CN120789594A - An intelligent weight-bearing training system and method for lower limbs suitable for supine rehabilitation - Google Patents
An intelligent weight-bearing training system and method for lower limbs suitable for supine rehabilitationInfo
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- CN120789594A CN120789594A CN202510835400.2A CN202510835400A CN120789594A CN 120789594 A CN120789594 A CN 120789594A CN 202510835400 A CN202510835400 A CN 202510835400A CN 120789594 A CN120789594 A CN 120789594A
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Abstract
The invention provides a double-lower-limb intelligent weight training system and method suitable for lying position rehabilitation, which relate to the technical field of rehabilitation training and comprise the following steps: after the patient wears the double-lower-limb training structure in the lying state, patient information is input and corresponding training data are queried, a training simulation is conducted on the patient without the stored training data, the training data are obtained and stored based on the detection value of the pressure sensor and the motion trail of the double-lower-limb training structure in the simulation training process, and then lower-limb training motion is conducted on the patient with the stored training data according to the corresponding training data. The method has the beneficial effects of effectively solving the problem that key stress stimulation is lost due to incapability of getting out of bed in early postoperative rehabilitation, providing accurate basis for monitoring and adjusting axial stress applied by the mechanical arm by the host, overcoming blindness of artificial force application, ensuring that the training load and the movement mode of the affected side are strictly matched with the self tolerance level and the functional state of a patient, and realizing accurate rehabilitation of 'one person with one policy'.
Description
Technical Field
The invention relates to the technical field of rehabilitation training, in particular to a double-lower-limb intelligent weight-bearing training system suitable for lying rehabilitation.
Background
A large amount of research evidences at home and abroad show that scientific and moderate axial stress is applied at different stages of fracture healing after lower limb fracture operation, poroma formation and bone reconstruction can be effectively stimulated, bone reconstruction and functional recovery are remarkably accelerated, and the key effect of early load is highlighted. However, making a safe and effective post-operative weight-bearing plan presents a significant challenge. On the one hand, lower limb fractures involve a wide range of sites (e.g., femur, tibia, ankle, etc.), and the severity of injuries (e.g., comminuted fracture, open fracture), age of the patient, bone condition, systemic complications, etc. are markedly different from each other, requiring highly personalized rehabilitation regimens. On the other hand, in clinical practice, how to enable patients to realize early, safe and individual weight training after operation always plagues both doctors and patients. In reality, most patients are forced to enter a long-term bedridden rest phase due to pain, swelling, concerns about fixation stability, lack of auxiliary equipment or blurred orders, etc.
There are significant limitations to rehabilitation training during bedridden periods. Although the traditional muscle strength exercise and joint mobility training are necessary, the standing or walking state cannot be simulated, and the critical axial stress necessary for promoting fracture healing cannot be applied. At the same time, even these exercises often result in poor results due to low patient compliance, painful disturbances or lack of effective guidance and supervision. Depending on the attempt of manually applying force (such as pressing the sole) by family members or accompanying persons, the method is difficult to accurately control the size and direction of the load, can not realize the visual monitoring and data recording of the load, and can not completely meet the core requirements of accurate and personalized rehabilitation.
Thus, the prior art has significant drawbacks. At present, an intelligent weight training instrument which is specially designed for patients after lower limb fracture operation and can be used in a lying position (on a bed) is lacking in the market. This prevents the patient from starting a controllable, load-simulating axial stress stimulus training in time during bed-ridding, missing the precious window of early rehabilitation. Whether the traditional method for exercising on the bed or other auxiliary means is adopted, the method is generally difficult to simultaneously have the key characteristics of simple operation, personalized customization, accurate and controllable load, visualization and data of the training process and the like, and the urgent requirements of modern rehabilitation medicine on efficient, safe and intelligent rehabilitation cannot be met.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a double-lower-limb intelligent weight training system suitable for recumbent rehabilitation, which comprises the following components:
the double-lower-limb training structure is used for being worn and fixed with the lower limbs of a patient in a lying state, and a pressure sensor is arranged on the contact surface of the double-lower-limb training structure and the sole of the patient;
The system comprises a host, wherein the host is connected with the lower limb training structure through a mechanical arm, the host is used for inputting patient information after the patient wears the lower limb training structure, inquiring whether training data corresponding to the patient information are stored or not, performing exercise simulation training on the patient without the stored training data, obtaining and storing training data based on detection values of the pressure sensors and simulated motion tracks of the double lower limb training structure in the simulation training process, and then performing lower limb training motion on the patient with the stored training data according to the corresponding training data.
Preferably, the double lower limb training structure comprises a left training structure and a right training structure, and the left training structure and the right training structure are identical in structure and both comprise:
thigh fixing parts provided with thigh fixing belts for fixing thighs of patients;
A shank fixing part provided with a shank fixing band for fixing the shank of the patient, and a transmission chain arranged on the side surface of the shank fixing plate;
a knee joint transmission part for transmitting and connecting the thigh fixing part and the shank fixing part through a plurality of groups of gears, and further comprising a driver for driving the thigh fixing part and the shank fixing part to rotate around the knee joint transmission part;
and the sole of the load bearing boot is connected with the transmission chain.
Preferably, the load shoe includes:
The loading boot shell is filled with a sole layer, one surface of the sole layer, which contacts with the sole of a patient, is provided with a flexible buffer layer, the loading boot shell is also provided with a plurality of foot fixing belts, and each foot fixing belt corresponds to the heel, the instep and the toe of the patient respectively;
the pressure sensor is disposed in the sole layer.
Preferably, the host is further provided with a host folding supporting device, and the host folding supporting device comprises foldable pins, and when the foldable pins are unfolded, the foldable pins are inserted into the limiting space to limit the displacement of the host.
Preferably, the main machine further comprises a flexible belt, one end of the flexible belt is fixed on the main machine folding support device, and the other end of the flexible belt is connected with a waist fixing piece worn on the waist of the patient.
Preferably, the host includes:
The ability evaluation module is used for performing exercise simulation training on an unevaluated patient after inputting patient information, acquiring a maximum detection value of a pressure sensor as the maximum trampling force of the double lower limbs of the patient in the process of performing exercise simulation training on the patient by using the exercise lower limbs, synchronously recording the motion telescopic length of the mechanical arm and the corresponding transmission included angle of the knee joint transmission part, and then processing to obtain a simulation motion track of the double lower limb training structure as training data for storage;
And the training module is connected with the ability evaluation module and is used for carrying out lower limb training exercise on the patient stored with the training data according to the corresponding training data.
Preferably, the capability assessment module includes:
The trampling force acquisition unit is used for acquiring the maximum detection value of the pressure sensor when the patient tramples the double lower limb training structure by using the healthy side lower limb and the affected side lower limb as the maximum trampling force of the double lower limb of the patient;
And the simulation track processing unit is used for recording the motion telescopic length of the mechanical arm and the corresponding transmission included angle of the knee joint transmission part at each moment when corresponding training actions are executed in the process of performing the training simulation training on the healthy side lower limbs of the patient, then processing the length parameters of the thigh fixing part, the shank fixing part, the knee joint transmission part and the load bearing boots according to the motion telescopic length, the transmission included angle and the length parameters of the double-lower-limb training structure to obtain relative space coordinates of the affected side limbs relative to the host machine, and then correspondingly connecting the relative space coordinates according to time sequence to obtain the simulation motion track for driving the affected side limbs to perform basic movement reference during training.
Preferably, the training module includes:
The training data storage unit is used for storing the training data in the process of performing the training simulation training on the healthy side lower limbs of the patient, wherein the training data comprise a first simulation motion track of ankle pump motion, a second simulation motion track of knee joint flexion, a third simulation motion track of hip joint flexion abduction and the maximum pedaling force of the two lower limbs;
The training unit is connected with the training data storage unit and used for carrying out lower limb training movement on the affected lower limb of the patient according to the first simulated movement track, the second simulated movement track and the third simulated movement track in sequence, driving the affected lower limb to carry out basic movement reference during training, and controlling the mechanical arm to slowly extend until the maximum detection value of the pressure sensor reaches the maximum trampling force of the double lower limbs after the lower limb of the patient is adjusted to be in a weight-bearing training posture.
The invention also provides a double-lower-limb intelligent weight training method suitable for lying position rehabilitation, which is applied to the double-lower-limb intelligent weight training system and comprises the following steps:
Step S1, the dual-lower-limb intelligent weight training system inputs patient information after the patient in the lying state wears the lower limb training structure, and inquires whether training data corresponding to the patient information is stored or not:
If yes, turning to step S2;
if not, performing side-building simulation training on the patient, obtaining training data based on the detection value of the pressure sensor and the simulation motion trail of the double-lower-limb training structure in the simulation training process, storing the training data, and then turning to the step S2;
and S2, performing lower limb training exercises on the patient stored with training data according to the corresponding training data by the double-lower limb intelligent weight training system.
Preferably, the dual lower limb training structure in the dual lower limb intelligent weight training system comprises a weight boot, a thigh fixing part, a shank fixing part, and a knee joint transmission part connecting the thigh fixing part and the shank fixing part;
When training data corresponding to the patient information is not queried in the step S1, the simulation training process includes:
step S11, the intelligent double-lower-limb weight training system acquires the maximum detection value of the pressure sensor when the patient steps on the double-lower-limb training structure by using the healthy side lower limb and the affected side lower limb as the maximum stepping force of the double lower limbs of the patient;
Step S12, when the intelligent double-lower-limb weight training system performs the training simulation on the healthy side of the patient by using the healthy side lower limb, the motion telescopic length of the mechanical arm and the transmission included angle of the corresponding knee joint transmission part at each moment are recorded;
Step S13, the intelligent double-lower-limb weight training system processes the relative space coordinates of the thigh fixing part, the shank fixing part, the knee joint transmission part and the weight boot relative to the host machine according to the motion telescopic length, the transmission included angle and the length parameters of the double-lower-limb training structure, and then correspondingly connects the relative space coordinates according to time sequence to obtain the simulated motion trail for driving the affected limb to do basic motion reference during training.
The technical scheme has the following advantages or beneficial effects:
1. The axial load training in the prone position is realized, a patient can receive the axial stress stimulation simulating standing load in a bedridden state without leaving the bed, and the problem that key stress stimulation is lost due to incapability of leaving the bed in early postoperative rehabilitation is effectively solved.
2. The accurate load application is achieved, the pressure sensor integrated on the sole contact surface provides real-time and quantized load data, an accurate basis is provided for the host machine to monitor and adjust the axial stress applied by the mechanical arm, and the blindness of manual force application is overcome.
3. Individuation of the training scheme, namely, individuation training data generated based on physiological movement capacity of lower limbs on healthy sides, ensuring that the training load and the movement mode on the affected sides are strictly matched with the tolerance level and the functional state of the patient, and realizing accurate rehabilitation of 'one person with one strategy'.
Drawings
FIG. 1 is a schematic diagram of a dual-limb intelligent weight-training system for recumbent rehabilitation, according to a preferred embodiment of the present invention;
FIG. 2 is a schematic diagram of a dual lower limb training structure according to the preferred embodiment of the present invention;
FIG. 3 is a top view of a host computer according to the preferred embodiment of the present invention;
FIG. 4 is a schematic block diagram of a host according to the preferred embodiment of the present invention;
FIG. 5 is a schematic diagram illustrating a motion profile simulation in accordance with a preferred embodiment of the present invention;
FIG. 6 is a schematic diagram illustrating a motion profile simulation in accordance with a preferred embodiment of the present invention;
FIG. 7 is a flow chart of a dual-limb intelligent weight training method for recumbent rehabilitation in accordance with the preferred embodiment of the present invention;
Fig. 8 is a flow chart of step S1 in the preferred embodiment of the invention.
Detailed Description
The invention will now be described in detail with reference to the drawings and specific examples. The present invention is not limited to the embodiment, and other embodiments may fall within the scope of the present invention as long as they conform to the gist of the present invention.
In accordance with the foregoing problems with the prior art, the present invention provides a dual-limb intelligent weight-training system for recumbent rehabilitation, as shown in fig. 1, comprising:
The double-lower-limb training structure 1 is used for being worn and fixed with the lower limbs of a patient in a lying state, and a pressure sensor is arranged on the contact surface of the double-lower-limb training structure with the soles of the patient;
The system comprises a host machine 2, wherein the host machine 2 is connected with a lower limb training structure 1 through a mechanical arm 3, the host machine is used for inputting patient information after the lower limb training structure is worn by a patient, inquiring whether training data corresponding to the patient information is stored or not, performing a training simulation training on the patient which does not store the training data, obtaining and storing the training data based on the detection value of a pressure sensor and the simulation motion trail of the double lower limb training structure in the simulation training process, and then performing lower limb training motion on the patient which stores the training data according to the corresponding training data.
Specifically, the embodiment provides a double-lower-limb intelligent weight training system suitable for recumbent rehabilitation. The system mainly comprises a double lower limb training structure and a host machine matched with the double lower limb training structure. The double-lower-limb training structure is used for being worn and fixed with lower limbs of a patient, and a pressure sensor is arranged on the contact surface of the double-lower-limb training structure and soles of the patient. The system comprises a main machine, a system, a pressure sensor, a double-lower-limb training structure, a training data acquisition device, a control device and a control device, wherein the main machine is connected with the double-lower-limb training structure through the mechanical arm, and is used for inputting patient information (usually information which can prove the identity of a patient such as a name, an identity card, a medical insurance number and the like) and inquiring whether training data corresponding to the patient information are stored after the patient wears the lower-limb training structure, controlling the patient who does not store the training data in the system to carry out side-building simulation training by using the side-building lower limb, acquiring and storing special training data of the patient based on the detection value of the pressure sensor and the simulation motion track of the double-lower-limb training structure in the simulation training process, and then controlling the mechanical arm to carry out accurate lower-limb training motion according to the training data corresponding to the patient in which the training data are stored in the system.
To lack the intelligent heavy burden training equipment that is applicable to lower limb fracture patient postoperative prone position and carry out rehabilitation among the prior art, lead to the patient unable defect of exerting effective axial stress in the bed period, this system is fixed through wearing of two lower limbs training structures and patient's lower limbs to combine the arm design of connecting in the host computer, make the patient be in prone position (bed) completely can use. The mechanical arm can actively drive the double-lower-limb training structure to generate motion, so that controllable axial stress is applied to lower limbs (particularly soles) of a patient, and the loading state during standing or walking is simulated. The core requirement that the patient can carry out weight bearing rehabilitation training during the bedridden period without getting out of the bed is effectively solved.
Aiming at the defect that the accuracy cannot be achieved by manually applying axial stress by virtue of families in the prior art, the system integrates the contact surface between the double lower limb training structure and the sole of a patient, and is provided with a pressure sensor. The sensor is capable of detecting the pressure value (i.e., the magnitude of the axial load) applied to the sole of the patient's foot in real time and quantitatively. The host can acquire and utilize the detection value in the training process, and provides a key data basis for realizing accurate monitoring of the load applied to the lower limbs of the patient, thereby overcoming the defect that the load is difficult to accurately control by manually applying force.
Aiming at the defect of lack of personalized rehabilitation training schemes in the prior art, a method for generating personalized training data based on training simulation on the health side is introduced into a host computer of the system. Specifically, the host computer guides the patient who does not store training data to perform simulated training using his healthy side lower limb. In the process, the system collects and stores key data (including the detection value of the pressure sensor and the simulated motion trail of the double-lower limb training structure) generated by the patient individual in the simulated motion to form the special training data of the patient. When the patient side lower limb training is carried out later, the main machine drives the mechanical arm to move strictly according to the training data corresponding to the patient. This approach ensures that the training parameters (e.g., target load, movement pattern) are derived from the physiological activity capabilities of the patient's own healthy side, primarily enabling personalized customization of rehabilitation training.
Aiming at the defect that the training process in the prior art cannot be visualized and dataized, a host computer of the system is used as a control core, and can continuously acquire and process real-time detection values of pressure sensors and simulated motion trail information of a double-lower-limb training structure in the training process of a healthy side and the subsequent rehabilitation training process. These key parameters are processed and saved as structured training data. As an intelligent system, the host computer has the capability of presenting the information (such as through a display unit), so that real-time load values, preset or executing motion tracks and historical training data records can be visually displayed to an operator or a patient, and visual monitoring and data management of the training process are realized.
Aiming at the defect that the method for assisting the lower limb training of the patient in the prior art is not simple to operate, the system integrates the functions of sensing (pressure sensor), driving (mechanical arm), controlling (host machine) and executing (double lower limb training structure) required by the weight training. The operation flow is clear, after the patient wears the fixed training structure, the information is input through the host computer and the evaluation or training program is started, and the core steps of subsequent force application control, data acquisition, training execution according to an individual plan and the like are automatically completed by the system. The integrated design and standardized operation flow obviously reduce the use complexity and improve the operation simplicity.
In summary, the intelligent double-lower-limb weight training system suitable for recumbent position rehabilitation is realized by the core principle that a double-lower-limb training structure is fixed with the lower limbs of a patient in a wearing way, a driving instruction from a host is received through a mechanical arm, the host firstly guides the patient to perform simulation training by using the healthy side lower limbs, the detection value of a pressure sensor and the simulation motion track of the double-lower-limb training structure in the process are collected and processed in real time, the healthy side motion track is used for driving the affected side limbs to perform basic motion reference when being used for training, individualized training data of the patient are generated and stored, and then, the host precisely controls the motion of the mechanical arm according to the exclusive training data, so that the training structure worn on the affected side lower limbs is driven to perform rehabilitation actions comprising axial stress application.
The remarkable technical effects correspondingly produced by the principle include:
The axial load training in the prone position is realized, a patient can receive the axial stress stimulation simulating standing load in a bedridden state without leaving the bed, and the problem that key stress stimulation is lost due to incapability of leaving the bed in early postoperative rehabilitation is effectively solved.
The accurate load application is achieved, the pressure sensor integrated on the sole contact surface provides real-time and quantized load data, an accurate basis is provided for the host machine to monitor and adjust the axial stress applied by the mechanical arm, and the blindness of manual force application is overcome.
Individuation of the training scheme, namely, individuation training data generated based on physiological movement capacity of lower limbs on healthy sides, ensuring that the training load and the movement mode on the affected sides are strictly matched with the tolerance level and the functional state of the patient, and realizing accurate rehabilitation of 'one person with one strategy'.
The method supports visualization and datamation of the training process, namely continuous acquisition, processing and storage of key parameters (pressure values and motion tracks) by a host computer, so that the training load size, the motion path and the history progress can be clearly presented and traced, and objective basis is provided for medical decision.
The system has the advantages of improving the overall operation simplicity, realizing high integration (integration of sensing, driving, controlling and executing) and flow standardization (wearing, inputting, evaluating and training), remarkably simplifying the operation steps and reducing the use threshold.
The invention provides an innovative solution capable of safely, effectively, accurately and conveniently performing intelligent weight bearing rehabilitation training on lower limbs in the postoperative bedridden period.
In the preferred embodiment of the present invention, as shown in fig. 2, the dual lower limb training structure 1 includes a left training structure and a right training structure, and the left training structure and the right training structure are identical in structure and each include:
thigh fixing parts 11, thigh fixing straps 12 for fixing thighs of the patient are provided on the thigh fixing parts 11;
A shank fixing portion 13, a shank fixing band 14 is provided on the shank fixing portion 13 for fixing the shank of the patient, and a transmission chain is provided on a side surface of the shank fixing portion 13;
A knee joint transmission part 15 for transmitting and connecting the thigh fixing part 11 and the shank fixing part 13 through a plurality of sets of gears 151, and further comprising a driver 152 for driving the thigh fixing part 11 and the shank fixing part 13 to rotate around the knee joint transmission part 15;
the load shoe 16, the sole of the load shoe 16 is connected with the drive chain 17.
In a preferred embodiment of the present invention, load shoe 16 comprises:
The load bearing boot shell 161, the load bearing boot shell 161 is filled with a sole layer 162, one surface of the sole layer contacting the sole of the foot of the patient is provided with a flexible buffer layer 163, the load bearing boot shell 161 is also provided with a plurality of foot fixing belts 164, and each foot fixing belt 164 corresponds to the heel, the instep and the toe of the foot of the patient respectively;
the pressure sensor is disposed in the sole layer 162.
Specifically, in this embodiment, the two lower limbs training structure adopts split type design, including left training structure and the right training structure that independently set up. The two are the same in structure and can operate independently, so that the system can flexibly adapt to the rehabilitation requirement of the unilateral or bilateral lower limbs. In particular, each training structure is further divided into a thigh fixing part, a shank fixing part, and a weight boot, and linkage is achieved through a knee joint transmission part. The modular design allows for local adjustment for patient limb length and joint mobility, effectively enhancing the individual adaptability of the device. Solves the defects of unstable lower limb fixation and misalignment of stress transmission in the prior art.
Thigh fixing portion 11 is provided with thigh fixing strap 12, shank fixing portion 13 is provided with shank fixing strap 14, and the weight boot is provided with a plurality of foot fixing straps (corresponding to heel, instep and toe, respectively). The three-point anchoring structure can firmly restrain each section of the lower limb in the whole training process, and avoids stress dispersion or force line deflection caused by soft tissue sliding. Meanwhile, the binding pressure can be uniformly dispersed in a sectional fixing mode, the risk of local pressure sores is obviously reduced, and the method is particularly suitable for postoperative swelling patients. Further guaranteeing limb fixation safety and force line conduction accuracy.
The knee joint transmission part 15 connects the thigh fixing part 11 and the shank fixing part 13 by transmission through a plurality of sets of gear 151 mechanisms, and is configured to drive both to rotate around the shaft by a driver 152. The multiple groups of gears in the drawing are only simple and schematic, and the gear sets which can simulate knee joint movement can be adopted according to the actual space configuration gears and transmission relations. Compared with the traditional hinge structure, the multistage gear transmission can more accurately simulate the dynamic change track of the instantaneous rotation center (ICR) of the knee joint of the human body. The design combines the closed-loop control of the driver, and can ensure the accurate and controllable output of the bending and stretching angle, the angular speed and the torque, thereby completely avoiding the interference of the shearing stress on fracture healing in the axial weight training. The knee joint movement control precision is improved.
The sole of the weight boot 16 is connected to the shank fixing portion 13 via a transmission chain 17 to form a rigid force transmission path. The sole layer 162 is arranged inside the mechanical arm, and the flexible buffer layer 163 is additionally arranged on the bottom surface of the contact sole, so that the mechanical arm thrust is efficiently transmitted and the impact energy is absorbed. In particular, the pressure sensor is directly embedded into the sole layer (rather than attached to the surface), so that the layout can avoid the interference of plantar soft tissue deformation on measurement, and the actual bearing data of the bony structure can be directly obtained. And the pressure equalizing characteristic of the flexible buffer layer is combined, so that high-precision control and monitoring of axial load application are finally realized.
Through the cooperation of above-mentioned structure, the cooperation technical effect that finally reaches includes:
1. the three-point fixing system ensures stable alignment of limbs;
2. the gear transmission knee joint realizes the reduction of the physiological motion trail;
3. The embedded sensing load boot completes accurate load transmission and measurement;
Therefore, a closed-loop control foundation is formed, so that the axial weight training in the prone position meets biomechanical requirements and parameters can be dynamically adjusted according to individual tolerance. The design fundamentally solves the technical bottleneck that the limb fixation is unstable, the joint movement is distorted and the load is difficult to quantify in the lying position rehabilitation.
In the preferred embodiment of the present invention, as shown in fig. 3, the host machine 2 is further provided with a host machine folding support device 21, which includes a foldable pin 22, and when the foldable pin 22 is folded by a folding joint 23, the foldable pin 22 is inserted into a limiting space to limit the displacement of the host machine.
In a preferred embodiment of the invention, the main machine further comprises a flexible belt, one end of the flexible belt is fixed on the main machine folding supporting device, and the other end of the flexible belt is connected with a waist fixing piece worn on the waist of the patient.
Specifically, the host in this embodiment is provided with a host folding support device formed by foldable pins, and when the pins are unfolded, the pins can be directly inserted into a limit space formed between a mattress and a bed board of a sickbed. According to the design, the physical anchoring of the host is realized by utilizing the inherent structure of the sickbed, so that the host cannot slide due to the reaction force when the mechanical arm applies pushing force or pulling force. Especially for a movable sickbed with weaker rigidity, the operation of embedding the pins into the bottom of the mattress does not need to modify the structure of the bed body, so that the clinical scene adaptability of the equipment is remarkably improved.
On the basis of the unfolding and anchoring of the folding pins 22, a flexible belt is additionally arranged for connecting the main machine and the waist of the patient, wherein one end of the flexible belt is fixed on the main machine folding supporting device, and the other end of the flexible belt is worn on the trunk of the patient through a waist fixing piece. Thereby forming a triangle restraint system of the host-patient-sickbed. When the mechanical arm drives the lower limb training structure to move, the tension force of the flexible belt can synchronously offset the relative displacement trend between the main machine and the body of the patient, so that the deviation of the force line caused by slight sliding of the trunk of the patient is avoided.
The flexible belt adopts the material (such as meshbelt, silica gel cladding hawser) that possesses elastic deformation characteristic, and its core effect lies in:
1. dynamic buffering, namely when the mechanical arm is suddenly started or stopped or suddenly changed in load, the elastic deformation of the flexible belt can absorb impact energy, so that lumbar vertebra injury caused by rigid traction is avoided;
2. The waist fixing piece disperses the pressure acted on the waist of the patient, and combines the moderate constraint of the flexible belt to allow the trunk to naturally adjust the posture in the safe range, thereby reducing the risk of lumbar back pressure sore caused by long-term bedridden;
3. and operating redundancy protection, namely, even if the pins cannot be completely limited due to abnormal bed structure, the flexible belt can still serve as a secondary protection mechanism to prevent the host from toppling over.
Through the combined design of folding pin and flexible belt, the whole technical effect that finally realizes includes:
1. The rigid anchoring (the pins are embedded into the mattress) and the flexible constraint (the elastic belt is connected with the trunk) form a double displacement prevention guarantee;
2. the stability of the main machine is improved, so that the output force of the mechanical arm is accurately transmitted to the affected limb, and the axial stress deviation caused by equipment displacement is avoided;
3. The patient-equipment integrated fixation reduces the dependence on family assistance in training and meets the autonomous rehabilitation requirement of bedridden patients.
The scheme fundamentally solves the problems of training errors and potential safety hazards caused by fixing failure of the recumbent rehabilitation equipment.
In a preferred embodiment of the present invention, as shown in fig. 4, the host 2 includes:
The ability evaluation module 210 is configured to perform a training simulation on a patient without evaluation after patient information is entered, collect a maximum detection value of a pressure sensor as a maximum trampling force of a double lower limb of the patient during the training simulation on the patient with the training lower limb, synchronously record a motion extension length of the mechanical arm and a transmission included angle of a corresponding knee joint transmission part, and then process to obtain a simulated motion track of the double lower limb training structure as training data for storage;
the training module 220 is connected to the ability evaluation module 210, and is configured to perform a lower limb training exercise on the patient having stored training data according to the corresponding training data.
In a preferred embodiment of the present invention, the capability assessment module 210 includes:
the trampling force acquisition unit 211 is used for acquiring the maximum detected value of the pressure sensor when the patient tramples the double lower limb training structure by the healthy side lower limb and the affected side lower limb as the maximum trampling force of the double lower limb of the patient;
the simulation track processing unit 212 is configured to record a motion extension length of the lower mechanical arm and a transmission angle of the corresponding knee joint transmission part at each moment when performing a corresponding training action in a process of performing a training simulation training on a patient with a training lower limb, then process to obtain relative space coordinates of the thigh fixing part, the shank fixing part, the knee joint transmission part and the weight-bearing boot relative to the host according to the motion extension length, the transmission angle and length parameters of the double-lower-limb training structure, and then correspondingly connect the relative space coordinates in time sequence to obtain a simulation motion track.
In a preferred embodiment of the present invention, the training module 220 includes:
A training data storage unit 221, configured to store training data during a patient performing a training simulation with a training lower limb, where the training data includes a first simulated motion trajectory of ankle pump motion, a second simulated motion trajectory of knee joint flexion, a third simulated motion trajectory of hip joint flexion abduction, and a maximum pedaling force of the two lower limbs;
The training unit 222 is connected to the training data storage unit 221, and is configured to perform a lower limb training motion on a patient's affected lower limb according to the first simulated motion trajectory, the second simulated motion trajectory, and the third simulated motion trajectory in sequence, and control the mechanical arm to slowly extend until the maximum detection value of the pressure sensor reaches the maximum trampling force of the two lower limbs after adjusting the patient's lower limb to the weight training posture.
Specifically, the ability evaluation module in this embodiment collects key physiological data during the process by guiding the patient to perform simulated training using the healthy side lower limb. Specifically, the pedal force acquisition unit acquires the peak detection value of the pressure sensor in real time, and takes the peak detection value as an individuation reference of the maximum pedal force of the double lower limbs. The maximum pedaling force is required to be evaluated on both sides, the maximum force of the healthy side and the maximum force of the affected side are different in training, and particularly the affected side is required to be controlled within the maximum force range. The design is based on the principle of symmetry of functions of two limbs of a human body, so that the activity capacity of a healthy side can be directly converted into the upper limit reference of the load of the training of a sick side, and the blindness of the traditional empirical load setting is fundamentally avoided.
In the training simulation, the simulation track processing unit synchronously records two core parameters, namely the motion telescopic length (L) of the mechanical arm and the real-time transmission included angle (theta) of the knee joint transmission part. The parameters of other components can be preconfigured in the host machine in advance and are not shown one by combining prestored parameters of the length of the double lower limb training structure (such as thigh fixing part length M, calf fixing part length S and the like in the figure), and the spatial positions of the components relative to the host machine are calculated in real time through a spatial coordinate conversion algorithm. For example, taking knee flexion as an example, as shown in fig. 5, a simplified schematic diagram is used to represent a simulated training track for a dual lower limb training structure, and the mechanical arm in this embodiment adopts a structure with adjustable pitch angle:
S1, when a patient performs knee bending training on a lower limb of a healthy side:
S2, recording a time t 1, namely the telescopic length L 1 of the mechanical arm and a gear transmission included angle theta 1;
s3, establishing a three-dimensional coordinate system according to the origin O of the mechanical arm base (namely the position of the mechanical arm extending from the host computer);
S4, calculating the sole center point coordinate K of the loading boot:
X-axis coordinates = L 1 X cos α (α is the pitch angle of the arm)
Z-axis coordinates = L 1 x sin alpha
S5, calculating the center point coordinate F of the knee joint transmission part:
Offset vector with respect to K point= [ s×sin (θ 1),0,-S×cos(θ1) ]
So the F-point coordinates=k-point coordinates+offset vector
And S6, connecting coordinate points at all moments in time sequence, namely generating a second simulated motion track (knee joint buckling track).
As shown in fig. 6, the training track of the dual lower limb training structure is represented by a simplified schematic diagram, and in this embodiment, the mechanical arm adopts a straight and elongated structure moving up and down, that is, the tail end of the mechanical arm is connected with the host through a sliding rail structure capable of moving up and down.
The process of calculating the sole center point coordinate K of the weight-bearing boot in this structure is different from that in the previous structure in that the coordinate origin P of the three-dimensional coordinate system is set as a fixed point (preferably, the base origin O of the mechanical arm in the initial state) in the host machine, the sole center point coordinate K of the weight-bearing boot is calculated according to the vertical displacement J and the telescopic length L1 between the base origin O and the coordinate origin P of the mechanical arm, and the process of calculating the center point coordinate F of the knee joint transmission part is the same as that in the previous structure.
The training module integrates the individuation parameters (maximum treading force F_max) and three types of movement tracks (ankle pump-using the healthy side simulation track to drive the affected side ankle joint to move so as to complete the movement plan, knee flexion-using the healthy side simulation track to drive the affected side knee joint to move so as to complete the movement plan, hip flexion abduction-using the healthy side simulation track to drive the affected side hip joint to move so as to complete the movement plan) acquired by the training data storage unit into a structural rehabilitation scheme. The training unit performs accordingly a phased control:
The sequential track reproduction is that the affected limb is driven strictly according to the sequence of the first track (ankle pump), the second track (knee flexion) and the third track (hip flexion abduction), so that the medical specification of the postoperative joint mobility training is met;
progressive loading, namely, in the weight training stage, the weight boots are in a vertical state, and the knee joints are in a straightening state and are fixed in angle. The mechanical arm slowly stretches, pressure born by the sole of the foot is sensed in real time in the process, and the stretching is stopped when the maximum load target is reached. The upper and lower limbs are used for loading alternately and simulating walking. And the mechanical arm is controlled to slowly extend until the pressure detection value reaches F_max, so that poroma injury caused by load mutation is avoided. The flow design ensures that the training intensity is always within the patient tolerance threshold.
The individual parameters of the ability evaluation module are extracted, the training module is accurately executed in stages, and a closed-loop rehabilitation control effect is finally achieved, so that an evaluation-planning-execution closed-loop rehabilitation process is formed, the training safety is improved, and the function reconstruction process is obviously accelerated.
The system comprises a host, a control unit, a communication module, a man-machine interaction interface, a touch screen, a storage module and a big data cloud platform, wherein the host is also provided with a voice playing module for playing music and training states, the control unit is used for controlling the mechanical arm to complete various training actions according to a training plan, the communication module is used for transmitting data to the man-machine interaction interface and the cloud platform in real time, the man-machine interaction interface is used for a touch screen for displaying task targets and real-time training states, the storage module is used for storing basic data and training information of patients, and the big data cloud platform is used for storing and sharing data in real time.
The invention also provides a double-lower-limb intelligent weight training method suitable for recumbent rehabilitation, which is applied to the double-lower-limb intelligent weight training system, as shown in fig. 7, and comprises the following steps:
Step S1, inputting patient information after the patient in the recumbent position state wears a lower limb training structure by the double-lower-limb intelligent weight training system, and inquiring whether training data corresponding to the patient information are stored or not:
If yes, turning to step S2;
If not, performing side-building simulation training on the patient, obtaining training data based on the detection value of the pressure sensor and the simulated motion trail of the double-lower-limb training structure in the simulation training process, storing the training data, and then turning to the step S2;
Step S2, the intelligent double-lower-limb weight training system performs lower limb training exercises on the patient with stored training data according to the corresponding training data.
Preferably, as shown in fig. 8, the dual lower limb training structure in the dual lower limb intelligent weight training system comprises a weight boot, a thigh fixing part, a shank fixing part, and a knee joint transmission part connecting the thigh fixing part and the shank fixing part;
When training data corresponding to the patient information is not queried in the step S1, the simulation training process includes:
Step S11, the intelligent double-lower-limb weight training system acquires the maximum detection value of the pressure sensor when the patient steps on the double-lower-limb training structure by using the healthy side lower limb and the affected side lower limb as the maximum stepping force of the double lower limbs of the patient;
Step S12, recording the motion telescopic length of the lower mechanical arm and the transmission included angle of the corresponding knee joint transmission part at each moment when the corresponding training action is executed in the process of performing the exercise simulation training on the lower limb of the patient by the exercise side by the double-lower-limb intelligent weight training system;
and S13, processing the intelligent double-lower-limb weight training system according to the length parameters of the motion telescopic length, the transmission included angle and the double-lower-limb training structure to obtain relative space coordinates of the thigh fixing part, the shank fixing part, the knee joint transmission part and the weight boots relative to the main machine, and correspondingly connecting the relative space coordinates according to a time sequence to obtain a simulated motion track.
The foregoing is merely illustrative of the preferred embodiments of the present invention and is not intended to limit the embodiments and scope of the present invention, and it should be appreciated by those skilled in the art that equivalent substitutions and obvious variations may be made using the description and illustrations herein, which should be included in the scope of the present invention.
Claims (10)
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