Muscular tension expression simulation method and system for intelligent medical robot with body

Abstract

The invention discloses a muscular tension performance simulation method and system of an intelligent medical robot with a body, the intelligent medical robot with the body comprises a plurality of movable joints and a driving motor, and the method comprises the following steps: S1, constructing a muscular tension simulation resistance moment model, and S2, obtaining a simulation case issued by a user; s3, acquiring a simulation parameter instruction of the user based on the simulation case; and S4, in response to the operation of the user on the muscular tension part, acquiring the passive rotation angle of the movable joint associated with the muscular tension part in real time, calculating the real-time muscular tension simulation resistance torque based on the muscular tension simulation resistance torque model, and sending the real-time muscular tension simulation resistance torque to a driving motor to output the real-time muscular tension simulation resistance torque to simulate muscular tension expression. According to the method, the intelligent medical robot with the body can give real-time interaction feedback when a user feels operation under different muscular tension modes of different parts, and the interaction experience is improved.

Description

Technical Field

[0001] This application relates to the field of simulation, and in particular to a method and system for simulating muscle tone performance in an embodied intelligent medical robot. Background Technology

[0002] Muscle tone refers to an involuntary, continuous, and subtle contraction of muscle tissue at rest. It is fundamental for maintaining various body postures and normal movement. It manifests as resting muscle tone, postural muscle tone, and kinetic muscle tone, and is evaluated through observation, palpation, and passive movement. Abnormalities include increased muscle tone and decreased muscle tone.

[0003] Existing muscle tone assessment training mainly relies on practical operations on real patients and some medical teaching models, but it has the following drawbacks: The lack of cooperation from real patients resulted in medical students lacking practical training during the teaching process; The simulation lacks abnormal pathological features, such as the simulation of special pathological features like clasp knife-like or lead pipe-like structures under conditions of increased muscle tone. Summary of the Invention

[0004] To address the aforementioned issues, this application provides a method for simulating muscle tone in a hymenoplasmic intelligent medical robot. The hymenoplasmic intelligent medical robot includes several movable joints and drive motors to simulate the movements of various joints in the human body. The method includes the following steps: S1, Construct a resistance torque model for muscle tension simulation, including: Based on the waveforms of muscle tone manifestations under different muscle tone patterns in clinical practice, and based on the correspondence between muscle tone manifestations and the simulated resistance torque of muscle tone output by the drive motor, a piecewise linear relationship is established between the simulated resistance torque of muscle tone output by the drive motor and the angle of passive rotation of the active joint. The muscle tone patterns include folding knife pattern and lead pipe pattern. The expression for the piecewise linear relationship of the muscle tension simulation resistance torque model is as follows: , Where: f(x) is the simulated resistance torque of muscle tension output by the drive motor; T is the angular travel of the simulated resistance torque of muscle tension; ω1, ω2, and ω3 are the proportions of the first, second, and third angular travel segments in the piecewise linear relationship of the simulated resistance torque model of muscle tension, respectively; M is the maximum value of the first segment torque in the piecewise linear relationship of the simulated resistance torque model of muscle tension; k is the slope of the second segment torque in the piecewise linear relationship of the simulated resistance torque model of muscle tension; and x is the angle of passive rotation of the movable joint. S2, Obtain the simulated case sent by the user, the simulated case including the muscle tension location and muscle tension pattern of the simulated patient; S3, obtain the user's simulation parameter instructions based on the simulated case. The simulation parameter instructions include the angle stroke of the muscle tension simulated resistance torque, the percentage of the first segment angle stroke, the percentage of the second segment angle stroke, the percentage of the third segment angle stroke, the maximum value of the first segment torque, and the slope of the second segment torque. S4, in response to the user's operation at the muscle tension site, acquires in real time the angle of passive rotation of the active joint associated with the muscle tension site, calculates the real-time muscle tension simulated resistance torque based on the muscle tension simulated resistance torque model, and sends it to the drive motor to output the real-time muscle tension simulated resistance torque to simulate muscle tension performance.

[0005] Furthermore, step S4 includes: S41, Based on the agreed mapping relationship between muscle tension sites and active joints and drive motors, determine the drive motor corresponding to the muscle tension site as the target drive motor; S42, in response to the user's operation at the muscle tension site, the angular displacement of the target drive motor under the operation is acquired in real time and marked as the angle of passive rotation of the movable joint; S43, Based on the muscle tension simulation resistance torque model, obtain the angle of passive rotation of the active joint and calculate the real-time muscle tension simulation resistance torque; S44, sends the real-time simulated muscle tension resistance torque to the target drive motor output to simulate the muscle tension resistance felt by the user at the muscle tension site.

[0006] Furthermore, after obtaining the user's simulation parameter instructions based on the simulated case in step S3, the simulation parameter instructions are also verified and corrected.

[0007] Furthermore, the simulation parameter commands are verified and corrected, specifically including: S31, Obtain the simulation parameter instruction, and obtain the current muscle tension simulation resistance torque waveform based on the muscle tension simulation resistance torque model; S32, determine the muscle tension pattern to which the current simulated resistance torque waveform belongs, and determine whether it is consistent with the muscle tension pattern in the simulated case. Yes, proceed to step S4. No, remind the user to correct the parameters.

[0008] Furthermore, step S32 determines the muscle tension mode to which the current simulated resistance torque waveform belongs, specifically including: S321, Establish a sample database of muscle tone patterns; Sample and label muscle tone waveforms of folding knife pattern and lead pipe pattern from clinical or medical textbooks, and establish sample databases of folding knife pattern and lead pipe pattern. S322, compare the similarity of the current muscle tension simulated resistance torque waveform with the muscle tension waveform samples in the muscle tension pattern sample database, and identify the muscle tension pattern corresponding to the muscle tension waveform sample with the highest similarity as the muscle tension pattern of the current muscle tension simulated resistance torque waveform.

[0009] Furthermore, it also includes S323, which saves the current muscle tension simulation resistance torque waveform and muscle tension pattern to the muscle tension pattern sample database.

[0010] This application also provides a muscle tone performance simulation system for an embodied intelligent medical robot, used to perform the above-described muscle tone performance simulation method for an embodied intelligent medical robot, the system comprising: The embody intelligent medical robot is configured to include several movable joints and drive motors; The database includes a simulated case database and a muscle tension pattern sample database. The simulated cases in the simulated case database include the muscle tension location and muscle tension pattern of the simulated patient. The samples in the muscle tension pattern sample database include muscle tension pattern waveforms and their corresponding muscle tension patterns, including folding knife pattern and lead pipe pattern. The input module is used by users to issue simulated cases and set simulation parameters; the simulation parameter commands include the angle stroke of the muscle tension simulated resistance torque, the percentage of the first segment angle stroke, the percentage of the second segment angle stroke, the percentage of the third segment angle stroke, the maximum value of the first segment torque, and the slope of the second segment torque; The muscle tension performance module has a preset muscle tension simulation resistance torque model algorithm. Based on the simulated case and set simulation parameters issued by the user, it responds to the user's operation at the muscle tension site, obtains the passive rotation angle of the associated joint in real time, calculates the real-time muscle tension simulation resistance torque based on the muscle tension simulation resistance torque model, and sends it to the drive motor to output the real-time muscle tension simulation resistance torque to simulate muscle tension performance.

[0011] Furthermore, it also includes a verification and correction module, which is used to obtain the simulation parameter instructions, obtain the current muscle tension simulation resistance torque waveform based on the muscle tension simulation resistance torque model, determine the muscle tension mode to which the current muscle tension simulation resistance torque waveform belongs by comparing it with samples in the muscle tension mode sample database, and remind the user to correct the parameters if it is inconsistent with the muscle tension mode in the simulated case.

[0012] The beneficial effects of this application are as follows: This application constructs a muscle tension simulation resistance torque model and uses an algorithm to simulate the waveforms of different muscle tension modes, including the folding knife mode and the lead pipe mode, thereby reducing development costs; users can set corresponding simulation parameter instructions according to different simulated cases, and when users perform operations, the embodied intelligent medical robot can provide real-time simulated feedback of muscle tension resistance based on the muscle tension location and muscle tension mode, thereby improving the interactive experience between users and the embodied intelligent medical robot. Attached Figure Description

[0013] Figure 1 This is a flowchart illustrating a method for simulating muscle tone in an embodied intelligent medical robot according to an embodiment of this application.

[0014] Figure 2 This is a flowchart illustrating step S4 of an embodiment of this application.

[0015] Figure 3 This is a flowchart illustrating the steps of verifying and correcting the simulation parameter instructions in the embodiments of this application.

[0016] Figure 4 This is a schematic diagram of the process for determining the muscle tension mode to which the simulated resistance torque waveform of the current muscle tension belongs in the embodiments of this application.

[0017] Figure 5 This is a schematic diagram showing the mapping relationship between muscle tension sites, movable joints, and drive motors in an embodiment of this application.

[0018] Figure 6 This is a schematic diagram of the movable joints and drive motors of the embodied intelligent medical robot arm according to an embodiment of this application.

[0019] Figure 7 This is a schematic diagram illustrating typical clinical manifestations of increased muscle tone under different conditions.

[0020] Figure 8 This is a schematic diagram of the resistance torque waveform for simulating muscle tension in a folding knife-like pattern, according to another embodiment of this application.

[0021] Figure 9 This is a schematic diagram of the resistance torque waveform for simulating muscle tension in a folding knife-like pattern, according to another embodiment of this application.

[0022] Figure 10 This is a schematic diagram of the resistance torque waveform for simulating muscle tension in a lead-pipe-like pattern, as described in other embodiments of this application. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of this application.

[0024] like Figures 1-10 As shown in the figure, this application provides a method for simulating muscle tone performance in a hymenoplasmic intelligent medical robot. The hymenoplasmic intelligent medical robot includes several movable joints and drive motors to simulate the movement of various joints in the human body. The method includes the following steps: S1, Construct a resistance torque model simulating muscle tension; S2, obtain the simulated case sent by the user. The simulated case includes the muscle tension location and muscle tension pattern of the simulated patient; S3, obtain the user's simulation parameter instructions based on the simulated case. The simulation parameter instructions include the angle stroke of the muscle tension simulated resistance torque, the percentage of the first angle stroke, the percentage of the second angle stroke, the percentage of the third angle stroke, the maximum value of the first torque, and the slope of the second torque. S4, in response to the user's operation on the muscle tension area, acquires the angle of passive rotation of the active joint associated with the muscle tension area in real time, calculates the real-time muscle tension simulated resistance torque based on the muscle tension simulated resistance torque model, and sends it to the drive motor to output the real-time muscle tension simulated resistance torque to simulate muscle tension performance.

[0025] like Figure 7 The image shows typical clinical manifestations of increased muscle tone in different states (Source: Neurology / Hao Junwei, Luo Yan, eds., 9th edition, p. 103, People's Medical Publishing House, July 2024 (National Higher Education Five-Year Undergraduate Clinical Medicine Major Tenth Round Planning Textbook). ISBN 978-7-117-36579-6). Figure 7 (a) shows a clasp-knife pattern of increased muscle tone. The left side shows the waveform trend of muscle tone resistance, and the right side shows the movement trend. In the clasp-knife pattern, the initial resistance is high. When the examiner begins to passively flex and extend the limb, they will feel obvious resistance. As the angle of movement continues to increase, the resistance will suddenly decrease significantly at a certain point, just like the feeling of opening and closing a folding knife. This is due to the hyperactivity of the stretch reflex (tendon reflex). The muscle reflexively contracts in the initial stage of being stretched. Once it exceeds a certain length, the inhibitory mechanism of the spinal reflex comes into play, resulting in a sudden drop in resistance. Common diseases: stroke, spinal cord injury, traumatic brain injury, amyotrophic lateral sclerosis (ALS), etc. Figure 7(b) shows a lead-pipe pattern of increased muscle tone. The left side shows the waveform trend of muscle tone resistance, and the right side shows the movement trend. In the lead-pipe pattern, a uniform, continuous, and stiff resistance is felt throughout the entire range of motion of the passive joint, feeling like bending a heavy lead pipe. The resistance is uniform throughout, without sudden drops. This is due to the simultaneous and continuous contraction of the agonist and antagonist muscles (generalized increase in muscle tone). This differs from the clasp-knife pattern of increased muscle tone, which only affects the stretch reflex. Lead-pipe rigidity indicates increased muscle tone even at rest. Common disease: Parkinson's disease.

[0026] In this embodiment, step S1, constructing a muscle tension simulation resistance torque model, includes: Based on the waveforms of muscle tone under different muscle tone patterns in clinical practice, and based on the correspondence between muscle tone manifestation and the simulated resistance torque of muscle tone output by the drive motor, a piecewise linear relationship is established between the simulated resistance torque of muscle tone output by the drive motor and the angle of passive rotation of the active joint. Among them, the muscle tone patterns include folding knife pattern and lead pipe pattern. The piecewise linear relationship expression for the resistance torque model simulating muscle tension is as follows: , Where: f(x) is the simulated resistance torque of muscle tension output by the drive motor; T is the angular travel of the simulated resistance torque of muscle tension; ω1, ω2, and ω3 are the proportions of the first, second, and third angular travel segments in the piecewise linear relationship of the simulated resistance torque model of muscle tension, respectively; M is the maximum value of the first segment torque in the piecewise linear relationship of the simulated resistance torque model of muscle tension; k is the slope of the second segment torque in the piecewise linear relationship of the simulated resistance torque model of muscle tension; and x is the angle of passive rotation of the movable joint.

[0027] In this step, a piecewise linear algorithm is used to obtain the user-set simulation parameter instructions, obtain the simulated resistance torque of muscle tension, and then drive the drive motor to output to simulate muscle tension resistance, thus realizing the simulation of muscle tension performance in folding knife-like mode and lead pipe-like mode.

[0028] The following example uses the elbow joint as the movable joint. By setting different simulation parameters, we can simulate the muscle tension performance of different muscle tension patterns. The normal range of motion of the human elbow joint is approximately 140 degrees. Here, we take 140 degrees as the maximum range of motion of the elbow joint. Specifically: Parameter settings 1: T=70 degrees, ω1=50%, ω2=0%, ω3=50%, k=0, M=2. The simulated resistance torque waveform of muscle tension obtained based on these parameters is as follows: Figure 8The diagram shown is a schematic of the simulated resistance torque waveform for muscle tension in a folding knife pattern. The angular travel of the simulated resistance torque is 70 degrees. The first segment of the angular travel accounts for 50%, so the first segment's angular travel is 35 degrees (70*50%). The second segment's angular travel accounts for 0%, so the second segment's angular travel is 0 degrees. The third segment's angular travel accounts for 50%, so the third segment's angular travel is 35 degrees (70*50%). From... Figure 8 As can be seen from the diagram: In the first segment, when the user operates the elbow joint, the simulated resistance torque gradually increases at the beginning, meaning the simulated resistance felt by the user gradually increases. When the elbow joint is passively rotated to 35 degrees, the simulated resistance torque reaches the maximum value of 2 (Nm) set for the first segment, and the user feels the maximum simulated resistance. In the second segment, the angle travel is 0 degrees, meaning there is no second segment waveform. In the third segment, as the elbow joint continues to rotate, the angle increases and the simulated resistance torque decreases, and the simulated resistance also decreases. When the angle travel reaches the set simulated resistance torque of 70 degrees, the simulated resistance torque disappears, and the simulated resistance felt by the user also disappears. In the fourth segment, the elbow joint range of motion is 0-140 degrees, the angle travel of the simulated resistance torque is 70 degrees, and when it is greater than 70 degrees, the simulated resistance torque is 0, and the simulated resistance felt by the user is 0.

[0029] Parameter setting 2: T=70 degrees, ω1=50%, ω2=30%, ω3=20%, k=0.005, M=2. The simulated resistance torque waveform of muscle tension obtained based on these parameters is as follows: Figure 9 The diagram shown is a schematic of the simulated resistance torque waveform for muscle tension in a folding knife pattern. The angular travel of the simulated resistance torque is 70 degrees. The first segment of the angular travel accounts for 50%, so the first segment's angular travel is 35 degrees (70*50%). The second segment accounts for 30%, so the second segment's angular travel is 21 degrees (70*30%). The third segment accounts for 50%, so the third segment's angular travel is 14 degrees (70*20%). From... Figure 9As can be seen from the data: In the first segment, when the user operates the elbow joint, the simulated resistance torque gradually increases at the beginning, meaning the simulated resistance felt by the user gradually increases. When the elbow joint is passively rotated to 35 degrees, the simulated resistance torque reaches the maximum value of 2 (Nm) set for the first segment. In the second segment, the angle travel is 21 degrees, and the slope of the torque in the second segment is positive. The simulated resistance torque continues to increase as the elbow joint rotation angle increases, reaching 56 degrees (35+21) before entering the third segment. In the third segment, as the elbow joint continues to rotate, the simulated resistance torque decreases as the angle increases, and the simulated resistance also decreases. When the angle travel reaches the set simulated resistance torque of 70 degrees, the simulated resistance torque disappears, and the simulated resistance felt by the user also disappears. In the fourth segment, the elbow joint range of motion is 0-140 degrees, and the angle travel of the simulated resistance torque is 70 degrees. When it is greater than 70 degrees, the simulated resistance torque is 0, and the simulated resistance felt by the user is 0.

[0030] Parameter setting 3: T=140 degrees, ω1=25%, ω2=50%, ω3=25%, k=-0.003, M=2. The simulated resistance torque waveform of muscle tension obtained based on these parameters is as follows: Figure 10 The diagram shown is a schematic of the simulated resistance torque waveform for muscle tension in a lead-pipe pattern. The simulated resistance torque has an angular travel of 140 degrees. The first segment of the angular travel accounts for 25%, so the first segment's angular travel is 35 degrees (140*25%). The second segment accounts for 50%, so the second segment's angular travel is 70 degrees (140*50%). The third segment accounts for 25%, so the third segment's angular travel is 35 degrees (140*25%). From... Figure 10 As can be seen, the 140-degree angle travel of the simulated resistance torque of muscle tension is consistent with the maximum range of motion of the elbow joint, which is 140 degrees. The entire waveform consists of three segments: the first segment, the second segment, and the third segment. In the first segment, when the user operates the elbow joint, the simulated resistance torque of muscle tension gradually increases at the beginning, meaning that the simulated resistance of muscle tension felt by the user gradually increases. When the elbow joint is passively rotated to 35 degrees, the simulated resistance torque of muscle tension reaches the maximum value of 2 (Nm) of the first segment torque. The angle travel of the second segment is 70 degrees, and the slope of the second segment torque is negative. The simulated resistance torque of muscle tension decreases as the rotation angle of the elbow joint increases. After reaching an angle of 105 degrees (35+70), it enters the third segment. In the third segment, as the elbow joint continues to be rotated, the angle increases and the simulated resistance torque of muscle tension decreases, and the simulated resistance of muscle tension also decreases until it disappears.

[0031] Figures 8-10In this diagram, the horizontal axis represents the range of motion of the joint, and the vertical axis represents the simulated resistance torque of muscle tension (Nm). The human elbow joint has a range of motion of approximately 140 degrees; therefore, in this example, the horizontal axis range is 0~140 degrees. Different human joints have different ranges of motion, and users can adjust these settings based on teaching materials, clinical data, and experience. This step allows for the calculation of simulated resistance torque of muscle tension under different muscle tension modes by adjusting the parameters, saving on the development costs of different modes.

[0032] In this embodiment, as Figure 2 As shown, step S4 includes: S41, Based on the agreed mapping relationship between muscle tension location and active joint and drive motor, determine the drive motor corresponding to the muscle tension location as the target drive motor; S42, in response to the user's operation on the muscle tension area, acquires the angular displacement of the target drive motor under the operation in real time and marks it as the angle of passive rotation of the active joint; S43, based on the muscle tension simulation resistance torque model, obtains the angle of passive rotation of the active joint to calculate the real-time muscle tension simulation resistance torque; S44 sends the real-time simulated muscle tension resistance torque to the target drive motor output to simulate the muscle tension resistance felt by the user at the muscle tension site.

[0033] Due to the complex structure of human muscles and joints, the influence of muscles in different parts on joints is also complex. For example, the deltoid, trapezius, pectoralis major, and latissimus dorsi muscles constrain the movement of the shoulder joint; the biceps, triceps, and brachialis muscles constrain the elbow joint; and the quadriceps and hamstrings constrain the knee joint. Furthermore, different joint movements require different drive motors. Taking the arm of a body-worn intelligent medical robot as an example... Figure 5 The diagram shows the structure of the movable joints and drive motors of the arm 100 of an embodied intelligent medical robot. The arm 100 is equipped with drive motor 101, which drives the arm 100 to swing forward and backward; drive motor 102, which drives the arm 100 to extend; drive motor 103, which drives the upper arm to rotate, leading to the forearm and hand; drive motor 104, which simulates elbow joint movement; and drive motor 105, which drives the forearm to rotate. In response to user input, the movable joints move under the applied force, providing muscle tension to simulate resistance. Therefore, this embodiment uses a defined mapping relationship between muscle tension locations, movable joints, and drive motors to facilitate rapid identification of the target drive motor. Figure 6As shown, this is a pre-defined mapping structure between muscle tension locations, active joints, and drive motors. By pre-defining the mapping relationship, the active joints and drive motors corresponding to the muscle tension locations can be quickly identified, thereby determining the target drive motor that needs to provide feedback on simulated muscle tension resistance. The working status of the target drive motor is then acquired, and the calculated real-time simulated muscle tension resistance torque is sent in a directional manner to drive it to simulate the muscle tension resistance felt by the user.

[0034] Simulation parameter commands are typically set by teachers or experienced users based on the muscle tone patterns and locations in simulated cases. Inexperienced users or novice medical students may inevitably make mistakes in setting these parameters, leading to incorrect resistance signals from the embodied intelligent medical robot. Therefore, in some embodiments, to prevent the muscle tone simulated resistance torque generated by the user-set simulation parameter commands from having a different muscle tone pattern than the muscle tone pattern in the simulated case, thus causing the embodied intelligent medical robot to provide incorrect muscle tone resistance feedback and mislead the user, step S3, after obtaining the user's simulation parameter commands based on the simulated case, also includes verifying and correcting the simulation parameter commands, such as... Figures 3-4 As shown, this step specifically includes: S31, Obtain simulation parameter command, and obtain the current muscle tension simulation resistance torque waveform based on the muscle tension simulation resistance torque model; S32, determine the muscle tension pattern to which the current simulated resistance torque waveform belongs, and judge whether it is consistent with the muscle tension pattern in the simulated case. Yes, proceed to step S4. No, remind the user to correct the parameters.

[0035] In this embodiment, step S32, which determines the muscle tension mode to which the current simulated resistance torque waveform belongs, specifically includes: S321, Establish a sample database of muscle tone patterns; Sample and label muscle tone waveforms of folding knife pattern and lead pipe pattern from clinical or medical textbooks, and establish sample databases of folding knife pattern and lead pipe pattern. S322, compare the similarity of the current muscle tension simulated resistance torque waveform with the muscle tension waveform samples in the muscle tension pattern sample database, and identify the muscle tension pattern corresponding to the muscle tension waveform sample with the highest similarity as the muscle tension pattern of the current muscle tension simulated resistance torque waveform.

[0036] Furthermore, it also includes S323, which saves the current muscle tension simulation resistance torque waveform and muscle tension pattern to the muscle tension pattern sample database.

[0037] In this step, a muscle tension pattern sample database is constructed to obtain simulation parameter commands. Based on the muscle tension simulation resistance torque model, the muscle tension simulation resistance torque waveform of the current simulation parameter command is obtained. The similarity is compared with the samples in the muscle tension pattern sample database to determine its muscle tension pattern and store it in the sample database. This not only increases the amount of data in the sample database and enriches the sample size, but also makes the comparison results more accurate by using one-to-one comparison.

[0038] This application embodiment also provides a muscle tone performance simulation system for an embodied intelligent medical robot, used to perform the above-described muscle tone performance simulation method for an embodied intelligent medical robot, the system comprising: The embody intelligent medical robot is configured to include several movable joints and drive motors; The database includes a simulated case database and a muscle tension pattern sample database. The simulated cases in the simulated case database include the muscle tension location and muscle tension pattern of the simulated patients. The samples in the muscle tension pattern sample database include muscle tension pattern waveforms and their corresponding muscle tension patterns, including clasp knife pattern and lead pipe pattern. The input module is used by users to issue simulated cases and set simulation parameters. The simulation parameter commands include the angle travel of the muscle tension simulated resistance torque, the percentage of the first angle travel, the percentage of the second angle travel, the percentage of the third angle travel, the maximum value of the first torque, and the slope of the second torque. The muscle tension performance module has a preset muscle tension simulation resistance torque model algorithm. Based on the simulated case and set simulation parameters issued by the user, it responds to the user's operation at the muscle tension site, obtains the passive rotation angle of the associated joint in real time, calculates the real-time muscle tension simulation resistance torque based on the muscle tension simulation resistance torque model, and sends it to the drive motor to output the real-time muscle tension simulation resistance torque to simulate muscle tension performance.

[0039] In this embodiment, a verification and correction module is also included, which is used to obtain simulation parameter instructions, obtain the current muscle tension simulation resistance torque waveform based on the muscle tension simulation resistance torque model, and determine the muscle tension mode to which the current muscle tension simulation resistance torque waveform belongs by comparing it with samples in the muscle tension mode sample database. If it is inconsistent with the muscle tension mode in the simulated case, the user is reminded to correct the parameters.

Claims

1. A method for simulating muscle tone performance in an embodied intelligent medical robot, characterized in that, The embodied intelligent medical robot includes several movable joints and drive motors to simulate the movement of various joints in the human body. The method includes the following steps: S1, Construct a resistance torque model for muscle tension simulation, including: Based on the waveforms of muscle tone manifestations under different muscle tone patterns in clinical practice, and based on the correspondence between muscle tone manifestations and the simulated resistance torque of muscle tone output by the drive motor, a piecewise linear relationship is established between the simulated resistance torque of muscle tone output by the drive motor and the angle of passive rotation of the active joint. The muscle tone patterns include folding knife pattern and lead pipe pattern. The piecewise linear relationship expression of the muscle tension simulation resistance torque model is as follows: ， Where: f(x) is the simulated resistance torque of muscle tension output by the drive motor; T is the angular travel of the simulated resistance torque of muscle tension; ω1, ω2, and ω3 are the proportions of the first, second, and third angular travel segments in the piecewise linear relationship of the simulated resistance torque model of muscle tension, respectively; M is the maximum value of the first segment torque in the piecewise linear relationship of the simulated resistance torque model of muscle tension; k is the slope of the second segment torque in the piecewise linear relationship of the simulated resistance torque model of muscle tension; and x is the angle of passive rotation of the movable joint. S2, Obtain the simulated case sent by the user, the simulated case including the muscle tension location and muscle tension pattern of the simulated patient; S3, obtain the user's simulation parameter instructions based on the simulated case. The simulation parameter instructions include the angle stroke of the muscle tension simulated resistance torque, the percentage of the first segment angle stroke, the percentage of the second segment angle stroke, the percentage of the third segment angle stroke, the maximum value of the first segment torque, and the slope of the second segment torque. S4, in response to the user's operation at the muscle tension site, acquires in real time the angle of passive rotation of the active joint associated with the muscle tension site, calculates the real-time muscle tension simulated resistance torque based on the muscle tension simulated resistance torque model, and sends it to the drive motor to output the real-time muscle tension simulated resistance torque to simulate muscle tension performance.

2. The method for simulating muscle tone performance in a hygienic intelligent medical robot according to claim 1, characterized in that, Step S4 includes: S41, Based on the agreed mapping relationship between muscle tension sites and active joints and drive motors, determine the drive motor corresponding to the muscle tension site as the target drive motor; S42, in response to the user's operation at the muscle tension site, the angular displacement of the target drive motor under the operation is acquired in real time and marked as the angle of passive rotation of the movable joint; S43, Based on the muscle tension simulation resistance torque model, obtain the angle of passive rotation of the active joint and calculate the real-time muscle tension simulation resistance torque; S44, sends the real-time simulated muscle tension resistance torque to the target drive motor output to simulate the muscle tension resistance felt by the user at the muscle tension site.

3. The method for simulating muscle tone performance in a hygienic intelligent medical robot according to claim 1, characterized in that, After obtaining the user's simulation parameter instructions based on the simulated case in step S3, the method further includes verifying and correcting the simulation parameter instructions.

4. The method for simulating muscle tone performance in a hygienic intelligent medical robot according to claim 3, characterized in that, The simulation parameter commands are verified and corrected, specifically including: S31, Obtain the simulation parameter instruction, and obtain the current muscle tension simulation resistance torque waveform based on the muscle tension simulation resistance torque model; S32, determine the muscle tension pattern to which the current simulated resistance torque waveform belongs, and determine whether it is consistent with the muscle tension pattern in the simulated case. Yes, proceed to step S4. No, remind the user to correct the parameters.

5. The method for simulating muscle tone performance in a hygienic intelligent medical robot according to claim 4, characterized in that, Step S32 determines the muscle tension mode to which the current simulated resistance torque waveform belongs, specifically including: S321, Establish a sample database of muscle tone patterns; Sample and label muscle tone waveforms of folding knife pattern and lead pipe pattern from clinical or medical textbooks, and establish sample databases of folding knife pattern and lead pipe pattern. S322, compare the similarity of the current muscle tension simulated resistance torque waveform with the muscle tension waveform samples in the muscle tension pattern sample database, and identify the muscle tension pattern corresponding to the muscle tension waveform sample with the highest similarity as the muscle tension pattern of the current muscle tension simulated resistance torque waveform.

6. The method for simulating muscle tone performance in a hygienic intelligent medical robot according to claim 5, characterized in that, It also includes S323, which saves the current muscle tension simulation resistance torque waveform and muscle tension pattern to the muscle tension pattern sample database.

7. A muscle tone simulation system for an embodied intelligent medical robot, characterized in that, A method for simulating muscle tone performance in an embodied intelligent medical robot as described in any one of claims 1 to 6, the system comprising: The embody intelligent medical robot is configured to include several movable joints and drive motors; The database includes a simulated case database and a muscle tension pattern sample database. The simulated cases in the simulated case database include the muscle tension location and muscle tension pattern of the simulated patient. The samples in the muscle tension pattern sample database include muscle tension pattern waveforms and their corresponding muscle tension patterns, including folding knife pattern and lead pipe pattern. The input module is used by users to issue simulated cases and set simulation parameters; the simulation parameter commands include the angle stroke of the muscle tension simulated resistance torque, the percentage of the first segment angle stroke, the percentage of the second segment angle stroke, the percentage of the third segment angle stroke, the maximum value of the first segment torque, and the slope of the second segment torque; The muscle tension performance module has a preset muscle tension simulation resistance torque model algorithm. Based on the simulated case and set simulation parameters issued by the user, it responds to the user's operation at the muscle tension site, obtains the passive rotation angle of the associated joint in real time, calculates the real-time muscle tension simulation resistance torque based on the muscle tension simulation resistance torque model, and sends it to the drive motor to output the real-time muscle tension simulation resistance torque to simulate muscle tension performance.

8. The muscle tone simulation system for a hymenoplasmic intelligent medical robot according to claim 7, characterized in that, It also includes a verification and correction module, which is used to obtain the simulation parameter instructions, obtain the current muscle tension simulation resistance torque waveform based on the muscle tension simulation resistance torque model, determine the muscle tension mode to which the current muscle tension simulation resistance torque waveform belongs by comparing it with samples in the muscle tension mode sample database, and remind the user to correct the parameters if it is inconsistent with the muscle tension mode in the simulated case.

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