CN111035896A - Lower limb rehabilitation training system - Google Patents
Lower limb rehabilitation training system Download PDFInfo
- Publication number
- CN111035896A CN111035896A CN201911406944.8A CN201911406944A CN111035896A CN 111035896 A CN111035896 A CN 111035896A CN 201911406944 A CN201911406944 A CN 201911406944A CN 111035896 A CN111035896 A CN 111035896A
- Authority
- CN
- China
- Prior art keywords
- patient
- push rod
- leg
- bed surface
- value
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000012549 training Methods 0.000 title claims abstract description 133
- 210000003141 lower extremity Anatomy 0.000 title claims abstract description 24
- 230000003993 interaction Effects 0.000 claims abstract description 17
- 210000002414 leg Anatomy 0.000 claims description 82
- 238000011156 evaluation Methods 0.000 claims description 76
- 230000000694 effects Effects 0.000 claims description 43
- 238000000034 method Methods 0.000 claims description 22
- 238000006073 displacement reaction Methods 0.000 claims description 18
- 230000008569 process Effects 0.000 claims description 18
- 238000012417 linear regression Methods 0.000 claims description 12
- 201000010099 disease Diseases 0.000 claims description 10
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims description 10
- 210000000689 upper leg Anatomy 0.000 claims description 10
- 230000008859 change Effects 0.000 claims description 9
- 238000002567 electromyography Methods 0.000 claims description 6
- 210000003205 muscle Anatomy 0.000 claims description 6
- 238000012937 correction Methods 0.000 claims description 5
- 230000003183 myoelectrical effect Effects 0.000 claims description 5
- 230000036544 posture Effects 0.000 abstract description 2
- 238000012545 processing Methods 0.000 description 4
- 230000007306 turnover Effects 0.000 description 4
- 208000006011 Stroke Diseases 0.000 description 2
- 210000003414 extremity Anatomy 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 230000001769 paralizing effect Effects 0.000 description 2
- 208000020431 spinal cord injury Diseases 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000005452 bending Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000009916 joint effect Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 239000013585 weight reducing agent Substances 0.000 description 1
Images
Classifications
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B23/00—Exercising apparatus specially adapted for particular parts of the body
- A63B23/035—Exercising apparatus specially adapted for particular parts of the body for limbs, i.e. upper or lower limbs, e.g. simultaneously
- A63B23/04—Exercising apparatus specially adapted for particular parts of the body for limbs, i.e. upper or lower limbs, e.g. simultaneously for lower limbs
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B24/00—Electric or electronic controls for exercising apparatus of preceding groups; Controlling or monitoring of exercises, sportive games, training or athletic performances
- A63B24/0062—Monitoring athletic performances, e.g. for determining the work of a user on an exercise apparatus, the completed jogging or cycling distance
Landscapes
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Physical Education & Sports Medicine (AREA)
- Orthopedic Medicine & Surgery (AREA)
- Rehabilitation Tools (AREA)
Abstract
The invention provides a lower limb rehabilitation training system which comprises a mechanical part, an actuating part, a sensing part, a control part and a human-computer interaction part, wherein the leg actuating device drives a leg actuating device of a patient to reciprocate up and down to enable the patient to perform simulated stepping motion, and the control part controls a bed surface vertical lifting push rod device, a bed surface integral overturning push rod device, a bed surface upper half part overturning push rod device, a bed body length adjusting push rod device and the push rod elongation of a weight-reducing up-down adjusting push rod device to enable the bed surface to vertically lift up and down, the bed surface to integrally overturn, the bed surface upper half part to overturn, the bed body length to adjust and the weight-reducing up-. The lower limb rehabilitation training device can perform lower limb rehabilitation training on various postures of a patient from lying to standing.
Description
Technical Field
The invention relates to the technical field of rehabilitation medical treatment, in particular to a rehabilitation training system.
Background
In China, tens of millions of stroke patients exist, millions of new patients exist every year, in addition, a large number of spinal cord injury patients exist, and the stroke, the spinal cord injury and other diseases cause a large number of patients to be hemiplegic, paralytic and lie in bed for a long time. Traditional motion rehabilitation training goes on under the artifical help of rehabilitation training person, overall efficiency is low, and training time and training intensity rely on rehabilitation training person physical power, under the condition of more and more patients, the training person number can not satisfy the demand, on the other hand, when the training person carries out the rehabilitation evaluation, score the patient rating based on the evaluation scale, this method is influenced by training person individual subjective factor greatly, make the uncertainty of evaluation increase, not only increase training person operating time, moreover the evaluation also is difficult to accomplish ration and objectively.
With the development of intelligent robot technology, more and more intelligent rehabilitation equipment for hemiplegic and paralytic patients is developed and applied at present, and the equipment generally comprises a mechanical structure device fixed with the body of the patient, a sensor for monitoring the motion state of the mechanical structure, an actuator for driving the mechanical structure to move, and a controller for receiving signals of the sensor, calculating and processing the signals, and outputting the signals to the actuator.
However, when the equipment works, the system effective measurement, analysis and record of the training process indexes are lacked, the rehabilitation trainees are still required to judge the exertion condition and the activity range change of the patient after the training is finished, the trainees and the patient cannot systematically and quantitatively know the training index change in the training process, the patient cannot know the self rehabilitation data change in real time, and the enthusiasm of the patient for the training is reduced, and the whole rehabilitation process of the patient can be indirectly influenced. Therefore, a rehabilitation training system is needed, which can perform rehabilitation training on a patient, monitor indexes such as a motion range and a strength degree in a training process in real time, and enable the patient and a trainer to know the rehabilitation training conditions quantitatively, objectively and in real time.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a lower limb rehabilitation training system.
The technical scheme adopted by the invention for solving the technical problems is as follows: a lower limb rehabilitation training system comprises a mechanical part, an actuating part, a sensing part, a control part and a man-machine interaction part.
The mechanical parts comprise a bed surface, an upper body fixing device, 2 leg fixing devices and 2 foot fixing devices, the upper body of a rehabilitation training patient is tightly attached to the bed surface, the upper body, the two legs and the two feet are respectively fixed by the upper body fixing device, the leg fixing devices and the foot fixing devices, and the foot fixing devices are connected with the bed surface through springs;
the actuating part comprises a leg actuating device, a bed surface vertical lifting push rod device, a bed surface integral overturning push rod device, a bed surface upper half part overturning push rod device, a bed body length adjusting push rod device and a weight-reducing up-down adjusting push rod device, wherein 2 leg actuating devices are respectively connected with 1 leg fixing device to drive the leg fixing devices to move; the bed surface vertical lifting push rod device and the bed surface integral overturning push rod device are respectively driven by the control part to drive the bed surface to lift and overturn; the upper half part of the bed surface is turned over by the push rod device to adjust the included angle between the upper half part of the bed surface and the lower half part of the bed surface; the bed body length adjusting push rod device adjusts the distance between the upper half part of the bed surface and the foot fixing device; the weight-reducing up-down adjusting push rod device adjusts the distance between the upper body fixing device and the leg fixing device;
the sensing part comprises a tension and pressure sensing device, a distance measuring sensing device, an angular displacement sensing device, a myoelectric sensing device and a push rod sensing control device, wherein 2 tension and pressure sensing devices are respectively arranged on the leg fixing device to measure the force F applied to the leg fixing deviceLL、FLRRepresenting the force of extension and flexion of the patient's leg; 2 distance measuring sensing devices are respectively arranged at the rear ends of the 2 foot fixing devices and used for measuring the up-and-down movement distance S of the foot fixing devicesL、SRIndirectly measuring the tension of the foot fixing device on the spring, representing the force on the sole of the foot of the patient; 2 angular displacement sensors are respectively arranged on the leg fixing device to measure the relative motion angle A between the leg fixing device and the bed surfaceL、AR(ii) a The myoelectricity sensing device is adhered to the muscle of the leg of the patient and measures the surface myoelectricity U generated when the leg of the patient moves1、U2、U3、U4The push rod sensing control device measures the extension of a push rod connected with the bed surface vertical lifting push rod device, the bed surface integral overturning push rod device, the upper half part overturning push rod device of the bed surface, the bed body length adjusting push rod device and the weight-reducing up-down adjusting push rod device;
the control part receives a control instruction sent by the human-computer interaction part and a sensing signal sent by the sensing part and generates a continuous control signal for the leg actuating device.
The control part calculates the strength of the patient in a set period
Wherein the force exerting degrees of the left leg and the right leg are respectively
And
FLL max、FLL minrespectively is the maximum value and the minimum value, F, measured by the left leg tension and pressure sensing device in a set periodLR max、FLR minRespectively is the maximum value and the minimum value, F, measured by the right leg pulling and pressing force sensing device in a set periodmax、FminThe maximum value and the minimum value which can be measured by the pull pressure sensing device are respectively.
The control part calculates the degree of the intention of the patient to exert force in a set period
Wherein,
is electromyographic U by surfaceiThe muscle strength intention is obtained, the value of n is the number of the used surface electromyography sensing devices, n is less than or equal to 4, Ui max、Ui minAre respectively an evaluationCycle inner surface myoelectric UiMaximum and minimum values of, Umax、UminThe maximum value and the minimum value which can be measured by the surface electromyography device are respectively.
The control part calculates the sole load degree of the patient in a set period as
Wherein S isL max、SL minRespectively is the maximum value and the minimum value of the vertical displacement of the left foot in an evaluation period SR max、SR minThe maximum and minimum values of the vertical displacement of the right foot in an evaluation period, k is the stiffness of the spring connected to the foot fixing means, and G is the weight of the patient.
The control unit calculates the balance ability of the patient in a set period
The control unit calculates the degree of articulation of the patient during a set period,
wherein,
the degree of joint movement of the left and right legs, A, respectively, of an evaluation cycleL max、AL minThe maximum and minimum values of the angle of the left thigh elevation in an evaluation period, AR max、AR minThe maximum value and the minimum value of the angle of the right thigh uplifted in an evaluation period, Amax、AminThe angular displacement sensing device can measure the maximum value and the minimum value of the thigh lifting angle.
The control part calculates a training effect evaluation value of a complete training as follows:
wherein,
is the average value of the leg strength during the training process,
the average value of the leg exertion intention in the training process,
is the average value of the degree of sole loading during the training process,
is the average value of the balance ability value in the training process,
v is the training speed, number of steps per minute, k is the average value of the degree of joint movement during the training process0、k1、k2、k3、k4、k5、k6Is a coefficient of a linear regression,
the trainer obtains a patient rating score according to the rehabilitation scale evaluation standard, and corrects the linear regression coefficient according to the rating score through a multivariate linear regression model to obtain a corrected training effect evaluation value as follows:
wherein S' is the training effect evaluation value of one complete training after correction, and is a number between 0 and 100, and k0′、k1′、k2′、k3′、k4′、k5′、k6' is the linear regression coefficient after the correction,
the human-computer interaction component is connected with the cloud platform through a network; defining the same type of patients of a certain patient as the patients with the difference between the age A 'and the age A of the patient being less than 5, the disease types M being the same, and the difference between the disease time D' and the disease time D of the patient being less than 2 years, calling the training effect evaluation values of all the same type of patients by the cloud platform, and calculating the training effect contrast value of the patients in the same type of patients as follows:
the cloud platform sends the Q value and the training effect evaluation value of the same type of patients to the human-computer interaction component, and generates corresponding curves of the number of the patients of the same type under different training effect evaluation values.
The human-computer interaction component is connected with the cloud platform through a network; and sending the patient training effect evaluation value to a cloud platform, sending the past one-month training effect evaluation value of the patient to a human-computer interaction component by the cloud platform, and generating and displaying a past one-month training effect evaluation value change curve of the patient.
The invention has the beneficial effects that: can carry out low limbs rehabilitation training to the various postures of standing upright from lying to the patient, gather the condition of exerting oneself, the intention of exerting oneself, joint activity angle, the training upset angle information of patient training process in real time through multiple sensing part to show on the all-in-one, do not need the training teacher to intervene, can make the accurate quantitative training condition of learning of training teacher and patient.
The patient training effect evaluation value is obtained through processing and calculation based on the sensing information values acquired by the various sensing parts, so that accurate and objective training effect evaluation reference is provided for most trainees, and the existing rehabilitation training evaluation method is enriched.
The change trend curve of the training contrast value and the self-training effect evaluation value of the patient and the patient of the same type is provided, the patient system can master the comprehensive change effect and the training process of the self-exertion condition, the exertion intention, the joint movement angle and the training turnover angle condition, the rehabilitation training difference between the patient and the patient of the same type is known, the rehabilitation confidence of the patient is prompted, the initiative of the patient in the active rehabilitation training is promoted, and the rehabilitation of the patient is accelerated.
Drawings
FIG. 1 is a schematic view and a partially enlarged view of the structure of the present invention;
FIG. 2 is a schematic structural view of the present invention;
FIG. 3 is a block diagram of the component connection of the present invention;
in the figure, 1-bed surface, 2-upper body fixing device, 3-angular displacement sensing device (1 on each of left and right leg fixing device), 4-leg fixing device (1 on each of left and right leg symmetrically), 5-pulling pressure sensing device (1 on each of left and right leg fixing device), 6-foot fixing device (2 on left and right symmetrically), 7-distance measuring sensing device (1 on each of left and right foot fixing device), 8-spring (1 on each of left and right foot fixing device), 9-bed board bracket, 10-myoelectricity sensing device jack, 11-bed length adjusting push rod device, 12-leg actuating device (1 on each of left and right leg symmetrically), 13-integrated machine, 14-hand controller, 15-bed surface integral turning push rod device, 16-bed surface vertical lifting push rod device, 17-a main controller, 18-a push rod sensing control device, 19-a push rod device for overturning the upper half part of the bed surface and 20-a weight-reducing up-down adjusting push rod device.
Detailed Description
The present invention will be further described with reference to the following drawings and examples, which include, but are not limited to, the following examples.
The invention provides a lower limb rehabilitation training system which comprises a mechanical part, an actuating part, a sensing part, a control part, a human-computer interaction part and a cloud platform.
The mechanical part comprises a bed board support, a bed surface, an upper body fixing device, 2 leg fixing devices and 2 foot fixing devices, a rehabilitation training patient lies on the bed surface, and the upper body, the two legs and the two feet are fixed with the upper body fixing device, the 2 leg fixing devices and the 2 foot fixing devices respectively.
The actuating part comprises 2 leg actuating devices, a bed surface vertical lifting push rod device, a bed surface integral overturning push rod device, a bed surface upper half part overturning push rod device, a bed body length adjusting push rod device and a weight-reducing upper and lower adjusting push rod device, wherein the 2 leg actuating devices are respectively connected with the 2 leg fixing devices, so that the leg actuating devices can drive the leg fixing devices to move.
The sensing component comprises 2 pulling pressure sensing devices, 2 distance measuring sensing devices, 2 angular displacement sensing devices, 4 groups of myoelectricity sensing devices and a push rod sensing control device.
The 2 tension and pressure sensing devices are respectively arranged on the 2 leg fixing devices, and measure the pressure and tension applied to the leg fixing devices, which represent the stretching and bending force of the legs of the patient.
2 range finding sensing device installs respectively behind 2 foot fixing device, has spring coupling between step fixing device and the bed board support, and range finding sensing device measures the distance of foot fixing device up-and-down motion, and spring tension is said, indirect measurement foot fixing device receives the pulling force of spring, represents the power that patient's sole received.
The 2 angular displacement sensing devices are respectively arranged on the 2 leg fixing devices, and are used for measuring the relative motion angle between the leg fixing devices and the bed surface to represent the lifting angle of the thighs of the patient.
The myoelectricity sensing device comprises a myoelectricity sensing patch, a myoelectricity patch line and a myoelectricity sensing device processing board, the myoelectricity sensing patch is pasted on leg muscles of a patient, the myoelectricity sensing patch is connected with the myoelectricity patch line, the myoelectricity patch line is connected with a myoelectricity sensing device jack on the myoelectricity sensing device processing board, and 4 groups of myoelectricity sensing devices respectively measure surface myoelectricity generated when the leg of the patient moves.
The push rod sensing control device is connected with the bed surface vertical lifting push rod device, the bed surface integral overturning push rod device, the upper half part overturning push rod device, the bed body length adjusting push rod device and the weight reduction up-down adjusting push rod device through digital signal wires, and measures the push rod elongation of each push rod device.
The control part comprises a main controller and a push rod sensing control device.
The main controller is respectively connected with the leg actuating device, the push rod sensing control device, the sensing component and the human-computer interaction component in a CAN (controller area network), serial digital signal wires and analog signal wires, receives a control instruction sent by the human-computer interaction component, receives a sensing signal sent by the sensing component, and generates a continuous control signal for the leg actuating device according to the control instruction and the sensing signal.
The push rod sensing control device controls the bed surface vertical lifting push rod device, the bed surface integral overturning push rod device, the bed surface upper half part overturning push rod device, the bed body length adjusting push rod device and the push rod elongation of the weight-reducing upper and lower adjusting push rod device, so that the bed surface vertical lifting, the bed surface integral overturning, the bed surface upper half part overturning, the bed body length adjusting and the weight-reducing upper and lower adjusting are controlled.
The human-computer interaction part comprises an all-in-one machine and a hand controller.
The all-in-one machine can receive input commands of the trainer in a touch mode, information is displayed through the display screen, and the hand controller receives the input commands of the trainer through the keys.
The hand controller is connected with the push rod sensing control device through a signal line and receives input commands of a trainer through keys.
The cloud platform is connected with the all-in-one machine through a network, and the cloud platform is specifically a commercial public cloud platform.
The lower limb rehabilitation training system is characterized in that a patient is fixed with the lower limb rehabilitation training system, a trainer inputs commands through an all-in-one machine, a main control part controls 2 leg actuating devices to drive 2 leg actuating devices to reciprocate up and down according to control commands, so that the patient can simulate stepping motion, the trainer inputs commands through a hand controller, the main control part controls a bed surface vertical lifting push rod device, a bed surface integral overturning push rod device, a bed surface upper half overturning push rod device, a bed body length adjusting push rod device and a weight reducing upper and lower adjusting push rod device to extend, so that the bed surface is vertically lifted up and down, the bed surface is integrally overturned, the bed surface upper half part is overturned, the bed body length is adjusted, and the weight.
A low limbs rehabilitation training system, before the first rehabilitation training of patient, the weight G of patient, patient age A, the sick type M of patient, sick time D are inputed to the training person on the all-in-one, and at the training in-process, 2 draw pressure sensing device to measure 2 power F that shank fixing device received respectivelyLL、FLRThat is, the force of two legs of the patient, 2 distance measuring sensors measure the up-and-down displacement S of 2 foot fixing devices respectivelyL、SRThat is, the left foot and the right foot of the patient move up and down, and 2 angular displacement measuring sensors respectively measure the lifting angles A of 2 leg fixing devicesL、ARThat is, the lifting angles of the left and right legs of the patient are measured by 4 groups of myoelectricity sensing devices respectively1、U2、U3、U4The push rod extension sensing device measures the extension amount of a push rod of the bed surface integral turnover push rod device, the bed surface turnover angle theta is obtained according to the relation between the extension amount of the push rod and the bed surface turnover angle in the design simulation, and when the training is finished, the all-in-one machine records the training time T and the training speed V.
The lower limb rehabilitation training system takes 10 seconds of patient training as an evaluation period, the unit of training speed V is the number of steps per minute, the number of steps of stepping a patient in the evaluation period is V/6, and the exertion degree in the evaluation period is as follows:
wherein, PLIs the degree of exertion of the leg in an evaluation cycle, is a number between 0 and 1, PLL、PLRThe force degree of the left leg and the right leg of an evaluation period, FLL max、FLL minRespectively is the maximum value and the minimum value, F, measured by the left leg pull pressure sensing device in an evaluation periodLR max、FLR minRespectively is the maximum value and the minimum value, F, measured by the right leg pulling and pressing sensing device in an evaluation periodmax、FminThe maximum value and the minimum value which can be measured by the leg pulling and pressing force sensing device are respectively.
The degree of exertion intention in one evaluation period is:
wherein R is the leg exertion intention of an evaluation period and is a number between 0 and 1, RiIs electromyographic U by surfaceiThe muscle strength intention is obtained, the value of n is the number of the used surface electromyography sensing devices, n is less than or equal to 4, Ui max、Ui minRespectively an evaluation period inner surface myoelectric UiMaximum and minimum values of, Umax、UminThe maximum value and the minimum value which can be measured by the surface electromyography device are respectively.
The degree of plantar load in one evaluation period was:
wherein, PFThe degree of sole load in an evaluation period is a number between 0 and 1, SL max、SL minRespectively is the maximum value and the minimum value of the vertical displacement of the left foot in an evaluation period SR max、SR minThe maximum value and the minimum value of the up-and-down displacement of the right foot in an evaluation period are respectively, and k is the rigidity of a spring connected with the foot fixing device.
The balance capability in one evaluation period is:
wherein, B is the balance ability value in an evaluation period and is a number between 0 and 1.
The degree of joint motion in one evaluation cycle was:
wherein D is the degree of joint movement of an evaluation cycle and is a number between 0 and 1, DL、DRThe degree of joint movement of the left and right legs, A, respectively, of an evaluation cycleL max、AL minThe maximum and minimum values of the angle of the left thigh elevation in an evaluation period, AR max、AR minThe maximum value and the minimum value of the angle of the right thigh uplifted in an evaluation period, Amax、AminThe angular displacement sensing device can measure the maximum value and the minimum value of the thigh lifting angle.
The evaluation value of the training effect of one complete training is as follows:
wherein S is an evaluation value of training effect of one complete training, is a number between 0 and 100,
for averaging the strength of the legs during the trainingThe value of the one or more of,
the average value of the leg exertion intention in the training process,
is the average value of the degree of sole loading during the training process,
is the average value of the balance ability value in the training process,
is the average value of the degree of joint movement during the training process, k0、k1、k2、k3、k4、k5、k6As linear regression coefficient, k at the initial time0Take 0, k1、k2、k3、k5Take 0.2, k4、k6Take 0.1.
The trainer obtains the rating scores of patients according to Fugl-Meyer lower limb rating scale and Berg balance scale rehabilitation scale evaluation standard, averages the rating scores of all scales to obtain total rating scores, and corrects the linear regression coefficient according to the total rating scores through a multivariate linear regression model to obtain a corrected training effect evaluation value as follows:
wherein S' is the training effect evaluation value of one complete training after correction, and is a number between 0 and 100, and k0′、k1′、k2′、k3′、k4′、k5′、k6' is the corrected linear regression coefficient.
The utility model provides a lower limbs rehabilitation training system, all-in-one show each sensing device real-time measuring value in real time to after the all-in-one calculated patient training effect evaluation value, send this evaluation value to the cloud platform, the same type patient of defining a certain patient is: the absolute value of the difference between the age A 'and the age A of the patient is less than 5, the disease type M is the same, the difference between the disease time D' and the disease time D of the patient is less than 2, the cloud platform calls the training effect evaluation values of all patients of the same type, and the contrast value of the training effect of the patients in the patients of the same type is calculated as follows:
wherein, Q is the training effect contrast value of this patient in the patient of the same type, be the number between 0 to 100%, N is the patient number that the training effect evaluation value is less than this patient training effect evaluation value for the training effect, N is the total number of people of the patient of the same type, Q value explains that this patient is better in the patient of the same type training effect more greatly, cloud platform sends Q value and the training effect evaluation value of the patient of the same type to the all-in-one, the all-in-one is sent to the all-in-one under the all-in-one generates different training effect evaluation values same type patient number corresponding curve, make this patient and training person know this patient and the training contrast.
According to the lower limb rehabilitation training system, after the all-in-one machine calculates the training effect evaluation value of a patient, the evaluation value is sent to the cloud platform, the cloud platform sends the training effect evaluation value of the patient in the past month to the all-in-one machine, the all-in-one machine generates the training effect evaluation value change curve of the patient in the past month, the patient can know the change of the training effect of the patient, and the training confidence of the patient is improved.
Claims (10)
1. The utility model provides a lower limbs rehabilitation training system, includes mechanical part, actuates part, sensing part, control unit and human-computer interaction part, its characterized in that: the mechanical parts comprise a bed surface, an upper body fixing device, 2 leg fixing devices and 2 foot fixing devices, the upper body of a rehabilitation training patient is tightly attached to the bed surface, and the upper body, the two legs and the two feet are respectively fixed by the upper body fixing device, the leg fixing devices and the two feetThe foot fixing device is fixed and is connected with the bed surface through a spring; the actuating part comprises a leg actuating device, a bed surface vertical lifting push rod device, a bed surface integral overturning push rod device, a bed surface upper half part overturning push rod device, a bed body length adjusting push rod device and a weight-reducing up-down adjusting push rod device, wherein 2 leg actuating devices are respectively connected with 1 leg fixing device to drive the leg fixing devices to move; the bed surface vertical lifting push rod device and the bed surface integral overturning push rod device are respectively driven by the control part to drive the bed surface to lift and overturn; the upper half part of the bed surface is turned over by the push rod device to adjust the included angle between the upper half part of the bed surface and the lower half part of the bed surface; the bed body length adjusting push rod device adjusts the distance between the upper half part of the bed surface and the foot fixing device; the weight-reducing up-down adjusting push rod device adjusts the distance between the upper body fixing device and the leg fixing device; the sensing part comprises a tension and pressure sensing device, a distance measuring sensing device, an angular displacement sensing device, a myoelectric sensing device and a push rod sensing control device, wherein 2 tension and pressure sensing devices are respectively arranged on the leg fixing device to measure the force F applied to the leg fixing deviceLL、FLRRepresenting the force of extension and flexion of the patient's leg; 2 distance measuring sensing devices are respectively arranged at the rear ends of the 2 foot fixing devices and used for measuring the up-and-down movement distance S of the foot fixing devicesL、SRIndirectly measuring the tension of the foot fixing device on the spring, representing the force on the sole of the foot of the patient; 2 angular displacement sensors are respectively arranged on the leg fixing device to measure the relative motion angle A between the leg fixing device and the bed surfaceL、AR(ii) a The myoelectricity sensing device is adhered to the muscle of the leg of the patient and measures the surface myoelectricity U generated when the leg of the patient moves1、U2、U3、U4The push rod sensing control device measures the extension of a push rod connected with the bed surface vertical lifting push rod device, the bed surface integral overturning push rod device, the upper half part overturning push rod device of the bed surface, the bed body length adjusting push rod device and the weight-reducing up-down adjusting push rod device; the control part receives a control instruction sent by the human-computer interaction part and a sensing signal sent by the sensing part and generates the control instruction and the sensing signal to the leg partA continuous control signal for the actuation means.
2. The lower extremity rehabilitation training system of claim 1, wherein: the control part calculates the strength of the patient in a set period
Wherein the force exerting degrees of the left leg and the right leg are respectively
And
FLL max、FLL minrespectively is the maximum value and the minimum value, F, measured by the left leg tension and pressure sensing device in a set periodLR max、FLR minRespectively is the maximum value and the minimum value, F, measured by the right leg pulling and pressing force sensing device in a set periodmax、FminThe maximum value and the minimum value which can be measured by the pull pressure sensing device are respectively.
3. The lower extremity rehabilitation training system of claim 1, wherein: the control part calculates the degree of the intention of the patient to exert force in a set period
Wherein,
is electromyographic U by surfaceiThe muscle strength intention is obtained, the value of n is the number of the used surface electromyography sensing devices, n is less than or equal to 4, Ui max、Ui minRespectively an evaluation period inner surface myoelectric UiMaximum and minimum values of, Umax、UminThe maximum value and the minimum value which can be measured by the surface electromyography device are respectively.
4. The lower extremity rehabilitation training system of claim 1, wherein: the control part calculates the sole load degree of the patient in a set period as
Wherein S isL max、SL minRespectively is the maximum value and the minimum value of the vertical displacement of the left foot in an evaluation period SR max、SR minThe maximum and minimum values of the vertical displacement of the right foot in an evaluation period, k is the stiffness of the spring connected to the foot fixing means, and G is the weight of the patient.
5. The lower extremity rehabilitation training system of claim 1, wherein: the control unit calculates the balance ability of the patient in a set period
6. The lower extremity rehabilitation training system of claim 1, wherein: the control unit calculates the degree of articulation of the patient during a set period,
wherein,
the degree of joint movement of the left and right legs, A, respectively, of an evaluation cycleL max、AL minThe maximum and minimum values of the angle of the left thigh elevation in an evaluation period, AR max、AR minThe maximum value and the minimum value of the angle of the right thigh uplifted in an evaluation period, Amax、AminThe angular displacement sensing device can measure the maximum value and the minimum value of the thigh lifting angle.
7. The lower extremity rehabilitation training system of claim 1, wherein: the control part calculates a training effect evaluation value of a complete training as follows:
wherein,
is the average value of the leg strength during the training process,
the average value of the leg exertion intention in the training process,
is the average value of the degree of sole loading during the training process,
is the average value of the balance ability value in the training process,
v is the training speed, number of steps per minute, k is the average value of the degree of joint movement during the training process0、k1、k2、k3、k4、k5、k6Is a coefficient of a linear regression,
8. the lower extremity rehabilitation training system of claim 1, wherein: the trainer obtains a patient rating score according to the rehabilitation scale evaluation standard, and corrects the linear regression coefficient according to the rating score through a multivariate linear regression model to obtain a corrected training effect evaluation value as follows:
9. the lower extremity rehabilitation training system of claim 1, wherein: the human-computer interaction component is connected with the cloud platform through a network; defining the patients of the same type of a certain patient as the patients with the age A ' less than 5 in absolute value of the difference between the age A ' and the age A of the patient, the disease types M being the same, and the difference between the disease time D ' and the disease time D of the patient less than 2 years, calling the training effect evaluation values of all the patients of the same type by the cloud platform, and calculating the training effect contrast values of the patients in the patients of the same type
The cloud platform sends the Q value and the training effect evaluation value of the same type of patients to the human-computer interaction component, and generates corresponding curves of the number of the patients of the same type under different training effect evaluation values.
10. The lower extremity rehabilitation training system of claim 1, wherein: the human-computer interaction component is connected with the cloud platform through a network; and sending the patient training effect evaluation value to a cloud platform, sending the past one-month training effect evaluation value of the patient to a human-computer interaction component by the cloud platform, and generating and displaying a past one-month training effect evaluation value change curve of the patient.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911406944.8A CN111035896B (en) | 2019-12-31 | 2019-12-31 | Lower limb rehabilitation training system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911406944.8A CN111035896B (en) | 2019-12-31 | 2019-12-31 | Lower limb rehabilitation training system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111035896A true CN111035896A (en) | 2020-04-21 |
| CN111035896B CN111035896B (en) | 2024-09-13 |
Family
ID=70242919
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911406944.8A Active CN111035896B (en) | 2019-12-31 | 2019-12-31 | Lower limb rehabilitation training system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111035896B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111481404A (en) * | 2020-05-27 | 2020-08-04 | 中航创世机器人(西安)有限公司 | Adjustable and accurate feedback hip joint training device |
| CN113559462A (en) * | 2021-08-24 | 2021-10-29 | 深圳市第二人民医院(深圳市转化医学研究院) | Rapid rehabilitation system for legs |
| CN117224904A (en) * | 2023-11-07 | 2023-12-15 | 山东泽普医疗科技有限公司 | A lower limb rehabilitation training bed and its control system |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102028475A (en) * | 2009-09-28 | 2011-04-27 | 上海理工大学 | Squat-stand type lower limb function evaluating and exercising system |
| CN102058464A (en) * | 2010-11-27 | 2011-05-18 | 上海大学 | Motion control method of lower limb rehabilitative robot |
| KR20110054275A (en) * | 2009-11-17 | 2011-05-25 | 을지대학교 산학협력단 | Lower extremity muscle strength assessment and training controls and methods |
| US20110251022A1 (en) * | 2010-04-07 | 2011-10-13 | Industry-Academic Cooperation Foundation, Kyungpook National University | Leg rehabilitation system having game function |
| CN103431976A (en) * | 2013-07-19 | 2013-12-11 | 燕山大学 | Lower limb rehabilitation robot system based on myoelectric signal feedback, and control method thereof |
| KR20140109090A (en) * | 2013-03-05 | 2014-09-15 | 인제대학교 산학협력단 | A leg muscular strength rehabilitation apparatus |
| CN106109174A (en) * | 2016-07-14 | 2016-11-16 | 燕山大学 | A kind of healing robot control method based on myoelectric feedback impedance self-adaptive |
| CN107315478A (en) * | 2017-07-05 | 2017-11-03 | 中国人民解放军第三军医大学 | A kind of Mental imagery upper limbs intelligent rehabilitation robot system and its training method |
| CN107753241A (en) * | 2017-11-20 | 2018-03-06 | 中航创世机器人（东莞）有限公司 | A kind of control method of lower limb rehabilitation treatment intelligent exoskeleton robot |
| CN108242261A (en) * | 2018-01-10 | 2018-07-03 | 苏州脉吉医疗技术有限公司 | Rehabilitation training planning system and method |
| US20180263535A1 (en) * | 2015-09-09 | 2018-09-20 | The Regents Of The University Of California | Systems and methods for facilitating rehabilitation therapy |
| CN211536386U (en) * | 2019-12-31 | 2020-09-22 | 中航创世机器人(西安)有限公司 | Lower limb rehabilitation training system |
-
2019
- 2019-12-31 CN CN201911406944.8A patent/CN111035896B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102028475A (en) * | 2009-09-28 | 2011-04-27 | 上海理工大学 | Squat-stand type lower limb function evaluating and exercising system |
| KR20110054275A (en) * | 2009-11-17 | 2011-05-25 | 을지대학교 산학협력단 | Lower extremity muscle strength assessment and training controls and methods |
| US20110251022A1 (en) * | 2010-04-07 | 2011-10-13 | Industry-Academic Cooperation Foundation, Kyungpook National University | Leg rehabilitation system having game function |
| CN102058464A (en) * | 2010-11-27 | 2011-05-18 | 上海大学 | Motion control method of lower limb rehabilitative robot |
| KR20140109090A (en) * | 2013-03-05 | 2014-09-15 | 인제대학교 산학협력단 | A leg muscular strength rehabilitation apparatus |
| CN103431976A (en) * | 2013-07-19 | 2013-12-11 | 燕山大学 | Lower limb rehabilitation robot system based on myoelectric signal feedback, and control method thereof |
| US20180263535A1 (en) * | 2015-09-09 | 2018-09-20 | The Regents Of The University Of California | Systems and methods for facilitating rehabilitation therapy |
| CN106109174A (en) * | 2016-07-14 | 2016-11-16 | 燕山大学 | A kind of healing robot control method based on myoelectric feedback impedance self-adaptive |
| CN107315478A (en) * | 2017-07-05 | 2017-11-03 | 中国人民解放军第三军医大学 | A kind of Mental imagery upper limbs intelligent rehabilitation robot system and its training method |
| CN107753241A (en) * | 2017-11-20 | 2018-03-06 | 中航创世机器人（东莞）有限公司 | A kind of control method of lower limb rehabilitation treatment intelligent exoskeleton robot |
| CN108242261A (en) * | 2018-01-10 | 2018-07-03 | 苏州脉吉医疗技术有限公司 | Rehabilitation training planning system and method |
| CN211536386U (en) * | 2019-12-31 | 2020-09-22 | 中航创世机器人(西安)有限公司 | Lower limb rehabilitation training system |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111481404A (en) * | 2020-05-27 | 2020-08-04 | 中航创世机器人(西安)有限公司 | Adjustable and accurate feedback hip joint training device |
| CN113559462A (en) * | 2021-08-24 | 2021-10-29 | 深圳市第二人民医院(深圳市转化医学研究院) | Rapid rehabilitation system for legs |
| CN117224904A (en) * | 2023-11-07 | 2023-12-15 | 山东泽普医疗科技有限公司 | A lower limb rehabilitation training bed and its control system |
| CN117224904B (en) * | 2023-11-07 | 2024-02-20 | 山东泽普医疗科技有限公司 | A lower limb rehabilitation training bed and its control system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111035896B (en) | 2024-09-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111631726B (en) | Upper limb function evaluation device and method and upper limb rehabilitation training system and method | |
| CN108939436B (en) | Active lower limb training system with healthy side and sick side synergistic function and operation method thereof | |
| WO2023109352A1 (en) | Remote rehabilitation training guidance system for chronic respiratory failure patient | |
| CN110811553B (en) | A method for detecting the boosting efficiency of a weight-bearing exoskeleton | |
| CN113101134B (en) | A children's lower limb movement-assisted rehabilitation system based on powered exoskeleton | |
| CN105342767B (en) | A kind of intelligent wheel chair controlled based on mobile terminal | |
| CN111067543A (en) | Man-machine interaction system of horizontal stepping type rehabilitation training robot | |
| CN110164525B (en) | Sports health management system and use method thereof | |
| US20070060445A1 (en) | Method and apparatus for automating arm and grasping movement training for rehabilitation of patients with motor impairment | |
| CN111035896A (en) | Lower limb rehabilitation training system | |
| Hanke et al. | Reliability of measurements of body center-of-mass momentum during sit-to-stand in healthy adults | |
| CN109701208A (en) | A kind of intelligent elderly muscle training equipment and method based on rowing action | |
| CN110916667A (en) | An intelligent assessment bed for supine position for hemiplegic patients | |
| Bae et al. | A mobile gait monitoring system for gait analysis | |
| CN103371802A (en) | Sit-to-stand function assessment method with non-therapeutic purpose | |
| TWI397408B (en) | Physiological signal measurement and oxygen concentration compensation of the sports training system | |
| CN211536386U (en) | Lower limb rehabilitation training system | |
| DE102010003344A1 (en) | Ergometry or training arrangement for use by patient to perform e.g. medical activity, has electronic unit characterizing measuring- and/or training- and/or environment- boundary conditions and estimating rating | |
| CN117860531A (en) | Spinal cord injury rehabilitation device based on myoelectricity biofeedback | |
| CN211403838U (en) | Children's foot deformity correction simulation teaching aid | |
| CN104757985A (en) | Wearable lower limb rehabilitation training and walking auxiliary system and method | |
| JP2008206932A (en) | Method for recovery support, evaluation, and training concerning nervous and sensory functions, and its apparatus | |
| CN212490661U (en) | Intelligent medical robot for lower limb rehabilitation | |
| CN219071104U (en) | A self-timed stand-up-walk test chair | |
| CN204600508U (en) | Wearable lower limb rehabilitation training and walking aid system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |