CN113350122A - Man-machine contact force detection device of lower limb rehabilitation training robot - Google Patents
Man-machine contact force detection device of lower limb rehabilitation training robot Download PDFInfo
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Abstract
The utility model provides a low limbs rehabilitation training robot's man-machine contact force detection device, includes that the cooperation wears ring, outer crown plate and power detection module on human low limbs, outer crown plate symmetry sets up the both sides of wearing the ring, is equipped with at least two sets of power detection module respectively between each side of wearing the ring and the outer crown plate that corresponds, outer crown plate passes through the length adjustment subassembly and installs on the connecting block, the length adjustment subassembly include two length adjustment screw, two length adjustment screw fixed connection are connected with the outer crown plate that corresponds respectively in the both sides of connecting block to fix through adjusting nut. This scheme acquires the novel wearing formula sensing mechanism of man-machine contact force through differential pressure detection to including the intelligent test device of signal conversion and processing, built-in machine learning algorithm predicts the motion intention, thereby the human low limbs motion intention of help recovered robot real-time detection assists the patient to accomplish rehabilitation training, improves recovered efficiency.
Description
Technical Field
The invention relates to the technical field of human-computer interaction of rehabilitation medical robots, in particular to a human-computer contact force detection device of a lower limb rehabilitation training robot.
Background
For a long time, the acquisition of human body active movement intention is always a research hotspot field of a service robot, and the human-machine contact force detection device is used as one of the acquisition ways of the human body active movement intention, so that an effective method for information acquisition and feedback is provided for the human-machine interaction capability of the robot. The method is commonly used in the field of rehabilitation robots for acquiring the lower limb action intention of a patient with lower limb function damage caused by conditions such as stroke, nerve damage or fracture, providing parameter adjustment basis for active/passive training of the rehabilitation robot and providing medical evaluation information for training of doctors. In the application of the power-assisted robot, the following movement of the power-assisted robot is controlled by acquiring the interaction information between a human body and the exoskeleton robot, judging the human-computer coordination.
At present, the rehabilitation robot faces many challenges in terms of hardware and software, and particularly, the robot lacks enough capacity to sufficiently recognize the behaviors and intentions of the wearer, so that the rehabilitation robot cannot well assist the patient. In view of this, methods currently commonly used by researchers in the relevant field are electrophysiological measurements and mechanical sensor measurements. Among them, electrophysiological measurements are divided into Electromyography (EMG), which is a measurement of the electrical activity produced by muscle cells in a muscle activity, which occurs approximately 100 milliseconds before the muscle activity, and electroencephalography (EEG); the electroencephalogram is divided into a visual evoked potential and a P300 potential in a stable state, and is monitored by the electroencephalogram by observing changes in brain waves that are produced by controlled external stimuli and vary with imaginary movement. The mechanical sensor measuring method is to place the common mechanical sensors for measuring force and kinematics at the positions of several key points of limbs during human motion to obtain human motion intention. Compared with the prior art, the electrophysiological measurement can predict the action intention of the human body before the action of the limbs of the human body, but the requirement on the measurement environment is higher, and the measurement result is greatly influenced by the muscle stretching, sweating and the like of the measurement part of an experimenter; since the mechanical sensor measurement has hysteresis in human body action intention recognition, prediction of human body action intention cannot be well realized in the measurement process.
Disclosure of Invention
In order to solve the technical problems, the invention aims to provide a human-machine contact force detection device of a lower limb rehabilitation training robot.
The technical scheme adopted by the invention is as follows: the utility model provides a low limbs rehabilitation training robot's man-machine contact force detection device, this man-machine contact force detection device pass through connecting block and coupling assembling and install on low limbs rehabilitation training robot, including the cooperation wear ring, outer crown plate and the power detection module on human low limbs, the both sides of ring are worn to outer crown plate symmetry setting, are equipped with at least two sets of power detection module respectively between each side of wearing the ring and the outer crown plate that corresponds, the outer crown plate passes through the length adjustment subassembly and installs on the connecting block, the length adjustment subassembly include two length adjustment screw rods, two length adjustment screw rod fixed connection are connected with the outer crown plate that corresponds respectively in the both sides of connecting block to fix through adjusting nut.
Preferably, two guide rods are arranged on each side surface of the wearing ring at intervals, a boss is correspondingly arranged on the inner side surface of the outer ring plate at a position corresponding to each guide rod, a guide groove for mounting the guide rods is formed in the end surface of the boss, and the force detection module comprises a film pressure sensor arranged in the guide groove, a force transmission assembly arranged between the guide rods and the film pressure sensor, and a signal conversion module for receiving and outputting a signal of the film pressure sensor.
Preferably, the guide rods on the two side surfaces of the wearing ring are positioned on the same horizontal plane, and the guide rods are fixedly connected to the bosses on the side surfaces of the outer ring plates through the jacking screws.
Preferably, the film pressure sensor is arranged at the bottom of the guide groove and is placed in the guide groove through an opening arranged at the bottom of the boss.
Preferably, the force transmission assembly comprises a spring connected to the end of the guide rod and a metal round pad arranged between the spring and the film pressure sensor, and after the wearing ring is subjected to a force applied to the patient, the force is applied to the film pressure sensor through the spring and the metal round pad.
Preferably, the signal conversion module is embedded in the outer side surface of the outer ring plate, and the film pressure sensor is arranged on the inner side of the outer ring plate and close to the signal conversion module.
Preferably, the length adjusting assembly is arranged in a manner that the two length adjusting threaded rods are distributed at two sides of the connecting block on different axes and are distributed one above the other.
Preferably, the wearing ring is composed of two semi-ring-shaped components, the two semi-ring-shaped components are provided with the binding belt holes, and the two semi-ring-shaped components are fixed on the lower limbs of the human body through the binding belt.
Preferably, the connecting block is connected with a boss of the lower limb rehabilitation training robot in a matching manner through a fixing bolt and a fixing nut.
The method for acquiring the training curve of the patient characteristics by using the detection device comprises the following steps:
s1, fixing the detection device on the lower limbs of the human body, and connecting the detection device to the lower limb rehabilitation training robot through a connecting block, wherein a signal conversion module in the detection device is connected with a control end of the lower limb rehabilitation training robot through a transmission line;
s2, in the rehabilitation training process, the direction in which the rehabilitation training robot drives the patient to walk is taken as a reference direction, and the sum of the detection values of the film pressure sensors positioned in front is subtracted from the sum of the detection values of the film pressure sensors positioned behind, so that the real-time human-computer contact force is obtained; by adopting the method, the actual human-machine contact force and the gait track of the patient in the processes of starting, periodic step and stopping are continuously monitored, and the data of the patient are obtained and used as a sample set;
S3、a method combining sparse learning and robust learning is adoptedl 1And (3) learning and removing abnormal points from the limited sample set by using a constrained Huber loss minimization learning algorithm to obtain a training curve with the characteristics of the patient.
The invention has the beneficial effects that:
the scheme is characterized in that the structure of the human-computer contact force detection device is optimally designed, so that the human-computer contact force detection device can be better matched with a rehabilitation training robot to complete a detection process, the scheme is a novel wearable sensing mechanism for obtaining human-computer contact force through differential pressure detection, and comprises an intelligent test device for signal conversion and processing, a built-in machine learning algorithm predicts movement intentions, so that the rehabilitation robot is helped to detect the movement intentions of lower limbs of a human body in real time, a patient is assisted to complete rehabilitation training, the training state in the patient rehabilitation process can be timely detected and evaluated, the rehabilitation efficiency is improved, the rehabilitation period is shortened, and the problems that the mechanical sensor is high in motion consciousness recognition lag and the weak biosensor is high in wearing requirement and unreliable in signal detection are solved;
simultaneously, this scheme still has following advantage:
according to the scheme, the size of the detection device can be adjusted in time according to the size of the leg circumference of the lower limbs of the patient by optimizing the structure of the wearing part of the device, so that the device is suitable for the patients with specific personalized differences, and the comfort and convenience of wearing the patient can be improved;
secondly, this scheme is through optimizing the connection structure to power detection module in the device, specifically is: the both sides that the ring was worn in outer crown plate symmetry setting are equipped with at least two sets of power detection module respectively between each side of wearing the ring and the outer crown plate that corresponds, outer crown plate passes through the length adjustment unit mount on the connecting block, realizes following effect: the detection device is in a differential mode in principle and a processing method, 4 film pressure sensors are arranged in front of and behind the lower limb of a patient, a force signal is detected at the same time, a front-back force signal difference value is analyzed and judged, and a measurement error is reduced;
thirdly, the scheme converts the detected signals into feedback signals to participate in control, realizes compliance and safe treatment of man-machine coordination and mutual assistance, and implements detection to prevent secondary damage to patients;
according to the scheme, the connecting part is optimally designed, and the connecting block is matched and connected with the boss of the lower limb rehabilitation training robot through the fixing bolt and the fixing nut, so that the lower limb rehabilitation training robot is convenient to install and disassemble and has the characteristic of better universality;
according to the scheme, the active movement consciousness of the patient is accurately reflected according to the measured contact force, a treating doctor can judge the rehabilitation degree of the patient according to the measured data, a treating scheme suitable for the actual condition of the patient is further worked out, and the pertinence and the effectiveness of rehabilitation treatment are improved;
according to the scheme, the intelligent learning and prediction method of the human motion consciousness is provided, so that the accuracy, stability and rapidity of human-computer interaction detection are greatly improved, and a predicted model has strong generalization capability.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic view of the overall structure of the present invention;
FIG. 2 is a cross-sectional view of the location of a diaphragm pressure sensor of the present invention;
FIG. 3 is a side view of the overall structure of the present invention;
FIG. 4 is a top view of the overall structure of the present invention;
FIG. 5 is an enlarged view of a portion of FIG. 4 at A;
fig. 6 is a schematic diagram of data processing in a use state of the present invention.
Reference numerals: 1. the device comprises a wearing ring, 101, a guide rod, 2, an outer ring plate, 201, a boss, 3, an adjusting nut, 4, a connecting block, 5, a fixing nut, 6, a fixing bolt, 7, a length adjusting screw, 8, a jacking screw, 9, a spring, 10, a metal round pad, 11, a film pressure sensor, 12, a signal conversion module, 13 and a bandage hole.
Detailed Description
The invention is described in detail below by way of exemplary embodiments. It should be understood, however, that elements, structures and features of one embodiment may be beneficially incorporated in other embodiments without further recitation.
It should be noted that: unless defined otherwise, technical or scientific terms used herein shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention belongs. The use of the words "a," "an," or "the" and similar referents in the specification of the present patent application does not imply a limitation of quantity, but rather the presence of at least one. The word "comprise" or "comprises", and the like, indicates that the element or item listed before "comprises" or "comprising" covers the element or item listed after "comprising" or "comprises" and its equivalents, but does not exclude other elements or items having the same function.
The utility model provides a low limbs rehabilitation training robot's man-machine contact force detection device, this man-machine contact force detection device pass through connecting block and coupling assembling and install on low limbs rehabilitation training robot, including the cooperation wear ring, outer crown plate and the power detection module on human low limbs, the both sides of ring are worn to outer crown plate symmetry setting, are equipped with at least two sets of power detection module respectively between each side of wearing the ring and the outer crown plate that corresponds, the outer crown plate passes through the length adjustment subassembly and installs on the connecting block, the length adjustment subassembly include two length adjustment screw rods, two length adjustment screw rod fixed connection are connected with the outer crown plate that corresponds respectively in the both sides of connecting block to fix through adjusting nut.
In the scheme, two guide rods which are arranged at intervals are respectively arranged on each side face of the wearing ring, a boss is correspondingly arranged on the inner side face of the outer ring plate at the position corresponding to each guide rod, a guide groove used for installing the guide rods is formed in the end face of the boss, and the force detection module comprises a film pressure sensor arranged in the guide groove, a force transmission assembly arranged between the guide rods and the film pressure sensor and a signal conversion module used for receiving signals of the film pressure sensor and outputting the signals.
In the scheme, the guide rods on the two side surfaces of the wearing ring are positioned on the same horizontal plane, and the guide rods are fixedly connected to the lug bosses on the side surfaces of the outer ring plates through the jacking screws.
In this scheme, power transmission assembly including connect the spring of guide arm tip and set up the metal round pad between spring and film pressure sensor, dress the ring and receive the effort back to the patient, this effort is applyed on film pressure sensor through spring and metal round pad.
In this scheme, the wearing ring constitute by two semi-annular components, be equipped with the band hole of tying up on it, two semi-annular components are fixed on human low limbs through tying up the band.
The method for acquiring the training curve of the patient characteristics by using the detection device comprises the following steps:
the detection device is fixed on the lower limbs of a human body and is connected to the lower limb rehabilitation training robot through a connecting block, and a signal conversion module in the detection device is connected with a control end of the lower limb rehabilitation training robot through a transmission line;
in the rehabilitation training process, the direction in which the rehabilitation training robot drives the patient to walk is taken as a reference direction, and the sum of the detection values of the film pressure sensors positioned in front is subtracted from the sum of the detection values of the film pressure sensors positioned behind, so that the real-time human-computer contact force is obtained; by adopting the method, the actual human-machine contact force and the gait track of the patient in the processes of starting, periodic step and stopping are continuously monitored, and the data of the patient are obtained and used as a sample set;
step three, a method combining sparse learning and robust learning is utilized, andl 1and (3) learning and removing abnormal points from the limited sample set by using a constrained Huber loss minimization learning algorithm to obtain a training curve with the characteristics of the patient.
The detailed structural composition of the present solution is described in detail below with reference to the accompanying fig. 1-6:
as shown in fig. 1-5, a man-machine contact force detection device of lower limbs rehabilitation training robot, this man-machine contact force detection device passes through connecting block 4 and coupling assembling and installs on lower limbs rehabilitation training robot, it includes the ring 1 of wearing of cooperation on human lower limbs, outer annular plate 2 and power detection module, wherein, wear ring 1 comprises two semi-annular components, be equipped with tie hole 13 on it, two semi-annular components are fixed on human lower limbs through tie the tie, the side of wearing each semi-annular component of ring 1 is equipped with the cylindric guide arm 101 that is that two intervals set up, outer annular plate 2 that corresponds with each semi-annular component, its inside face is equipped with two cylindric bosss 201 of interval, it is to notice: the cylindrical bosses 201 correspond to the guide rods 101 one by one, a guide groove for mounting the guide rods 101 is arranged on the end face of each cylindrical boss 201, the force detection module comprises a film pressure sensor 11 arranged in the guide groove, a force transmission assembly arranged between the guide rod 101 and the film pressure sensor 11, and a signal conversion module 12 for receiving and outputting a signal of the film pressure sensor 11, and for convenience of mounting, the signal conversion module 12 is embedded in a mounting groove on the outer side of the outer annular plate 2 and is electrically connected with the film pressure sensor 11 through a lead; in this embodiment, the film pressure sensor is disposed at the bottom of the guide groove and is placed therein through an opening disposed at the bottom of the boss 201; the outer ring plates 2 are arranged on the connecting blocks 4 through length adjusting components, each length adjusting component comprises two length adjusting screw rods 7, one ends of the two length adjusting screw rods 7 are fixedly connected to two side faces of each connecting block 4 respectively, and the other ends of the two length adjusting screw rods are connected with the corresponding outer ring plates 2 through screw holes in the outer ring plates and adjusting nuts; this structure can in time adjust detection device's size according to patient's low limbs leg encloses the size, adapts to the patient of specific individualized difference, can increase comfort and the convenience that the patient dressed.
In this embodiment, adopt two length adjustment screw 7 to add the reverse precession of adjusting nut 3 and realize that the removal of outer crown plate 2 is fixed in order to adapt to different patients, secondly, length adjustment screw 7 still has following effect: the double-cylinder guide rod 101 of the wearing ring 1 is arranged in the hole of the boss 201, and the degree of freedom is limited by the length adjusting screw 7 to play a guiding role.
In the embodiment, 4 film pressure sensors 11 are arranged in front of and behind the lower limb of the patient, the detection device principle and the processing method are in a differential mode, the output signal is detected, the difference value of the front and rear force signals is analyzed and judged, and the measurement error is reduced.
In this embodiment, as shown in fig. 2 and 5, the force transmission component is a spring 9 connected to the end of the guide rod 101 and a metal round pad 10 arranged between the spring 9 and the film pressure sensor 11, when the force transmission component is installed, the spring 9 and the metal round pad 10 are embedded in a concave hole of a boss 201 on the outer ring plate 2, the metal round pad 10 is installed on the film pressure sensor 11, and the tightening screw 8 is connected to the position of the concave hole of the outer ring plate; wearing ring 1 receives behind the effect of power to the patient through spring 9, can know by the elastic characteristic of spring again, make metal round pad 10 receive behind the effect of power to spring 9, transmit film pressure sensor 11 again, signal conversion module 12 converts film pressure sensor 11's resistance signal into voltage signal, realize the real-time collection and the storage of man-machine contact force through the embedded collection system of DSP, and calculate the pressure that receives this moment according to film pressure sensor 11's demarcation formula, save the data that obtains to the host computer together, again through the conversion of signal conversion module 12 the value of measuring, transmit again in the robot, finally accomplish the detection to the power size.
In this embodiment, as shown in fig. 2, in order to ensure that the effective detection area of the film pressure sensor 11 can detect the contact force transmitted by the spring 9 and the metal circular pad 10 through the double-cylinder guide rod on the wearing ring 1 in the concave hole of the boss 201 of the outer ring plate 2, the guide rod 101, the spring 9, the metal circular pad 10 of the wearing ring 1 and the boss 201 of the outer ring plate 2 need to be installed in a coaxial manner, and then fixed by the tightening screw 8 after installation.
In this embodiment, as shown in fig. 3, the two length-adjusting screws 7 are respectively distributed at two different axial sides of the connecting block 4, and are distributed one above the other.
In this embodiment, as shown in fig. 4, the connecting block 4 is connected to the boss of the lower limb exoskeleton robot in a matching manner, and is connected by the fixing bolt 6, and finally, the fixing bolt is fastened by the fixing nut 5 in a pre-tightening manner, and finally, the connection between the human-computer contact force detection device and the lower limb rehabilitation training robot is completed.
In the rehabilitation exercise training process, because the patient and the lower limb rehabilitation training robot do not move synchronously, a constantly changing contact force exists between the lower limb of the human body and the lower limb rehabilitation training robot, the active participation consciousness of the patient is analyzed through the detection and the processing of the contact force of the human body and the human body, and the information feedback of interactive control is provided for the rehabilitation training robot;
the data processing principle of the actual human-machine contact force value is shown in fig. 6, and can be seen from the figure, wherein: the inner ring is a wearing ring 1, the outer ring is an outer ring plate 2, the x direction is the direction in which the lower limb rehabilitation training robot drives a patient to walk, and the 1, 2, 3 and 4 represent the arrangement positions of four film pressure sensors positioned on two sides of the lower limb;
taking the direction of the lower limb rehabilitation training robot driving the patient to walk as a reference, subtracting the sum of the detection values of 3 and 4 from the sum of the detection values of the two film pressure sensors 1 and 2 positioned in front to obtain real-time human-machine contact force; two film pressure sensors are arranged on each side, so that measurement errors caused by deviation of the device in patient walking are avoided; subtracting the driving force of the human leg from the driving force provided by the exoskeleton through the contact force of the human machine in the active rehabilitation training; in the passive rehabilitation training, the human legs do not actively participate in driving, and the detection value provides driving force for the exoskeleton. The human-machine contact force thus reflects the active participation intention of the patient;
the human body walking process has rhythmicity, and the patient is driven by the rehabilitation training robot to repeatedly train according to the preset rehabilitation gait, so that the human-computer contact force signal also has periodicity which is consistent with the periodicity of the walking gait; according to the method, the device is adopted to continuously monitor the actual human-machine contact force and the gait track of the patient in the processes of starting, periodic step and stopping, and the data of the patient is obtained to be used as a sample set;
a method combining sparse learning and robust learning is adoptedl 1A constrained Huber loss minimization learning algorithm is used for learning and removing abnormal points from a limited sample set to obtain a training curve with patient characteristics; the sparse learning algorithm improves the speed of model learning and quickly solves each parameter; the robust learning algorithm keeps the stability and reliability of the model when the training sample contains abnormal values, combines the two algorithms together, and has strong generalization capability on obtaining a prediction model for the nonlinear characteristics of human-computer contact force and data errors caused by randomness in the human body walking process.
According to the scheme, the multi-contact-point film pressure sensor is adopted, and the contact force between the man machine and the machine is detected by utilizing the characteristic that the resistance value of the film resistor is changed; the overall dimension of the detection device takes the dimension of the leg circumference of the lower limbs of the standard human body as the basis, and the wearing requirements of human bodies with different body states are met through the design of adjustable parts. The positions of main muscles participating in walking in the walking process of a human body are known, the auxiliary motion of the robot is transmitted to the lower limbs of the human body through the binding bands at the front parts and the rear parts of thighs and shanks to push the front pendulum and the rear pendulum of the lower limbs to act on the front parts and the rear parts of the lower limbs, and therefore the self-made human-machine contact force sensors are arranged at the front parts and the rear parts of the lower limbs and are not required to be arranged in a narrow space between the human body and the exoskeleton.
It should be noted that while the invention has been described in terms of the above-mentioned embodiments, other embodiments are also possible. It will be apparent to those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention, and it is intended that all such changes and modifications be covered by the appended claims and their equivalents.
Claims (10)
1. The utility model provides a low limbs rehabilitation training robot's man-machine contact force detection device, this man-machine contact force detection device passes through connecting block and coupling assembling to be installed on low limbs rehabilitation training robot, its characterized in that: including the cooperation ring of wearing on human low limbs, outer crown plate and power detection module, outer crown plate symmetry sets up the both sides of wearing the ring, is equipped with at least two sets of power detection module respectively between each side of wearing the ring and the outer crown plate that corresponds, outer crown plate passes through the length adjustment subassembly and installs on the connecting block, the length adjustment subassembly include two length adjustment screw rods, two length adjustment screw rod fixed connection are connected with the outer crown plate that corresponds respectively in the both sides of connecting block to fix through adjusting nut.
2. The device for detecting a human-machine contact force of a lower limb rehabilitation training robot according to claim 1, wherein: the force detection module comprises a film pressure sensor arranged in the guide groove, a force transmission assembly arranged between the guide rod and the film pressure sensor and a signal conversion module used for receiving and outputting a signal of the film pressure sensor.
3. The device for detecting a human-machine contact force of a lower limb rehabilitation training robot according to claim 2, wherein: the guide rods on the two side surfaces of the wearing ring are positioned on the same horizontal plane, and the guide rods are fixedly connected to the bosses on the side surfaces of the outer ring plates through the jacking screws.
4. The device for detecting a human-machine contact force of a lower limb rehabilitation training robot according to claim 2, wherein: the film pressure sensor is arranged at the bottom of the guide groove and is placed in the guide groove through an opening formed in the bottom of the boss.
5. The device for detecting a human-machine contact force of a lower limb rehabilitation training robot according to claim 2, wherein: the power transmission assembly comprises a spring connected to the end of the guide rod and a metal round pad arranged between the spring and the film pressure sensor, and after the wearing ring receives the force action to a patient, the acting force is applied to the film pressure sensor through the spring and the metal round pad.
6. The device for detecting a human-machine contact force of a lower limb rehabilitation training robot according to claim 2, wherein: the signal conversion module is embedded on the outer side surface of the outer ring plate, and the film pressure sensor is arranged on the inner side of the outer ring plate and close to the signal conversion module.
7. The human-machine contact force detection device of the lower limb rehabilitation training robot according to claim 1 or 2, wherein: the length adjustment subassembly, two the length adjustment threaded rod distributes in the both sides position of the disalignment of connecting block, is the distribution of one on top of the other.
8. The device for detecting a human-machine contact force of a lower limb rehabilitation training robot according to claim 1, wherein: the wearing ring is composed of two semi-annular components, a binding belt hole is arranged on the wearing ring, and the two semi-annular components are fixed on the lower limbs of the human body through the binding belt.
9. The device for detecting a human-machine contact force of a lower limb rehabilitation training robot according to claim 1, wherein: the connecting block is connected with a boss of the lower limb rehabilitation training robot in a matching manner through a fixing bolt and a fixing nut.
10. The method for acquiring a training curve of a patient characteristic according to any one of claims 1 to 9, wherein: the method comprises the following steps:
s1, fixing the detection device on the lower limbs of the human body, and connecting the detection device to the lower limb rehabilitation training robot through a connecting block, wherein a signal conversion module in the detection device is connected with a control end of the lower limb rehabilitation training robot through a transmission line;
s2, in the rehabilitation training process, the direction in which the rehabilitation training robot drives the patient to walk is taken as a reference direction, and the sum of the detection values of the film pressure sensors positioned in front is subtracted from the sum of the detection values of the film pressure sensors positioned behind, so that the real-time human-computer contact force is obtained; by adopting the method, the actual human-machine contact force and the gait track of the patient in the processes of starting, periodic step and stopping are continuously monitored, and the data of the patient are obtained and used as a sample set;
s3, combining sparse learning and robust learning, adoptingl 1And (3) learning and removing abnormal points from the limited sample set by using a constrained Huber loss minimization learning algorithm to obtain a training curve with the characteristics of the patient.
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