CN107080672B - A kind of rehabilitation ectoskeleton training mode control system and method - Google Patents
A kind of rehabilitation ectoskeleton training mode control system and method Download PDFInfo
- Publication number
- CN107080672B CN107080672B CN201710203825.7A CN201710203825A CN107080672B CN 107080672 B CN107080672 B CN 107080672B CN 201710203825 A CN201710203825 A CN 201710203825A CN 107080672 B CN107080672 B CN 107080672B
- Authority
- CN
- China
- Prior art keywords
- training
- characteristic attribute
- training mode
- rehabilitation
- assessment
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
- A61H3/00—Appliances for aiding patients or disabled persons to walk about
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
- A61H1/00—Apparatus for passive exercising; Vibrating apparatus ; Chiropractic devices, e.g. body impacting devices, external devices for briefly extending or aligning unbroken bones
- A61H1/02—Stretching or bending or torsioning apparatus for exercising
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
- A61H2201/00—Characteristics of apparatus not provided for in the preceding codes
- A61H2201/50—Control means thereof
- A61H2201/5007—Control means thereof computer controlled
- A61H2201/501—Control means thereof computer controlled connected to external computer devices or networks
- A61H2201/5012—Control means thereof computer controlled connected to external computer devices or networks using the internet
Abstract
A kind of rehabilitation ectoskeleton training mode control system and method, system include rehabilitation ectoskeleton database, the host computer that can carry out quantity extension according to demand, pass through network connection between rehabilitation ectoskeleton database and host computer；Every host computer includes data reception module, training mode selecting module, training effect evaluation module, training mode adjustment module；The system is by 1 sets of data library, and communication network, one arrives more set host computers and forms with the matched rehabilitation exoskeleton device of every host computer, human-computer interaction, medical instruments and equipment.The rehabilitation ectoskeleton training mode that the system can be suitble to according to patient's own characteristic for its customization, and training effect can be assessed, the rehabilitation ectoskeleton training mode bad to training effect can be carried out adjustment and generate new rehabilitation ectoskeleton training mode；System is in addition to being capable of providing automation rehabilitation training, and also reserved man-machine interactive interface, doctor, patient freely control rehabilitation training.
Description
Technical field
The present invention relates to rehabilitation medical field more particularly to a kind of rehabilitation dermoskeletons shared based on network, database data
Bone training mode control system and method.
Background technique
The limbs of people are a compound and accurate dynamic systems, if impaired cause the dyskinesia of limbs will be direct
The quality of life of people is influenced, the rehabilitation of science plays very important work to the recovery and raising of extremity motor function in time
With.Rehabilitation ectoskeleton is ectoskeleton technology and the new opplication that rehabilitation medical combines, with computer technology, medical science of recovery therapy, machine
Device people learns and the fast development of the emerging science and technology such as microelectric technique, has carried forward vigorously the intelligence of rehabilitation medical facility, has given
Medical Robot's development brings new opportunities.
In recent years, many scientific research personnel both domestic and external had been developed that the rehabilitation ectoskeleton training system of various different styles,
Science training method abundant and training effect evaluation index can be provided for four limbs impaired subjects, patient is helped to carry out rehabilitation instruction
Practice, but rehabilitation ectoskeleton training system is single machine control at present, the related datas such as training mode can not all be shared；Training mode
Relatively single, selectable training mode is limited；It is less to the individual difference consideration for participating in rehabilitation training patient, it generally will not root
Training mode is customized according to patient characteristic for it；Not enough to effective experience accumulation in rehabilitation ectoskeleton training process, in training process
Effective training mode can not be recorded, for subsequent use.
Summary of the invention
Technology of the invention solves the problems, such as: having overcome the deficiencies of the prior art and provide a kind of based on network, database number
According to shared rehabilitation ectoskeleton training mode control system and method.
The technical solution of the invention is as follows: a kind of rehabilitation ectoskeleton training mode control system, including rehabilitation ectoskeleton
Database, the host computer that can carry out quantity extension according to demand are connected between rehabilitation ectoskeleton database and host computer by network
It connects；Every host computer includes data reception module, training mode selecting module, training effect evaluation module, training mode adjustment
Module；
In rehabilitation ectoskeleton database according to clinical information be stored in advance patient characteristic attribute, training mode characteristic attribute,
Assess the relationship map chain between characteristic attribute and three；
Data reception module on every host computer is received by human-computer interaction interface to be believed to the characteristic attribute of rehabilitation
Breath, and receive the newest assessment characteristic attribute information of the patient that Medical Instruments is sent；
Training mode selecting module will store in the received above- mentioned information of data reception module and rehabilitation ectoskeleton database
Information be compared, and then determine current optimal training mode characteristic attribute, and send out according to the training mode characteristic attribute
It send corresponding instruction to rehabilitation ectoskeleton training device, command adapted thereto is executed by rehabilitation ectoskeleton training device, patient is carried out often
Group training；The newest assessment characteristic attribute information initial value of the patient that the Medical Instruments is sent is commenting for the preceding patient of training
Estimate characteristic attribute information；
Medical Instruments acquires the assessment characteristic attribute information of patient and is sent to data reception module after every group of training；
Training effect evaluation module calculates evaluation parameter according to the assessment characteristic attribute information after every group of training, if evaluation
This group of rehabilitation training of parameter characterization is effective, then by the characteristic attribute information of the patient, training before assessment characteristic attribute information with
And the opening relationships in rehabilitation ectoskeleton database of corresponding training mode characteristic attribute maps chain；If invalid, start training mould
Formula adjusts module；
Training mode adjusts module according to the assessment characteristic attribute information adjusting training pattern feature attribute of patient, according to tune
Training mode characteristic attribute after whole sends control instruction to rehabilitation ectoskeleton training device and carries out one group of training.
Further, the human-computer interaction interface includes emergency stop function region and function selection control area；Institute
The function selection control area stated provides training mode characteristic attribute and manually adjusts interface and training mode selection interface, artificial
Adjustment interface is directly received by the data reception module in host computer by being manually entered after corresponding numerical value, training mode adjustment
Directly data send corresponding control instruction to module based on the received；In training mode selection interface, manually have in database
Training mode selected, corresponding control is directly sent according to the training mode of selection by training mode selecting module and is referred to
It enables.
Further, training mode selecting module determines the implementation of current optimal training mode characteristic attribute such as
Under:
(1) according to each characteristic attribute i and assessment feature category that exoskeleton rehabilitation medicinal empirical data is patient
Property j be arranged weighted value Pi、Pj, ∑iPi=1, ∑jPj=1；
For patient characteristic attribute, weighted value P is set31, for assessment characteristic attribute, weighted value P is set32, P31+P32=1, P32>
P31；
(2) according to the characteristic attribute value a of current training patientiAnd current newest assessment characteristic attribute value bj, it calculates
With canned data similarity { s in database1,s2…sm…sn}；
Wherein, Aim、BjmFor the corresponding characteristic attribute value of the m articles relationship map chain in database and assessment characteristic attribute
Value；
N is the relationship map chain quantity stored in database；
(3) best similarity x=min { s is found out1,s2……sn, the corresponding s of xmIt is most close with training patient's states
, according to smCorresponding training mode characteristic attribute value, the as patient are found most by relationship map chain in the database
Good training mode.
Further, training effect evaluation module judges that whether effective rehabilitation training implementation be as follows:
(1) according to the type of impairment of exoskeleton rehabilitation medicinal empirical data combination patient itself and damage rank, solution
Calculate goal-based assessment spy attribute value indicative obj；
(2) according to the assessment characteristic attribute information b after trainingjEvaluation parameter is resolved with goal-based assessment characteristic attribute value
(3) judge whether g falls into preset threshold range, if falling into, it is effective to characterize this group of rehabilitation training, otherwise without
Effect.
Further, the preset threshold range (0~5).
Further, goal-based assessment spy attribute value indicative objDetermination steps are as follows:
It (1.1) is that classification is built respectively with type of impairment and impairment scale according to exoskeleton rehabilitation medicinal empirical data
The change rate of each assessment characteristic attribute is found referring to table；
(1.2) according to the type of impairment of patient and damage rank, for each assessment characteristic attribute respectively in above-mentioned attribute
Change rate is referring to finding out corresponding attribute change rate set in table；
(1.3) it is directed to each assessment characteristic attribute, takes and finds out corresponding attribute change rate intersection of sets collection as the assessment
The change rate of characteristic attribute；
(14) it is directed to each assessment characteristic attribute, the assessment characteristic attribute value before training is added in step (1.3) and is obtained
Corresponding change rate to get arrive the assessment characteristic attribute goal-based assessment spy's attribute value indicative.
Further, training mode adjustment module utilizes following formula adjusting training pattern feature attribute values:
h'i=hi+∑j(b'j-bj)×kij×Pj
Wherein, hiFor training mode characteristic attribute value,
hi' it is training mode characteristic attribute value after adjustment,
bj' to assess characteristic ginseng value after training,
PjFor assess characteristic attribute j weighted value,
kijFor the empirical coefficient of training mode characteristic attribute regulation and assessment characteristic attribute change rate relationship.
A kind of rehabilitation ectoskeleton training mode control method, steps are as follows:
(1) patient characteristic attribute, training mode are stored in advance according to clinical information in rehabilitation ectoskeleton database in advance
Relationship map chain between characteristic attribute, assessment characteristic attribute and three；
(2) it will be attached between rehabilitation ectoskeleton database and more host computers by network, the quantity root of host computer
It is arranged according to actual demand；Every host computer for participating in training executes every group of training as steps described below:
(2.1) the externally input characteristic attribute information to rehabilitation is received；
(2.2) by it is received to the characteristic attribute information of rehabilitation, the newest assessment characteristic attribute information of the patient with
The information stored in rehabilitation ectoskeleton database is compared, and then determines current optimal training mode characteristic attribute, and root
Corresponding instruction is sent to rehabilitation ectoskeleton training device according to the training mode characteristic attribute, is held by rehabilitation ectoskeleton training device
The training that row command adapted thereto currently organizes patient；The newest assessment characteristic attribute information starts in first group of training
The preceding assessment characteristic attribute information for patient before training, every later group of assessment for being trained for the patient acquired after previous group training are special
Levy attribute information；
(2.3) after current group training, the assessment characteristic attribute information of patient is acquired by Medical Instruments；
(2.4) evaluation parameter is calculated according to the assessment characteristic attribute information after training, if evaluation parameter characterizes this group of health
Refreshment is practiced effectively, then (2.5) is gone to step, if in vain, going to step (2.6)；
(2.5) by the characteristic attribute information of the patient, training before assessment characteristic attribute information and corresponding trained mould
The opening relationships in rehabilitation ectoskeleton database of formula characteristic attribute maps chain, goes to step (2.2) and carries out next group of training；
(2.6) according to the assessment characteristic attribute information adjusting training pattern feature attribute of patient, according to training adjusted
After pattern feature attribute sends control instruction to rehabilitation ectoskeleton training device one group of training of progress, (2.3) are gone to step.
Further, the human-computer interaction interface includes emergency stop function region and function selection control area；Institute
The function selection control area stated provides training mode characteristic attribute and manually adjusts interface and training mode selection interface, artificial
By being manually entered after corresponding numerical value, directly by host computer, data send corresponding control instruction to rehabilitation based on the received at adjustment interface
Ectoskeleton training device is transferred to step (2.3) and starts to execute；In training mode selection interface, manually to existing in database
Training mode is selected, and directly sends corresponding control instruction to rehabilitation ectoskeleton according to the training mode of selection by host computer
Training device is transferred to step (2.3) and starts to execute.
The present invention has the beneficial effect that compared with prior art
Present system/method is based on network and database technology, can generate to the rehabilitation exoskeleton system for being connected into network
Training mode and related data be collected, and store in the database, realize the training mode experience accumulation of rehabilitation ectoskeleton,
Database data is shared into each rehabilitation exoskeleton system on network simultaneously and searches calling for it.With rehabilitation in database
Ectoskeleton training mode and its related data are continuously increased abundant, and finer, accurate rehabilitation ectoskeleton instruction will be provided for patient
Practice mode.
The invention proposes a kind of rehabilitation ectoskeleton training mode control system and methods.The system is led to by 1 sets of data library
Communication network, one to more set host computers and with the matched rehabilitation exoskeleton device of every host computer, human-computer interaction, medical instruments and equipment
Composition.The rehabilitation ectoskeleton training mode that the system can be suitble to according to patient's own characteristic for its customization, and training can be imitated
Fruit assessment, the rehabilitation ectoskeleton training mode bad to training effect can be carried out adjustment and generate new rehabilitation ectoskeleton training mould
Formula；System is in addition to being capable of providing automation rehabilitation training, and also reserved man-machine interactive interface, doctor, patient freely control health
Refreshment is practiced.
Detailed description of the invention
Fig. 1 is system structure of the invention figure；
Fig. 2 is that training mode of the present invention selects flow chart；
Fig. 3 is training mode recruitment evaluation flow chart of the present invention；
Fig. 4 is that training mode of the present invention adjusts flow chart；
Fig. 5 is relationship map chain figure of the present invention.
Specific embodiment
With reference to the accompanying drawing and example elaborates to the present invention.
System proposed in this paper is as shown in Figure 1, including rehabilitation ectoskeleton database, can carrying out quantity extension according to demand
Host computer passes through network connection (such as local area network or internet etc.) between rehabilitation ectoskeleton database and host computer；Every
Host computer includes data reception module, training mode selecting module, training effect evaluation module, training mode adjustment module.
Each part is described as follows below
(1) rehabilitation ectoskeleton database
It is the important component of rehabilitation ectoskeleton training mode control system, is a set of large buffer memory Database Systems,
It is rehabilitation ectoskeleton training mode sample space for storing rehabilitation exoskeleton system related data, is the various algorithms of host computer
It resolves and data support is provided, be the basis for realizing more set rehabilitation exoskeleton system data sharings on local area network.Rehabilitation ectoskeleton number
Patient characteristic attribute, training mode characteristic attribute, assessment characteristic attribute and three are stored in advance according to clinical information according in library
Between relationship map chain.
Following information is stored in database:
Patient characteristic attribute: be mainly used to describe patient body and psychological characteristics, such as may include: gender, the age,
Weight, rehabilitation limbs length, type of impairment, impairment scale, psychological condition；According to actual needs, in general, type of impairment,
Impairment scale is necessary feature, other are optional feature, and other feature can also be added as needed.
Training mode characteristic attribute: it is mainly used to description rehabilitation ectoskeleton training motion feature within the set time, mainly
Including motion profile, speed, bend and stretch angle, traction dynamics and training time.
Assessment characteristic attribute: be mainly used to describe patient body functioning characteristics, characteristic attribute include muscle activity, heart rate and
Oxygen demand.
Relationship map chain, as shown in Figure 5:
It builds patient characteristic attribute list respectively in the database, assesses characteristic attribute table, training mode characteristic attribute table and pass
System's mapping chained list.
Patient characteristic attribute list stores patient characteristic attribute value and Major key a_pk
Assess characteristic attribute table storage assessment characteristic attribute value and Major key b_pk
Training mode characteristic attribute table deposits training mode characteristic attribute value and Major key h_pk
Relationship map storage of linked list a_pk, b_pk, h_pk and Major key rc_pk establish patient by relationship map chained list
Mapping relations between characteristic attribute, assessment characteristic attribute and training mode characteristic attribute.
(2) Medical Instruments
Medical Instruments is used to measure heart rate, oxygen demand and muscle activity of the patient before rehabilitation training and in training process,
Data measured is sent to host computer by host computer demand.Using current existing equipment.
(3) host computer
Data reception module on host computer receives the characteristic attribute information to rehabilitation by human-computer interaction interface, with
And receive the newest assessment characteristic attribute information of the patient that Medical Instruments is sent；
(a) training mode selecting module
Training mode selecting module will store in the received above- mentioned information of data reception module and rehabilitation ectoskeleton database
Information be compared, and then determine current optimal training mode characteristic attribute, and send out according to the training mode characteristic attribute
It send corresponding instruction to rehabilitation ectoskeleton training device, command adapted thereto is executed by rehabilitation ectoskeleton training device, patient is carried out often
Group training；The newest assessment characteristic attribute information initial value of the patient that the Medical Instruments is sent is commenting for the preceding patient of training
Estimate characteristic attribute information；
Such as Fig. 2, training mode selects flow chart, specifically includes the following steps: obtaining from Medical Instruments, patient is newest to be commented
Estimate characteristic attribute value A, patient characteristic attribute value is obtained from human-computer interaction, patient evaluation characteristic attribute value A and patient characteristic category
Property enter ginseng of the value as attribute value weighted registration selection algorithm, optimum training mode is calculated from database, according to best instruction
Practice mode and obtain training mode characteristic value, is sent to control driver control rehabilitation ectoskeleton and does training.
According to each characteristic attribute that exoskeleton rehabilitation medicinal empirical data is patient, weighted value P is set11, P12,
P13,P14,P15,P16,P17Respectively correspond gender, age, weight, rehabilitation limbs length, limbs type, type of impairment, damage etc.
Grade, psychological condition, P11+P12+P13+P14+P15+P16+P17=1
According to each characteristic attribute that exoskeleton rehabilitation medicinal empirical data is assessment, weighted value P is set21, P22,P23
Respectively correspond muscle activity, heart rate, oxygen demand, P21+P22+P23=1
P31For patient characteristic attribute, weighted value, P are set32For assessment characteristic attribute, weighted value, P are set31+P32=1
Characteristic attribute value (a of training patient1,a2,a3,a4,a5,a6,a7),
The assessment characteristic attribute value (b of training patient1,b2,b3),
Relationship map chained list is traversed, by the a_pk and b_pk stored in relationship map chained list, in patient characteristic attribute list
It is extracted respectively with assessment characteristic attribute table, patient characteristic attribute value sequence:
{(a11,a12,a13,a14,a15,a16,a17),(a21,a22,a23,a24,a25,a26,a27)……(an1,an2,an3,an4,
an5,an6,an7)}；
With assessment characteristic attribute value sequence:
{(b11,b12,b13),(b21,b22,b23)……(bn1,bn2,bn3)},
Find out best similarity x=min { s1,s2……sn, the corresponding s of xiIt is and trains patient's states most similar,
According to siCorresponding rc can be foundi(Major key { rc in relationship map chained list1,rc2......rcnAnd similarity comparison value { s1,
s2,…….snBe one-to-one relationship), pass through rciThe corresponding value of h_kp is found in relationship map chained list, passes through h_kp value
Corresponding training mode characteristic attribute value, as the optimum training mode of the patient are found in training mode characteristic attribute table.
(b) training effect evaluation module
Evaluation parameter is calculated according to the assessment characteristic attribute information after every group of training, if evaluation parameter characterizes this group of rehabilitation
Training is effective, then by the assessment characteristic attribute information and corresponding training mode before the characteristic attribute information of the patient, training
Characteristic attribute opening relationships in rehabilitation ectoskeleton database maps chain；If invalid, starting training mode adjusts module；
It is specific to be realized as shown in figure 3, being referred under type such as:
(1) according to the type of impairment of exoskeleton rehabilitation medicinal empirical data combination patient itself and damage rank, solution
Calculate goal-based assessment spy attribute value indicative obj；Target signature attribute: it is mainly used to describe patient by one group of rehabilitation ectoskeleton training
The expected functioning characteristics of body afterwards, characteristic attribute includes muscle activity, heart rate and oxygen demand.
It is that muscle is established in classification respectively with type of impairment and impairment scale according to exoskeleton rehabilitation medicinal empirical data
Activity profile change rate is referring to table
Heart rate attribute change rate is referring to table
Oxygen demand attribute change rate is referring to table
Muscle activity goal-based assessment value solves:
1 according to the type of impairment a5 of patient in evaluation attribute change rate referring to finding corresponding muscle activity change rate in table
Set Di={ di1...dij…din}；
2 according to the damage rank a6 of patient in evaluation attribute change rate referring to finding corresponding muscle activity change rate in table
Set Dj={ d1...dij…dmj}；
3 muscle activity attribute change rate D=Di∩Dj={ dij}；
4 muscle activity goal-based assessment value ob1=b1+dij。
b1For the muscle activity value of patient before training.
Heart rate goal assessed value solves:
1 according to the type of impairment a5 of patient in evaluation attribute change rate referring to finding corresponding change rate of heartbeat set in table
Ei={ ei1…eij…ein}；
2 according to the damage rank a6 of patient in evaluation attribute change rate referring to finding corresponding change rate of heartbeat set in table
Ej={ e1j…eij…emj}；
3 heart rate attribute change rate E=Ej∩Ej={ eij}；
4 heart rate goal assessed value ob2=b2+eij。
b2For the heart rate of patient before training.
Oxygen demand goal-based assessment value solves:
1 according to the type of impairment a5 of patient in evaluation attribute change rate referring to finding corresponding oxygen demand change rate collection in table
Close Fi={ fi1…fij…fin}；
2 according to the damage rank a6 of patient in evaluation attribute change rate referring to finding corresponding oxygen demand change rate collection in table
Close Fj={ f1j…fij…fmj}；
3 oxygen demand attribute change rate F=Fi∩Fj={ fij}；
4 oxygen demand goal-based assessment value ob3=b3+fij。
b3For the oxygen demand of patient before training.
Calculate goal-based assessment spy attribute value indicative OB={ ob1,ob2,ob3}。
(2) according to the assessment characteristic attribute information b after trainingjEvaluation parameter is resolved with goal-based assessment characteristic attribute value
(3) judge whether g falls into preset threshold range (value within the scope of general recommendations 0-5), if falling into, characterize this
Group rehabilitation training is effective, otherwise in vain.
(c) training mode adjusts module
Training mode adjusts module according to the assessment characteristic attribute information adjusting training pattern feature attribute of patient, according to tune
Training mode characteristic attribute after whole sends control instruction to rehabilitation ectoskeleton training device and carries out one group of training.
As shown in figure 4, for example, training mode characteristic attribute tune can be established according to exoskeleton rehabilitation medicinal empirical data
Empirical coefficient table between whole rate and assessment characteristic attribute change rate:
Assessment characteristic attribute value (b before training patient motion1,b2,b3)
b1,b2,b3Muscle activity value, heart rate value, oxygen consumption magnitude respectively before training
Assessment characteristic attribute value (b after training patient motion1',b2',b3')
b1',b2',b3' it is respectively muscle activity after training, heart rate, oxygen demand
Training mode characteristic attribute value (h1,h2,h3,h4,h5)
h1,h2,h3,h4,h5Preceding motion profile, speed are adjusted for training mode, bend and stretch angle, traction dynamics and training time
Training mode characteristic attribute value (h after adjustment1',h2',h3',h4',h5')
h1',h2',h3',h4',h5' for training mode adjustment after motion profile, speed, bend and stretch angle, traction dynamics and instruction
Practice the time
According to each characteristic attribute that exoskeleton rehabilitation medicinal empirical data is assessment, weighted value P is set21, P22, P23
Respectively correspond muscle activity, heart rate, oxygen demand, P21+P22+P23=1
P31For patient characteristic attribute, weighted value, P are set32For assessment characteristic attribute, weighted value, P are set31+P32=1
Motion profile solves after adjustment:
h1'=h1+(b1'-b1)×k11×P21+(b2'-b2)×k12×P22+(b3'-b3)×k13×P23
Speed solves after adjustment:
h2'=h2+(b1'-b1)×k21×P21+(b2'-b2)×k22×P22+(b3'-b3)×k23×P23
Angle solution is bent and stretched after adjustment:
h3'=h3+(b1'-b1)×k31×P21+(b2'-b2)×k32×P22+(b3'-b3)×k33×P23
Traction dynamics are adjusted to solve:
h4'=h4+(b1'-b1)×k41×P21+(b2'-b2)×k42×P22+(b3'-b3)×k43×P23
The adjusting training time solves:
h5'=h5+(b1'-b1)×k51×P21+(b2'-b2)×k52×P22+(b3'-b3)×k53×P23
hiFor training mode characteristic attribute value,
hi' it is training mode characteristic attribute value after adjustment,
bj' it is to assess characteristic ginseng value after training
kijFor the empirical coefficient of training mode characteristic attribute regulation and assessment characteristic attribute change rate relationship
h'i=hi+∑j(b'j-bj)×kij×Pj
(4) rehabilitation ectoskeleton training device
Rehabilitation ectoskeleton training device can be using existing convalescence device currently on the market, can also be using institute in Fig. 1
The example given carries out rehabilitation training.
As shown in Figure 1, device includes ectoskeleton skeleton, joint motor, control driver, sensor (position sensor, angle
Spend sensor, pickoff)；
Ectoskeleton skeleton: immobilized patients upper limb/lower limb follows motor to move by control strategy.
Joint motor: providing joint mechanical power source, drives ectoskeleton skeleton motion.
Control driver: the control instruction transmitted according to host computer forms motor work order, and driving motor presses pre- cover half
Formula movement.
Sensor: monitoring ectoskeleton motion process simultaneously gives data feedback to control driver.Angular transducer measures dermoskeleton
The angle of bone joint motions；Position sensor measures ectoskeleton movement position；Pickoff measures patient's upper limb/lower limb flesh
Meat pressure state.
(5) human-computer interaction interface
Human-computer interaction interface can carry out Function Extension according to actual needs, include in this example emergency stop function region and
Function selects control area；Emergency stop function region provides the means of emergent management for patient or doctor, for example, by using behaviour
The mode of vertical pole or button carries out emergency stop to training in progress.
The function selection control area provides training mode characteristic attribute and manually adjusts interface and training mode selection
Interface is manually adjusting interface by directly being received by the data reception module in host computer after corresponding numerical value is manually entered,
Training mode adjusts module, and directly data send corresponding control instruction based on the received；It is artificial right in training mode selection interface
Existing training mode is selected in database, directly sends phase according to the training mode of selection by training mode selecting module
The control instruction answered.
The present invention also provides a kind of rehabilitation ectoskeleton training mode control methods, and steps are as follows:
(1) patient characteristic attribute, training mode are stored in advance according to clinical information in rehabilitation ectoskeleton database in advance
Relationship map chain between characteristic attribute, assessment characteristic attribute and three；
(2) it will be attached between rehabilitation ectoskeleton database and more host computers by network, the quantity root of host computer
It is arranged according to actual demand；Every host computer for participating in training executes every group of training as steps described below:
(2.1) the externally input characteristic attribute information to rehabilitation is received；
(2.2) by it is received to the characteristic attribute information of rehabilitation, the newest assessment characteristic attribute information of the patient with
The information stored in rehabilitation ectoskeleton database is compared, and then determines current optimal training mode characteristic attribute, and root
Corresponding instruction is sent to rehabilitation ectoskeleton training device according to the training mode characteristic attribute, is held by rehabilitation ectoskeleton training device
The training that row command adapted thereto currently organizes patient；The newest assessment characteristic attribute information starts in first group of training
The preceding assessment characteristic attribute information for patient before training, every later group of assessment for being trained for the patient acquired after previous group training are special
Levy attribute information；
(2.3) after current group training, the assessment characteristic attribute information of patient is acquired by Medical Instruments；
(2.4) evaluation parameter is calculated according to the assessment characteristic attribute information after training, if evaluation parameter characterizes this group of health
Refreshment is practiced effectively, then (2.5) is gone to step, if in vain, going to step (2.6)；
(2.5) by the characteristic attribute information of the patient, training before assessment characteristic attribute information and corresponding trained mould
The opening relationships in rehabilitation ectoskeleton database of formula characteristic attribute maps chain, goes to step (2.2) and carries out next group of training；
(2.6) according to the assessment characteristic attribute information adjusting training pattern feature attribute of patient, according to training adjusted
After pattern feature attribute sends control instruction to rehabilitation ectoskeleton training device one group of training of progress, (2.3) are gone to step.
The human-computer interaction interface includes emergency stop function region and function selection control area；The function choosing
Select control area provide training mode characteristic attribute manually adjust interface and training mode selection interface, manually adjust interface by
It is manually entered after corresponding numerical value directly that data send corresponding control instruction to the training of rehabilitation ectoskeleton based on the received by host computer
Device is transferred to step (2.3) and starts to execute；In training mode selection interface, manually to training mode existing in database into
Row selection directly sends corresponding control instruction to rehabilitation ectoskeleton training device according to the training mode of selection by host computer,
Step (2.3) is transferred to start to execute.
The realization of specific steps can use identical processing mode with system in method, not repeated excessively herein.
Unspecified part of the present invention belongs to common sense well known to those skilled in the art.
Claims (6)
1. a kind of rehabilitation ectoskeleton training mode control system, it is characterised in that: including rehabilitation ectoskeleton database, can be according to need
The host computer for carrying out quantity extension is sought, passes through network connection between rehabilitation ectoskeleton database and host computer；Every host computer packet
Include data reception module, training mode selecting module, training effect evaluation module, training mode adjustment module；
Patient characteristic attribute, training mode characteristic attribute, assessment are stored in advance according to clinical information in rehabilitation ectoskeleton database
Relationship map chain between characteristic attribute and three；
Data reception module on every host computer receives the characteristic attribute information to rehabilitation by human-computer interaction interface, with
And receive the newest assessment characteristic attribute information of the patient that Medical Instruments is sent；
The letter that training mode selecting module will store in the received above- mentioned information of data reception module and rehabilitation ectoskeleton database
Breath is compared, and then determines current optimal training mode characteristic attribute, and send phase according to the training mode characteristic attribute
The instruction answered executes command adapted thereto by rehabilitation ectoskeleton training device and carries out every group of instruction to patient to rehabilitation ectoskeleton training device
Practice；The newest assessment characteristic attribute information initial value of the patient that the Medical Instruments is sent is the assessment spy of patient before training
Levy attribute information；
Medical Instruments acquires the assessment characteristic attribute information of patient and is sent to data reception module after every group of training；
Training effect evaluation module calculates evaluation parameter according to the assessment characteristic attribute information after every group of training, if evaluation parameter
Characterize that this group of rehabilitation training is effective, then by assessment characteristic attribute information before the characteristic attribute information of the patient, training and right
The training mode characteristic attribute answered opening relationships in rehabilitation ectoskeleton database maps chain；If invalid, start training mode tune
Mould preparation block；
Training mode adjusts module according to the assessment characteristic attribute information adjusting training pattern feature attribute of patient, after adjustment
Training mode characteristic attribute send control instruction to rehabilitation ectoskeleton training device carry out one group of training；
The training mode selecting module determines that the implementation of current optimal training mode characteristic attribute is as follows:
(1) it is set according to each characteristic attribute i and assessment characteristic attribute j that exoskeleton rehabilitation medicinal empirical data is patient
Set weighted value Pi、Pj,,；
For patient characteristic attribute, weighted value P is set31, for assessment characteristic attribute, weighted value P is set32, P31+P32=1, P32> P31；
(2) according to the characteristic attribute value a of current training patientiAnd current newest assessment characteristic attribute value bj, calculate and data
Canned data similarity { s in library1,s2…sm…sn}；
Wherein, Aim、BjmFor the characteristic attribute value of the corresponding patient of the m articles relationship map chain in database and assessment characteristic attribute
Value；
N is the relationship map chain quantity stored in database；
(3) best similarity x=min { s is found out1,s2……sn, the corresponding s of xmIt is, root most similar with training patient's states
According to smCorresponding training mode characteristic attribute value, the as optimum training of the patient are found by relationship map chain in the database
Mode.
2. system according to claim 1, it is characterised in that: the human-computer interaction interface includes emergency stop function region
Control area is selected with function；The function selection control area provides training mode characteristic attribute and manually adjusts interface and instruction
Practice model selection interface, manually adjust interface by after corresponding numerical value is manually entered directly by the data reception module in host computer
It is received, training mode adjusts module, and directly data send corresponding control instruction based on the received；Boundary is selected in training mode
Face manually selects training mode existing in database, by training mode selecting module directly according to the training of selection
Mode sends corresponding control instruction.
3. system according to claim 1, it is characterised in that: training effect evaluation module judges whether rehabilitation training is effective
Implementation is as follows:
(1) it according to the type of impairment of exoskeleton rehabilitation medicinal empirical data combination patient itself and damage rank, calculates
Goal-based assessment attributive character value obj；
(2) according to the assessment characteristic attribute information b after trainingjWith goal-based assessment attributive character value objResolve evaluation parameter；
(3) judge whether g falls into preset threshold range, if falling into, it is effective to characterize this group of rehabilitation training, otherwise in vain.
4. system according to claim 3, it is characterised in that: the preset threshold range is (0 ~ 5).
5. system according to claim 3, it is characterised in that: goal-based assessment attributive character value objDetermination steps are as follows:
It (1.1) is that classification is established often respectively with type of impairment and impairment scale according to exoskeleton rehabilitation medicinal empirical data
The change rate of a assessment characteristic attribute is referring to table；
(1.2) according to the type of impairment of patient and damage rank, become respectively in above-mentioned attribute for each assessment characteristic attribute
Rate is referring to finding out corresponding attribute change rate set in table；
(1.3) it is directed to each assessment characteristic attribute, removes to find out corresponding attribute change rate intersection of sets collection as the assessment feature
The change rate of attribute；
(1.4) it is directed to each assessment characteristic attribute, by the assessment characteristic attribute value before training plus right obtained in step (1.3)
The change rate answered is to get the goal-based assessment attributive character value for arriving the assessment characteristic attribute.
6. system according to claim 1, it is characterised in that: training mode adjusts module and utilizes following formula adjusting trainings
Pattern feature attribute value:
Wherein, hiFor training mode characteristic attribute value,
hi' it is training mode characteristic attribute value after adjustment,
bj' to assess characteristic ginseng value after training,
PjFor assess characteristic attribute j weighted value,
kijFor the empirical coefficient of training mode characteristic attribute regulation and assessment characteristic attribute change rate relationship.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710203825.7A CN107080672B (en) | 2017-03-30 | 2017-03-30 | A kind of rehabilitation ectoskeleton training mode control system and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710203825.7A CN107080672B (en) | 2017-03-30 | 2017-03-30 | A kind of rehabilitation ectoskeleton training mode control system and method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107080672A CN107080672A (en) | 2017-08-22 |
| CN107080672B true CN107080672B (en) | 2019-10-22 |
Family
ID=59614307
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710203825.7A Active CN107080672B (en) | 2017-03-30 | 2017-03-30 | A kind of rehabilitation ectoskeleton training mode control system and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107080672B (en) |
Families Citing this family (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108154913A (en) * | 2017-12-29 | 2018-06-12 | 北京精密机电控制设备研究所 | A kind of rehabilitation training parameter determination method, device, electronic equipment and system |
| CN108654060B (en) * | 2018-05-11 | 2020-06-12 | 北京爱康宜诚医疗器材有限公司 | Method and device for determining rehabilitation training time |
| CN109157376A (en) * | 2018-08-08 | 2019-01-08 | 郑州大学 | A kind of horizontal lower limb rehabilitation robot in the ward ICU of shrinkable movement |
| CN109009873A (en) * | 2018-08-16 | 2018-12-18 | 常州市钱璟康复股份有限公司 | The recovery training method and its rehabilitation training system of upper-limbs rehabilitation training robot |
| CN111249106B (en) * | 2020-01-16 | 2022-01-28 | 江苏经贸职业技术学院 | Training control device and system of old people rehabilitation robot |
| CN113018091A (en) * | 2021-02-22 | 2021-06-25 | 中国科学院深圳先进技术研究院 | Exoskeleton rehabilitation robot sharing control system and method |
| CN113180993A (en) * | 2021-03-12 | 2021-07-30 | 上海健康医学院 | Exoskeleton hand rehabilitation training system based on force feedback, storage medium and terminal |
| CN114949777A (en) * | 2022-06-28 | 2022-08-30 | 北京欧应科技有限公司 | Knee joint postoperative rehabilitation system |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140272891A1 (en) * | 2013-03-15 | 2014-09-18 | Joseph Saladino | System and method for remote fitness training |
| US20150072327A1 (en) * | 2013-09-12 | 2015-03-12 | STRETCHING CHARTS, INC. dba VHI | Web site for use by physicians for treating patients with musculoskeletal conditions |
| CN104794668A (en) * | 2015-05-05 | 2015-07-22 | 成都沃瑞特医疗设备有限公司 | Quality control method of rehabilitation assessment therapy system |
| CN205359906U (en) * | 2016-02-03 | 2016-07-06 | 苏州经贸职业技术学院 | Intelligence recovered system that helps disabled |
| CN106109176A (en) * | 2016-07-18 | 2016-11-16 | 张力心 | A kind of based on cloud platform intelligent rehabilitation robot system and operational approach thereof |
| CN106491309B (en) * | 2016-11-17 | 2019-03-26 | 合肥工业大学 | A kind of limb rehabilitation training system |
-
2017
- 2017-03-30 CN CN201710203825.7A patent/CN107080672B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN107080672A (en) | 2017-08-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107080672B (en) | A kind of rehabilitation ectoskeleton training mode control system and method | |
| US11763697B2 (en) | User interface system for movement skill analysis and skill augmentation | |
| CN110322947B (en) | Hypertension elderly exercise prescription recommendation method based on deep learning | |
| US11679300B2 (en) | Systems and methods for real-time data quantification, acquisition, analysis, and feedback | |
| CN110070944A (en) | Training system is assessed based on virtual environment and the social function of virtual role | |
| US20170035313A1 (en) | Movement pattern measuring apparatus using eeg and emg and method thereof | |
| CN109637625B (en) | Self-learning fitness plan generation system | |
| CN108986884A (en) | The training system and method that a kind of balanced rehabilitation and cognitive rehabilitation blend | |
| US9826923B2 (en) | Motion analysis method | |
| US11747904B2 (en) | Electronic training system and method for electronic evaluation and feedback of sports performance | |
| CN113647939A (en) | Artificial intelligence rehabilitation evaluation and training system for spinal degenerative diseases | |
| JP2022507628A (en) | Feedback from neuromuscular activation in various types of virtual reality and / or augmented reality environments | |
| CN111345823A (en) | Remote exercise rehabilitation method and device and computer readable storage medium | |
| CN109599178A (en) | Threshold determination model determines method, apparatus, medical treatment detection device and storage medium | |
| CN108743222B (en) | Finger symmetry rehabilitation error correction method based on Leap Motion | |
| Schack | Mental representation in action: A cognitive architecture approach | |
| Bevilacqua et al. | Combining real-time segmentation and classification of rehabilitation exercises with LSTM networks and pointwise boosting | |
| CN113877157B (en) | Hand function rehabilitation system combining data glove and VR technology | |
| CN115394412A (en) | Comfort evaluation method for transfer nursing robot | |
| CN106773708A (en) | Multifunction nursing bed long-range control method and system | |
| CN117157622A (en) | Motion monitoring method and device | |
| CN109192315B (en) | Comprehensive age detection system based on weighted kernel regression and packaged deviation search | |
| CN111341435B (en) | User IoT (Internet of things) equipment for disease diagnosis | |
| CN110534199A (en) | A kind of psychosomatic training effect evaluation method | |
| Perl et al. | Sensors, monitoring, and model-based data analysis in sports, exercise and rehabilitation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |