CN111939529B - A kind of active rehabilitation training method and system based on muscle strength measuring device - Google Patents
A kind of active rehabilitation training method and system based on muscle strength measuring device Download PDFInfo
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Abstract
本发明涉及一种基于肌力测量装置的主动式康复训练方法、系统。根据患者的不同病因构建不同的训练方案集合，上传至云知识库；向云知识库中输入患者信息，与云知识库中的训练方案集合进行匹配，匹配到相似患者，利用相似患者的训练方案模型作为训练方案，如果无法匹配到相似患者，则通过训练方案决策机制生成新的训练方案模型；将得到的新的训练方案模型存储至云知识库中的训练方案集合中。通过康复训练方法生成康复训练方案，并可实现训练方案的更新，减少了训练实施过程中的依赖性。
The invention relates to an active rehabilitation training method and system based on a muscle strength measuring device. Construct different sets of training programs according to different etiologies of patients and upload them to the cloud knowledge base; input patient information into the cloud knowledge base, match with the training program sets in the cloud knowledge base, match to similar patients, and use the training programs of similar patients The model is used as a training scheme. If similar patients cannot be matched, a new training scheme model is generated through the training scheme decision-making mechanism; the obtained new training scheme model is stored in the training scheme set in the cloud knowledge base. The rehabilitation training program is generated by the rehabilitation training method, and the updating of the training program can be realized, which reduces the dependence in the training implementation process.
Description
Technical Field
The invention belongs to the technical field of muscle strength rehabilitation training, and particularly relates to an active rehabilitation training method and system based on a muscle strength measuring device.
Background
The information in this background section is only for enhancement of understanding of the general background of the invention and is not necessarily to be construed as an admission or any form of suggestion that this information forms the prior art that is already known to a person of ordinary skill in the art.
In clinical work, patients with nervous system diseases such as stroke and spinal cord injury, patients with osteoarticular diseases such as fracture and osteoarthritis, and patients who lie in bed after various operations all have obvious reduction of activity of lower limbs, the reduction of the activity of the lower limbs often causes rehabilitation problems such as muscular atrophy, muscle endurance reduction, joint contracture and the like of the lower limbs, serious adverse consequences such as venous thrombosis of the lower limbs and pulmonary embolism can be caused seriously, the occurrence of the adverse consequences can directly cause the extension of the hospitalization period of the patients, the increase of medical expenses, and heavy burden is brought to individuals, families and society. At present, many clinicians have paid attention to the importance of early lower limb rehabilitation training of bedridden patients, however, because of the restriction of patient conditions, treatment resource distribution, the limitation of application conditions of the existing lower limb rehabilitation equipment, and other factors, the early active lower limb rehabilitation work is obviously insufficient, the early lower limb rehabilitation training of many bedridden patients still takes the exercises of ankle pump movement, quadriceps femoris muscle strength training and the like which are automatically performed by the patients under the guidance of doctors as the main part, the self-training process of the patients lacks supervision and real-time guidance, the training action is stereotyped and monotonous, and the patients are difficult to effectively insist on for a long time.
At present, the instruments suitable for lower limb rehabilitation training of bedridden patients are complex in operation, some rehabilitation devices can be trained only by being assisted by others, passive training is more, and the cost is higher.
Disclosure of Invention
In view of the above problems in the prior art, an object of the present invention is to provide an active rehabilitation training method and system based on a muscle strength measuring device.
In order to solve the technical problems, the technical scheme of the invention is as follows:
in a first aspect, an active rehabilitation training method based on a muscle force measuring device comprises the following specific steps:
acquiring patient information, and matching the patient information with a training scheme set in a cloud knowledge base; wherein training scheme sets of different causes are stored in the cloud knowledge base;
if similar patients are matched, using the training scheme models of the similar patients as training schemes, and if the similar patients cannot be matched, generating a new training scheme model through a training scheme decision mechanism;
and storing the obtained new training scheme model into a training scheme set in a cloud knowledge base.
Because the rehabilitation training schemes have larger difference due to different causes, in order to improve the reliability of the autonomous generation of the rehabilitation training schemes, different training scheme sets are constructed in the cloud knowledge base according to different causes of patients. In the rehabilitation training method, according to the etiology of a patient, inputting the etiology into a cloud knowledge base, training the patients with similar attributes by using training scheme models of the similar patients;
and inputting the mechanical information of the patient acquired by the muscle strength measuring device into the cloud knowledge base, generating a new training scheme model for the patient to use according to a scheme decision mechanism, uploading the new training scheme model to the cloud knowledge base, and expanding the knowledge base information.
In a second aspect, a rehabilitation training system comprises:
the cloud knowledge base is used for storing the training scheme;
the muscle force measuring device is used for limb rehabilitation training of the patient and collecting mechanical information of the patient;
the display is used for displaying mechanical information of the patient in the rehabilitation training process, wherein the mechanical information comprises information such as an analysis curve obtained after the data is subjected to secondary analysis processing;
the intermediate processing module is used for inputting the information of the patient to obtain a training scheme model of the patient: the information is matched and screened by collecting the patient information and feeding back the information to the cloud knowledge base, and an existing training scheme or an application scheme decision mechanism is called to generate an individualized training model according to whether the information is matched or not.
The invention has the beneficial effects that:
1. the muscle strength measuring device is small in size, the foldable structure is convenient to carry and store, the installation and operation method is simple, the testing can be carried out at any time, and the muscle strength testing of large muscle groups such as lower limb quadriceps femoris, popliteal cord muscles, tibialis anterior muscles and crus triceps can be realized according to different placement positions and modes of the air bags.
2. Muscle strength measuring device can show user's muscle effort and the change of action time in real time, and clear visual information feedback lets the user more have the control to the recovered process of oneself and feels, has improved user rehabilitation training's enthusiasm, does benefit to the user and insists on for a long time, consolidates the training effect.
3. The gasbag that contacts the limbs during the use adopts the rubber material, and the three-dimensional bump of surface distribution is used and is experienced comfortablely, and the limbs that are tested are the relaxed state before using and place on the gasbag, and the sense input of multiplicable central nervous system improves the cognitive feedback of organism to the action start-up, promotes better planning, the start-up of central nervous system and controls the training action.
4. When medical staff applied the device and carried out muscle strength measurement and training to the patient, can effectively liberate medical staff's both hands, reduce the strength of medical staff bare-handed work, the better change condition of observing patient power consumption in-process mechanics information of medical staff of being convenient for can in time make feedback guidance to developing of patient's follow-up training.
5. The active rehabilitation training scheme based on the muscle force measuring device can be used for generating the rehabilitation training scheme of the patient through an autonomous decision-making method, dependence on medical staff in the training process of the patient is reduced, and measurement training can be carried out at any time. A large number of rehabilitation training schemes are stored in a cloud knowledge base, and the training schemes generated through a training scheme decision mechanism can fully use the existing schemes and fully consider the personal attributes of patients; the training scheme updating mechanism updates the scheme according to the rehabilitation requirements of the patient in different rehabilitation stages, so that the insufficient strength or the excessive fatigue of the patient in the training process is avoided, and the rehabilitation treatment effect of the patient is effectively improved; the scheme evaluation mechanism realizes the screening of the scheme and improves the reliability and the effectiveness of the training scheme.
The device design is brief, and durable, the cost is controllable, and the user cost is less, and clinical demand is wide, and cerebral apoplexy, peripheral nerve damage, bone joint damage, postoperative patient, old person and daily body-building fan all can use, and market prospect is wide.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description, serve to explain the invention and not to limit the invention.
FIG. 1 is a side view of a muscle force measuring apparatus according to the present invention, wherein a is a side view, b is a right side view, and c is a top view;
FIG. 2 is a rehabilitation training method based on a muscle force measuring device according to the present invention;
wherein, 1-a cross foot plate; 2-a foldable structure; 3-a vertical foot plate; 4-a first pressure sensor; 5-a first balloon; 6-foot binding band; 7-a second pressure sensor; 8-a retractable metal rod; 9-knee strap; 10-a second balloon; 11-knee plate; 12-a third pressure sensor; 13-fourth pressure sensor.
Detailed Description
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
An active rehabilitation training method based on a muscle force measuring device comprises the following specific steps:
testing by using the muscle strength measuring device to obtain a test result of the patient, transmitting the test result to the intermediate processing module, and matching the patient information with a training scheme set in the cloud knowledge base by using the intermediate processing module;
if the similar patients are matched, calling the training scheme models of the similar patients as training schemes, and if the similar patients cannot be matched, generating new training scheme models through a training scheme decision mechanism;
and storing the obtained new training scheme model into a training scheme set in a cloud knowledge base.
The patient information mainly comprises two parts of basic information and mechanical information: basic information: basic data such as sex, age, occupation, course of disease, and main causes of disability; mechanical information: the muscle force measuring device is used for pre-testing the patient to obtain the information of the patient's muscle force, action time and the like and correspondingly generated muscle force-time curves and the like.
Because the rehabilitation training schemes have larger difference due to different causes, in order to improve the reliability of the autonomous generation of the rehabilitation training schemes, different training scheme sets are constructed in the cloud knowledge base according to different causes of patients. When rehabilitation training is carried out, the training data is input into a cloud knowledge base according to the etiology of a patient, the patient with similar attributes is trained by utilizing a training scheme model of the similar patient;
and (4) testing the patients without similar attributes by using a muscle strength measuring device to obtain the mechanical information of the patients, inputting the mechanical information into a cloud knowledge base, and generating a new training scheme model according to a scheme decision mechanism.
Preferably, the patient information includes basic information and mechanical information, the basic information includes basic data such as sex, age, occupation, disease course, main causes of disability and the like of the patient; the mechanical information is the information of the patient muscle strength, action time and the like obtained by applying a muscle strength measuring device to pretest the patient, a correspondingly generated muscle strength-time curve and the like.
In some embodiments of the present invention, the cloud knowledge base includes a training scheme set, the training scheme set includes a plurality of training scheme models, and the training scheme models also include descriptions of attributes of corresponding patients and descriptions of information of rehabilitation devices, so as to facilitate matching or decision making according to attributes of new patients. The training scheme sets generated based on different causes are stored in the cloud knowledge base, and along with continuous accumulation of data in the cloud knowledge base, the training scheme sets can be classified to form subsets of the training schemes according to information such as age, gender and main evaluation indexes of functional states of patients under the same cause data set, so that accurate matching of the training schemes is facilitated.
In some embodiments of the present invention, the method of the scheme decision mechanism is: and sequentially splitting the attributes into a plurality of characteristics by using an intermediate processing module, searching for similar characteristics, obtaining training steps and parameters, and screening and fusing based on rules to obtain a training scheme.
Preferably, the attribute is patient information, the patient information includes basic information and mechanical information, the basic information includes basic information such as sex, age, occupation, course of disease, main cause of disability and the like of the patient, and the mechanical information includes muscle acting force, acting time, acting force-time curve, maximum value of acting force and the like.
Preferably, the method for searching for similar features is to search for similar features in a cloud knowledge base based on a MapReduce algorithm.
Preferably, the method for screening and fusing based on the rule is as follows: based on MapReduce algorithm, a plurality of existing patient training schemes with similar characteristics can be obtained according to the characteristics of the patients, different weights are distributed to the characteristics of the patients, after each characteristic value is multiplied by the weight, the rehabilitation training schemes of a plurality of existing patients most similar to the patients are obtained, the rehabilitation training schemes of the existing patients are decomposed into minimum training steps, and the minimum training steps are carried out again for tissue fusion. The fusion method is an averaging or fitting interpolation method.
In some embodiments of the present invention, the muscle strength measuring device includes a supporting device, a pressure airbag, a mechanical sensor, an intermediate processing module, and a display screen, wherein the pressure airbag is disposed on the supporting device, the mechanical sensor is disposed on the supporting device at a position corresponding to the pressure airbag, the intermediate processing module is connected to the mechanical sensor through a wire, and the intermediate processing module is connected to the display screen.
The design of this device is based on clinical demand, the limbs muscle contraction form is mainly with isometric contraction during the use, isometric contraction is assisted, isometric contraction can make muscle produce very big tension in the short time, it is significant to the recovery reinforcing of muscular strength, be fit for the effectual muscle contraction motion that bed patient developed, simultaneously, the training that the strength is big and the number of repetitions is few not only can recruit more motion units and participate in the muscle contraction, increase muscular strength, also can change central nervous system to the effect of motion unit simultaneously, promote the synchronous shrink of more motion units, produce bigger strength, the muscle that has important effect to improving user's muscular strength.
The muscle strength measuring device can relatively accurately measure the muscle strength information of the corresponding muscle group of the patient, and can also be used for rehabilitation training, because the patient can simultaneously see the muscle strength information on the display screen when performing muscle strength movement on the pressure air bag, the intermediate processing module transmits data to the display screen, the user can see the real-time force and action time of the individual and other mechanical information, and can also see the content of action force peak value, action time peak value, mechanical change curve and the like generated by statistical analysis of the previous training data of the individual, the training target and scheme can be accurately formulated according to the training requirements of the user, good feedback guidance effect can be played for the training of the user, and the lower limb muscle strength training process developed by the individual can be more controllable and effective.
In some embodiments of the present invention, the method for obtaining the mechanical information of the patient by the intermediate processing module is as follows: the mechanical sensor transmits data such as muscle acting force and muscle acting time to the intermediate processing module, the intermediate processing module analyzes and processes mechanical information to obtain test data, and an acting force-time curve and the like are generated.
In some embodiments of the invention, the support device comprises a horizontal foot plate, a vertical foot plate, a knee cover plate, a telescopic connecting rod and a binding band, the horizontal foot plate and the vertical foot plate are vertically arranged and connected through the connecting rod, the horizontal foot plate and the knee cover plate are connected through the telescopic connecting rod, the horizontal foot plate and the knee cover plate are arranged in parallel, the vertical foot plate and the knee cover plate are respectively connected with the binding band, and the binding band surrounds the upper surfaces of the vertical foot plate and the knee cover plate to form the arc-shaped binding band.
In some embodiments of the present invention, four pressure sensors are provided, which are a first pressure sensor, a second pressure sensor, a third pressure sensor and a fourth pressure sensor, and the first pressure sensor and the second pressure sensor are respectively provided at one end of the inner surface of the arc-shaped binding belt, which is close to the vertical foot plate and the knee cover plate. The third pressure sensor and the fourth pressure sensor are respectively arranged on the upper surfaces of the vertical foot plate, the knee plate and the arc-shaped binding belt, and the first pressure sensor and the second pressure sensor are respectively used for measuring mechanical information of ankle joint dorsal extension and knee joint flexion. The third pressure sensor primarily measures the plantar flexion of the ankle joint. The fourth pressure sensor primarily measures the extension movement of the knee joint.
The pressure value range of the pressure sensor is 0-400 newton.
In some embodiments of the invention, two air bags are provided, namely a first air bag and a second air bag, the first air bag is arranged on the standing plate, the second air bag is arranged on the knee cover plate, and a plurality of bulges are arranged on the surface of the air bags. The pressure air bag of the present invention may be an inflatable rubber or other elastic material ball. The shape is round or oval, square, etc. The provision of the projections helps to improve the sensory feedback of the patient.
In some embodiments of the present invention, the telescopic connecting rod comprises three connecting tubes, the connecting tubes have different diameters and are sequentially sleeved in the connecting tubes, and a locking structure is arranged on the telescopic connecting rod. The pipe diameter difference can be for being first festival connecting pipe, second festival connecting pipe, third festival connecting pipe respectively according to the pipe diameter size, and the second festival connecting pipe can be retracted in the first festival connecting pipe, and the third festival connecting pipe can be retracted in the second festival connecting pipe, all can lock through locking structure at arbitrary length, and the locking degree can be adjusted through the screw to guarantee that the locking is reliable.
The length adjustment of the telescopic connecting rod can be adjusted according to the length of a human body.
The connecting rod sets up beta structure with the one end of erecting the foot board and being connected, can realize folding effect of placing.
In some embodiments of the invention, the cloud knowledge base is a Hadoop platform-based columnar storage database HBase.
In some embodiments of the invention, the scheme decision mechanism performs algorithm design based on the MapReduce programming framework.
In some embodiments of the invention, training regimen models in the cloud knowledge base are fed back and screened through a regimen scoring mechanism. And the scheme scoring mechanism feeds back and screens the training scheme model through the intermediate processing module, and the scheme scoring mechanism is designed based on a MapReduce programming framework.
In a second aspect, a rehabilitation training system comprises:
the cloud knowledge base is used for storing the training scheme;
the muscle force measuring device is used for limb rehabilitation training of the patient and collecting mechanical information of the patient;
the display is used for displaying mechanical information of the patient in the rehabilitation training process, wherein the mechanical information comprises information such as an analysis curve obtained after the data is subjected to secondary analysis processing;
the intermediate processing module is used for inputting the information of the patient to obtain a training scheme model of the patient: the information is matched and screened by collecting the patient information and feeding back the information to the cloud knowledge base, and an existing training scheme or an application scheme decision mechanism is called to generate an individualized training model according to whether the information is matched or not.
Example 1
As shown in fig. 2, different training scheme sets are constructed according to different causes of the patient and uploaded to the cloud knowledge base, the training scheme sets are training scheme models grouped according to different causes, and the training scheme models also include descriptions of attributes of corresponding patients and descriptions of information of rehabilitation devices, so that matching or decision making can be performed according to attributes of new patients. The patient attribute can be the condition of the personalized etiology and the like of the patient, and the rehabilitation equipment information can be the rehabilitation equipment resource, the rehabilitation ability and the like;
when a patient is trained, inputting the attributes of the patient, and comparing the attributes with different training scheme models in a training scheme set in a cloud knowledge base to obtain a training scheme model corresponding to the patient;
the attributes of the patient include the individual's height, weight, age, sex, occupation, etiology, and mechanical information measured using a muscle force measuring device.
If the similar patients can not be matched, generating a new training scheme model through a training scheme decision mechanism;
the training scheme decision mechanism is a method for sequentially splitting the patient attributes into a plurality of features and searching for similar features by using an intermediate processing module, and the similar features are searched in a cloud knowledge base based on a MapReduce algorithm.
Based on MapReduce algorithm, a plurality of existing patient training schemes with similar characteristics can be obtained according to the characteristics of the patients, different weights are distributed to the characteristics of the patients, after each characteristic value is multiplied by the weight, the rehabilitation training schemes of a plurality of existing patients most similar to the patients are obtained, the rehabilitation training schemes of the existing patients are decomposed into minimum training steps, and the minimum training steps are carried out again for tissue fusion. The fusion method is an averaging or fitting interpolation method. And screening and fusing based on the rules to obtain a new training scheme.
And storing the obtained new training scheme model into a cloud knowledge base to serve as one training scheme model in a training scheme set and one of a plurality of training scheme models under one cause. And updating the training scheme set.
The training scheme set can be fed back and screened through a scheme scoring mechanism, high-quality schemes are reserved, and poor-quality schemes are eliminated.
The muscle force measuring device realizes the measurement of mechanical information such as the muscle force of a patient, generates a muscle force-time curve, and obtains the acting force and time when the ankle joint and the knee joint of a specific individual do corresponding actions, so that data for training according to the requirement of the specific individual can be obtained. Then, the specific individual training data is input into a cloud knowledge base, and the corresponding training scheme can be seen when the same kind of patients are encountered next time. The patient can conveniently know how to train or a therapist can conveniently carry out targeted rehabilitation training on different patients.
The use process of the rehabilitation training system is as follows:
as shown in a, b and c of fig. 1, the muscle force measuring device is used for testing mechanical data, the muscle force measuring device comprises a cross foot plate 1, a vertical foot plate 3, a first air bag 5, a first pressure sensor 4, a second pressure sensor 7, a telescopic metal rod 8, a second air bag 10, a foot binding band 6, a knee binding band 9, a knee plate 11, a third pressure sensor 12 and a fourth pressure sensor 13, the cross foot plate 1 is connected with the knee cover plate 11 through the telescopic metal rod, the cross foot plate 1 is connected with the vertical foot plate 3 through a connecting rod, and a foldable structure 2 is arranged at one end of the connecting rod connected with the vertical foot plate 3, so that the function of folding and placing can be realized. The first air bag 5 and the second air bag 10 are respectively stuck on the vertical foot plate and the knee cover plate in an adhesion mode. The foot bandage 6 and the knee bandage 9 are respectively connected with the vertical foot plate and the knee plate, the inner surfaces of the foot bandage 6 and the knee bandage 9 are respectively provided with a first pressure sensor 4 and a second pressure sensor 7, and the third pressure sensor 12 and the fourth pressure sensor 13 are respectively positioned on the upper surfaces of the vertical foot plate and the knee plate opposite to the arc bandage, namely the positions where the vertical foot plate and the knee cover plate are jointed with the pressure air bags.
The lower limb part to be trained is placed above the air bag, the pressure sensor is used for conducting the pressure value to the lower part of the air bag or the inner surface of the bandage after the air bag or the bandage is pressed, the pressure sensor is used for conducting the acting force and acting time data to the display screen after being processed by the intermediate processing module, and the acting force and the acting time can be seen by a user in real time. In addition, the muscle force measuring device can be used as a part of a measuring device module to upload the measured muscle acting force, acting time and the like of the patient to a cloud knowledge base for storage and subsequent analysis.
Training scheme models in a cloud knowledge base:
the training scheme model comprises a large number of existing rehabilitation training schemes in the early stage and a rehabilitation training scheme newly generated by the cloud knowledge base, and meanwhile, the training scheme model also covers the description of the attributes of the corresponding patient and the description of the information of the rehabilitation equipment, so that matching or decision making can be conveniently carried out according to the attributes of the new patient.
The personal attribute model comprises information of the height, age, sex, occupation, etiology, measured muscle acting force and acting time and the like of the patient, and is a sufficient description for the patient who is subjected to rehabilitation training. The measurement data related to the personal attribute model can be acquired by the measurement device module.
The hospital resource model describes all rehabilitation equipment in a hospital and the rehabilitation capacity of the equipment, and provides a basis for generating a training scheme.
And applying an ontology language OWL to model a personal attribute model, a hospital resource model and a training scheme model. And modeling the model by adopting an ontology editor prot g.
The column type storage database HBase based on the Hadoop platform has the characteristics of expandable storage space, dynamically changeable storage structure, support for efficient access and the like. Therefore, the rehabilitation training scheme set of the cloud knowledge base is constructed based on the HBase. In terms of database access, the access of the MapReduce programming framework provided for Hadoop is supported, so that the training scheme decision mechanism, the training scheme updating mechanism and the scheme evaluation mechanism are designed based on the MapReduce programming framework to carry out related algorithms.
The active rehabilitation training method based on the muscle force measuring device has the use process that:
for a patient A, firstly, measuring attributes of the patient, such as height, age, sex, occupation, etiology, measured muscle acting force, acting time and the like by using a measuring device module comprising a muscle force measuring device and other measuring devices, then inputting input information of the patient into a cloud knowledge base module under a corresponding etiology group according to the etiology, secondly, matching the personal attributes of the patient with the personal attributes of a large number of patients in the cloud knowledge base, and if a similar patient B is matched, acquiring a rehabilitation training scheme of the patient B, and directly taking the training scheme as the training scheme of the patient A; if similar patients cannot be matched, a new training scheme needs to be generated through a training scheme decision mechanism. All training schemes are fed back and screened through a scheme scoring mechanism, so that high-quality schemes are reserved, and poor-quality schemes are eliminated. In the process of rehabilitation training of a patient, information such as muscle acting force and acting time can be measured regularly through a muscle force measuring device, the measurement result is uploaded to a cloud knowledge base, and the rehabilitation training scheme is updated through a training scheme updating mechanism, so that the effectiveness of the training scheme of the patient in different rehabilitation stages is guaranteed.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (12)
1. An active rehabilitation training method based on a muscle force measuring device is characterized in that: the method comprises the following specific steps:
testing by using the muscle strength measuring device to obtain a test result of the patient, transmitting the test result to the intermediate processing module, and matching the patient information with the training scheme model in the cloud knowledge base by using the intermediate processing module;
if the similar patients are matched, calling the training scheme models of the similar patients as training schemes, and if the similar patients cannot be matched, generating new training scheme models through a training scheme decision mechanism;
storing the obtained new training scheme model into a training scheme set in a cloud knowledge base;
the cloud knowledge base comprises a training scheme set, the training scheme set comprises a plurality of training scheme models, the training scheme models comprise a large number of existing rehabilitation training schemes in the early stage and rehabilitation training schemes newly generated by the cloud knowledge base, and meanwhile, the training scheme models also comprise descriptions of corresponding patient attributes and descriptions of rehabilitation equipment information, so that matching or decision making can be conveniently carried out according to the attributes of new patients;
the method of the scheme decision mechanism comprises the following steps: sequentially splitting the attributes of the patient into a plurality of characteristics by using an intermediate processing module, searching for similar characteristics, obtaining corresponding training steps and parameters, and screening and fusing based on rules to obtain a new training scheme;
the attributes are patient information, the patient information comprises basic information and mechanical information, the basic information comprises the sex, age, occupation, course of disease and basic data of main causes of disability of a patient, and the mechanical information comprises muscle acting force, acting time, an acting force-time curve and the maximum value of the acting force;
the method for screening and fusing based on the rule comprises the following steps: based on MapReduce algorithm, a plurality of existing patient training schemes with similar characteristics can be obtained according to the characteristics of the patients, different weights are distributed to the characteristics of the patients, after each characteristic value is multiplied by the weight, the rehabilitation training schemes of a plurality of existing patients most similar to the patients are obtained, the rehabilitation training schemes of the existing patients are decomposed into minimum training steps, and the minimum training steps are carried out again for tissue fusion.
2. The active rehabilitation training method based on muscle force measuring device according to claim 1, wherein: the patient information comprises basic information and mechanical information, wherein the basic information comprises the sex, age, occupation, course of disease and basic data of main causes of disability of a patient; the mechanical information is the patient muscle strength, action time information and a correspondingly generated muscle strength-time curve obtained by pre-testing the patient by applying the muscle strength measuring device.
3. The active rehabilitation training method based on muscle force measuring device according to claim 1, wherein: the method for searching for similar features is to search for similar features in a cloud knowledge base based on a MapReduce algorithm.
4. The active rehabilitation training method based on muscle force measuring device according to claim 1, wherein: the muscle strength measuring device comprises a supporting device, a pressure air bag, a mechanical sensor, an intermediate processing module and a display screen, wherein the pressure air bag is arranged on the supporting device, the mechanical sensor is arranged on the supporting device and corresponds to the pressure air bag, the intermediate processing module is connected with the mechanical sensor through a lead, and the intermediate processing module is connected with the display screen.
5. The active rehabilitation training method based on muscle force measuring device of claim 4, wherein: the method for obtaining the mechanical information of the patient by the intermediate processing module comprises the following steps: the mechanical sensor transmits the muscle acting force and the muscle acting time to the intermediate processing module, and the intermediate processing module analyzes and processes the mechanical information to obtain test data and generate an acting force-time curve.
6. The active rehabilitation training method based on muscle force measuring device of claim 4, wherein: the supporting device comprises a transverse foot plate, a vertical foot plate, a knee cover plate, a telescopic connecting rod and a binding band, the transverse foot plate is perpendicular to the vertical foot plate and is connected with the knee plate through the connecting rod, the transverse foot plate is connected with the knee plate through the telescopic connecting rod, the transverse foot plate is parallel to the knee plate, the vertical foot plate and the knee plate are respectively connected with the binding band, and the binding band surrounds the upper surface of the vertical foot plate and the upper surface of the knee cover plate to form an arc-shaped binding band.
7. The active rehabilitation training method based on muscle force measuring device of claim 4, wherein: the four pressure sensors are respectively a first pressure sensor, a second pressure sensor, a third pressure sensor and a fourth pressure sensor, the first pressure sensor and the second pressure sensor are respectively arranged at one end, close to the vertical foot plate and the knee cover plate, of the inner portion of the arc-shaped binding band, and the third pressure sensor and the fourth pressure sensor are respectively arranged on the upper surface, opposite to the arc-shaped binding band, of the vertical foot plate and the knee cover plate.
8. The active rehabilitation training method based on muscle force measuring device of claim 4, wherein: the surface of the pressure air bag is provided with a plurality of bulges.
9. The active rehabilitation training method based on muscle force measuring device of claim 4, wherein: the telescopic connecting rod comprises three connecting pipes, the pipe diameters are different, the telescopic connecting rods are sequentially sleeved, and a locking structure is arranged on the telescopic connecting rod.
10. The active rehabilitation training method based on muscle force measuring device according to claim 1, wherein: the cloud knowledge base is a column type storage database HBase based on a Hadoop platform.
11. The active rehabilitation training method based on muscle force measuring device according to claim 1, wherein: and the scheme decision mechanism carries out algorithm design based on a MapReduce programming framework.
12. The active rehabilitation training method based on muscle force measuring device according to claim 1, wherein: and the training scheme model in the cloud knowledge base is fed back and screened through a scheme scoring mechanism.
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