Orthopedic patient lower limb rehabilitation training device

Abstract

The invention discloses an orthopedic patient lower limb rehabilitation training device which comprises a frame, a seat, a grip, a pedal, a flywheel, an electromagnetic resistance regulator, a band-type brake, a first angular velocity sensor used for measuring the rotation angular velocity of the flywheel, a second angular velocity sensor used for measuring the rotation angular velocity of the pedal, and a pedal pressure sensor used for measuring the rotation angular velocity of the flywheel. The pedal pressure sensor is used for measuring the pressure of a patient stepping on a pedal, the bioelectric sensor wearing device is used for being worn on the body of the patient, the operation panel is provided with a central control chip, and the central control chip is used for measuring the pressure of the patient stepping on the pedal according to a first angular velocity sensor, a second angular velocity sensor, a pedal pressure sensor and the bioelectric sensor wearing device. The riding power, the joint movement change rate, the strength balance degree, the heart rate and the blood oxygen saturation degree are calculated, and an electromagnetic resistance regulator and a band-type brake are controlled to work. Therefore, on one hand, the beneficial effect that personalized rehabilitation training can be provided for the patient is achieved, and on the other hand, the beneficial effect that training safety is good is achieved.

Description

Technical Field

[0001] The invention relates to the field of medical equipment, and in particular to a lower limb rehabilitation training device for orthopedic patients. Background Art

[0002] The lower limbs are important supporting and moving parts of the human body, and their rehabilitation directly affects the patient's quality of life. During the rehabilitation process of orthopedic patients, especially after lower limb injuries or surgery, appropriate rehabilitation training plays an irreplaceable role in restoring lower limb function, improving joint mobility, enhancing muscle strength and promoting blood circulation.

[0003] Traditional lower limb rehabilitation training methods include manual assisted training and simple equipment training. Manual assisted training relies on the help of medical staff or family members. This method is not only manpower-consuming, but also difficult to ensure the standardization and continuity of training. Although simple equipment training can help patients to conduct independent training to a certain extent, its functions are relatively single and cannot be personalized according to the patient's specific situation. It is also difficult to comprehensively monitor the patient's various physiological indicators and movement parameters during the training process. For example, some conventional pedal-type training equipment can only provide a fixed resistance mode and cannot adapt to the strength changes and joint mobility of different patients at different stages of rehabilitation.

[0004] In recent years, intelligent rehabilitation training devices have been able to monitor patients' training status more accurately and provide personalized training plans based on individual differences in patients. However, some existing intelligent rehabilitation training devices still have some shortcomings. For example, although some devices can collect some motion data, the data analysis is not comprehensive enough and cannot accurately evaluate important indicators such as the patient's strength balance. Or the safety protection is not perfect enough and cannot respond to emergencies that may occur during patient training in a timely and effective manner. Summary of the invention

[0005] The present invention aims to solve the technical problems in the above-mentioned technology at least to some extent.

[0006] To this end, the present invention discloses a lower limb rehabilitation training device for orthopedic patients, comprising:

[0007] frame;

[0008] A seat, which is arranged on the frame and is used for a patient to sit on;

[0009] A handle, which is arranged on the frame and is used for the patient to grasp;

[0010] A foot pedal, which is arranged on the frame and is used for the patient to step on;

[0011] A flywheel, which is arranged on the frame and is linked to the pedal via a chain;

[0012] An electromagnetic resistance regulator, which is arranged on the flywheel and is used to adjust the rotation resistance of the flywheel;

[0013] A holding brake, which is arranged on the flywheel and is used to stop the rotation of the flywheel;

[0014] a first angular velocity sensor, which is disposed on the flywheel and is used to measure the rotational angular velocity of the flywheel;

[0015] A second angular velocity sensor, which is arranged at the connecting shaft of the pedal and is used to measure the rotational angular velocity of the pedal;

[0016] A foot pressure sensor, which is arranged on the foot pedal and is used to measure the pressure of the patient stepping on the foot pedal;

[0017] A wearable bioelectric sensor device, which is used to be worn on the patient's body;

[0018] An operation panel is arranged on the frame and is provided with a central control chip. The central control chip is used to calculate the riding power, the rate of change of joint activity, the strength balance, the heart rate and the blood oxygen saturation according to the first angular velocity sensor, the second angular velocity sensor, the pedal pressure sensor and the bioelectric sensor wearable device, and to control the operation of the electromagnetic resistance regulator and the brake.

[0019] The lower limb rehabilitation training device for orthopedic patients disclosed in the present invention has the following effects:

[0020] (1) It can provide personalized rehabilitation training for patients. The device can accurately collect corresponding data through the first angular velocity sensor, the second angular velocity sensor, the pedal pressure sensor and the bioelectric sensor. The central control chip dynamically adjusts the output value of the electromagnetic resistance regulator according to the analysis data to achieve personalized rehabilitation training and effectively improve the rehabilitation effect.

[0021] (2) It has good training safety. The device is equipped with a brake. During the training process, the central control chip determines whether the brake needs to be activated based on the analysis data to ensure training safety.

[0022] In addition, the lower limb rehabilitation training device for orthopedic patients disclosed in the present invention may also have the following additional technical features:

[0023] In one embodiment of the present invention, the time interval between two sampling points of the first angular velocity sensor, the second angular velocity sensor, the pedal pressure sensor and the bioelectric sensor wearable device is Δt.

[0024] In one embodiment of the present invention, the central control chip constructs a first formula to calculate the riding power, specifically: P i =F i ×v i , F i =Fl i +F ri , where P i For the time T i The riding power, F li is the pedal pressure sensor at time T i The force measured on the left pedal, F ri is the pedal pressure sensor at time T i The force measured on the right pedal, v i The first angular velocity sensor at time T i The measured angular velocity of rotation of the flywheel;

[0025] The central control chip constructs a second formula to calculate the joint activity change rate, specifically: Among them, R i is the change rate of the joint activity within the time interval △t, θ i-1 The second angular velocity sensor at time T i-1 The measured rotation angle of the pedal, θ i The second angular velocity sensor at time T i The measured rotation angle of the foot pedal;

[0026] The central control chip constructs a third formula to calculate the power balance, specifically: Among them, B i For the time T i of the said force balance.

[0027] In one embodiment of the present invention, the central control chip dynamically adjusts the output value Y of the electromagnetic resistance regulator according to the following steps: a , specifically:

[0028] S1-1, constructing the first decision tree model, the input feature is the cycling power P i , the joint activity change rate R i , the power balance B i , the heart rate H i and the blood oxygen saturation S i , the input vector is x i =(P i ,R i ,B i ,H i ,Si );

[0029] S1-2, through the training data set X = {x1, x2, ..., x n} Train the first decision tree model to output the output value Y of the electromagnetic resistance regulator a , Y a ∈[0,1];

[0030] S1-3, using mean square error MSE as a first loss function to optimize the first decision tree model;

[0031] The central control chip dynamically adjusts the output value Y of the brake according to the following steps b , specifically:

[0032] S2-1, construct a second decision tree model, the input feature is the cycling power P i , the joint activity change rate R i , the power balance B i , the heart rate H i and the blood oxygen saturation S i , the input vector is x i =(P i ,R i ,B i ,H i ,S i );

[0033] S2-2, through the training data set X = {x1, x2, ..., x n} Train the second decision tree model to output the output value Y of the brake b , Y b ∈{0,1};

[0034] S2-3, using the cross entropy loss CEL as the second loss function to optimize the second decision tree model.

[0035] In one embodiment of the present invention, it also includes:

[0036] An emergency brake button, which is arranged on the frame and is used to immediately activate the brake;

[0037] A display is arranged on the operation panel, and is used to display the cycling power, the rate of change of the joint activity, the strength balance, the heart rate and the blood oxygen saturation.

[0038] In one embodiment of the present invention, it also includes:

[0039] The electric adjustment mechanism is arranged between the seat and the frame and is used for adjusting the height of the seat.

[0040] In one embodiment of the present invention, the surface of the foot pedal is provided with an anti-slip coating.

[0041] In one embodiment of the present invention, the frame is made of aluminum alloy, and the surface of the frame is frosted and matte.

[0042] Additional contents and advantages of the present invention will be given in the following description or will be understood through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The technical solutions and beneficial effects of the present invention will become apparent and easily understood from the following contents in conjunction with the accompanying drawings, wherein:

[0044] Figure 1 The structure of the lower limb rehabilitation training device for orthopedic patients in one embodiment of the present invention is shown in FIG. Figure 1 ;

[0045] Figure 2 The structure of the lower limb rehabilitation training device for orthopedic patients in one embodiment of the present invention is shown in FIG. Figure 2 ;

[0046] Figure 3 The structure of the lower limb rehabilitation training device for orthopedic patients in one embodiment of the present invention is shown in FIG. Figure 3 ;

[0047] Figure 4 A system block diagram of a lower limb rehabilitation training device for orthopedic patients in one embodiment of the present invention;

[0048] As shown in the figure:

[0049] 1-frame, 2-seat, 3-handle, 4-pedal, 5-flywheel, 6-electromagnetic resistance regulator, 7-brake, 8-first angular velocity sensor, 9-second angular velocity sensor, 10-pedal pressure sensor, 11-bioelectric sensor wearable device, 12-operation panel, 13-central control chip, 14-emergency brake button, 15-display, 16-electric adjustment mechanism. DETAILED DESCRIPTION

[0050] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0051] The lower limb rehabilitation training device for orthopedic patients disclosed in the present invention will be described below with reference to the accompanying drawings.

[0052] like Figure 1 , Figure 2 , Figure 3 and Figure 4As shown, a lower limb rehabilitation training device for orthopedic patients comprises:

[0053] Frame 1;

[0054] A seat 2, which is arranged on the frame 1 and is used for a patient to sit on;

[0055] A handle 3, which is arranged on the frame 1 and is used for the patient to grasp;

[0056] A foot pedal 4, which is arranged on the frame 1 and is used for the patient to step on;

[0057] A flywheel 5 is arranged on the frame 1 and is linked to the pedal 4 through a chain;

[0058] An electromagnetic resistance regulator 6, which is arranged on the flywheel 5 and is used to adjust the rotation resistance of the flywheel 5;

[0059] A holding brake 7, which is arranged on the flywheel 5 and is used to stop the rotation of the flywheel 5;

[0060] A first angular velocity sensor 8, which is arranged on the flywheel 5 and is used to measure the rotational angular velocity of the flywheel 5;

[0061] A second angular velocity sensor 9, which is arranged at the connecting shaft of the pedal 4 and is used to measure the rotational angular velocity of the pedal 4;

[0062] A foot pressure sensor 10 is provided on the foot pedal 4 and is used to measure the pressure of the patient stepping on the foot pedal 4;

[0063] A bioelectric sensor wearable device 11, which is used to be worn on the patient;

[0064] The operation panel 12 is arranged on the frame 1 and is provided with a central control chip 13. The central control chip 13 is used to calculate the riding power, the change rate of joint activity, the strength balance, the heart rate and the blood oxygen saturation according to the first angular velocity sensor 8, the second angular velocity sensor 9, the pedal pressure sensor 10 and the bioelectric sensor wearable device 11, and control the electromagnetic resistance regulator 6 and the brake 7 to work;

[0065] Specifically, place the lower limb rehabilitation training device for orthopedic patients on a stable ground, ensure that the frame 1 is stable, and the components are connected normally and without signs of looseness. The patient slowly sits on the seat 2, places his feet naturally on the foot pedals 4, and holds the handles 3 with both hands.

[0066] The time interval between two sampling points of the first angular velocity sensor 8, the second angular velocity sensor 9, the pedal pressure sensor 10 and the bioelectric sensor wearable device 11 is Δt.

[0067] Specifically, after the patient is ready, the entire lower limb rehabilitation training device for orthopedic patients is started, and at the same time, the first angular velocity sensor 8, the second angular velocity sensor 9, the pedal pressure sensor 10 and the bioelectric sensor wearable device 11 start working;

[0068] Assume that the patient begins to step on the pedal at a certain frequency. At the initial time T1, the first angular velocity sensor 8 measures the rotational angular velocity v1 = 5 rad / s of the flywheel 5, and the second angular velocity sensor 9 measures the rotational angle θ1 = 30° (converted to radians: ), the pedal pressure sensor 10 measures the force F of the left pedal l1 =20N, force F on the right pedal r1 =18N, the bioelectric sensor wearable device 11 collects the patient's heart rate H1=75times / min, and the blood oxygen saturation S1=97%;

[0069] The central control chip 13 constructs a first formula to calculate the riding power, specifically: P i =F i ×v i , F i =F li +F ri , where P i For the time T i Cycling power, F li The pedal pressure sensor 10 at time T i The measured force of the left pedal 4, F ri The pedal pressure sensor 10 at time T i The measured force on the right pedal 4, v i is the first angular velocity sensor 8 at time T i The measured rotational angular velocity of the flywheel 5;

[0070] Specifically, P1 = F1 × v1 = (F li +F ri )×v1=(20N+18N)×5rad / s=190W;

[0071] The central control chip 13 constructs a second formula to calculate the change rate of joint activity, specifically: Among them, R i is the rate of change of joint activity within the time interval △t, θ i-1 is the second angular velocity sensor 9 at time T i-1 The measured rotation angle of the pedal 4, θ i is the second angular velocity sensor 9 at time T i The measured rotation angle of the foot pedal 4;

[0072] Specifically, assuming that at the last moment T0 the pedal 4 rotates at an angle θ0 = 0° (converted to radians, 0), and the sampling interval △t = 1s, then

[0073] The central control chip 13 constructs a third formula to calculate the power balance, which is: Among them, B i For the time T i The balance of power;

[0074] Specifically,

[0075] The central control chip 13 dynamically adjusts the output value Y of the electromagnetic resistance regulator 6 according to the following steps: a , specifically:

[0076] S1-1, build the first decision tree model, the input feature is cycling power P i , joint activity change rate R i , Power Balance B i , heart rate i and blood oxygen saturation S i , the input vector is x i =(P i ,R i ,B i ,H i ,S i );

[0077] S1-2, through the training data set X = {x1, x2, ..., x n} Train the first decision tree model and output the output value Y of the electromagnetic resistance regulator 6 a , Y a ∈[0,1];

[0078] S1-3, using mean square error MSE as the first loss function to optimize the first decision tree model;

[0079] Specifically, a training dataset X = {x1, x2, …, x 100 Each set of data includes five characteristics: cycling power P, joint activity change rate R, strength balance B, heart rate H and blood oxygen saturation S, as well as the corresponding optimal output value of the electromagnetic resistance regulator. These data are determined through a large number of experiments and clinical experience;

[0080] Build the first decision tree model, select the CART algorithm, use the information gain ratio as the basis for feature selection, and start building the decision tree;

[0081] The information gain ratio of each feature in the training data set is calculated. It is found that the information gain ratio of the joint activity change rate R is relatively large. The joint activity change rate R is used as the root node for splitting. For example, the splitting threshold is set to 0.4. When R>0.4, it is one branch, and when R≤0.4, it is another branch.

[0082] Continue to calculate the information gain ratio of other features for the two subsets after the split, select the next best split feature, and repeat this process recursively until the stopping condition is met, such as the number of samples in the node is less than 10 or the depth of the tree reaches 5 layers, and finally build a decision tree model;

[0083] Input the parameter vector x1={P1=190, R1=0.52, B1=0.95, H1=75, S1=0.97} calculated at the current moment into the trained first decision tree model;

[0084] Starting from the root node, according to R1=0.52>0.4, traverse the decision tree downward along the corresponding branch. After a series of feature judgments, the final model outputs the output value Y of the electromagnetic resistance regulator. a =0.6, which is in the range of [0,1], indicating the relative size of the electromagnetic resistance. According to this output value, the electromagnetic resistance regulator 6 adjusts the rotational resistance of the flywheel 5 so that the patient feels a certain resistance increase to adapt to his current rehabilitation status and training progress.

[0085] The central control chip 13 dynamically adjusts the output value Y of the brake 7 according to the following steps: b , specifically:

[0086] S2-1, build the second decision tree model, the input feature is cycling power P i , joint activity change rate R i , Power Balance B i , heart rate i and blood oxygen saturation S i , the input vector is x i =(P i ,R i ,B i ,H i ,S i );

[0087] S2-2, through the training data set X = {x1, x2, ..., x n} Train the second decision tree model and output the output value Y of brake 7 b , Y b ∈{0,1};

[0088] S2-3, use the cross entropy loss CEL as the second loss function to optimize the second decision tree model.

[0089] Specifically, we use the training data set X = {x1, x2, …, x 100 Each set of data includes five characteristics: cycling power P, joint activity change rate R, strength balance B, heart rate H and blood oxygen saturation S, as well as the corresponding optimal output value of the electromagnetic resistance regulator. These data are determined through a large number of experiments and clinical experience;

[0090] Construct the second decision tree model, select the ID3 algorithm, and use information gain as the feature selection standard;

[0091] The information gain of each feature is calculated, and it is found that the information gain of blood oxygen saturation S is the largest. The blood oxygen saturation S is used as the root node for splitting, and the splitting threshold is set to 95%. When S>95%, it is one branch, and when S≤95%, it is another branch;

[0092] Continue to calculate the information gain of other features for the split subsets, select the best split feature for the next layer of splitting, and repeat this process until the stopping condition is met, such as all samples belong to the same category or there are no features available for splitting, or the depth of the tree reaches the set maximum value, which is assumed to be 4 layers here, to build a decision tree model for judging the brake output value;

[0093] Input the parameter vector x1={P1=190, R1=0.52, B1=0.95, H1=75, S1=0.97} calculated at the current moment into the trained second decision tree model;

[0094] Starting from the root node, since S1=97%>95%, we continue to judge the characteristics of subsequent nodes along the corresponding branches. After a series of calculations and judgments, the model outputs the output value Y of the brake. b =0, indicating that the brake 7 does not need to be activated in the current state, and the patient can continue to perform rehabilitation training safely;

[0095] As the training progresses, the above-mentioned data collection, parameter calculation, model decision-making and other processes are repeated at subsequent times T2, T3, ..., and the output values ​​of the electromagnetic resistance regulator 6 and the brake 7 are continuously adjusted to provide patients with personalized, safe and effective rehabilitation training.

[0096] In addition, the lower limb rehabilitation training device for orthopedic patients also includes:

[0097] An emergency brake button 14, which is arranged on the frame 1 and is used to immediately activate the brake 7;

[0098] A display 15, which is arranged on the operation panel 12, and is used to display cycling power, joint activity change rate, strength balance, heart rate and blood oxygen saturation;

[0099] An electric adjustment mechanism 16, which is arranged between the seat 2 and the frame 1, and is used to adjust the height of the seat 2;

[0100] Specifically, in an emergency, the patient or medical staff can directly press the button to immediately activate the brake 7 and stop the rotation of the flywheel 5 to prevent accidents;

[0101] Medical staff can intuitively understand the patient's training status and physical reaction based on the information displayed on the display 15, and adjust the training plan in time or perform necessary medical intervention on the patient. At the same time, patients can also better understand their training progress and physical condition by observing these parameters, thereby improving their enthusiasm and initiative in rehabilitation training.

[0102] The surface of the footrest 4 is provided with an anti-slip coating, the frame 1 is made of aluminum alloy, and the surface of the frame 1 is frosted and matte.

[0103] In summary, according to the lower limb rehabilitation training device for orthopedic patients disclosed in the present invention, on the one hand, personalized rehabilitation training can be provided for patients. The device can accurately collect corresponding data through the first angular velocity sensor 8, the second angular velocity sensor 9, the pedal pressure sensor 10 and the bioelectric sensor wearable device 11. The central control chip 13 dynamically adjusts the output value of the electromagnetic resistance regulator 6 according to the analysis data to achieve personalized rehabilitation training and effectively improve the rehabilitation effect. On the other hand, it has good training safety. The device is equipped with a brake 7. During the training process, the central control chip 13 determines whether the brake 7 needs to be started according to the analysis data to ensure training safety.

[0104] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A lower limb rehabilitation training device for orthopedic patients, characterized in that: include: frame; A seat, which is arranged on the frame and is used for a patient to sit on; A handle, which is arranged on the frame and is used for the patient to grasp; A foot pedal, which is arranged on the frame and is used for the patient to step on; A flywheel, which is arranged on the frame and is linked to the pedal via a chain; An electromagnetic resistance regulator, which is arranged on the flywheel and is used to adjust the rotation resistance of the flywheel; A holding brake, which is arranged on the flywheel and is used to stop the rotation of the flywheel; a first angular velocity sensor, which is disposed on the flywheel and is used to measure the rotational angular velocity of the flywheel; A second angular velocity sensor, which is arranged at the connecting shaft of the pedal and is used to measure the rotational angular velocity of the pedal; A foot pressure sensor, which is arranged on the foot pedal and is used to measure the pressure of the patient stepping on the foot pedal; A wearable bioelectric sensor device, which is used to be worn on the patient's body; An operation panel is arranged on the frame and is provided with a central control chip. The central control chip is used to calculate the riding power, the rate of change of joint activity, the strength balance, the heart rate and the blood oxygen saturation according to the first angular velocity sensor, the second angular velocity sensor, the pedal pressure sensor and the bioelectric sensor wearable device, and to control the operation of the electromagnetic resistance regulator and the brake.

2. The lower limb rehabilitation training device for orthopedic patients according to claim 1, characterized in that: The time interval between two sampling points of the first angular velocity sensor, the second angular velocity sensor, the pedal pressure sensor and the bioelectric sensor wearable device is Δt.

3. The lower limb rehabilitation training device for orthopedic patients according to claim 1, characterized in that: The central control chip constructs a first formula to calculate the riding power, specifically: P i =F i ×v i , F i =F li +F ri , where P i For at time T i The riding power, F li is the pedal pressure sensor at time T i The force measured on the left pedal, F ri is the pedal pressure sensor at time T i The force measured on the right pedal, v i The first angular velocity sensor at time T i The measured angular velocity of rotation of the flywheel; The central control chip constructs a second formula to calculate the joint activity change rate, specifically: Among them, R i is the change rate of the joint activity within the time interval △t, θ i-1 The second angular velocity sensor at time T i-1 The measured rotation angle of the pedal, θ i The second angular velocity sensor at time T i The measured rotation angle of the foot pedal; The central control chip constructs a third formula to calculate the power balance, specifically: Among them, B i For at time T i of the said force balance.

4. The lower limb rehabilitation training device for orthopedic patients as claimed in claim 3, characterized in that: The central control chip dynamically adjusts the output value Y of the electromagnetic resistance regulator according to the following steps a , specifically: S1-1, construct the first decision tree model, the input feature is the cycling power P i , the joint activity change rate R i , the power balance B i , the heart rate H i and the blood oxygen saturation S i , the input vector is x i =(P i ,R i ,B i ,H i ,S i ); S1-2, through the training data set X = {x1, x2, ..., x n } Train the first decision tree model to output the output value Y of the electromagnetic resistance regulator a , Y a ∈[0,1]; S1-3, using mean square error MSE as a first loss function to optimize the first decision tree model; The central control chip dynamically adjusts the output value Y of the brake according to the following steps b , specifically: S2-1, construct a second decision tree model, the input feature is the cycling power P i , the joint activity change rate R i , the power balance B i , the heart rate H i and the blood oxygen saturation S i , the input vector is x i =(P i ,R i ,B i ,H i ,S i ); S2-2, through the training data set X = {x1, x2, ..., x n } Train the second decision tree model to output the output value Y of the brake b , Y b ∈{0,1}; S2-3, using the cross entropy loss CEL as the second loss function to optimize the second decision tree model.

5. The lower limb rehabilitation training device for orthopedic patients according to claim 1, characterized in that: Also includes: An emergency brake button, which is arranged on the frame and is used to immediately activate the brake; A display is arranged on the operation panel, and is used to display the cycling power, the rate of change of the joint activity, the strength balance, the heart rate and the blood oxygen saturation.

6. The lower limb rehabilitation training device for orthopedic patients as claimed in claim 1, characterized in that: Also includes: The electric adjustment mechanism is arranged between the seat and the frame and is used for adjusting the height of the seat.

7. The lower limb rehabilitation training device for orthopedic patients as claimed in claim 1, characterized in that: The surface of the foot pedal is provided with an anti-slip coating.

8. The lower limb rehabilitation training device for orthopedic patients as claimed in claim 1, characterized in that: The frame is made of aluminum alloy, and the surface of the frame is frosted and matte.

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