CN108261274A - A kind of two-way deformed limb interface system controlled for prosthetic hand with perceiving - Google Patents
A kind of two-way deformed limb interface system controlled for prosthetic hand with perceiving Download PDFInfo
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- CN108261274A CN108261274A CN201810220841.1A CN201810220841A CN108261274A CN 108261274 A CN108261274 A CN 108261274A CN 201810220841 A CN201810220841 A CN 201810220841A CN 108261274 A CN108261274 A CN 108261274A
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- 238000000034 method Methods 0.000 claims abstract description 30
- 230000001953 sensory effect Effects 0.000 claims abstract description 4
- 238000012545 processing Methods 0.000 claims description 30
- 238000012549 training Methods 0.000 claims description 27
- 238000000605 extraction Methods 0.000 claims description 9
- 230000009471 action Effects 0.000 claims description 8
- 230000003183 myoelectrical effect Effects 0.000 claims description 8
- 238000012706 support-vector machine Methods 0.000 claims description 8
- 238000004891 communication Methods 0.000 claims description 7
- 230000000694 effects Effects 0.000 claims description 6
- 230000008569 process Effects 0.000 claims description 6
- 239000011159 matrix material Substances 0.000 claims description 5
- 238000001914 filtration Methods 0.000 claims description 4
- 230000004118 muscle contraction Effects 0.000 claims description 4
- 238000002329 infrared spectrum Methods 0.000 claims description 3
- 210000003205 muscle Anatomy 0.000 claims description 3
- 230000002093 peripheral effect Effects 0.000 claims description 3
- 239000002184 metal Substances 0.000 claims description 2
- 238000004519 manufacturing process Methods 0.000 claims 1
- 230000035945 sensitivity Effects 0.000 claims 1
- 238000002266 amputation Methods 0.000 abstract description 13
- 230000000007 visual effect Effects 0.000 abstract description 2
- 210000003414 extremity Anatomy 0.000 description 67
- 238000002567 electromyography Methods 0.000 description 7
- 230000006870 function Effects 0.000 description 6
- 238000010586 diagram Methods 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 5
- 230000003796 beauty Effects 0.000 description 2
- 210000000245 forearm Anatomy 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 230000008447 perception Effects 0.000 description 2
- 230000000638 stimulation Effects 0.000 description 2
- 241001062009 Indigofera Species 0.000 description 1
- 210000003447 amputation stump Anatomy 0.000 description 1
- 210000001367 artery Anatomy 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 239000002537 cosmetic Substances 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000008676 import Effects 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000000192 social effect Effects 0.000 description 1
- 238000001228 spectrum Methods 0.000 description 1
- 210000000623 ulna Anatomy 0.000 description 1
- 210000003462 vein Anatomy 0.000 description 1
- 230000035899 viability Effects 0.000 description 1
Classifications
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61F—FILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS
- A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
- A61F2/50—Prostheses not implantable in the body
- A61F2/68—Operating or control means
- A61F2/70—Operating or control means electrical
- A61F2/72—Bioelectric control, e.g. myoelectric
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61F—FILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS
- A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
- A61F2/50—Prostheses not implantable in the body
- A61F2/68—Operating or control means
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61F—FILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS
- A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
- A61F2/50—Prostheses not implantable in the body
- A61F2/68—Operating or control means
- A61F2002/6827—Feedback system for providing user sensation, e.g. by force, contact or position
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61F—FILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS
- A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
- A61F2/50—Prostheses not implantable in the body
- A61F2/68—Operating or control means
- A61F2002/6881—Operating or control means optical
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- Health & Medical Sciences (AREA)
- Cardiology (AREA)
- Oral & Maxillofacial Surgery (AREA)
- Transplantation (AREA)
- Engineering & Computer Science (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Vascular Medicine (AREA)
- Life Sciences & Earth Sciences (AREA)
- Animal Behavior & Ethology (AREA)
- General Health & Medical Sciences (AREA)
- Public Health (AREA)
- Veterinary Medicine (AREA)
- Prostheses (AREA)
Abstract
The invention discloses a kind of two-way deformed limb interface systems for controlling and perceiving for prosthetic hand, it is related to patients with amputation rehabilitation and dexterous artificial limb Intelligent control field, including information collection and feedback module, signal decoding and feedback encoding module, prosthesis control and sensing module, computer assisted training software；Information collection acquires deformed limb bio signal with feedback module, and signal decoding is parsed with feedback encoding module and decodes movement instruction；The sensory feedback pattern of artificial limb is passed to signal decoding and feedback encoding module by prosthesis control with sensing module, and signal decoding is encoded with feedback encoding module and passes to information collection and feedback module；Signal is decoded also radios to computer assisted training software with feedback encoding module by deformed limb bio signal.The present invention had not only realized visual control to multiple degrees of freedom dexterity artificial limb, but also can perceive the crawl information of artificial limb, and patient can be helped to grasp the control method of dexterous artificial limb rapidly.
Description
Technical field
The present invention relates to patients with amputation rehabilitations and dexterous artificial limb Intelligent control field more particularly to one kind to control in prosthetic hand
With the two-way deformed limb interface system of perception.
Background technology
Disabled population of China enormous amount, it is to improve disabled living quality of patients and help the disabled that limb function, which is substituted with rehabilitation appliances,
The indispensable people's livelihood equipment of poverty alleviation.Patients with amputation work and viability decline caused by losing hand, it has also become can not
The social concern of avoidance.The most of physical disabilities patients in China do not obtain effective rehabilitation at present.On the whole, it is existing
High-performance dexterity artificial limb is on the high side, has exceeded the ability to bear of most of patients with amputation；And the artificial limb work(of relative low price
It can be generally insufficient with performance.Patients with amputation is most of or wears beauty artificial limb, and the number of applications of this cosmetic limb accounts for about
More than half of artificial limb market, but beauty artificial limb does not have operating function, is helpless to disabled person and restores live and work ability.It is existing
Functional artificial limb main product be single-degree-of-freedom artificial limb, and such artificial limb can be only done simple clipping operation, it is difficult to full
The life requirement of sufficient patients with amputation.
The multi-freedom artificial limb of external import and domestic more finger prosthesis are dexterous enough in structure, but its myoelectricity
Interface is still traditional switch control, passes through frequent contraction of muscle and realizes switching between degree of freedom so that prosthesis control is cumbersome,
It is unnatural.The mode identification technology of electromyography signal realizes the intuitive mapping that nature contraction of muscle is acted to prosthetic hand, but also not
Business artificial limb application is converted into, and the rehabilitation training that most of patients with amputation take a long time could be grasped from laboratory research
Control skill.In addition, current artificial limb interface only focuses on the positive information transmitted, ignore artificial limb seized condition of control instruction
Feedback, patient lack the perceptibility to artificial limb.If patients with amputation cannot experience touching, pressure, sliding during prosthetic hand captures
Perception informations are waited, can largely influence the acceptance of artificial limb.Just because of the handling of artificial limb it is low and lack perceive it is anti-
Feedback, it is relatively low that the artificial limb of patients with amputation installs and uses ratio.
Therefore, those skilled in the art is dedicated to developing a kind of two-way deformed limb interface controlled for prosthetic hand with perceiving
System for improving the quality of life of physical disabilities patient, the group being helped to restore life and part ability to work, has important
Social effect and economic value.
Invention content
In view of the drawbacks described above of the prior art, the technical problems to be solved by the invention can be realized to multiple degrees of freedom
The visual control of dexterous artificial limb, and the crawl information of artificial limb can be perceived, computer assisted training software can help patient rapid
Grasp the control method of dexterous artificial limb.
To achieve the above object, the present invention provides a kind of two-way deformed limb interface systems for controlling and perceiving for prosthetic hand
System.
In the better embodiment of the present invention, a kind of two-way deformed limb interface system controlled for prosthetic hand with perceiving,
It is instructed including information collection and feedback module, signal decoding with feedback encoding module, prosthesis control and sensing module, area of computer aided
Practice software；Collected deformed limb bio signal is transmitted to signal decoding and feedback encoding module, letter by information collection with feedback module
Number decoding parses the bio signal and sends the movement instruction decoded to prosthesis control with feedback encoding module
With sensing module controlling the operation of artificial limb；The sensory feedback pattern of artificial limb is passed to signal by prosthesis control with sensing module
Decoding and feedback encoding module, signal decoding encode feedback model with feedback encoding module and are passed feedback stimulus signal
Pass information collection and feedback module；Signal decode information collection can also be acquired with feedback encoding module with feedback module it is residual
Limb bio signal radios to computer assisted training software, and rehabilitation training is carried out by virtual artificial limb.
Further, described information acquisition includes at least biosensor of four-way, at least a channel with feedback module
Stimulator and retractable structure, biosensor and the stimulator are worn on deformed limb by retractable structure.
Further, the biosensor is myoelectricity or near infrared spectrum or flesh sound or the combination sensor of three, is used
To acquire the corresponding bio signal of deformed limb muscle activity.
Further, the stimulator is egersimeter or vibrations stimulator or combination, deformed limb to be stimulated to produce
The feelings such as raw tactile, pressure, sliding.
Further, it is real using metal electrode film and filtering and amplifying circuit when the biosensor is myoelectric sensor
It is existing；The biosensor is near infrared light time spectrum, is realized using near-infrared light source and photodetector；The biosensor
During for flesh sound sensor, realized using highly sensitive microphone or micro-acceleration gauge or piezoelectric transducer and filtering and amplifying circuit.
Further, signal decoding and feedback encoding module include digital signal processing chip, memory chip, wireless
Chip and peripheral circuit.
Further, with feedback encoding module there are two types of working method, working method one includes training mode for signal decoding
With use mode, be connected with prosthesis control with sensing module；Working method two is wireless communication modalities, with computer assisted training
Software is connected.
Further, the prosthesis control includes control chip, driving circuit and rechargeable battery with sensing module, will transport
The instruction morphing driving control signal for prosthetic hand motor is moved, while the perceptual signal of prosthetic hand is converted into feedback model.
Further, when the signal decoding operates in the training mode of working method one with feedback encoding module, signal
Decoding sends training movement instruction with feedback encoding module and performs setting successively to prosthesis control and sensing module control prosthetic hand
Training action, patient then with deformed limb follow artificial limb perform respective muscle shrink；Signal decoding is right successively with feedback encoding module
Deformed limb bio signal is digitized processing, data windowing process, feature extraction are handled and trains and obtains linear discriminant analysis point
Class device or support vector machine classifier are stored in the matrix form in the memory chip；It is described to be characterized as the exhausted of bio signal
To average value, zero passage points, slope variation number, waveform length and Parameters of Autoregressive Models；The signal decoding and feedback encoding
The use mode of working method one is automatically switched to after the completion of the training mode of module, is digitized place to bio signal successively
Reason, data windowing process, feature extraction processing and pattern classification processing obtain movement instruction, while carry out arteries and veins to feedback model
It rushes coded treatment and generates feedback stimulus signal.
Further, the linear discriminant analysis grader is expressed as follows：
Wherein μiRepresent that the i-th class acts the characteristics of mean vector of corresponding bio signal, p (ωi) represent the action of the i-th class
Prior probability, ∑ represent bio signal feature vector covariance matrix, by Bayes decision rule judge current signature to
Measure the action classification belonging to x.
Further, the optimization method of the support vector machine classifier is as follows：
s.t.yi(wTφ(xi+b)≥1-ξi
ξi≥0
Wherein w represents the weight matrix of support vector machine classifier；B represents the biasing of support vector machine classifier；L is represented
The quantity of training sample；ξiFor slack variable, effect is to ensure that optimization problem has when different action classifications is distributed overlapping
Solution；C is penalty factor, for controlling regression criterion；Y represents indicator vector；φ represents the kernel function of support vector machine classifier,
Selection Gaussian radial basis function is kernel function.
Further, when the signal decoding operates in the wireless communication modalities of working method two with feedback encoding module,
The bio signal of digitized processing is wirelessly transmitted to the computer assisted training software, while wireless receiving area of computer aided
The feedback model of training software generation simultaneously carries out pulse code processing generation feedback stimulus signal.
Further, the computer assisted training software includes bio signal display interface, virtual artificial limb interface and instruction
Practice interface；The computer assisted training software bio signal is carried out successively data windowing processes, feature extraction processing and
Pattern classification processing show that movement instruction controls virtual prosthetic hand action, while the perceptual signal of virtual prosthetic hand is converted into instead
Feedback pattern；The absolute average for being characterized as bio signal, zero passage points, slope variation number, waveform length and autoregression mould
Shape parameter；The pattern classification is linear discriminant analysis or support vector machines, can be obtained by the training of training interface.
Compared with prior art, the advantageous effect brought of the present invention is：
1) intuitive manipulation of the patients with amputation deformed limb to artificial limb can be achieved, be obviously improved the handling of dexterous artificial limb, promote
The upgrading of prosthesis control interfacing；
2) perceptible feedback channel is established, the bi-directional ring of amputation stump and artificial limb is formd, user is allowed to experience vacation
Acceptance of the patients with amputation to artificial limb can be substantially improved in the mode of operation of limb；
3) the computer assisted training software provided reduces dependence of the rehabilitation training to specialist of patients with amputation, profit
The using skill of Multifunction artificial limb is quickly grasped convenient for patient with virtual training platform, returns normal life early.
The technique effect of the design of the present invention, concrete structure and generation is described further below with reference to attached drawing, with
It is fully understood from the purpose of the present invention, feature and effect.
Description of the drawings
Fig. 1 is the two-way deformed limb interface system group controlled for prosthetic hand with perceiving of the preferred embodiment of the present invention
Into schematic diagram；
Fig. 2 is the system structure diagram of presently preferred embodiments of the present invention；
Fig. 3 is the electromyographic signal collection flow chart of presently preferred embodiments of the present invention；
Fig. 4 is that the information collection of presently preferred embodiments of the present invention and feedback module are worn on deformed limb schematic diagram；
Fig. 5 is the signal processing flow figure of presently preferred embodiments of the present invention；
Fig. 6 is the computer assisted training software interface schematic diagram of presently preferred embodiments of the present invention.
Wherein, 100- signal acquisitions and feedback module, 101- myoelectric sensors, 102- myoelectricity reference electrodes, 103- myoelectricities
Differential electrode, 104- signal bus male connectors, the decoding of 200- signals and feedback encoding module, 201- status switches, 202- signals are total
Line female, 203- controlling bus females, 300- prosthesis controls and sensing module, 301- controlling bus male connectors, 302- battery contacts,
303- prosthetic hand interfaces, 400- forearm deformed limbs, 401- deformed limb skins, 402- deformed limb radius, 403- deformed limb ulnas.
Specific embodiment
Multiple preferred embodiments of the present invention are introduced below with reference to Figure of description, make its technology contents more clear and just
In understanding.The present invention can be emerged from by many various forms of embodiments, and protection scope of the present invention not only limits
The embodiment that Yu Wenzhong is mentioned.
In the accompanying drawings, the identical component of structure is represented with same numbers label, everywhere the similar component of structure or function with
Like numeral label represents.The size and thickness of each component shown in the drawings are to be arbitrarily shown, and there is no limit by the present invention
The size and thickness of each component.In order to make diagram apparent, some places suitably exaggerate the thickness of component in attached drawing.
As depicted in figs. 1 and 2, the two-way deformed limb interface system for controlling and perceiving for prosthetic hand of the invention includes information
Acquisition and feedback module 100, signal decoding and feedback encoding module 200, prosthesis control and sensing module 300 and area of computer aided
Training software.Information collection passes through signal bus male connector 104 and signal decoding and feedback encoding module 200 with feedback module 100
Signal bus female 202 connect, by collected deformed limb bio signal be transmitted to signal decoding with feedback encoding module 200.Letter
Number decoding passes through controlling bus female 203 and prosthesis control with feedback encoding module 200 and the controlling bus of sensing module 300 is public
First 301 connection.Signal, which is decoded, to be parsed bio signal with feedback encoding module 200 and is transmitted the movement instruction decoded
To prosthesis control and sensing module 300 to control the operation of artificial limb, prosthesis control passes through prosthetic hand interface with sensing module 300
303 are connected with artificial limb.The sensory feedback pattern of artificial limb is passed to signal decoding with sensing module 300 and is compiled with feedback by prosthesis control
Code module 200, signal decoding encode feedback model with feedback encoding module 200 and feedback stimulus signal are passed to letter
Breath acquisition and feedback module 100.Signal decoding can also acquire information collection and feedback module 100 with feedback encoding module 200
Deformed limb bio signal radio to computer assisted training software, by virtual artificial limb carry out rehabilitation training.
Information collection in the embodiment contains 101 and one channel of myoelectric sensor of eight channels with feedback module 100
Vibratory stimulation device, vibratory stimulation device can be integrated in any myoelectric sensor 101.Myoelectric sensor 101 is referred to by myoelectricity
Electrode 102 and myoelectricity differential electrode 103 acquire deformed limb electromyography signal.As shown in figure 3, myoelectric sensor 101 has been internally integrated and has put
For big filter circuit to acquire the electromyography signal of high quality, the bandwidth of wave filter is set as 20~450Hz.When it is implemented, such as Fig. 4
Shown, information collection and the thickness of the myoelectric sensor 101 of feedback module 100 are can be controlled within 5mm, according to amputation user's
400 situation of forearm deformed limb, is integrated in customized prosthetic socket and is steadily contacted with deformed limb skin 401.
Signal is decoded includes digital signal processing chip stm32F4, memory chip, bluetooth core with feedback encoding module 200
The pcb board of piece and peripheral circuit composition.Signal is decoded with feedback encoding module 200 there are two types of working method, and working method one is wrapped
It includes trained mode and using mode, is connected with prosthesis control with sensing module 300；Second working method is switched to radio communication mold
State is connected with computer assisted training software.It is working method one that signal, which is decoded with the default conditions of feedback encoding module 200,.
Computer assisted training software is furnished with Bluetooth adapter, only signal decoding and the Bluetooth chip and indigo plant of feedback encoding module 200
When tooth adapter successfully matches, signal decoding is just switched to working method two, i.e. radio communication mold with feedback encoding module 200
State.
Prosthesis control includes control chip MSP430, driving circuit with sensing module 300, is connected by battery contact 302
Rechargeable battery.Movement instruction can be converted into the driving control signal of prosthetic hand motor with sensing module 300 by prosthesis control, together
When the perceptual signal of prosthetic hand is converted into feedback model.
Signal is decoded operates in working method for the moment with feedback encoding module 200, and long-press status switch 201 can enter training
Mode, signal decoding send training movement instruction with feedback encoding module 200 and control artificial limb to prosthesis control and sensing module 300
Hand performs the training action of setting successively, and patient then follows artificial limb to perform respective muscle contraction with deformed limb.As shown in figure 5, training
After, signal decoding is with feedback encoding module 200 successively to the deformed limb electromyography signal of acquisition is digitized processing, data add
Window processing, feature extraction are handled and are trained and obtain linear discriminant analysis grader, are stored in memory chip in the matrix form.Institute
The feature of extraction is joined for the absolute average of electromyography signal, zero passage points, slope variation number, waveform length and autoregression model
Number.Signal is automatically switched to after the completion of decoding the training mode with feedback encoding module 200 using mode, successively to electromyography signal
It is digitized processing, data windowing process, feature extraction processing and pattern classification processing and obtains movement instruction, while to anti-
Feedback pattern carries out pulse code processing and generates feedback stimulus signal.Subsequently in use, after the power is turned on without be instructed again to model
Practice, short-press status switch 201 is directly entered using mode.
When signal decodes and feedback encoding module 200 operates in the wireless communication modalities of working method two, it can will digitize
The electromyography signal of processing is by Bluetooth transmission to computer assisted training software, while wireless receiving computer assisted training software
The feedback model of generation simultaneously carries out pulse code processing generation feedback stimulus signal.As shown in fig. 6, computer assisted training software
Including bio signal display interface, virtual artificial limb interface and training interface.The flow of computer assisted training software signal processing
It is decoded with signal identical with the working method one of feedback encoding module 200.
The preferred embodiment of the present invention described in detail above.It should be appreciated that the ordinary skill of this field is without wound
The property made labour, which according to the present invention can conceive, makes many modifications and variations.Therefore, all technician in the art
Pass through the available technology of logical analysis, reasoning, or a limited experiment on the basis of existing technology under this invention's idea
Scheme, all should be in the protection domain being defined in the patent claims.
Claims (10)
1. a kind of two-way deformed limb interface system for being used for prosthetic hand and controlling and perceiving, which is characterized in that including information collection and instead
Present module, signal decoding and feedback encoding module, prosthesis control and sensing module, computer assisted training software；Described information
Collected deformed limb bio signal is transmitted to the signal decoding and feedback encoding module, the signal solution by acquisition with feedback module
Code parses the bio signal with feedback encoding module and sends the movement instruction decoded to the prosthesis control
With sensing module controlling the operation of artificial limb；The prosthesis control passes to the sensory feedback pattern of artificial limb with sensing module
The signal decoding and feedback encoding module, the signal decoding encode feedback model with feedback encoding module and will be anti-
Feedback stimulus signal passes to described information acquisition and feedback module；The signal decoding is with feedback encoding module also by described information
The deformed limb bio signal of acquisition and feedback module acquisition radios to the computer assisted training software, by virtual artificial limb
Carry out rehabilitation training.
2. the two-way deformed limb interface system with perceiving is controlled for prosthetic hand as described in claim 1, which is characterized in that described
Described information is acquired includes at least biosensor of four-way, at least stimulator of a channel and scalable knot with feedback module
Structure is worn on the biosensor and the stimulator on deformed limb by the retractable structure.
3. the two-way deformed limb interface system with perceiving is controlled for prosthetic hand as claimed in claim 2, which is characterized in that described
Biosensor is myoelectricity or near infrared spectrum or flesh sound or the combination sensor of three, is corresponded to acquire deformed limb muscle activity
Bio signal, the stimulator is egersimeter or vibrations stimulator or combination, to stimulate deformed limb generate touch,
Pressure, sliding feeling.
4. the two-way deformed limb interface system with perceiving is controlled for prosthetic hand as claimed in claim 3, which is characterized in that described
When biosensor is myoelectric sensor, realized using metal electrode film and filtering and amplifying circuit；The biosensor is near
During infrared spectrum, realized using near-infrared light source and photodetector；When the biosensor is flesh sound sensor, using height
Sensitivity microphones or micro-acceleration gauge or piezoelectric transducer and filtering and amplifying circuit are realized.
5. the two-way deformed limb interface system with perceiving is controlled for prosthetic hand as described in claim 1, which is characterized in that described
Signal is decoded includes digital signal processing chip, memory chip, wireless chip and peripheral circuit with feedback encoding module.
6. the two-way deformed limb interface system controlled for prosthetic hand with perceiving as described in claim 1 or 5, which is characterized in that
With feedback encoding module there are two types of working method, working method one includes training mode and using mode for signal decoding, with
Prosthesis control is connected with sensing module；Working method two is wireless communication modalities, is connected with computer assisted training software.
7. the two-way deformed limb interface system with perceiving is controlled for prosthetic hand as described in claim 1, which is characterized in that described
Prosthesis control includes control chip, driving circuit and rechargeable battery with sensing module, and movement instruction is converted into artificial limb flashlight
The driving control signal of machine, while the perceptual signal of prosthetic hand is converted into feedback model.
8. the two-way deformed limb interface system with perceiving is controlled for prosthetic hand as claimed in claim 6, which is characterized in that described
When the signal decoding operates in the training mode of working method one with feedback encoding module, the signal decoding and feedback encoding
Module sends the training action that training movement instruction performs setting to the prosthesis control and sensing module control prosthetic hand successively,
Patient follows artificial limb to perform respective muscle contraction with deformed limb；The signal decoding successively believes deformed limb biology with feedback encoding module
Number it is digitized processing, data windowing process, feature extraction are handled and trained and obtain linear discriminant analysis grader or support
Vector machine classifier is stored in the matrix form in the memory chip；The absolute average for being characterized as bio signal, mistake
Zero number, slope variation number, waveform length and Parameters of Autoregressive Models；The signal decoding and the training mould of feedback encoding module
The use mode of working method one is automatically switched to after the completion of state, is digitized processing, data adding window to bio signal successively
Processing, feature extraction processing and pattern classification processing obtain movement instruction, while carry out pulse code processing to feedback model
Generate feedback stimulus signal.
9. the two-way deformed limb interface system with perceiving is controlled for prosthetic hand as claimed in claim 6, which is characterized in that described
When signal decodes and feedback encoding module operates in the wireless communication modalities of working method two, by the bio signal of digitized processing
It is wirelessly transmitted to the computer assisted training software, while the feedback that computer assisted training software described in wireless receiving generates
Pattern simultaneously carries out pulse code processing generation feedback stimulus signal.
10. the two-way deformed limb interface system with perceiving is controlled for prosthetic hand as described in claim 1, which is characterized in that institute
It states computer assisted training software and includes bio signal display interface, virtual artificial limb interface and training interface；The computer aided manufacturing
Training software is helped to carry out data windowing process, feature extraction processing and pattern classification processing to bio signal successively and obtains movement
Instruction controls virtual prosthetic hand action, while the perceptual signal of virtual prosthetic hand is converted into feedback model；The feature is made a living
The absolute average of object signal, zero passage points, slope variation number, waveform length and Parameters of Autoregressive Models；The pattern classification
For linear discriminant analysis or support vector machines, can be obtained by the training of training interface.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109846582A (en) * | 2019-03-20 | 2019-06-07 | 上海交通大学 | A kind of electric stimulation based on multi-modal perceptible feedback |
| CN110811940A (en) * | 2019-10-31 | 2020-02-21 | 中国科学院长春光学精密机械与物理研究所 | Intelligent artificial limb device and control method |
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| CN110824970A (en) * | 2018-08-13 | 2020-02-21 | 珠海格力电器股份有限公司 | Household appliance control method and device and brain-computer interface |
| CN111297322A (en) * | 2018-12-12 | 2020-06-19 | 财团法人工业技术研究院 | Physiological signal sensing system and method |
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| CN111297322B (en) * | 2018-12-12 | 2023-09-26 | 财团法人工业技术研究院 | Physiological signal sensing system and method |
| CN109846582A (en) * | 2019-03-20 | 2019-06-07 | 上海交通大学 | A kind of electric stimulation based on multi-modal perceptible feedback |
| CN109846582B (en) * | 2019-03-20 | 2021-05-28 | 上海交通大学 | Electrical stimulation system based on multi-mode perception feedback |
| CN110811940A (en) * | 2019-10-31 | 2020-02-21 | 中国科学院长春光学精密机械与物理研究所 | Intelligent artificial limb device and control method |
| CN113367862A (en) * | 2021-06-07 | 2021-09-10 | 中国科学院深圳先进技术研究院 | Feedback joint |
| CN113367862B (en) * | 2021-06-07 | 2022-05-17 | 中国科学院深圳先进技术研究院 | Feedback joint |
| CN114681172A (en) * | 2022-03-11 | 2022-07-01 | 哈尔滨工业大学 | Modular closed-loop artificial limb control system for upper limb amputation patient |
| CN114681172B (en) * | 2022-03-11 | 2024-05-14 | 哈尔滨工业大学 | Modularized closed-loop artificial limb control system for upper limb amputee |
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