representing the mass, g representing the acceleration of gravity;
s6, acquiring motion state data of the knee joint of the user in real time through a data processing module, and optimizing the output torque of the torque output module according to a reward mechanism based on a reinforcement learning algorithm;
The rewarding mechanism is constructed based on a reinforcement learning algorithm, and adopts an Actor-Criti method to evaluate the current motion state of the user by combining a strategy function and a cost function, wherein the strategy function and the cost function are respectively represented by the following formulas (6) and (7):
V(s)←V(s)+α[r+γV(s′)-V(s)] (7);
Wherein:
In the formulas (6) - (10), θ represents a parameter of a policy function, J (θ) represents an objective function of a policy, α represents a learning rate, s represents a current state, s ' represents a next state, a represents an action taken in the state s, a ' represents an action taken in the state s ', V(s) represents a value of the state s, V (s ') represents a value of the state s ', Q (s, a) represents a value of the action a taken in the state s, and Q (s ', a ') represents a value of the action a ' taken in the state s '; r represents current rewards, gamma represents discount factors for balancing the current rewards and future rewards, and the value range of gamma is more than or equal to 0 and less than or equal to 10 and less than or equal to 1; R+gamma V (s') -V(s) represent dominant functions and represent the merits of the current actions; Representing an objective function updated by adopting a strategy gradient;
S7, detecting moment data of the knee joint of the user in real time through a static torque sensor and transmitting the moment data to a data processing module;
and S8, receiving moment data of the knee joint of the user through a data processing module, processing and analyzing the moment data to generate a rehabilitation strategy, and simultaneously displaying and interacting data through a user interaction module.
Third embodiment muscle training of leg
S1, a user is positioned on a seat, the thigh is fixed with the seat through thigh binding bands, and the shank is fixed with an optical axis through shank binding bands;
S2, a user selects a corresponding preset execution program of leg muscle training through a user interaction module;
S3, starting a motor, driving an optical axis to perform simple pendulum motion at a preset angular velocity through a harmonic reducer, driving a user' S lower leg to bend and stretch and driving the optical axis to slide and stretch on a linear bearing, and simultaneously enabling a moment output measurement module to slide on a circular rail under the traction action of the lower leg stretching action, so that a rotation axis of the moment output measurement module is always aligned with a rotation axis of a knee joint of the user;
s4, detecting the knee joint bending and stretching angle of the user in real time through a potentiometer, transmitting the knee joint bending and stretching angle to a data processing module, and collecting the lower limb parameters of the user in real time through the data processing module;
S5, controlling the output torque of the torque output module by the data processing module based on the biomechanical model and combining with a fuzzy PID control algorithm;
S6, detecting moment data of the knee joint of the user in real time through a static torque sensor, transmitting the moment data to a data processing module, analyzing the moment data through the data processing module based on a muscle-bone model and a fatigue monitoring algorithm, and judging the fatigue degree of the muscle of the user;
the data processing module is used for judging the motion state by analyzing the change trend of signal characteristics based on the moment, angle and angular velocity data of the knee joint of the user based on a muscle-bone model combined fatigue monitoring algorithm, wherein the signal characteristics comprise the maximum moment, average moment, angle change range and angular velocity change value of the knee joint;
S7, optimizing the output torque of the torque output module according to the fatigue degree of the user muscle, and gradually reducing the torque output after training for a certain period of time;
and S8, displaying related data in real time in the whole training process through a user interaction module, and generating training suggestions after the training is finished.
In the above embodiment, the output torque of the torque output module controlled by the fuzzy PID control algorithm is represented by the following formula (11):
in the formula (11), u (t) represents control output, e (t) represents error of target torque and actual torque, d represents differentiation, t represents time, K p、Ki、Kd is respectively proportional, integral and differential coefficient, and fuzzy rule tables of K p、Ki、Kd are respectively shown in figures 9, 10 and 11.
The fuzzy PID control algorithm is suitable for nonlinear system control, has strong robustness to system parameter changes and external interference, can establish a fuzzy rule base based on expert experience and experimental data, is easy to realize and adjust, and ensures scientificity and effectiveness of device torque measurement, rehabilitation training and muscle training.
The above embodiments are merely illustrative of the preferred embodiments of the present invention and are not intended to limit the scope of the present invention, and various modifications and improvements made by those skilled in the art to the technical solution of the present invention should fall within the protection scope defined by the claims of the present invention without departing from the design spirit of the present invention.

Claims (8)

1.一种自对心的膝关节测训系统，包括座椅以及设置在座椅上用于固定用户大腿部的大腿绑带，其特征在于，还包括设置在所述座椅上的旋转轴对齐机构、力矩输出机构、力矩测量机构、屈伸机构以及数据处理模块；1. A self-aligning knee joint testing and training system, comprising a seat and a thigh strap arranged on the seat for fixing the thigh of a user, characterized in that it also comprises a rotation axis alignment mechanism, a torque output mechanism, a torque measurement mechanism, a flexion and extension mechanism and a data processing module arranged on the seat; 所述旋转轴对齐机构包括平行设置在所述座椅左右两侧的直线导轨；The rotation axis alignment mechanism includes linear guide rails arranged in parallel on the left and right sides of the seat; 所述力矩输出机构包括与所述直线导轨滑动连接的电机以及与所述电机的电机轴同轴连接的谐波减速器，所述电机的电机轴与所述直线导轨垂直，所述电机通过PID控制器动态调整输出力矩；The torque output mechanism comprises a motor slidably connected to the linear guide rail and a harmonic reducer coaxially connected to the motor shaft of the motor, the motor shaft of the motor is perpendicular to the linear guide rail, and the motor dynamically adjusts the output torque through a PID controller; 所述力矩测量机构包括内置于所述电机用于检测用户膝关节屈伸角度的电位器以及与所述谐波减速器同轴连接的用于测量用户膝关节力矩的静态扭矩传感器；The torque measurement mechanism includes a potentiometer built into the motor for detecting the flexion and extension angle of the user's knee joint and a static torque sensor coaxially connected to the harmonic reducer for measuring the user's knee joint torque; 所述屈伸机构包括与静态扭矩传感器连接的导轨支架、设置在所述导轨支架上的直线轴承、一端设置在所述直线轴承内且能够与所述直线轴承滑动连接的光轴以及设置在所述光轴的另一端用于固定用户小腿部的小腿绑带；The flexion and extension mechanism includes a guide rail bracket connected to the static torque sensor, a linear bearing arranged on the guide rail bracket, an optical axis at one end of which is arranged in the linear bearing and can be slidably connected to the linear bearing, and a calf strap arranged at the other end of the optical axis for fixing the user's calf; 所述数据处理模块采用嵌入式处理器，能够基于生物力学模型或逆动力学模型结合模糊PID控制算法控制所述力矩输出机构的输出力矩，并能够基于机器学习算法对所述力矩测量机构检测到的数据进行处理和分析。The data processing module uses an embedded processor, which can control the output torque of the torque output mechanism based on a biomechanical model or an inverse dynamics model combined with a fuzzy PID control algorithm, and can process and analyze the data detected by the torque measurement mechanism based on a machine learning algorithm. 2.根据权利要求1所述的一种自对心的膝关节测训系统，其特征在于，还包括用户交互模块和电源模块；2. A self-aligning knee joint testing and training system according to claim 1, characterized in that it also includes a user interaction module and a power supply module; 所述用户交互模块与所述数据处理模块的外部接口连接，包括工控屏和扬声器，用于信息传递和用户交互；The user interaction module is connected to the external interface of the data processing module, and includes an industrial control screen and a speaker for information transmission and user interaction; 所述电源模块用于系统供电并提供电路保护；The power module is used to supply power to the system and provide circuit protection; 所述数据处理模块根据用户的测量或训练需求预设有相应的执行程序，并配置有生物力学模型、逆动力学模型、肌肉-骨骼模型、疲劳监测算法以及强化学习算法。The data processing module is preset with a corresponding execution program according to the user's measurement or training requirements, and is configured with a biomechanical model, an inverse dynamics model, a muscle-skeletal model, a fatigue monitoring algorithm and a reinforcement learning algorithm. 3.根据权利要求1所述的一种自对心的膝关节测训系统，其特征在于，所述直线导轨包括与所述座椅的外侧面固定连接的圆轨以及套置在所述圆轨上的滑块；所述电机通过机架与所述滑块滑动连接，所述机架上设有霍尔传感器作为所述电机的急停开关，所述霍尔传感器能够在周围磁通密度达到预设阈值时向所述PID控制器发送电机停转命令。3. A self-aligning knee joint testing and training system according to claim 1, characterized in that the linear guide rail includes a circular rail fixedly connected to the outer side surface of the seat and a slider sleeved on the circular rail; the motor is slidably connected to the slider through a frame, and a Hall sensor is provided on the frame as an emergency stop switch of the motor, and the Hall sensor can send a motor stop command to the PID controller when the surrounding magnetic flux density reaches a preset threshold. 4.根据权利要求1所述的一种自对心的膝关节测训系统，其特征在于，所述导轨支架上设置有永磁铁，能够与霍尔传感器配合用于所述电机的急停控制。4. A self-aligning knee joint testing and training system according to claim 1, characterized in that a permanent magnet is provided on the guide rail bracket, which can be used in conjunction with a Hall sensor for emergency stop control of the motor. 5.一种自对心的膝关节测训方法，是基于上述权利要求1-4任一所述的自对心的膝关节测训系统实现的，其特征在于，所述测训方法包括等速运动膝关节力矩测量方法，具体包括以下步骤：5. A self-aligning knee joint training method, which is implemented based on the self-aligning knee joint training system described in any one of claims 1 to 4, characterized in that the training method includes an isokinetic knee joint torque measurement method, specifically comprising the following steps: S1、用户位于座椅上通过大腿绑带将大腿与座椅固定，并通过小腿绑带将小腿与光轴固定；S1. The user is sitting on the seat and fixes the thigh to the seat through the thigh strap, and fixes the calf to the optical axis through the calf strap; S2、用户通过用户交互模块选择等速运动膝关节力矩测量相应的预设执行程序；S2, the user selects the corresponding preset execution program for isokinetic knee joint torque measurement through the user interaction module; S3、启动电机，通过谐波减速器驱动光轴以预设角速度进行单摆运动，带动用户小腿屈伸并带动光轴在直线轴承上滑动伸长，同时力矩输出测量模块受小腿伸长动作的牵拉作用在圆轨上滑动，使力矩输出测量模块的旋转轴始终与用户膝关节的旋转轴对齐；S3, start the motor, drive the optical axis to perform a single pendulum motion at a preset angular velocity through the harmonic reducer, drive the user's calf to flex and extend, and drive the optical axis to slide and extend on the linear bearing. At the same time, the torque output measurement module slides on the circular rail under the pulling effect of the calf extension action, so that the rotation axis of the torque output measurement module is always aligned with the rotation axis of the user's knee joint; S4、通过电位器实时检测用户的膝关节屈伸角度并传输至数据处理模块，并通过数据处理模块实时采集用户的下肢参数；S4, detecting the user's knee flexion and extension angle in real time through a potentiometer and transmitting the angle to a data processing module, and collecting the user's lower limb parameters in real time through the data processing module; 所述下肢参数包括用户大腿、小腿和足部的质量、长度、转动惯量、质心位置；The lower limb parameters include the mass, length, moment of inertia, and center of mass position of the user's thigh, calf, and foot; S5、通过数据处理模块基于逆动力学模型结合模糊PID控制算法控制力矩输出模块的输出力矩；S5, controlling the output torque of the torque output module through the data processing module based on the inverse dynamics model combined with the fuzzy PID control algorithm; 所述逆动力学模型能够根据用户膝关节的运动状态基于以下公式(1)计算膝关节所需的力矩：The inverse dynamics model can calculate the torque required for the knee joint according to the motion state of the user's knee joint based on the following formula (1): 公式(1)中：τ表示膝关节所需的力矩；M(q)为质量矩阵，表示系统的惯性特性；表示科里奥利力和离心力矩阵；G(q)重力矩阵；q表示膝关节屈伸角度；表示膝关节角速度；表示膝关节角加速度；所述和分别通过q的一阶和二阶导数得到；In formula (1), τ represents the torque required by the knee joint; M(q) is the mass matrix, which represents the inertial characteristics of the system; represents the Coriolis force and centrifugal force matrix; G(q) gravity matrix; q represents the knee flexion and extension angle; represents the angular velocity of the knee joint; represents the angular acceleration of the knee joint; and They are obtained by the first and second order derivatives of q respectively; S6、通过静态扭矩传感器实时检测用户膝关节的力矩数据并传输至数据处理模块；S6, detecting the torque data of the user's knee joint in real time through a static torque sensor and transmitting the data to a data processing module; S7、通过数据处理模块接收用户膝关节的力矩数据并进行处理和分析，生成力矩测量报告，同时通过用户交互模块进行数据显示和交互。S7. Receive the torque data of the user's knee joint through the data processing module, process and analyze it, generate a torque measurement report, and display and interact with the data through the user interaction module. 6.根据权利要求5所述的一种自对心的膝关节测训方法，其特征在于，所述测训方法还包括膝关节损伤患者的康复训练方法，具体包括以下步骤：6. A self-aligned knee joint testing and training method according to claim 5, characterized in that the testing and training method also includes a rehabilitation training method for patients with knee joint injuries, specifically comprising the following steps: S1、用户位于座椅上通过大腿绑带将大腿与座椅固定，并通过小腿绑带将小腿与光轴固定；S1. The user is sitting on the seat and fixes the thigh to the seat through the thigh strap, and fixes the calf to the optical axis through the calf strap; S2、用户通过用户交互模块选择膝关节损伤患者的康复训练相应的预设执行程序；S2. The user selects a preset execution program corresponding to the rehabilitation training for the patient with knee joint injury through the user interaction module; S3、启动电机，通过谐波减速器驱动光轴以预设角速度进行单摆运动，带动用户小腿屈伸并带动光轴在直线轴承上滑动伸长，同时力矩输出测量模块受小腿伸长动作的牵拉作用在圆轨上滑动，使力矩输出测量模块的旋转轴始终与用户膝关节的旋转轴对齐；S3, start the motor, drive the optical axis to perform a single pendulum motion at a preset angular velocity through the harmonic reducer, drive the user's calf to flex and extend, and drive the optical axis to slide and extend on the linear bearing. At the same time, the torque output measurement module slides on the circular rail under the pulling effect of the calf extension action, so that the rotation axis of the torque output measurement module is always aligned with the rotation axis of the user's knee joint; S4、通过电位器实时检测用户的膝关节屈伸角度并传输至数据处理模块，并通过数据处理模块实时采集用户的下肢参数；S4, detecting the user's knee flexion and extension angle in real time through a potentiometer and transmitting the angle to a data processing module, and collecting the user's lower limb parameters in real time through the data processing module; S5、通过数据处理模块基于生物力学模型结合模糊PID控制算法控制力矩输出模块的输出力矩；S5, controlling the output torque of the torque output module through the data processing module based on the biomechanical model combined with the fuzzy PID control algorithm; 所述生物力学模型能够根据用户膝关节的运动学和力学特性基于以下公式(2)计算膝关节所需的力矩：The biomechanical model can calculate the required torque of the knee joint according to the kinematic and mechanical characteristics of the user's knee joint based on the following formula (2): τ＝τinertial+τcoriolis+τgravity (2)；τ＝τ inertial +τ coriolis +τ gravity (2); 其中：in: τgravity＝mgl sinθ (5)；τ gravity = mgl sinθ (5); 公式(2)-(5)中：τ表示膝关节所需的力矩；τinertial表示膝关节角加速度引起的惯性力；τcoriolis表示膝关节角引起的科里奥利力和离心力；τgravity表示重力引起的力矩；θ表示膝关节屈伸角度；表示膝关节角速度；表示角加速度；所述和分别通过θ的一阶和二阶导数得到；I表示转动惯量；表示科里奥利力和离心力矩阵；l表示质心到旋转轴的距离；m表示质量；g表示重力加速度；In formulas (2)-(5): τ represents the torque required by the knee joint; τ inertial represents the inertial force caused by the angular acceleration of the knee joint; τ coriolis represents the Coriolis force and centrifugal force caused by the knee joint angle; τ gravity represents the torque caused by gravity; θ represents the flexion and extension angle of the knee joint; represents the angular velocity of the knee joint; represents angular acceleration; and They are obtained by the first and second order derivatives of θ respectively; I represents the moment of inertia; represents the Coriolis force and centrifugal force matrix; l represents the distance from the center of mass to the rotation axis; m represents the mass; g represents the gravitational acceleration; S6、通过数据处理模块实时采集用户膝关节的运动状态数据，并基于强化学习算法根据奖励机制对力矩输出模块的输出力矩进行优化；S6. The motion state data of the user's knee joint is collected in real time through the data processing module, and the output torque of the torque output module is optimized according to the reward mechanism based on the reinforcement learning algorithm; 所述奖励机制为：正奖励出现在用户完成训练目标时，负奖励出现在用户不适或训练效果不佳时；所述奖励机制是基于强化学习算法构建的，采用Actor-Criti方法结合策略函数和价值函数评价用户当前运动状态，所述策略函数和价值函数分别通过以下公式(6)和(7)表示：The reward mechanism is as follows: positive rewards appear when the user completes the training goal, and negative rewards appear when the user is uncomfortable or the training effect is not good. The reward mechanism is constructed based on the reinforcement learning algorithm, and the Actor-Criti method is used to combine the strategy function and the value function to evaluate the user's current motion state. The strategy function and the value function are respectively expressed by the following formulas (6) and (7): V(s)←V(s)+α[r+γV(s′)-V(s)] (7)；V(s)←V(s)+α[r+γV(s′)-V(s)] (7); 其中：in: 公式(6)-(10)中：θ表示策略函数的参数；J(θ)表示策略的目标函数；α表示学习速率；s表示当前状态；s′表示下一状态；a表示状态s下采取的动作；a′表示状态s′下采取的动作；V(s)表示状态s的价值；V(s′)表示状态s′的价值；Q(s,a)表示在状态s下采取动作a的价值；Q(s′,a′)表示在状态s′下采取动作a′的价值；表示期望；r表示当前奖励；γ表示折扣因子，用于平衡当前奖励和未来奖励，其取值范围为0≤γ≤10≤γ≤1；表示策略函数的梯度；r+γV(s′)-V(s)表示优势函数，表示当前动作的优劣；表示采用策略梯度更新后的目标函数；In formulas (6)-(10), θ represents the parameters of the policy function; J(θ) represents the objective function of the policy; α represents the learning rate; s represents the current state; s′ represents the next state; a represents the action taken in state s; a′ represents the action taken in state s′; V(s) represents the value of state s; V(s′) represents the value of state s′; Q(s,a) represents the value of taking action a in state s; Q(s′,a′) represents the value of taking action a′ in state s′; represents expectation; r represents current reward; γ represents discount factor, which is used to balance current reward and future reward, and its value range is 0≤γ≤10≤γ≤1; represents the gradient of the policy function; r+γV(s′)-V(s) represents the advantage function, which indicates the pros and cons of the current action; Represents the objective function after updating using policy gradient; S7、通过静态扭矩传感器实时检测用户膝关节的力矩数据并传输至数据处理模块；S7, detecting the torque data of the user's knee joint in real time through a static torque sensor and transmitting the data to a data processing module; S8、通过数据处理模块接收用户膝关节的力矩数据并进行处理和分析，生成康复策略，同时通过用户交互模块进行数据显示和交互。S8. Receive the torque data of the user's knee joint through the data processing module, process and analyze it, generate a rehabilitation strategy, and display and interact with the data through the user interaction module. 7.根据权利要求5所述的一种自对心的膝关节测训方法，其特征在于，所述测训方法还包括腿部的肌肉训练方法，具体包括以下步骤：7. A self-aligned knee joint training method according to claim 5, characterized in that the training method also includes a leg muscle training method, specifically comprising the following steps: S1、用户位于座椅上通过大腿绑带将大腿与座椅固定，并通过小腿绑带将小腿与光轴固定；S1. The user is sitting on the seat and fixes the thigh to the seat through the thigh strap, and fixes the calf to the optical axis through the calf strap; S2、用户通过用户交互模块选择腿部的肌肉训练相应的预设执行程序；S2, the user selects a preset execution program corresponding to the leg muscle training through the user interaction module; S3、启动电机，通过谐波减速器驱动光轴以预设角速度进行单摆运动，带动用户小腿屈伸并带动光轴在直线轴承上滑动伸长，同时力矩输出测量模块受小腿伸长动作的牵拉作用在圆轨上滑动，使力矩输出测量模块的旋转轴始终与用户膝关节的旋转轴对齐；S3, start the motor, drive the optical axis to perform a single pendulum motion at a preset angular velocity through the harmonic reducer, drive the user's calf to flex and extend, and drive the optical axis to slide and extend on the linear bearing. At the same time, the torque output measurement module slides on the circular rail under the pulling effect of the calf extension action, so that the rotation axis of the torque output measurement module is always aligned with the rotation axis of the user's knee joint; S4、通过电位器实时检测用户的膝关节屈伸角度并传输至数据处理模块，并通过数据处理模块实时采集用户的下肢参数；S4, detecting the user's knee flexion and extension angle in real time through a potentiometer and transmitting the angle to a data processing module, and collecting the user's lower limb parameters in real time through the data processing module; S5、通过数据处理模块基于生物力学模型结合模糊PID控制算法控制力矩输出模块的输出力矩；S5, controlling the output torque of the torque output module through the data processing module based on the biomechanical model combined with the fuzzy PID control algorithm; S6、通过静态扭矩传感器实时检测用户膝关节的力矩数据并传输至数据处理模块，通过数据处理模块基于肌肉-骨骼模型结合疲劳监测算法对力矩数据进行分析并判断用户肌肉的疲劳程度；S6. Detect the torque data of the user's knee joint in real time through a static torque sensor and transmit it to a data processing module. The data processing module analyzes the torque data based on a muscle-bone model combined with a fatigue monitoring algorithm and determines the fatigue degree of the user's muscles; 所述数据处理模块基于肌肉-骨骼模型结合疲劳监测算法是通过用户膝关节的力矩、角度、角速度数据通过分析信号特征的变化趋势来判断运动状态的，所述信号特征包括膝关节最大力矩、平均力矩、角度变化范围、角速度变化值；The data processing module is based on the muscle-skeletal model combined with the fatigue monitoring algorithm to judge the motion state by analyzing the change trend of signal characteristics through the torque, angle and angular velocity data of the user's knee joint. The signal characteristics include the maximum torque of the knee joint, the average torque, the angle change range, and the angular velocity change value; S7、根据用户肌肉的疲劳程度优化力矩输出模块的输出力矩，训练达到一定时长后逐渐降低力矩输出；S7. Optimize the output torque of the torque output module according to the fatigue level of the user's muscles, and gradually reduce the torque output after the training reaches a certain length of time; S8、通过用户交互模块在整个训练过程中实时显示相关数据，并在训练结束后生成训练建议。S8. Display relevant data in real time during the entire training process through the user interaction module, and generate training suggestions after the training is completed. 8.根据权利要求6-7任一所述的一种自对心的膝关节测训方法，其特征在于，所述模糊PID控制算法控制力矩输出模块的输出力矩通过以下公式(11)进行表示：8. A self-aligning knee joint testing and training method according to any one of claims 6-7, characterized in that the output torque of the torque output module controlled by the fuzzy PID control algorithm is expressed by the following formula (11): 公式(11)中：u(t)表示控制输出；e(t)表示目标力矩和实际力矩的误差；d表示微分；t表示时间；Kp、Ki、Kd、分别为比例、积分、微分系数。In formula (11), u(t) represents the control output; e(t) represents the error between the target torque and the actual torque; d represents differential; t represents time; Kp , Ki , Kd are proportional, integral, and differential coefficients, respectively.
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