CN108379038B - A kind of lower limb rehabilitation exoskeleton system and its walking control method - Google Patents
A kind of lower limb rehabilitation exoskeleton system and its walking control method Download PDFInfo
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- 210000003141 lower extremity Anatomy 0.000 title claims abstract description 53
- 238000000034 method Methods 0.000 title claims abstract description 48
- 230000005021 gait Effects 0.000 claims abstract description 101
- 230000005484 gravity Effects 0.000 claims abstract description 51
- 238000012546 transfer Methods 0.000 claims abstract description 32
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- 238000004590 computer program Methods 0.000 claims description 6
- 238000013480 data collection Methods 0.000 claims description 6
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- 238000007689 inspection Methods 0.000 claims 1
- 238000012549 training Methods 0.000 abstract description 16
- 210000002414 leg Anatomy 0.000 description 83
- 210000002683 foot Anatomy 0.000 description 45
- 210000001699 lower leg Anatomy 0.000 description 20
- 210000000689 upper leg Anatomy 0.000 description 11
- 210000000544 articulatio talocruralis Anatomy 0.000 description 6
- 210000000988 bone and bone Anatomy 0.000 description 6
- 244000309466 calf Species 0.000 description 5
- 210000004744 fore-foot Anatomy 0.000 description 5
- 210000001624 hip Anatomy 0.000 description 5
- 210000004394 hip joint Anatomy 0.000 description 5
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- 238000005259 measurement Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
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- 206010008190 Cerebrovascular accident Diseases 0.000 description 1
- 241001269238 Data Species 0.000 description 1
- 206010019468 Hemiplegia Diseases 0.000 description 1
- 238000011579 SCID mouse model Methods 0.000 description 1
- 208000006011 Stroke Diseases 0.000 description 1
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- 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
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- 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
- A61H2003/005—Appliances for aiding patients or disabled persons to walk about with knee, leg or stump rests
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- 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
- A61H2003/007—Appliances for aiding patients or disabled persons to walk about secured to the patient, e.g. with belts
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Abstract
The present invention relates to a kind of lower limb rehabilitation exoskeleton system and its walking control methods, belong to medical robot technical field.Walking control method includes Real time data acquisition step, gait phase identification step and ectoskeleton rate-determining steps；Ectoskeleton rate-determining steps include leading leg liftoff into the swing process that will be landed of leading leg in ectoskeleton, control its main supporting leg and keep generally upstanding state；And ectoskeleton be in lead leg liftoff gait phase when, and meet center of gravity transfer criterion after, control leading leg for ectoskeleton and carry out liftoff wobbling action；Center of gravity transfer criterion is that the upper body inclination angle of ectoskeleton wearer is in the first pre-set interval, and its plantar pressure is in the second pre-set interval.Based on the walking control method, lateral tilting moment can be effectively eliminated, so that it is guaranteed that the walking of ectoskeleton wearer is stablized, can be widely applied to weakness of the lower extremities or the rehabilitation training of hemiplegic patient.
Description
Technical field
The present invention relates to a kind of medical robot and its control methods, specifically, being related to a kind of lower limb rehabilitation ectoskeleton
System and its walking control method.
Background technique
Currently, China gradually steps into aging population society, and the elderly group is increasingly huge, quite a few the elderly
The principal disease that group faces is cerebral apoplexy；In addition, various accidents are also increasing to also result in the no small limb function barrier of quantity
Hinder patient.According to incompletely statistics, the number of above-mentioned patient is more than 8,000,000, in this huge PATIENT POPULATION, there is suitable one
The patient divided can be improved or be restored its motion function by rehabilitation training.
Common rehabilitation training completes rehabilitation instruction predominantly under the guidance of medical practitioner with the help of nurse or family members
Practice, this training method not only time and effort consuming, but also rehabilitation efficacy is largely dependent on the experience of doctor and nurse and family members,
Its caused rehabilitation efficacy hardly results in guarantee.
With the development of robot technology, more and more scientific research institutions start for robot technology to be applied to rehabilitation instruction
Practice, with the existing rehabilitation training technology that substituted expenses are high and effect is difficult to ensure.In alternative solution, ectoskeleton is mainly utilized
Healing robot assists patient to carry out rehabilitation training, can not only save labour cost, and can to the data in rehabilitation course into
Row is collected to make better rehabilitation training plans.
The walking control method of the ectoskeleton of common lower limb rehabilitation is equal are as follows: (1) gait information of normal person's walking is collected,
The content of the gait information mainly includes hip, SCID Mice angle；(2) control ectoskeleton drive patient follows the step of normal person
State curved path walking is to reaching rehabilitation efficacy.But in order to keep the counterbalance effect of ambulation training, generally use suspension-type dermoskeleton
Bone original place rehabilitation training, it is difficult to simulate reality scene, be unfavorable for exciting rehabilitation interest, enthusiasm or the rehabilitation of rehabilitation
Patient's both hands lean on crutch to keep balancing, and upper body arm strength deficiency or hemiplegic patient are not suitable for, to make this control
Method needs to face a very big problem in practical applications, i.e. hemiplegia, the lower limb muscles of weakness of the lower extremities patient are powerless, it is difficult to prop up
The lateral tilting moment occurred in its swing phase for balancing normal person's gait is supportted, is easy to cause and drives Rehabilitation step in ectoskeleton
The problem of occurring unstability during row, or even falling.
Summary of the invention
The main object of the present invention is to provide a kind of walking control method of lower limb rehabilitation exoskeleton system, to improve its step
The stability of row process；
It is a further object of the present invention to provide a kind of exoskeleton systems, to improve the stability in its gait processes.
In order to achieve the above-mentioned main objectives, walking control method provided by the invention includes Real time data acquisition step, step
State phase identification step and ectoskeleton rate-determining steps；Real time data acquisition step includes the real-time upper body for obtaining ectoskeleton wearer
Inclination data, plantar pressure data and joint of lower extremity angle-data；Gait phase identification step includes according to joint of lower extremity angle
Reference data identifies the current gait phase of ectoskeleton wearer based on the joint of lower extremity angle-data obtained in real time；Dermoskeleton
Bone rate-determining steps include leading leg liftoff into the swing process that will be landed of leading leg in ectoskeleton, control its main supporting leg
Keep generally upstanding state；And ectoskeleton be in lead leg liftoff gait phase when, and meet center of gravity transfer criterion after,
Leading leg for ectoskeleton of control carries out liftoff wobbling action；Center of gravity shifts the upper body inclination angle that criterion is ectoskeleton wearer and is in the
In one pre-set interval, and its plantar pressure is in the second pre-set interval.
After gait phase by identifying ectoskeleton wearer, lead leg from lead leg by it is liftoff to lead leg by
In the swing process on ground, controls its main supporting leg and keep generally upstanding state；And lead leg it is liftoff before, make upper body inclination angle and foot
Bottom pressure is maintained in predetermined interval, so that wearer's upper body, which tilts to its center of gravity towards main supporting leg side, is transferred to main support leg
On supporting surface, lateral tilting moment is effectively eliminated, and the main supporting leg generally remains uprightly, the most weight of human body can lead to
It crosses ectoskeleton supporting leg bar and is transmitted to ground, mitigate the burden of wearing patient support leg, so that it is guaranteed that the step of ectoskeleton wearer
Row is stablized, so that the patient of weakness of the lower extremities can also participate in corresponding rehabilitation training.
Specific scheme be ectoskeleton rate-determining steps include when ectoskeleton is in and leads leg the gait phase that will be landed, and
Satisfaction is landed in advance after criterion, control the joint action led leg of ectoskeleton to its it is submissive land, the criterion that lands in advance is outer
The plantar pressure of bone wearer is in third pre-set interval, and the submissive plantar pressure to land to lead leg in the process of landing is small
In the first preset value.Occur leading leg land in advance when, by controlling each joint action rate, by this lead leg
Plantar pressure during ground controls under predetermined value, if so that realization effectively avoids the problem that lands firmly along ground.
If more specific scheme is that rate-determining steps include that ectoskeleton is in when leading leg liftoff gait phase, and discontented
The lumping weight heart shifts criterion, then voice reminder ectoskeleton wearer adjusts upper body inclination angle.Pass through voice reminder ectoskeleton wearer
Its upper body inclination angle is adjusted, and is effectively prevented from its center of gravity and falls within except the supporting surface of main supporting leg and generate lateral tilting moment,
Effectively improve the stability of ectoskeleton wearer in the process of walking.
Preferred scheme be include the step of obtaining pre-set interval and joint of lower extremity angle reference data data collection steps,
Data processing step and data plan as a whole step；Data collection steps include that collecting sample crowd is simulating default center of gravity transfer gait
Walking step state data in the process, walking step state data include joint of lower extremity angle-data, upper body inclination data and foot force
Data；Default center of gravity transfer gait is the situation of change according to plantar pressure in the support phase and swing phase of a gait cycle,
Gait cycle is divided into eight gait phases, is led leg liftoff to this in aforementioned eight gait phases, and leading leg
On the gait phase for being included by the process to land, main supporting leg keeps generally upstanding；Data processing step includes walking to walking
State data are filtered, amplify, denoising and sliding-model control, obtain the gait number of independent sample different moments within a period
According to the gait data for gathering sample population constitutes gait data library；It includes planning as a whole gait in gait data library that data, which plan as a whole step,
Data obtain the corresponding plantar pressure value pre-set interval of joint of lower extremity angle value and upper body of different moments in a gait cycle
The joint of lower extremity angle-data of inclination value pre-set interval, a gait cycle different moments constitutes joint of lower extremity angle reference number
According to.
Preferred scheme is that Real time data acquisition step includes obtaining human-computer interaction force data, human-computer interaction force data by
The tension sensor output being built in thigh and calf bandage；Ectoskeleton rate-determining steps include dynamic in the joint of lower extremity for controlling ectoskeleton
During work, keep human-computer interaction power less than the second preset value.So that ectoskeleton wearer can be carried out interaction in gait processes
Power Shared control.
In order to achieve the above-mentioned another object, lower limb rehabilitation exoskeleton system provided by the invention includes control unit, to control
The detection unit of unit input detection signal processed and the ectoskeleton controlled by control unit；Detection unit includes plantar pressure detection
Device, upper body tilt angle detector and joint of lower extremity angle detector, control unit include processor and memory, memory storage
There is computer program, Real time data acquisition step, gait phase identification step are able to achieve when computer program is executed by processor
And ectoskeleton rate-determining steps；Real time data acquisition step includes the real-time plantar pressure number for obtaining the output of plantar pressure detector
According to the upper body inclination data of, upper body tilt angle detector output and the joint of lower extremity angle number of joint of lower extremity angle detector output
According to；Gait phase identification step includes according to joint of lower extremity angle reference data, based on the joint of lower extremity angle number obtained in real time
According to identifying the current gait phase of ectoskeleton wearer；Ectoskeleton rate-determining steps include will be liftoff in leading leg for ectoskeleton
Into the swing process that will be landed of leading leg, controls its main supporting leg and keep generally upstanding state；And it is in and swings in ectoskeleton
When leg is by liftoff gait phase, and meet center of gravity transfer criterion after, control leading leg for ectoskeleton and carry out liftoff wobbling action；
Center of gravity transfer criterion is that the upper body inclination angle of ectoskeleton wearer is in the first pre-set interval, and its plantar pressure is in second in advance
If in section.
After gait phase by identifying ectoskeleton wearer, lead leg from lead leg by it is liftoff to lead leg by
In the swing process on ground, controls its main supporting leg and keep generally upstanding state；And lead leg it is liftoff before, make upper body inclination angle and foot
Bottom pressure is maintained in predetermined interval, so that wearer's upper body, which tilts to its center of gravity towards main supporting leg side, is transferred to main support leg
On supporting surface, lateral tilting moment is effectively eliminated, and the main supporting leg generally remains uprightly, the most weight of human body can lead to
It crosses ectoskeleton supporting leg bar and is transmitted to ground, mitigate the burden of wearing patient support leg, so that it is guaranteed that the step of ectoskeleton wearer
Row is stablized, so that the patient of weakness of the lower extremities can also participate in corresponding rehabilitation training.
Specific scheme be ectoskeleton rate-determining steps include when ectoskeleton is in and leads leg the gait phase that will be landed, and
Satisfaction is landed in advance after criterion, control the joint action led leg of ectoskeleton to its it is submissive land, the criterion that lands in advance is outer
The plantar pressure of bone wearer is in third pre-set interval, and the submissive plantar pressure to land to lead leg in the process of landing is small
In the first preset value.Occur leading leg land in advance when, by controlling each joint action rate, by this lead leg
Plantar pressure during ground controls under predetermined value, if so that realization effectively avoids the problem that lands firmly along ground.
If more specific scheme is that rate-determining steps include that ectoskeleton is in when leading leg liftoff gait phase, and discontented
The lumping weight heart shifts criterion, then voice reminder ectoskeleton wearer adjusts upper body inclination angle.Pass through voice reminder ectoskeleton wearer
Its upper body inclination angle is adjusted, and is effectively prevented from its center of gravity and falls within except the supporting surface of main supporting leg and generate lateral tilting moment,
Effectively improve the stability of ectoskeleton wearer in the process of walking.
Preferred scheme be include the step of obtaining pre-set interval and joint of lower extremity angle reference data data collection steps,
Data processing step and data plan as a whole step；Data collection steps include that collecting sample crowd is simulating default center of gravity transfer gait
Walking step state data in the process, walking step state data include joint of lower extremity angle-data, upper body inclination data and foot force
Data；Default center of gravity transfer gait is the situation of change according to plantar pressure in the support phase and swing phase of a gait cycle,
Gait cycle is divided into eight gait phases, is led leg liftoff to this in aforementioned eight gait phases, and leading leg
On the gait phase for being included by the process to land, main supporting leg keeps generally upstanding；Data processing step includes walking to walking
State data are filtered, amplify, denoising and sliding-model control, obtain the gait number of independent sample different moments within a period
According to the gait data for gathering sample population constitutes gait data library；It includes planning as a whole gait in gait data library that data, which plan as a whole step,
Data obtain the corresponding plantar pressure value pre-set interval of joint of lower extremity angle value and upper body of different moments in a gait cycle
The joint of lower extremity angle-data of inclination value pre-set interval, a gait cycle different moments constitutes joint of lower extremity angle reference number
According to.
Preferred scheme is that Real time data acquisition step includes obtaining human-computer interaction force data, human-computer interaction force data by
The tension sensor output being built in thigh and calf bandage；Ectoskeleton rate-determining steps include dynamic in the joint of lower extremity for controlling ectoskeleton
During work, keep human-computer interaction power less than the second preset value.So that ectoskeleton wearer can be carried out interaction in gait processes
Power Shared control.
Detailed description of the invention
Fig. 1 is the structural schematic diagram for being worn on the exoskeleton system embodiment of the present invention with ectoskeleton wearer；
Fig. 2 is the position schematic diagram of the plantar pressure sensor in exoskeleton system embodiment of the present invention；
Fig. 3 is the electric control structure schematic diagram of exoskeleton system embodiment of the present invention
Fig. 4 is the process schematic of the default center of gravity transfer gait in exoskeleton system embodiment of the present invention；
Fig. 5 is the flow chart for constructing center of gravity transfer gait data library in this present invention exoskeleton system embodiment；
Fig. 6 is the flow chart of the walking control method of exoskeleton system embodiment of the present invention.
Specific embodiment
With reference to embodiments and its attached drawing the invention will be further described.
Exoskeleton system embodiment
Referring to Fig. 1 to Fig. 3, exoskeleton system 1 of the present invention includes control unit, inputs detection signal to the control unit
Detection unit and the ectoskeleton controlled by the control unit.
As shown in Figure 1, exoskeleton system includes the control knapsack 10 being worn on on ectoskeleton wearer, control back
Packet 10 includes backpack strip 100, Knapsack bag 101 and the supplying cell 103 and main control unit 102 being placed in Knapsack bag 101, master control
Unit 102 constitutes the control unit in the present embodiment, and main control unit 102 includes processor and memory, and supplying cell 103 is whole
The normal work of a exoskeleton system is powered.
As shown in Figures 1 and 2, ectoskeleton unit include waist worn unit 11, it is hip joint unit 12, thigh bar 14, big
Leg bandage 13, knee joint unit 15, shank bandage 16, shank bar 17, ankle-joint unit 18 and flexible vola unit 19.Waist is worn
Wearing unit 11 is used for the fixation of ectoskeleton and human body waist；Hip joint unit 12, knee joint unit 15 and ankle-joint unit 18 are equal
Including joint driver, joint driver joint motor and matched retarder, for accordingly driving the hip on ectoskeleton to close
Section, knee joint and ankle-joint rotate；Thigh bar 14 is for driving human thigh to move, and shank bar 17 is for driving human calf to transport
It is dynamic.Bandage is used for connection leg bar and leg, to fix ectoskeleton；Wherein, two leg thigh bandages 13 are tied up on every side thigh；It is flexible
Vola unit and human foot are dressed.
Detection unit includes the upper body tilt angle detector for detecting ectoskeleton wearer's upper body inclination angle, for detecting lower limb
The joint of lower extremity angle detector of joint angles is mounted on flexible vola unit 19 for detecting ectoskeleton wearer vola not
With the plantar pressure detector of pressure at position, and the sensor for measuring human-computer interaction power between people and ectoskeleton；These
Detector exports real time detection signal, including upper body dip angle signal, joint of lower extremity angle signal, vola pressure to main control unit 102
Force signal and human-computer interaction force signal.In the present embodiment, upper body tilt angle detector is on 1 be placed in control knapsack 10
Body obliquity sensor, in the present embodiment upper body obliquity sensor select gyroscope, for measure on ectoskeleton wearer in
Inclination data in human body sagittal plane and frontal plane；Joint of lower extremity angle detector is the joint angles being placed at corresponding joint
Sensor, for measuring the corner of the hip joint on ectoskeleton, knee joint, ankle-joint, totally 6；Human-computer interaction force sensor
S type pull pressure sensor is selected, for measuring the human-computer interaction power between people and ectoskeleton, i.e., for detecting thigh bar and thigh
Between or shank bar and shank internode interaction force situation of change, be placed in the thigh and calf bandage of ectoskeleton, totally 6；Vola
Pressure detector is the plantar pressure sensor being placed on flexible vola unit, the specific F l for selecting U.S. Tekscan company
ExiForce type pressure sensor, for measuring the pressure at the sole different location of left and right, as shown in Fig. 2, specifically detecting position
For 4 positions of heel and forefoot, tiptoe, i.e., each vola has 4, and totally 8.
As shown in figure 3, the collected detection signal of each detection sensor institute in detection unit 30 is defeated by capture card 31
Main control unit 102 is given, main control unit 102 drives each joint motor according to detection signal and preset program control driver 32
33 movements, joint motor drives the movement of ectoskeleton corresponding joint, so that ectoskeleton wearer be assisted to complete scheduled rehabilitation training
Movement.Following processing in real time is carried out to the 31 collected signal of institute of capture card:
(1) it is filtered: bandpass filtering is carried out to signal；
(2) enhanced processing；
(3) remove noise processed, the noise of removal include detect signal in flip-flop, skin friction high-frequency noise
And Hz noise, weighted average mode is specifically used, to increase signal-to-noise ratio, to reduce influence of the noise to detection signal；
(4) Data Discretization is handled.
Before stating exoskeleton system in use, center of gravity transfer gait data library, in the present embodiment, structure need to be first built out
The process for building center of gravity transfer gait data library includes the default center of gravity transfer gait walking for allowing sample population simulation to be pre-designed out,
After sample population skillfully grasps the default center of gravity transfer gait, sensed by three-dimensional light motion capture system, upper body inclination angle
Device, plantar pressure sensor collecting sample crowd are in the walking step state Information Number for simulating the process for presetting center of gravity transfer gait
According to according to data collected construction center of gravity transfer gait data library.As shown in figure 5, the construction in center of gravity transfer gait data library
Process the following steps are included:
(1) training step S11 allows normal sample crowd to simulate default center of gravity transfer gait and walks and skillfully grasp.
In the present embodiment, center of gravity transfer gait is preset as shown in figure 4, in the figure with solid line characterizes right crus of diaphragm and uses dotted line
Left foot is characterized, according to the variation of right crus of diaphragm plantar pressure in the support phase and swing phase of a gait cycle, by a gait cycle
8 stages are divided into, which has 8 phases, i.e. (A) full foot support-is preceding, and the full foot plate surface of right crus of diaphragm lands, and right crus of diaphragm
Preceding, at this point, body weight is divided equally on the bipod of left and right；(B) full foot support --- turn, right leg is generally upstanding, the full sole of right crus of diaphragm
Face lands, and the left foot palm touches ground, at this point, human body upper body Right deviation, center of gravity between bipod from being transferred on right crus of diaphragm supporting surface, human body
Most of weight support is on right leg；(C) full foot support-, right leg is generally upstanding, and the full foot plate surface of right crus of diaphragm lands, and left foot is liftoff
It swings, at this point, human body upper body Right deviation, still on right crus of diaphragm supporting surface, weight is supported by right crus of diaphragm center of gravity completely；(D) full foot support-
Booth, right leg is generally upstanding, and the full foot plate surface of right crus of diaphragm lands, and left heel touches ground, at this point, human body upper body Right deviation, human body is most of
Weight is supported by right crus of diaphragm；(E) after full foot support-, the full foot plate surface of right crus of diaphragm lands, and right crus of diaphragm is rear, at this point, body weight is on a left side
Divide equally on right bipod；(F) sole support ground, left leg is generally upstanding, and the full foot plate surface of left foot lands, and the right crus of diaphragm palm touches ground, at this point, people
Body upper body is left-leaning, center of gravity from bipod it is equal between be transferred on left foot supporting surface, most of weight support is on left leg；(G) sole
Liftoff, left leg is generally upstanding, and the full foot plate surface of left foot lands, swing that right crus of diaphragm is liftoff, at this point, human body upper body is left-leaning, center of gravity is still on a left side
On foot supporting surface, weight is supported by left foot completely；And (H) is heelstrike, left leg is generally upstanding, and the full foot plate surface of left foot lands, right
Heel touches ground, at this point, human body upper body is left-leaning, human body major part weight is supported by left foot.Sample population is allowed to be repeated in
It states default center of gravity and shifts gait to skilled grasp.
I.e. in this default center of gravity transfer gait, in support phase, right leg is main supporting leg, and left leg is to lead leg；And
In swing phase, right leg is to lead leg, and left leg is main supporting leg；And in full foot support-phase inversion position (B) to (D) full foot branch
Support-booth phase and (F) sole support ground phase, will be liftoff to being somebody's turn to do for leading leg for ectoskeleton to the process of (H) heelstrike phase
It leads leg the swing process that will be landed.
(2) data collection steps S12, the sample population that aforementioned default center of gravity transfer gait has skillfully been grasped in acquisition are being simulated
Walking step state information data during the default center of gravity transfer gait.
Sample people is obtained by three-dimensional light motion capture system optrack, upper body obliquity sensor, plantar pressure sensor
Walking step state data of the group in the multiple periods for simulating the default center of gravity transfer gait gait processes, under walking step state data include
Limb joint angles data, plantar pressure data and upper body attitude data；Wherein, joint of lower extremity angle-data includes hip joint, knee
The joint angles data of joint and ankle-joint, plantar pressure data include the pressure data of heel, forefoot and tiptoe, upper figure
State data include the inclination data on human body in human body sagittal plane and frontal plane.Wherein, plantar pressure data are using arrangement
Plantar pressure sensor on vola at different location carries out detection acquisition, which selects the U.S.
The FlexiForce type pressure sensor of Tekscan company, the position of four pressure sensors is as shown in Fig. 2, be located at
4 positions of heel and forefoot, tiptoe, for detecting the contact condition and its interaction force in vola and ground.
(3) database steps S13 is constructed, walking step state data collected are handled, constructs center of gravity transfer step
State database.
(3.1) data processing step: the gait data in multiple periods collected is filtered, is amplified, denoise with from
Dispersion processing, obtains the gait data of any time in a period, gait data includes joint angles data, plantar pressure data
With upper body inclination data；
(3.2) database steps are constructed: simultaneously to the data of sample population repeated acquisition multiple groups more than preset quantity threshold value
Data processing is carried out, database is established.(1) it compares between difference and the different samples between the same sample different cycles
Difference, integral data simultaneously optimize, and specially remove the data to differ greatly, deviate ensemble average value in the present embodiment for removal
Ratio be more than that the data of preset threshold obtain sample number in database such as more than 30%, and by remaining data average treatment
According to；(2) plan as a whole all sample datas, the joint angle angle value for obtaining any time in a gait cycle corresponds to the vola pressure at moment
Force value confidence interval and upper body inclination value confidence interval, and change the weight for obtaining any time in gait cycle according to plantar pressure
Heart position, for example, will be located at same default weight section in a kind of data of the sample population in same phase maximum value with most
Endpoint value of the small value as such data confidence interval of sample population in the default weight section；Further according to 8 phases of gait
It is divided, by (B) full foot support --- data confidence interval when phase inversion position is liftoff as control ectoskeleton driving people's back leg
The criterion on opportunity is defined as center of gravity transfer criterion, the i.e. phase when the rear foot will be liftoff, by judging whether plantar pressure is located at
Whether during plantar pressure confidence and upper body inclination angle, which is located at during the confidence of upper body inclination angle, judges whether center of gravity shifts；It will
(D) full foot support --- data confidence interval when the phase of booth drives people's front foot to land the criterion on opportunity as control ectoskeleton,
It is defined as the criterion that lands in advance, i.e., when front foot will land, to judge whether occur landing in advance in the process of landing.For each
Phase judges that its upper body inclination angle, plantar pressure are respectively positioned in confidence interval, is sentenced using the stabilization as the no energy stabilized walking of ectoskeleton
According to being defined as stability criterion, that is, judge whether to will appear unstable phenomenon.Wherein, plantar pressure value confidence interval constitutes this implementation
The second pre-set interval and third pre-set interval in example, upper body inclination value confidence interval constitute the first preset areas in the present embodiment
Between.
Referring to Fig. 6, walking database is shifted according to the above-mentioned center of gravity having been built up out, above-mentioned exoskeleton system is controlled and carries out
The control method of walking the following steps are included:
(1) parameter initialization step S21 is carried out just according to control parameter of the rehabilitation biological information to exoskeleton system
Beginningization, to select confidence interval corresponding to its weight, i.e. pre-set interval.
After rehabilitation is put on exoskeleton system 1 and is ready to, exoskeleton system first drives patient's lower limb slight jitter
For a period of time, using the average value of the summation of the plantar pressure value measured as the weight value of reference, and the weight value according to acquisition,
It selects to preset the corresponding subdata base in weight section where weight value, corresponding subdata base includes joint of lower extremity angle and its right
The upper body inclination angle confidence interval and plantar pressure confidence interval answered, using the human-computer interaction power measured as the human-computer interaction power of reference
Initial value.
(2) Real time data acquisition step S22, obtaining detection unit has the patient of above-mentioned exoskeleton system in rehabilitation wearing
Walking step state data in training process.
When the rehabilitation personnels such as patient are when wearing has above-mentioned exoskeleton system 1 to carry out walking rehabilitation training, pass through detector
30 acquire its walking step state information in rehabilitation training.Specifically, passing through the real-time measurement rehabilitation of upper body obliquity sensor
The upper inclination data in human body sagittal plane and frontal plane of patient, passes through the angle in the ectoskeleton joint of angular transducer real-time measurement
The angle data of degree evidence, i.e. hip joint, knee joint and ankle-joint passes through two sole of plantar pressure sensor real-time measurement or so
Pressure data, and pass through the human-computer interaction power between human-computer interaction force sensor measuring people and ectoskeleton.
(3) data processing step S23, the walking step state data received are filtered, signal amplification, denoising and it is discrete
Change processing.
(4) gait stability judgment step S24 judges ectoskeleton according to stability criterion according to the walking step state data of acquisition
Walking states it is whether stable；If unstability, according to unstability situation with and unstability trend correct gait track, control as quickly as possible
Ectoskeleton joint angles processed reach stable state；If stablizing, carries out gait phase and identify in real time.
(5) gait phase identification step S25, according in real-time collected walking step state data joint angles data with
Joint angles data in gait data library are compared, and identify the real-time gait phase of ectoskeleton, that is, judge current time
In which of above-mentioned eight phases.
(6) ectoskeleton rate-determining steps S26, according to current joint of lower extremity angle-data, upper body inclination data and plantar pressure
Data match the joint angles data of subsequent time；And lead leg will be liftoff when, judge whether to meet center of gravity transfer and sentence
According to, with control lead leg liftoff opportunity；When leading leg will land, judge whether to meet the criterion that lands in advance, with control
Lead leg the process that lands in advance joint action and realize submissive land.
(6.1) judge ectoskeleton be in lead leg liftoff phase i.e. when, i.e., the full foot support-phase inversion position (B) with
(F) sole support ground phase shifts criterion according to center of gravity, compares the moment collected plantar pressure, upper body inclination data and number
Data when according to library corresponding phase, to judge whether center of gravity shifts completion；If patient's center of gravity do not shift or shift it is insufficient,
Then rear foot stress, in the foot force of the rear foot, the pressure value of 3 pressure sensors acquisition at tiptoe and forefoot will compare
Greatly, for the sum of 3 pressure values more than the value of the confidence that rear foot center of gravity shifts, usually taking the value of the confidence is to obtain in parameter initialization step
The 15% of weight value, at the same front foot foot force value and can lower than front foot center of gravity transfer the value of the confidence, usually take the value of the confidence
It is 85% of acquisition weight value in parameter initialization step；At this point, ectoskeleton can lead to speaker sound prompt wearing personnel slightly
Upper body is rolled, angle of heel angle value is further reminded according to upper body inclination data, and wait and being adjusted in place；On the contrary, if patient
Center of gravity is transferred into position, then the rear foot only gently contacts to earth, 3 pressure in the foot force of the rear foot, at tiptoe and forefoot
The pressure value of sensor acquisition will be smaller, and the sum of 3 pressure values usually takes this to set less than the value of the confidence that rear foot center of gravity shifts
Letter value be parameter initialization step in obtain weight value 15%, while front foot foot force value and can be greater than front foot center of gravity turn
The value of the confidence of shifting, usually taking the value of the confidence is that the 85% of weight value is obtained in parameter initialization step.
(6.2) judge ectoskeleton be in lead leg the phase that will be landed when, i.e., (D) full foot support-spread out phase with
(H) heel support ground phase compares the moment collected plantar pressure, upper body inclination data and number according to the criterion that lands in advance
Data when according to library corresponding phase, judge whether ectoskeleton can land in advance, for example, can make when there is protrusion on travel path outer
Leading leg for bone lands in advance than default opportunity, that is, corresponding joint angles data of leading leg are not up to the data that land, and put
There are plantar pressure data in advance in dynamic legs and feet bottom, at this point, the pressure value of heel can become larger in advance in plantar pressure of leading leg, if
Not landing in advance, the number is often smaller, and usually about zero, it is timely according to the numerical value of plantar pressure and joint angles at this time
Rationally amendment ectoskeleton joint angles curve, make ectoskeleton is submissive to land, avoid ectoskeleton lead leg land in advance bring punching
It hits and unstability.
(6.3) the lower limb exoskeleton joint angles information that matching obtains is passed into corresponding joint motor driver, controlled
Corresponding joint motor rotation is made, it is real by the S type tension sensor being built in thigh and calf bandage in motor rotation process
When the obtained people of measurement and ectoskeleton between human-computer interaction power realize the Shared control of human-computer interaction power, if what is measured is man-machine
Reciprocal force is more than the maximum value of setting, by reducing motor speed, decelerating motor shaft torque, it is ensured that between people and ectoskeleton
Human-computer interaction power ensures good man-machine harmony between people and ectoskeleton, to realize dermoskeleton in the range of safety and comfort
The stability contorting of bone.
In the main control unit 102 of this exoskeleton system, computer program is stored in memory, the computer program
When being executed by its processor, it is able to achieve above-mentioned parameter initialization step S21, Real time data acquisition step S22, data processing step
S23, gait stability judgment step S24, gait phase identification step S25, ectoskeleton rate-determining steps S26.
Walking control method embodiment
Walking control method embodiment of the present invention is illustrated in above-mentioned exoskeleton system embodiment, herein not
It repeats again.
Claims (5)
1. a kind of lower limb rehabilitation exoskeleton system inputs the detection list of detection signal including control unit, to described control unit
Member and the ectoskeleton controlled by described control unit；
It is characterized in that, the detection unit includes plantar pressure detector, upper body tilt angle detector and the inspection of joint of lower extremity angle
Device is surveyed, described control unit includes processor and memory, and the memory is stored with computer program, the computer program
Following steps are able to achieve when being executed by the processor:
Real time data acquisition step obtains the plantar pressure data of the plantar pressure detector output in real time, the upper body inclines
The upper body inclination data of angle detector output and the joint of lower extremity angle-data of joint of lower extremity angle detector output；
Gait phase identification step, according to joint of lower extremity angle reference data, based on the joint of lower extremity angle-data obtained in real time,
Identify the current gait phase of ectoskeleton wearer；
Ectoskeleton rate-determining steps are controlled in leading leg in the swing process led leg and will landed for ectoskeleton
Its main supporting leg keeps generally upstanding state；And when ectoskeleton is in and leads leg liftoff gait phase, and meeting weight
After the heart shifts criterion, controls leading leg for ectoskeleton and carry out liftoff wobbling action；The center of gravity transfer criterion is ectoskeleton wearing
The upper body inclination angle of person is in the first pre-set interval, and its plantar pressure is in the second pre-set interval；Pendulum is in ectoskeleton
When the gait phase that dynamic leg will land, and after meeting the criterion that lands in advance, the joint action of ectoskeleton led leg is controlled extremely
Its is submissive to land, and the plantar pressure that criterion is ectoskeleton wearer that lands in advance is in third pre-set interval, described soft
It is the plantar pressure led leg in the process of landing less than the first preset value along ground.
2. exoskeleton system according to claim 1, which is characterized in that the ectoskeleton rate-determining steps include:
If ectoskeleton is in when leading leg liftoff gait phase, and is unsatisfactory for the center of gravity transfer criterion, then voice reminder
Ectoskeleton wearer adjusts upper body inclination angle.
3. exoskeleton system according to claim 1 or 2, which is characterized in that obtain pre-set interval and joint of lower extremity angle
The step of reference data includes:
Data collection steps, walking step state data of collecting sample crowd during simulating default center of gravity transfer gait are described
Walking step state data include joint of lower extremity angle-data, upper body inclination data and foot force data；The default center of gravity transfer
Gait is the situation of change according to plantar pressure in the support phase and swing phase of a gait cycle, and the gait cycle is divided
For eight gait phases, in eight gait phases, and leading leg the liftoff process institute that leads leg and will land to this
On the gait phase for including, main supporting leg keeps generally upstanding；
Data processing step, is filtered the walking step state data, amplifies, denoising and sliding-model control, obtains independent sample
The gait data of this different moments within a period, the gait data for gathering the sample population constitute gait data library；
Data plan as a whole step, plan as a whole gait data in the gait data library, obtain in a gait cycle under different moments
The corresponding plantar pressure value pre-set interval of limb joint angle angle value and upper body inclination value pre-set interval, when different in a gait cycle
The joint of lower extremity angle-data at quarter constitutes joint of lower extremity angle reference data.
4. exoskeleton system according to claim 3, it is characterised in that:
The Real time data acquisition step includes obtaining human-computer interaction force data, and the human-computer interaction force data is by being built in size
Tension sensor output in leg bandage；
The ectoskeleton rate-determining steps include keeping human-computer interaction power small during controlling the joint of lower extremity movement of ectoskeleton
In the second preset value.
5. exoskeleton system according to claim 1 or 2, it is characterised in that:
The Real time data acquisition step includes obtaining human-computer interaction force data, and the human-computer interaction force data is by being built in size
Tension sensor output in leg bandage；
The ectoskeleton rate-determining steps include keeping human-computer interaction power small during controlling the joint of lower extremity movement of ectoskeleton
In the second preset value.
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Families Citing this family (17)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109316186B (en) * | 2018-10-30 | 2021-04-27 | 北京机械设备研究所 | Full flexible sensing trousers with multisource sensing information |
| CN110731881B (en) * | 2019-09-09 | 2022-09-16 | 无锡美安雷克斯医疗机器人有限公司 | Medical walking aid walking safety protection system |
| CN110721055B (en) * | 2019-10-17 | 2021-11-02 | 深圳市迈步机器人科技有限公司 | Control method of lower limb walking aid exoskeleton robot and exoskeleton robot |
| CN110974631B (en) * | 2019-10-23 | 2022-05-17 | 布法罗机器人科技（成都）有限公司 | Asymmetric lower limb exoskeleton robot and control method |
| CN110755184B (en) * | 2019-11-08 | 2021-09-24 | 哈工大机器人湖州国际创新研究院 | Prosthetic knee joint control method |
| CN110842893B (en) * | 2019-11-10 | 2021-12-03 | 北京机械设备研究所 | Exoskeleton carrying gait judging method, device and system |
| CN110993057B (en) * | 2019-12-10 | 2024-04-19 | 上海金矢机器人科技有限公司 | Rehabilitation training system and method based on cloud platform and lower limb rehabilitation robot |
| CN111469117B (en) * | 2020-04-14 | 2022-06-03 | 武汉理工大学 | Human motion mode detection method of rigid-flexible coupling active exoskeleton |
| CN111481405A (en) * | 2020-04-22 | 2020-08-04 | 北京海益同展信息科技有限公司 | Motion instruction triggering method and device and exoskeleton equipment |
| CN112494272B (en) * | 2020-11-27 | 2021-12-24 | 中国科学院自动化研究所 | Foot drop rehabilitation exoskeleton robot and self-adaptive gait auxiliary control method |
| CN113520688B (en) * | 2021-06-17 | 2024-08-27 | 四川护理职业学院 | Intelligent ankle and foot correction device and method for cerebral palsy children |
| CN113599781B (en) * | 2021-06-25 | 2022-05-03 | 浙江大学 | Wearable walking fitness system based on exoskeleton, control method and storage medium |
| CN113576845A (en) * | 2021-08-02 | 2021-11-02 | 哈尔滨工程大学 | Human body consciousness recognition control device and method applied to exoskeleton robot |
| CN114831857B (en) * | 2022-03-21 | 2023-03-28 | 中国科学院自动化研究所 | Lower limb exoskeleton robot |
| CN115337009A (en) * | 2022-08-23 | 2022-11-15 | 电子科技大学 | Gait recognition and prediction method based on full-connection and cyclic neural network |
| CN115245447A (en) * | 2022-09-22 | 2022-10-28 | 山东海天智能工程有限公司 | System and method for coordinating exoskeleton intelligent distribution through brain-computer interface |
| CN118576460B (en) * | 2024-07-31 | 2024-10-08 | 佛山市欧斯特医疗器械科技有限公司 | Walking aid for rehabilitation training |
Family Cites Families (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP4184679B2 (en) * | 2001-08-01 | 2008-11-19 | 本田技研工業株式会社 | Method for estimating floor reaction force of bipedal mobile body and method for estimating joint moment of bipedal mobile body |
| JP3968064B2 (en) * | 2003-08-22 | 2007-08-29 | 株式会社今仙技術研究所 | Prosthetic bounce device |
| JP2006075456A (en) * | 2004-09-13 | 2006-03-23 | Tohoku Univ | Wearing type support system based on human body model |
| JP2010178937A (en) * | 2009-02-06 | 2010-08-19 | Honda Motor Co Ltd | Exercise assisting apparatus |
| US20130184616A1 (en) * | 2011-09-29 | 2013-07-18 | Michael R. Sanders | Mobility device |
| JP2013075342A (en) * | 2011-09-30 | 2013-04-25 | Equos Research Co Ltd | Joint angle predicting device and joint angle predicting method |
| CA2902616A1 (en) * | 2013-03-14 | 2014-10-02 | Ekso Bionics, Inc. | Powered orthotic system for cooperative overground rehabilitation |
| CN105769513A (en) * | 2014-12-23 | 2016-07-20 | 北京大学深圳研究生院 | Power-assisted mechanical exoskeleton system with automatic obstacle-avoiding function and footing-losing-preventing function |
| CN105456000B (en) * | 2015-11-10 | 2018-09-14 | 华南理工大学 | A kind of ambulation control method of wearable bionic exoskeleton pedipulator convalescence device |
| CN105326627B (en) * | 2015-11-25 | 2018-04-13 | 华南理工大学 | Convalescence device walking trigger control method based on trunk centre-of gravity shift |
| TWI564129B (en) * | 2015-11-27 | 2017-01-01 | 財團法人工業技術研究院 | Method for estimating posture of robotic walking aid |
| CN106325273B (en) * | 2016-08-22 | 2019-04-12 | 江苏中科伟思智能机器人科技有限公司 | The leggy gait handover control system and its control method of assistance exoskeleton robot |
| CN107126344B (en) * | 2017-07-05 | 2023-08-18 | 天津科技大学 | Exoskeleton rehabilitation robot for rehabilitation of lower limb walking function and control system and method |
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