CN109976522A - A kind of man-machine interaction method stopping triggering with brain wave perception based on human eye vision - Google Patents
A kind of man-machine interaction method stopping triggering with brain wave perception based on human eye vision Download PDFInfo
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- CN109976522A CN109976522A CN201910225122.3A CN201910225122A CN109976522A CN 109976522 A CN109976522 A CN 109976522A CN 201910225122 A CN201910225122 A CN 201910225122A CN 109976522 A CN109976522 A CN 109976522A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/011—Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
- G06F3/013—Eye tracking input arrangements
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/011—Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
- G06F3/015—Input arrangements based on nervous system activity detection, e.g. brain waves [EEG] detection, electromyograms [EMG] detection, electrodermal response detection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/06—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
- G06N3/061—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using biological neurons, e.g. biological neurons connected to an integrated circuit
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/082—Learning methods modifying the architecture, e.g. adding, deleting or silencing nodes or connections
Abstract
The invention discloses a kind of man-machine interaction methods that triggering with brain wave perception are stopped based on human eye vision, interactive function is triggered based on automatic detection identification human eye data, it realizes and is focused by being stopped in specified region human eye, recognize human eye data, triggering interaction starts to carry out, and human body electroencephalogram's wave signal is read automatically, and all kinds of emotions of the people at that time are identified in conjunction with brain wave technology, mood, the state of mind such as state realize all kinds of scenes of suitable this person in real time or function interaction, it realizes and carries out the triggering of human-computer interaction by automatic identification human eye when human eye vision stops in wider distance range and read human body electroencephalogram's wave signal automatically to carry out human-computer interactive control.
Description
Technical field
The invention belongs to man-machine interaction method technical fields, and in particular to one kind stops triggering and brain electricity based on human eye vision
The man-machine interaction method of wave perception.
Background technique
Human brain is made of tens neurons, and the total length of aixs cylinder is about 170000 kilometers.Whenever generation one
When idea, brain will generate associated there, faint but clearly electric signal.These electric pulses are by between neuron
Chemical reaction generate, therefore can recorde and measure.Research before this is that these brain waves are inputted computer, borrows
It helps computer to receive these signals and then responds or make a series of actions.
Based on brain wave mechanics of communication, field of human-computer interaction can be applied to, realize the human-computer interaction for reading core type, complete more
Add intelligentized interactive function.Currently, to be all based on numerous human input devices substantially autonomous by the signal of human body for human-computer interaction
Input interacts movement further according to the signal of input, while the application of human body electroencephalogram's wave is also limited to wearing and accessible formula
Equipment cannot achieve the touching that human-computer interaction is carried out by automatic identification human eye when human eye vision stops in wider distance range
Hair and automatic human body electroencephalogram's wave signal that reads carry out human-computer interactive control.
Summary of the invention
It is an object of the invention to: it solves current human-computer interaction and is all based on numerous human input devices substantially for human body
Signal interacts movement from primary input, further according to the signal of input, at the same the application of human body electroencephalogram's wave be also limited to wearing and
Accessible formula equipment cannot achieve man-machine by automatic identification human eye progress when human eye vision stops in wider distance range
Interactive triggering and automatic the problem of reading human body electroencephalogram's wave signal progress human-computer interactive control.
The technical solution adopted by the invention is as follows:
A kind of man-machine interaction method stopping triggering with brain wave perception based on human eye vision, method and step include:
Step 1, by include be not fixed installation be located at air chip sensor of the specified region with sensitive chip and
Any or combined mode of the image capture module of fixed installation acquires identification human eyeball's data, and is recognizing human body
Sensor or image capture module export trigger signal to central processing unit after eye data；
Step 2 passes through the air chip sensor perception human body brain with electric wave detection including distribution setting in place
Electric wave and human body electroencephalogram's wave, the centre are perceived with any or combined mode of the brain wave sensor of human contact's formula
Reason device controls air chip sensor by communication network after receiving trigger signal or brain wave sensor starts to work and acquires people
Body eeg signal；
Step 3, human body electroencephalogram's wave signal data are transmitted to central processing unit by communication network, and central processing unit will
Online learning methods of the collected human body electroencephalogram's wave signal Jing Guo deep learning obtain human body state of mind data；
Obtained human body state of mind data are transmitted to man-machine friendship by communication network by step 4, the central processing unit
Mutual equipment, human-computer interaction device interact according to human body state of mind data.
Further, identification human eyeball's data method includes following any one or more combined modes: to photosensitive
Chip or image capture module acquired image carry out body iris identification, collect to sensitive chip or image capture module
Multiple image using human eye vision persist rotation imaging establish complete stereo-picture, identify people from complete stereo-picture
Eye eyeball image.
Further, the air chip include include being made of microprocessor, two-way radios device, wireless network
SMART DUST, as soon as the SMART DUST is dissipated some micronic dusts in place by wireless network, they can mutually determine
Position further collects data by two-way radios device and transmits information to microprocessor, and the microprocessor is to base station
Cloud library of factors transmit information；It further include the unfixed air chip of form, the air chip includes sequentially connected
One electrode layer, function material layer, the second electrode lay；It further include the third operation layer being connect with the second electrode lay and cloud transmitting
Layer, in which: the first electrode layer is for simulating the postsynaptic, and the second electrode lay is for simulating the presynaptic, the function material
The material of the bed of material is chalcogenide compound, and the conductance of the function material layer is for simulating synapse weight；By to first electricity
Pole layer applies the second pulse signal to simulate postsynaptic stimulation, by applying the first pulse signal to the second electrode lay come mould
Quasi- presynaptic stimulation；The resistance of the function material layer is used to simulate the excitation state or tranquillization state of biological neuron；The third
Height of the operation layer for air chip is bionical, extracts operation analog functuion, and simulation biological neuron completes high intelligent operation, and will
Operational data is uploaded to the storage of cloud library of factors by cloud transfer layer；The behavior of the neural network is determined by the network architecture
Fixed, the network architecture includes: neuron number, the number of plies, connection type between layers, is attached on SMART DUST and micro- place
Manage device connection eeg signal capture module and sensitive chip, sensitive chip by the optical signal of acquisition be converted to electric signal and by
Microprocessor is converted to image data, and air chip carries out human body electroencephalogram's wave signal capture by SMART DUST, and SMART DUST is logical
It crosses wireless network and receives control signal.
Further, the method for human body state of mind data being obtained by human body electroencephalogram's wave signal in the step 3 are as follows:
History human body electroencephalogram's wave signal data is carried out state of mind classification by step 3.1, by the human body brain of each classification
Electric wave signal data carry out independent component analysis and carry out cognitive potential extraction and analysis to each independent element；
Step 3.2 passes through deep learning model to the data comprising tag along sort for each classification that step 3.1 obtains
Training is extracted the feature of the global and local information of cognitive potential comprising every a kind of eeg signal, is carried out to this feature linear
Deep learning model training is completed in discriminant analysis；
Step 3.3, the collected human body electroencephalogram's wave signal of step 2 is carried out independent component analysis and to each independence at
Divide and carry out cognitive potential extraction and analysis, the trained deep learning model of data input step 3.2 that will be obtained obtains human body essence
Refreshing status categories data.
Further, the human-computer interaction device includes intelligent control device and intelligent display device, intelligent display device
It include immersion line holographic projections, air imaging system.
Further, human body electroencephalogram's wave signal transmits in a communication network is transmitted using the method for compressed sensing.
Further, the communication network uses 5G communication network.
In conclusion by adopting the above-described technical solution, the beneficial effects of the present invention are:
1, in the present invention, interactive function is triggered based on automatic detection identification human eye data, is realized by specified region
Human eye, which stops, to be focused, and recognizes human eye data, triggering interaction starts to carry out, and reads human body electroencephalogram's wave signal automatically, and combine
Brain wave technology identifies that the state of mind such as the people's all kinds of emotions at that time, mood, state realize that suitable this person's in real time is all kinds of
Scene or function interaction, realize and carry out man-machine friendship by automatic identification human eye when human eye vision stops in wider distance range
Mutual triggering and automatic human body electroencephalogram's wave signal that reads carry out human-computer interactive control.By photosensitive including being not fixed having for installation
Any or combined mode of the image capture module of the air chip sensor and fixed installation of chip acquires identification human body
, it can be achieved that more flexible human eye data identify, the identification device position range for being not limited by fixed setting limits eye data,
By including being distributed air chip sensor perception human body electroencephalogram's wave of setting in place and being passed with the brain wave of human contact's formula
Any or combined mode of sensor perceives human body electroencephalogram's wave, realizes remote active probe human body electroencephalogram wave signal, will not
Receiving present brain wave detecting devices must be the limitation that contact equipment was worn and installed to human body.
2, in the present invention, the human body state of mind is obtained by human body electroencephalogram's wave signal using the method for neural-network learning model
Data, data-handling efficiency is high, and accuracy rate is high.
3, in the present invention, human body electroencephalogram's wave signal transmits in a communication network to be transmitted using the method for compressed sensing,
It is first converted to two systems coding and carries out compression transmission, then be decoded reading, can satisfy the remote transmission of brain wave data, energy
Enough meet more application scenarios.
Detailed description of the invention
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below will be to needed in the embodiment attached
Figure is briefly described, it should be understood that the following drawings illustrates only certain embodiments of the present invention, therefore is not construed as pair
The restriction of range for those of ordinary skill in the art without creative efforts, can also be according to this
A little attached drawings obtain other relevant attached drawings.
Fig. 1 is the method for the present invention flow chart.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that described herein, specific examples are only used to explain the present invention, not
For limiting the present invention, i.e., described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is logical
The component for the embodiment of the present invention being often described and illustrated herein in the accompanying drawings can be arranged and be designed with a variety of different configurations.
Therefore, the detailed description of the embodiment of the present invention provided in the accompanying drawings is not intended to limit below claimed
The scope of the present invention, but be merely representative of selected embodiment of the invention.Based on the embodiment of the present invention, those skilled in the art
Member's every other embodiment obtained without making creative work, shall fall within the protection scope of the present invention.
It should be noted that the relational terms of term " first " and " second " or the like be used merely to an entity or
Operation is distinguished with another entity or operation, and without necessarily requiring or implying between these entities or operation, there are any
This actual relationship or sequence.Moreover, the terms "include", "comprise" or its any other variant be intended to it is non-exclusive
Property include so that include a series of elements process, method, article or equipment not only include those elements, but also
Further include other elements that are not explicitly listed, or further include for this process, method, article or equipment it is intrinsic
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including described
There is also other identical elements in the process, method, article or equipment of element.
A kind of man-machine interaction method stopping triggering with brain wave perception based on human eye vision, method and step include:
Step 1, by include be not fixed installation be located at air chip sensor of the specified region with sensitive chip and
Any or combined mode of the image capture module of fixed installation acquires identification human eyeball's data, and is recognizing human body
Sensor or image capture module export trigger signal to central processing unit after eye data；
Step 2 passes through the air chip sensor perception human body brain with electric wave detection including distribution setting in place
Electric wave and human body electroencephalogram's wave, the centre are perceived with any or combined mode of the brain wave sensor of human contact's formula
Reason device controls air chip sensor by communication network after receiving trigger signal or brain wave sensor starts to work and acquires people
Body eeg signal；
Step 3, human body electroencephalogram's wave signal data are transmitted to central processing unit by communication network, and central processing unit will
Online learning methods of the collected human body electroencephalogram's wave signal Jing Guo deep learning obtain human body state of mind data；
Obtained human body state of mind data are transmitted to man-machine friendship by communication network by step 4, the central processing unit
Mutual equipment, human-computer interaction device interact according to human body state of mind data.
The present invention is based on automatic detection identification human eye data to trigger interactive function, realize by stopping in specified region human eye
Focusing is stayed, recognizes human eye data, triggering interaction starts to carry out, and reads human body electroencephalogram's wave signal automatically, and combines brain wave
Technology identify the state of mind such as the people's all kinds of emotions at that time, mood, state realize all kinds of scenes of suitable this person in real time or
The touching that human-computer interaction is carried out by automatic identification human eye when human eye vision stops in wider distance range is realized in function interaction
Hair and automatic human body electroencephalogram's wave signal that reads carry out human-computer interactive control.By include be not fixed installation with sensitive chip
Any or combined mode of air chip sensor and the image capture module of fixed installation acquires identification human eyeball's number
According to, it can be achieved that more flexible human eye data identify, the identification device position range for being not limited by fixed setting is limited, and passes through packet
Include be distributed in place setting air chip sensor perception human body electroencephalogram's wave and with the brain wave sensor of human contact's formula
Any or combined mode perceives human body electroencephalogram's wave, realizes remote active probe human body electroencephalogram wave signal, not will receive existing
It must be the limitation that contact equipment was worn and installed to human body in brain wave detecting devices.
Further, identification human eyeball's data method includes following any one or more combined modes: to photosensitive
Chip or image capture module acquired image carry out body iris identification, collect to sensitive chip or image capture module
Multiple image using human eye vision persist rotation imaging establish complete stereo-picture, identify people from complete stereo-picture
Eye eyeball image.Body iris identification can pass through body iris training set data using the method for neural network model training
Training neural network model, the image data and image capture module that air chip is acquired by sensitive chip are collected
Image data inputs neural network model, obtains eye image data recognition result.
Further, the air chip include include being made of microprocessor, two-way radios device, wireless network
SMART DUST, as soon as the SMART DUST is dissipated some micronic dusts in place by wireless network, they can mutually determine
Position further collects data by two-way radios device and transmits information to microprocessor, and the microprocessor is to base station
Cloud library of factors transmit information；It further include the unfixed air chip of form, the air chip includes sequentially connected
One electrode layer, function material layer, the second electrode lay；It further include the third operation layer being connect with the second electrode lay and cloud transmitting
Layer, in which: the first electrode layer is for simulating the postsynaptic, and the second electrode lay is for simulating the presynaptic, the function material
The material of the bed of material is chalcogenide compound, and the conductance of the function material layer is for simulating synapse weight；By to first electricity
Pole layer applies the second pulse signal to simulate postsynaptic stimulation, by applying the first pulse signal to the second electrode lay come mould
Quasi- presynaptic stimulation；The resistance of the function material layer is used to simulate the excitation state or tranquillization state of biological neuron；The third
Height of the operation layer for air chip is bionical, extracts operation analog functuion, and simulation biological neuron completes high intelligent operation, and will
Operational data is uploaded to the storage of cloud library of factors by cloud transfer layer；The behavior of the neural network is determined by the network architecture
Fixed, the network architecture includes: neuron number, the number of plies, connection type between layers, is attached on SMART DUST and micro- place
Manage device connection eeg signal capture module and sensitive chip, sensitive chip by the optical signal of acquisition be converted to electric signal and by
Microprocessor is converted to image data, and air chip carries out human body electroencephalogram's wave signal capture by SMART DUST, and SMART DUST is logical
It crosses wireless network and receives control signal.
Further, the method for human body state of mind data being obtained by human body electroencephalogram's wave signal in the step 3 are as follows:
History human body electroencephalogram's wave signal data is carried out state of mind classification by step 3.1, by the human body brain of each classification
Electric wave signal data carry out independent component analysis and carry out cognitive potential extraction and analysis to each independent element；
Step 3.2 passes through deep learning model to the data comprising tag along sort for each classification that step 3.1 obtains
Training is extracted the feature of the global and local information of cognitive potential comprising every a kind of eeg signal, is carried out to this feature linear
Deep learning model training is completed in discriminant analysis；
Step 3.3, the collected human body electroencephalogram's wave signal of step 2 is carried out independent component analysis and to each independence at
Divide and carry out cognitive potential extraction and analysis, the trained deep learning model of data input step 3.2 that will be obtained obtains human body essence
Refreshing status categories data.
Invention obtains human body state of mind data by human body electroencephalogram's wave signal using the method for neural-network learning model, number
According to treatment effeciency height, accuracy rate is high.Further, the human-computer interaction device includes that intelligent control device and intelligent display are set
Standby, intelligent display device includes immersion line holographic projections, air imaging system.
Further, human body electroencephalogram's wave signal transmits in a communication network is transmitted using the method for compressed sensing.
Human body electroencephalogram's wave signal transmits in a communication network to be transmitted using the method for compressed sensing, is first converted to two systems coding and is carried out
Compression transmission, then it is decoded reading, it can satisfy the remote transmission of brain wave data, can satisfy more applied fields
Scape.
Further, the communication network uses 5G communication network.
Communication network can also use the communication network method of Internet of Things.
Claims (7)
1. a kind of man-machine interaction method for stopping triggering with brain wave perception based on human eye vision, it is characterised in that: method and step
Include:
Step 1 passes through the air chip sensor and the fixation that are located at specified region and have sensitive chip including being not fixed installation
Any or combined mode of the image capture module of installation acquires identification human eyeball's data, and is recognizing human eyeball
Sensor or image capture module export trigger signal to central processing unit after data；
Step 2 passes through air chip sensor perception human body electroencephalogram's wave with electric wave detection including distribution setting in place
Human body electroencephalogram's wave, the central processing unit are perceived with any or combined mode with the brain wave sensor of human contact's formula
Air chip sensor is controlled by communication network after receiving trigger signal or brain wave sensor starts to work and acquires human body brain
Electric wave signal；
Step 3, human body electroencephalogram's wave signal data are transmitted to central processing unit by communication network, and central processing unit will acquire
To online learning methods of human body electroencephalogram's wave signal Jing Guo deep learning obtain human body state of mind data；
Obtained human body state of mind data are transmitted to human-computer interaction by communication network and set by step 4, the central processing unit
Standby, human-computer interaction device interacts according to human body state of mind data.
2. the man-machine interaction method of a kind of Behavior-based control action triggers according to claim 1 and brain wave perception, special
Sign is: identification human eyeball's data method includes following any one or more combined modes: to sensitive chip or figure
As acquisition module acquired image carries out body iris identification, to sensitive chip or the collected multiframe figure of image capture module
Complete stereo-picture is established as persisting rotation imaging using human eye vision, human eye eyeball figure is identified from complete stereo-picture
Picture.
3. the man-machine interaction method of a kind of Behavior-based control action triggers according to claim 1 and brain wave perception, special
Sign is: the air chip include include the intelligent dirt being made of microprocessor, two-way radios device, wireless network
Angstrom, as soon as the SMART DUST is dissipated some micronic dusts in place by wireless network, they can be mutually located, into one
Step collects data by two-way radios device and transmits information, cloud system of the microprocessor to base station to microprocessor
Transmit information in number library；Further include the unfixed air chip of form, the air chip include sequentially connected first electrode layer,
Function material layer, the second electrode lay；It further include the third operation layer being connect with the second electrode lay and cloud transfer layer, in which: institute
First electrode layer is stated for simulating the postsynaptic, the second electrode lay is for simulating the presynaptic, the material of the function material layer
For chalcogenide compound, the conductance of the function material layer is for simulating synapse weight；By applying the to the first electrode layer
Two pulse signals stimulate to simulate the postsynaptic, simulate presynaptic thorn by applying the first pulse signal to the second electrode lay
Swash；The resistance of the function material layer is used to simulate the excitation state or tranquillization state of biological neuron；The third operation layer is used for
The height of air chip is bionical, extracts operation analog functuion, simulation biological neuron completes high intelligent operation, and operational data is led to
It crosses cloud transfer layer and is uploaded to the storage of cloud library of factors；The behavior of the neural network is determined by the network architecture, network
Framework includes: neuron number, the number of plies, connection type between layers, is attached on SMART DUST and connect with microprocessor
Eeg signal capture module and sensitive chip, the optical signal of acquisition is converted to electric signal and by microprocessor by sensitive chip
Image data is converted to, air chip carries out human body electroencephalogram's wave signal capture by SMART DUST, and SMART DUST passes through wireless network
Network receives control signal.
4. the man-machine interaction method of a kind of Behavior-based control action triggers according to claim 1 and brain wave perception, special
Sign is: the method for obtaining human body state of mind data by human body electroencephalogram's wave signal in the step 3 are as follows:
History human body electroencephalogram's wave signal data is carried out state of mind classification by step 3.1, by human body electroencephalogram's wave of each classification
Signal data carries out independent component analysis and carries out cognitive potential extraction and analysis to each independent element；
Step 3.2 instructs the data comprising tag along sort for each classification that step 3.1 obtains by deep learning model
Practice, extracts the feature of the global and local information of cognitive potential comprising every a kind of eeg signal, this feature is linearly sentenced
Deep learning model training Fen Xi not completed；
Step 3.3, the collected human body electroencephalogram's wave signal of step 2 is carried out independent component analysis and to each independent element into
Row cognitive potential extraction and analysis, the trained deep learning model of data input step 3.2 that will be obtained, obtains human body spirit shape
State categorical data.
5. the man-machine interaction method of a kind of Behavior-based control action triggers according to claim 1 and brain wave perception, special
Sign is: the human-computer interaction device includes intelligent control device and intelligent display device, and intelligent display device includes heavy
Immersion line holographic projections, air imaging system.
6. the man-machine interaction method of a kind of Behavior-based control action triggers according to claim 1 and brain wave perception, special
Sign is: human body electroencephalogram's wave signal transmits in a communication network to be transmitted using the method for compressed sensing.
7. the man-machine interaction method of a kind of Behavior-based control action triggers according to claim 1 and brain wave perception, special
Sign is: the communication network uses 5G communication network.
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| CN113608621A (en) * | 2021-08-17 | 2021-11-05 | 融信信息科技有限公司 | Multifunctional AR glasses and interaction method thereof |
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