CN109758157A - Gait rehabilitation training and estimating method and system based on augmented reality - Google Patents
Gait rehabilitation training and estimating method and system based on augmented reality Download PDFInfo
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- CN109758157A CN109758157A CN201910084978.3A CN201910084978A CN109758157A CN 109758157 A CN109758157 A CN 109758157A CN 201910084978 A CN201910084978 A CN 201910084978A CN 109758157 A CN109758157 A CN 109758157A
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- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
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- A63B23/035—Exercising apparatus specially adapted for particular parts of the body for limbs, i.e. upper or lower limbs, e.g. simultaneously
- A63B23/04—Exercising apparatus specially adapted for particular parts of the body for limbs, i.e. upper or lower limbs, e.g. simultaneously for lower limbs
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Abstract
The present invention relates to augmented reality fields, are related to a kind of gait rehabilitation training and estimating method and system based on augmented reality, and method includes: the ambulation training environment that lower limb are selected according to the evaluation result of the walking-function of rehabilitation training patient；Select lower limb ambulation training mode；Patient's footprint is projected on treadmill conveyer belt, ambulation training augmented reality environment is built；It guides the patient to carry out ambulation training, judges that the foot of patient in preset time steps on middle rate to augmented reality footprint in ambulation training augmented reality environment, and give and feed back；After ambulation training, rehabilitation training data are handled, export the lose points analysis of causes and the rehabilitation assessment report of ambulation training.The present invention guides patient targetedly to carry out ambulation training by building ambulation training augmented reality environment, provides ambulation training scheme abundant and improves the interest of patient's ambulation training, improves the effect of lower limb walking rehabilitation training.
Description
Technical field
The present invention relates to augmented reality field, in particular to a kind of gait rehabilitation training and estimating method based on augmented reality
With system.
Background technique
Numerous cerebral apoplexies, brain trauma, spinal cord injury and other Bones and joints illness patient all have that walking is unstable, walking appearance
Situations such as gesture is not to, dysbasia.The ambulation training of this some patients, mostly at present is artificial one-to-one training, such as on ground
Upper patch walking footprint labeling, a rehabilitation therapist instruct a patient to step on footprint labeling and carry out ambulation training.
This traditional walking rehabilitation training mode has the following problems: training court occupies big, training environment dullness, trouble
Person's training is uninteresting, and therapist occupies human cost height, and there are also problems in terms of the assessment of ambulation training performance.
Summary of the invention
Embodiments of the present invention aim to solve at least one of the technical problems existing in the prior art.
For this purpose, embodiments of the present invention need to provide a kind of gait rehabilitation training and estimating method based on augmented reality,
It is characterised by comprising:
Step 1, according to the evaluation result of the walking-function of rehabilitation training patient, the ambulation training environment of lower limb is selected；Its
In, ambulation training environment includes one of level walking environment, upward slope environment and descending environment or a variety of；
Step 2, lower limb ambulation training mode is selected；Wherein, training mode includes in easy, medium, more difficult and customized
Any one walking complexity mode；
Step 3, footprint of the patient in current lower limb ambulation training mode is projected on treadmill conveyer belt, builds step
Row training augmented reality environment, for guiding patient to carry out ambulation training；
Step 4, guidance patient carries out ambulation training, judges that the foot of patient in preset time instructs walking in the training process
Practice augmented reality footprint in augmented reality environment and step on middle rate, and gives and feed back；
Step 5, after ambulation training, rehabilitation training data are handled, export the reason of losing points of ambulation training
Analysis and rehabilitation assessment report.
In a kind of embodiment, step 3 includes: that footprint of the patient in current lower limb ambulation training mode is projected to race
On step machine conveyer belt, ambulation training augmented reality ring is built by Kinect somatosensory device, computer, treadmill and projector
Border；Wherein, build ambulation training augmented reality environment include: be pre-designed one include virtual footprint augmented reality environment；
Then augmented reality environment is projected on treadmill conveyer belt by projector, in patient's ambulation training by Kinect somatosensory
Devices collect data simultaneously transfers to computer that gait data is calculated and steps on middle rate to augmented reality footprint.
In a kind of embodiment, step 2 includes: selection lower limb ambulation training mode, and passes through control augmented reality footprint
Step-length, step pitch and treadmill conveyor belt speed, to present including any one step in easy, medium, more difficult and customized
Row complexity mode.
In a kind of embodiment, step 4 includes: that guidance patient carries out ambulation training, utilizes Kinect in the training process
The skeleton point three-dimensional location coordinates of somatosensory device acquisition patient are simultaneously transmitted to computer, are calculated by computer including step
Gait data including length, step width, step are high, and judge that the foot of patient in preset time steps on middle rate to augmented reality footprint, it gives
Give feedback.
In a kind of embodiment, step 5 includes: preparatory building lower limb walking rehabilitation training recruitment evaluation model, in walking
After training, rehabilitation training data are handled using lower limb walking rehabilitation training recruitment evaluation model, output walking instruction
Experienced the lose points analysis of causes and rehabilitation assessment report；Wherein, building lower limb walking rehabilitation training recruitment evaluation model includes in advance
It determines the two-level index including the preceding situation of training, training facilities and training process situation, and is obtained using Network Analysis Method
The weight of each index obtains assessment result in conjunction with weight vectors and grey evaluation matrix and is documented in rehabilitation assessment report
In.
Embodiment of the present invention also proposes that a kind of gait rehabilitation Training valuation system based on augmented reality, feature exist
In, comprising:
Environmental selection module selects the walking of lower limb for the evaluation result according to the walking-function of rehabilitation training patient
Training environment；Wherein, ambulation training environment includes one of level walking environment, upward slope environment and descending environment or a variety of；
Mode selection module, for selecting lower limb ambulation training mode；Wherein, training mode includes easy, medium, more difficult
With it is customized in any one walking complexity mode；
Augmented reality builds module, for footprint of the patient in current lower limb ambulation training mode to be projected to treadmill
On conveyer belt, ambulation training augmented reality environment is built, for guiding patient to carry out ambulation training；
Training computing module, for judging the foot of patient in preset time to ambulation training augmented reality in the training process
Augmented reality footprint steps on middle rate in environment, and gives and feed back；
Analysis module, for handling rehabilitation training data, exporting the mistake of ambulation training after ambulation training
Divide the analysis of causes and rehabilitation assessment report.
In a kind of embodiment, augmented reality builds module, is specifically used for patient in current lower limb ambulation training mode
In footprint project on treadmill conveyer belt, walking is built by Kinect somatosensory device, computer, treadmill and projector
Training augmented reality environment；Wherein, building ambulation training augmented reality environment includes: to be pre-designed one to include virtual footprint
Augmented reality environment；Then augmented reality environment is projected on treadmill conveyer belt by projector, in patient's ambulation training
When acquired by Kinect somatosensory device and data and transfer to computer that gait data is calculated and steps on to augmented reality footprint
Middle rate.
In a kind of embodiment, mode selection module is specifically used for selection lower limb ambulation training mode, and is increased by control
Step-length, step pitch and the treadmill conveyor belt speed of strong reality footprint, to present including in easy, medium, more difficult and customized
Any one walking complexity mode.
In a kind of embodiment, training computing module, specifically for being adopted in the training process using Kinect somatosensory device
Collect the skeleton point three-dimensional location coordinates of patient and be transmitted to computer, is calculated by computer including step-length, step width, step
Gait data including height, and judge that the foot of patient in preset time steps on middle rate to augmented reality footprint, it gives and feeds back.
In a kind of embodiment, analysis module is specifically used for building lower limb walking rehabilitation training recruitment evaluation model in advance,
After ambulation training, rehabilitation training data are handled using lower limb walking rehabilitation training recruitment evaluation model, are exported
The lose points analysis of causes and the rehabilitation assessment report of ambulation training；Wherein, lower limb walking rehabilitation training recruitment evaluation mould is constructed in advance
Two-level index of the type including determining situation before training, training facilities and training process situation, and utilize network analysis
Method obtains the weight of each index, obtains assessment result in conjunction with weight vectors and grey evaluation matrix and is documented in rehabilitation assessment
In report.
The gait rehabilitation training and estimating method and system based on augmented reality of embodiment of the present invention, by building walking
Training augmented reality environment guidance patient targetedly carries out ambulation training, and can set by adjusting augmented reality footprint
Different training modes are set, may be implemented to timely feedback and give reason of accurately losing points in training after training and assess and generate
Assessment report greatly improves the effect of lower limb rehabilitation training.
The advantages of additional aspect of the invention, will be set forth in part in the description, and will partially become from the following description
Obviously, or practice through the invention is recognized.
Detailed description of the invention
The above-mentioned and/or additional aspect and advantage of embodiments of the present invention are from combination following accompanying drawings to embodiment
It will be apparent and be readily appreciated that in description, in which:
Fig. 1 is the flow diagram of the gait rehabilitation training and estimating method based on augmented reality of embodiment of the present invention；
Fig. 2 is the composition schematic diagram of the gait rehabilitation Training valuation system based on augmented reality of embodiment of the present invention；
Fig. 3 is the equipment connection schematic diagram of ambulation training augmented reality environmental structure in embodiment of the present invention；
Fig. 4 is the guidance walking schematic diagram of ambulation training in embodiment of the present invention.
Specific embodiment
Embodiments of the present invention are described below in detail, the example of embodiment is shown in the accompanying drawings, wherein identical or class
As label indicate same or similar element or element with the same or similar functions from beginning to end.Below with reference to attached
The embodiment of figure description is exemplary, and can only be used to explain embodiments of the present invention, and should not be understood as to the present invention
Embodiment limitation.
Referring to Fig. 1, the gait rehabilitation training and estimating method based on augmented reality of embodiment of the present invention, comprising:
Step 1, according to the evaluation result of the walking-function of rehabilitation training patient, the ambulation training environment of lower limb is selected；Its
In, ambulation training environment includes one of level walking environment, upward slope environment and descending environment or a variety of；
Step 2, lower limb ambulation training mode is selected；Wherein, training mode includes in easy, medium, more difficult and customized
Any one walking complexity mode；
Step 3, footprint of the patient in current lower limb ambulation training mode is projected on treadmill conveyer belt, builds step
Row training augmented reality environment, for guiding patient to carry out ambulation training；
Step 4, guidance patient carries out ambulation training, judges that the foot of patient in preset time instructs walking in the training process
Practice augmented reality footprint in augmented reality environment and step on middle rate, and gives and feed back；
Step 5, after ambulation training, rehabilitation training data are carried out with the reason point of losing points of processing output ambulation training
Analysis and rehabilitation assessment report.
Referring to Fig. 2, the gait rehabilitation Training valuation system based on augmented reality of embodiment of the present invention, comprising:
Environmental selection module selects the walking of lower limb for the evaluation result according to the walking-function of rehabilitation training patient
Training environment；Wherein, ambulation training environment includes one of level walking environment, upward slope environment and descending environment or a variety of；
Mode selection module, for selecting lower limb ambulation training mode；Wherein, training mode includes easy, medium, more difficult
With it is customized in any one walking complexity mode；
Augmented reality builds module, for footprint of the patient in current lower limb ambulation training mode to be projected to treadmill
On conveyer belt, ambulation training augmented reality environment is built, for guiding patient to carry out ambulation training；
Training computing module judges patient in preset time for guiding patient to carry out ambulation training in the training process
Foot middle rate is stepped on to augmented reality footprint in ambulation training augmented reality environment, and give and feed back；
Analysis module, for after ambulation training, rehabilitation training data to be carried out with the mistake of processing output ambulation training
Divide the analysis of causes and rehabilitation assessment report.
In this embodiment, the gait rehabilitation training and estimating method based on augmented reality is with the gait based on augmented reality
Execution object of the rehabilitation training assessment system as step, or the execution object using the modules in system as step.
Specifically, execution object of the step 1 using environmental selection module as step, step 2 selecting module holding as step in mode
Row object, step 3 build module as the execution object of step using augmented reality, and step 4 is to train computing module as step
Execution object, execution object of the step 5 using analysis module as step.
In step 1, environmental selection module determines lower limb according to the evaluation result of the walking-function of rehabilitation training patient
Ambulation training environment is level walking environment, upward slope environment, descending environment or integrated environment, the change of this ambulation training environment
Change, treadmill, then the angle by converting treadmill plane can be pushed to realize by dynamic structure.
In step 2, after determining certain ambulation training environment, mode selection module selection includes easy, medium, more difficult and oneself
Any one lower limb ambulation training mode in definition；I.e. ambulation training mode includes a variety of complexities, can be by by walking
The parameters such as speed, step-length, step width, walking time are set.
In step 3, augmented reality builds module in the training process, is instructed patient in current lower limb walking by projector
The footprint practiced in mode projects on treadmill conveyer belt, ambulation training augmented reality environment is built, for guiding patient to carry out
Ambulation training.
Specifically, step 3 includes: to be projected to footprint of the patient in current lower limb ambulation training mode by projector
On treadmill conveyer belt, augmented reality builds module and builds step by Kinect somatosensory device, computer, treadmill and projector
Row training augmented reality environment；Wherein, building ambulation training augmented reality environment includes: to be pre-designed one to include virtual footprint
Augmented reality environment；Then augmented reality environment is projected in above treadmill conveyer belt by projector, in patient's walking
Data are acquired by Kinect somatosensory device when training and computer is transferred to gait data to be calculated and to augmented reality footprint
Step on middle rate.
Kinect somatosensory device is a kind of 3D body-sensing video camera that Microsoft releases, and has dynamic capture immediately, image
The functions such as identification, microphone input, speech recognition, community interactive.Kinect somatosensory device is not needed using any controller, can
To rely on the movement of player in cameras capture three-dimensional space, and face can be also recognized, can also recognize sound and is taken orders.?
It, can be by the depth camera real-time tracking of Kinect somatosensory device and the three-dimensional of acquisition 25 skeleton points of human body in the present invention
Location information.
Referring to Fig. 3, including Kinect somatosensory device, computer, projector and treadmill in Fig. 3, first by Kinect
Somatosensory device is connected with projector, computer.Then the enhancing of guidance walking is established in computer Unity3D game engine
Real bad border guides the augmented reality footprint of walking to be recycled according to the fixed step size and step width of setting and occurs.Pass through again
Kinect somatosensory device obtains human skeleton artis three dimensional space coordinate, obtains carry out rehabilitation training within sweep of the eye in real time
The every frame of patient joint dot position information (i.e. the three dimensional local information of skeleton point), then by joint dot position information these
Data are sent to computer, calculate patient according to the joint dot position information of real-time detection by computer and step on middle augmented reality foot
The coincidence factor of print, statistics step on middle number, and material calculation, step width, the high data of step.
Further, mode selection module selection lower limb ambulation training mode can use the walking instruction built in step 2
Practice augmented reality environment, by control augmented reality footprint step-length, step pitch and treadmill conveyor belt speed, come present including
Any one walking complexity mode in easy, medium, more difficult and customized.
In step 4, referring to Fig. 4, the true footprint 2 of patient, patient's footprint is overlapped with virtual footprint including virtual footprint 1
Region 3 and identified areas 4.Training computing module guidance patient carries out ambulation training, is set in the training process by Kinect somatosensory
The standby joint dot position information for obtaining patient's skeleton in real time is simultaneously handled, and taking ankle-joint Ankle is calculating benchmark, in real time
Information, that is, the AnkleLeft and AnkleRight for obtaining left and right ankle-joint, take the difference of two ankle-joint depth distances (i.e. Z value)
Absolute value changes as real-time spacing according to this spacing come dividing gait cycles.Simultaneously with the difference of left and right ankle-joint depth distance
Maximum value be recorded as current period step-length, left and right ankle-joint is based on the maximum of the difference of Kinect horizontal direction distance (i.e. X value)
Value is current period step width, and the maximum value that left and right ankle-joint is based on the difference of Kinect vertical direction distance (i.e. Y value) is current week
Phase step is high.
When patient carries out ambulation training on a treadmill, there is the increasing of guidance walking in ambulation training augmented reality enviromental cycle
Augmented reality footprint, is projected in above running belt of running machine, as shown in figure 4, wherein virtual footprint 1 by strong reality footprint by projector
Come out by projector, can with running belt of running machine speed slide, according to the training demand of medical science of recovery therapy be provided with include
The speed class of multiple difficulty such as easy, medium, difficult and customized.Each grade of difficulty has corresponding speed, simultaneously will
1 movement velocity of virtual footprint is arranged to match the speed of treadbelt in virtual scene, it is made to complete to synchronize.When virtual footprint 1 is mobile
When to identified areas 4, patient needs for foot to be moved to the position of virtual footprint 1, distinguishes left and right foot.Shadow region is overlapped in figure
Region 3, the size that virtual footprint projects are arranged referring to normal person's footprint size, keep its closer to the truth.Cause
It relative to the camera position of Kinect somatosensory device is fixed for identified areas 4, so the people for only needing to obtain in real time
Body ankle-joint and the location information of foot are calculated, the center position information of available patient's foot.Due to everyone
Foot length and width are all different, done unitized processing here, and length and width are so that it is more convenient for such as virtual footprint when reference area
It calculates.Note shaded area is Sy, virtual footprint area is S, so footprint coincidence factor P isTrain computing module benefit
The skeleton point three-dimensional location coordinates of patient are acquired with Kinect somatosensory device and are transmitted to computer, are calculated by computer
Gait data including step-length, step width, step including high out, and judge that the foot of patient in preset time steps on augmented reality footprint
Middle rate, gives and feeds back, and the form fed back in training can be voice prompting and be also possible to be prompted with image mode, herein
Without limitation.
In step 5, analysis module constructs lower limb walking rehabilitation training recruitment evaluation model in advance, terminates in ambulation training
Afterwards, rehabilitation training data are handled using lower limb walking rehabilitation training recruitment evaluation model, exports losing points for ambulation training
The analysis of causes and rehabilitation assessment report；Wherein, building lower limb walking rehabilitation training recruitment evaluation model includes determining training in advance
Two-level index including preceding situation, training facilities and training process situation, and each index is obtained using Network Analysis Method
Weight, obtain assessment result in conjunction with weight vectors and grey evaluation matrix and be documented in rehabilitation training report.
Specifically, analysis module constructs lower limb walking rehabilitation training recruitment evaluation model, it is first determined evaluation index, according to
The content and feature integrative medicine demand index for selection of this rehabilitation training.Then the network hierarchical structure for establishing index, under
The actual conditions of limbs rehabilitation training are established.In order to reasonably divide evaluation index, two-level index is set: being broadly divided into trained cause
Condition, training facilities and 3 class of training process situation, every one kind two-level index include the three-level index of different numbers again.Wherein,
Situation includes lower limb Lovett muscular strength grade assessment, the evaluation of Berg balance scale, lower limb Fugl- before training in two-level index
The assessment of Meyer motor function；Training setting in two-level index includes virtual footprint complexity, training duration, training speed；
Training process situation in two-level index include footprint coincidence factor, reaction speed, training completed percentage, movement locus smoothness,
Direction of action accuracy.Indexs at different levels in lower limb rehabilitation training evaluation index are as shown in table 1:
Table 1
Then the weight of each index is obtained by following steps according to Network Analysis Method, comprising:
(1) initial hypermatrix is constructed
(2) construction weighting hypermatrix
(3) limit hypermatrix is calculated
(4) weight of each index is finally obtained.
Network Analysis Method (ANP) is a kind of adaptation that the T.L.Saaty professor of Univ. of Pittsburgh proposed in 1996
The decision-making technique of the recursive hierarchy structure of dependent, it is in analytic hierarchy process (AHP) (Analytic Hierarchy Process, letter
Claim AHP) on the basis of develop and the new practical decision-making technique of one kind for being formed.For AHP as a kind of decision process, it provides one
Kind indicates the basic skills that decision factor is estimated.This method uses the form of relative scale.Under recursive hierarchy structure, its root
According to relative scale-proportion quotiety of defined, the relative importance to same level in relation to element is compared two-by-two, and is pressed
Level synthetic schemes estimating for decision objective from top to bottom.The present invention then obtains lower limb rehabilitation using above-mentioned multiple steps
The weight of each index in Training valuation index.
Fuzzy evaluation matrix is constructed by gray system theory again, initially sets up sample matrix, then determines and assesses grey class, most
The grey evaluation matrix of evaluation index is constructed afterwards.In conjunction with weight vectors and grey evaluation matrix it can be concluded that final assessment result.
In control theory, people often describe the clear-cut degree of information with the depth of color, such as unknown with " black " expression information, with " white "
It indicates that information is completely clear, indicates that partial information is clear, partial information is indefinite with " ash ".Correspondingly, information is completely specific
System is known as white system；The completely indefinite system of information is known as darky system；Partial information is clear, partial information is indefinite
System be known as gray system.The research object of gray system theory is " partial information is known, partial information is unknown " " poor letter
Breath " uncertain system, it passes through the generation of " part " Given information, exploitation, realizes to the definite description of real world and understanding.
Its main contents studied includes the theoretical system based on the dim collection of grey, is the analysis system relied on grey correlation space
System, by gray system generate based on method system, with gray model (GM) be core model system, with network analysis,
Assessment, modeling, prediction, decision, control, the technical system based on optimization.The present invention is then constructed using gray system theory
The grey evaluation matrix of lower limb rehabilitation training evaluation index, to come in conjunction with the weight vectors and grey evaluation matrix obtained before
Show that final patient carries out the assessment result of ambulation training.
In conclusion the present invention guides patient targetedly to carry out walking instruction by building ambulation training augmented reality environment
Practice, and different training modes can be set by adjusting augmented reality footprint, may be implemented to timely feedback simultaneously in training
Reason of accurately losing points is given after training and assesses and generate rehabilitation assessment report, and ambulation training scheme abundant and raising are provided
The interest of patient's ambulation training improves the effect of lower limb walking rehabilitation training.
In the description of embodiments of the present invention, it is to be understood that term " center ", " longitudinal direction ", " transverse direction ", " length
Degree ", " width ", " thickness ", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner",
The orientation or positional relationship of the instructions such as "outside", " clockwise ", " counterclockwise " is to be based on the orientation or positional relationship shown in the drawings, only
It is embodiments of the present invention and simplified description for ease of description, rather than the device or element of indication or suggestion meaning are necessary
It with specific orientation, is constructed and operated in a specific orientation, therefore should not be understood as the limitation to embodiments of the present invention.
In addition, term " first ", " second " are used for descriptive purposes only and cannot be understood as indicating or suggesting relative importance or imply
Indicate the quantity of indicated technical characteristic." first " is defined as a result, the feature of " second " can be expressed or impliedly wrap
Include one or more feature.In the description of embodiments of the present invention, the meaning of " plurality " is two or two
More than, unless otherwise specifically defined.
In the description of embodiments of the present invention, it should be noted that unless otherwise clearly defined and limited, term
" installation ", " connected ", " connection " shall be understood in a broad sense, for example, it may be fixedly connected, may be a detachable connection or one
Connect to body；It can be mechanical connection, be also possible to be electrically connected or can mutually communicate；It can be directly connected, can also lead to
It crosses intermediary to be indirectly connected, can be the connection inside two elements or the interaction relationship of two elements.For ability
For the those of ordinary skill in domain, can understand as the case may be above-mentioned term in embodiments of the present invention specifically contain
Justice.
In embodiments of the present invention unless specifically defined or limited otherwise, fisrt feature second feature it
"upper" or "lower" may include that the first and second features directly contact, may include the first and second features be not directly to connect yet
It touches but by the other characterisation contact between them.Moreover, fisrt feature second feature " on ", " top " and " on
Face " includes fisrt feature right above second feature and oblique upper, or to be merely representative of first feature horizontal height special higher than second
Sign.Fisrt feature include under the second feature " below ", " below " and " below " fisrt feature immediately below second feature and obliquely downward
Side, or first feature horizontal height is merely representative of less than second feature.
Following disclosure provides many different embodiments or example is used to realize embodiments of the present invention not
Same structure.In order to simplify the disclosure of embodiments of the present invention, hereinafter the component of specific examples and setting are described.When
So, they are merely examples, and is not intended to limit the present invention.In addition, embodiments of the present invention can be in different examples
Repeat reference numerals and/or reference letter in son, this repetition are for purposes of simplicity and clarity, itself not indicate to be begged for
By the relationship between various embodiments and/or setting.In addition, the various specific techniques that embodiments of the present invention provide
With the example of material, but those of ordinary skill in the art may be aware that the application of other techniques and/or other materials make
With.
In the description of this specification, reference term " embodiment ", " some embodiments ", " schematically implementation
The description of mode ", " example ", specific examples or " some examples " etc. means the tool described in conjunction with the embodiment or example
Body characteristics, structure, material or feature are contained at least one embodiment or example of the invention.In the present specification,
Schematic expression of the above terms are not necessarily referring to identical embodiment or example.Moreover, the specific features of description, knot
Structure, material or feature can be combined in any suitable manner in any one or more embodiments or example.
Any process described otherwise above or method description are construed as in flow chart or herein, and expression includes
It is one or more for realizing specific logical function or process the step of executable instruction code module, segment or portion
Point, and the range of the preferred embodiment of the present invention includes other realization, wherein can not press shown or discussed suitable
Sequence, including according to related function by it is basic simultaneously in the way of or in the opposite order, Lai Zhihang function, this should be of the invention
Embodiment person of ordinary skill in the field understood.
Expression or logic and/or step described otherwise above herein in flow charts, for example, being considered use
In the order list for the executable instruction for realizing logic function, may be embodied in any computer-readable medium, for
Instruction execution system, device or equipment (such as computer based system, including the system of processing module or other can be from instruction
Execute system, device or equipment instruction fetch and the system that executes instruction) use, or combine these instruction execution systems, device or
Equipment and use.For the purpose of this specification, " computer-readable medium " can be it is any may include, store, communicating, propagating or
Transfer program uses for instruction execution system, device or equipment or in conjunction with these instruction execution systems, device or equipment
Device.The more specific example (non-exhaustive list) of computer-readable medium include the following: there are one or more wirings
Electrical connection section (electronic device), portable computer diskette box (magnetic device), random access memory (RAM), read-only memory
(ROM), erasable edit read-only storage (EPROM or flash memory), fiber device and portable optic disk is read-only deposits
Reservoir (CDROM).In addition, computer-readable medium can even is that the paper that can print described program on it or other are suitable
Medium, because can then be edited, be interpreted or when necessary with it for example by carrying out optical scanner to paper or other media
His suitable method is handled electronically to obtain described program, is then stored in computer storage.
It should be appreciated that each section of embodiments of the present invention can be with hardware, software, firmware or their combination come real
It is existing.In the above-described embodiment, multiple steps or method can be with storages in memory and by suitable instruction execution system
The software or firmware of execution is realized.For example, if realized with hardware, in another embodiment, ability can be used
Any one of following technology or their combination well known to domain is realized: being had for realizing logic function to data-signal
The discrete logic of logic gates, the specific integrated circuit with suitable combinational logic gate circuit, programmable gate array
(PGA), field programmable gate array (FPGA) etc..
Those skilled in the art are understood that realize all or part of step that above-described embodiment method carries
It suddenly is that relevant hardware can be instructed to complete by program, the program can store in a kind of computer-readable storage medium
In matter, which when being executed, includes the steps that one or a combination set of embodiment of the method.In addition, in each implementation of the invention
Each functional unit in example can integrate in a processing module, is also possible to each unit and physically exists alone, can also be with
Two or more units are integrated in a module.Above-mentioned integrated module both can take the form of hardware realization,
It can be realized in the form of software function module.If the integrated module is realized and is made in the form of software function module
It is independent product when selling or using, also can store in a computer readable storage medium.
Storage medium mentioned above can be read-only memory, disk or CD etc..
Although the embodiments of the present invention has been shown and described above, it is to be understood that above-described embodiment is example
Property, it is not considered as limiting the invention, those skilled in the art within the scope of the invention can be to above-mentioned
Embodiment is changed, modifies, replacement and variant.
Claims (10)
1. a kind of gait rehabilitation training and estimating method based on augmented reality characterized by comprising
Step 1, according to the evaluation result of the walking-function of rehabilitation training patient, the ambulation training environment of lower limb is selected；Wherein, it walks
Row training environment includes one of level walking environment, upward slope environment and descending environment or a variety of；
Step 2, lower limb ambulation training mode is selected；Wherein, training mode includes any in easy, medium, more difficult and customized
A kind of walking complexity mode；
Step 3, footprint of the patient in current lower limb ambulation training mode is projected on treadmill conveyer belt, builds walking instruction
Practice augmented reality environment, for guiding patient to carry out ambulation training；
Step 4, guidance patient carries out ambulation training, judges that the foot of patient in preset time increases ambulation training in the training process
Augmented reality footprint steps on middle rate in strong actual environment, and gives and feed back；
Step 5, after ambulation training, rehabilitation training data are handled, export the analysis of causes of losing points of ambulation training
It is reported with rehabilitation assessment.
2. the gait rehabilitation training and estimating method based on augmented reality as described in claim 1, which is characterized in that step 3 includes:
Footprint of the patient in current lower limb ambulation training mode is projected on treadmill conveyer belt, by Kinect somatosensory device,
Computer, treadmill and projector build ambulation training augmented reality environment；Wherein, ambulation training augmented reality environment packet is built
Include: be pre-designed one include virtual footprint augmented reality environment；Then augmented reality environment is projected in by projector
On treadmill conveyer belt, data are acquired by Kinect somatosensory device in patient's ambulation training and transfer to computer that step is calculated
State data and middle rate is stepped on to augmented reality footprint.
3. the gait rehabilitation training and estimating method based on augmented reality as claimed in claim 2, which is characterized in that step 2 includes:
Lower limb ambulation training mode is selected, and by step-length, step pitch and the treadmill conveyor belt speed of control augmented reality footprint, is come
Presenting includes any one walking complexity mode in easy, medium, more difficult and customized.
4. the gait rehabilitation training and estimating method based on augmented reality as claimed in claim 3, which is characterized in that step 4 includes:
It guides patient to carry out ambulation training, utilizes the skeleton point three-dimensional position of Kinect somatosensory device acquisition patient in the training process
It sets coordinate and is transmitted to computer, the gait data including step-length, step width, step including high is calculated by computer, and judge
The foot of patient steps on middle rate to augmented reality footprint in preset time, gives and feeds back.
5. the gait rehabilitation training and estimating method based on augmented reality as claimed in claim 4, which is characterized in that step 5 includes:
Building lower limb walking rehabilitation training recruitment evaluation model in advance is imitated after ambulation training using lower limb walking rehabilitation training
Fruit assessment models handle rehabilitation training data, export the lose points analysis of causes and the rehabilitation assessment report of ambulation training；Its
In, constructing lower limb walking rehabilitation training recruitment evaluation model in advance includes situation before determining training, training facilities and training
Two-level index including process condition, and the weight of each index is obtained using Network Analysis Method, in conjunction with weight vectors and ash
Color evaluating matrix obtains assessment result and is documented in rehabilitation assessment report.
6. a kind of gait rehabilitation Training valuation system based on augmented reality characterized by comprising
Environmental selection module selects the ambulation training of lower limb for the evaluation result according to the walking-function of rehabilitation training patient
Environment；Wherein, ambulation training environment includes one of level walking environment, upward slope environment and descending environment or a variety of；
Mode selection module, for selecting lower limb ambulation training mode；Wherein, training mode include it is easy, medium, more difficult and oneself
Any one walking complexity mode in definition；
Augmented reality builds module, for footprint of the patient in current lower limb ambulation training mode to be projected to treadmill transmission
It takes, builds ambulation training augmented reality environment, for guiding patient to carry out ambulation training；
Training computing module, for judging the foot of patient in preset time to ambulation training augmented reality environment in the training process
Middle augmented reality footprint steps on middle rate, and gives and feed back；
Analysis module, for handling rehabilitation training data, exporting the original of losing points of ambulation training after ambulation training
Because of analysis and rehabilitation assessment report.
7. the gait rehabilitation Training valuation system based on augmented reality as claimed in claim 6, which is characterized in that augmented reality is taken
Modeling block passes through specifically for projecting to footprint of the patient in current lower limb ambulation training mode on treadmill conveyer belt
Kinect somatosensory device, computer, treadmill and projector build ambulation training augmented reality environment；Wherein, walking instruction is built
Practice augmented reality environment include: be pre-designed one include virtual footprint augmented reality environment；Then will be increased by projector
Strong actual environment is projected on treadmill conveyer belt, is acquired data by Kinect somatosensory device in patient's ambulation training and is transferred to
Computer is calculated gait data and steps on middle rate to augmented reality footprint.
8. the gait rehabilitation Training valuation system based on augmented reality as claimed in claim 7, which is characterized in that model selection mould
Block is specifically used for selection lower limb ambulation training mode, and is passed by the step-length, step pitch and treadmill of control augmented reality footprint
Tape speed is sent, to present including any one walking complexity mode in easy, medium, more difficult and customized.
9. the gait rehabilitation Training valuation system based on augmented reality as claimed in claim 8, which is characterized in that training calculates mould
Block, specifically for utilizing the skeleton point three-dimensional location coordinates of Kinect somatosensory device acquisition patient in the training process and passing
Computer is transported to, the gait data including step-length, step width, step including high is calculated by computer, and judge in preset time
The foot of patient steps on middle rate to augmented reality footprint, gives and feeds back.
10. the gait rehabilitation Training valuation system based on augmented reality as claimed in claim 9, which is characterized in that analysis module,
Specifically for constructing lower limb walking rehabilitation training recruitment evaluation model in advance, after ambulation training, lower limb walking health is utilized
Refreshment is practiced recruitment evaluation model and is handled rehabilitation training data, and the lose points analysis of causes and the rehabilitation assessment of ambulation training are exported
Report；Wherein, building lower limb walking rehabilitation training recruitment evaluation model includes situation before determining training, training facilities in advance
With the two-level index including training process situation, and obtain using Network Analysis Method the weight of each index, in conjunction with weight to
Amount and grey evaluation matrix obtain assessment result and are documented in rehabilitation assessment report.
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| PCT/CN2019/076165 WO2020155252A1 (en) | 2019-01-29 | 2019-02-26 | Augmented reality-based gait rehabilitation training evaluation method and system |
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