CN109350051A - The head wearable device and its working method with adjusting are assessed for the state of mind - Google Patents
The head wearable device and its working method with adjusting are assessed for the state of mind Download PDFInfo
- Publication number
- CN109350051A CN109350051A CN201811430882.XA CN201811430882A CN109350051A CN 109350051 A CN109350051 A CN 109350051A CN 201811430882 A CN201811430882 A CN 201811430882A CN 109350051 A CN109350051 A CN 109350051A
- Authority
- CN
- China
- Prior art keywords
- state
- mind
- audio
- module
- subject
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 39
- 238000011156 evaluation Methods 0.000 claims abstract description 54
- 230000008451 emotion Effects 0.000 claims abstract description 16
- 230000000638 stimulation Effects 0.000 claims abstract description 10
- 210000003128 head Anatomy 0.000 claims description 40
- 210000001061 forehead Anatomy 0.000 claims description 29
- 230000036651 mood Effects 0.000 claims description 27
- 238000013527 convolutional neural network Methods 0.000 claims description 18
- 210000004556 brain Anatomy 0.000 claims description 16
- NJPPVKZQTLUDBO-UHFFFAOYSA-N novaluron Chemical compound C1=C(Cl)C(OC(F)(F)C(OC(F)(F)F)F)=CC=C1NC(=O)NC(=O)C1=C(F)C=CC=C1F NJPPVKZQTLUDBO-UHFFFAOYSA-N 0.000 claims description 14
- 238000000605 extraction Methods 0.000 claims description 13
- 230000000994 depressogenic effect Effects 0.000 claims description 11
- 210000000988 bone and bone Anatomy 0.000 claims description 10
- 230000005611 electricity Effects 0.000 claims description 9
- 230000008569 process Effects 0.000 claims description 9
- 238000004891 communication Methods 0.000 claims description 7
- 230000005236 sound signal Effects 0.000 claims description 6
- 238000004458 analytical method Methods 0.000 claims description 4
- 238000000513 principal component analysis Methods 0.000 claims description 4
- 238000002567 electromyography Methods 0.000 claims description 3
- 239000000284 extract Substances 0.000 claims description 3
- 239000000203 mixture Substances 0.000 claims description 3
- 238000010586 diagram Methods 0.000 description 7
- 238000013528 artificial neural network Methods 0.000 description 4
- 238000013135 deep learning Methods 0.000 description 4
- 230000000694 effects Effects 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 230000015572 biosynthetic process Effects 0.000 description 2
- 238000012937 correction Methods 0.000 description 2
- 238000007405 data analysis Methods 0.000 description 2
- 238000013500 data storage Methods 0.000 description 2
- 230000007812 deficiency Effects 0.000 description 2
- 230000005484 gravity Effects 0.000 description 2
- 230000010358 mechanical oscillation Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 210000003625 skull Anatomy 0.000 description 2
- 230000007480 spreading Effects 0.000 description 2
- 238000000547 structure data Methods 0.000 description 2
- 235000013399 edible fruits Nutrition 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000003203 everyday effect Effects 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 238000001727 in vivo Methods 0.000 description 1
- 210000001595 mastoid Anatomy 0.000 description 1
- 230000004630 mental health Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 210000004126 nerve fiber Anatomy 0.000 description 1
- 230000035479 physiological effects, processes and functions Effects 0.000 description 1
- 238000010183 spectrum analysis Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/369—Electroencephalography [EEG]
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/16—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state
- A61B5/165—Evaluating the state of mind, e.g. depression, anxiety
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Psychiatry (AREA)
- Engineering & Computer Science (AREA)
- Surgery (AREA)
- Animal Behavior & Ethology (AREA)
- Pathology (AREA)
- Physics & Mathematics (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Medical Informatics (AREA)
- Molecular Biology (AREA)
- Psychology (AREA)
- Biophysics (AREA)
- General Health & Medical Sciences (AREA)
- Public Health (AREA)
- Veterinary Medicine (AREA)
- Child & Adolescent Psychology (AREA)
- Developmental Disabilities (AREA)
- Educational Technology (AREA)
- Hospice & Palliative Care (AREA)
- Social Psychology (AREA)
- Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
Abstract
The present invention provides a kind of head wearable devices assessed for the state of mind with adjusting, it is characterised in that: includes: the audio playing module for playing out audio source file；For acquiring the physiological signal collection module of subject's physiological signal；Assess to obtain the state of mind evaluation module that state of mind assessment result and feeding back to audio playing module adjusts the audio source file of broadcasting for carrying out Emotion identification and the state of mind to the collected physiological signal of physiological signal collection module.The state of mind is assessed to adjust with intervention and is integrated in one by the equipment, easy to use, is fast and effeciently carried out state of mind assessment to subject and is adjusted with intervention.The present invention also provides a kind of working methods of above-mentioned head wearable device, the working method can acquire the physiological signal of subject when subject receives audio stimulation to assess the state of mind of subject, and Real-time Feedback adjusts audio broadcasting content, so that subject's state of mind be adjusted in real time.
Description
Technical field
The present invention relates to state of mind assessments and regulation technology field, are used for the state of mind more specifically to one kind
Assessment and the head wearable device and its working method adjusted.
Background technique
People are generally be easy to cause the state of mind not by from multi-party surface pressure, these pressure such as work, study, lives
It is good, hidden danger is brought to people's mental health.In order to obtaining people's state of mind information, there is head wearable device at this stage,
The physiological signal of people can be acquired, so that people's state of mind is tested and assessed, but existing head can be worn
It wears equipment and there is following deficiency:
(1) existing head wearable device can only realize single function, and majority is only capable of through the physiological signal to human body
It is acquired, needs to transfer data to later to be analyzed and processed in other equipment and obtain state of mind recognition result, it cannot
The state of mind is adjusted effectively in real time；
(2) existing state of mind assessment system passes through the physiological signal of acquisition human body mostly, such as brain electricity, skin electricity, flesh
The signals such as electricity, heart rate analyze the mood of people, to realize the assessment to the state of mind；But it is existing based on brain electricity
State of mind assessment system be that EEG signals are acquired by electrode, then calculated with Short Time Fourier Transform, principal component analysis etc.
Method carries out data processing, extracts data characteristics, identifies in different frequency range to mood, but the feature application that the algorithm extracts
Effect is bad when Emotion identification；
(3) need to be adjusted position when existing head wearable device is worn, it is inconvenient to wear；After wearing with head
It is not fixed firmly, is easy to appear positional shift and leads to effectively to collect physiological signal, or be easy to slide from head；It wears
It is poor to wear comfort, is not suitable for using for a long time.
Summary of the invention
To overcome shortcoming and deficiency of the prior art, it is an object of the present invention to provide one kind to be used for the state of mind
Assessment can acquire the physiological signal of subject with the head wearable device adjusted, the equipment when subject receives audio stimulation
Assess the state of mind of subject, and Real-time Feedback adjusts audio broadcasting content, thus in real time to subject's state of mind into
Row is adjusted, which assesses the state of mind and be integrated in one with intervening to adjust, easy to use, quickly, it is effective, in real time to subject
Person carries out state of mind assessment and intervenes adjusting.It is another object of the present invention to provide a kind of above-mentioned head wearable devices
Working method, which can acquire the physiological signal of subject when subject receives audio stimulation to assess subject
The state of mind, and Real-time Feedback adjust audio broadcasting content, so that subject's state of mind be adjusted in real time.
In order to achieve the above object, the technical scheme is that: one kind for the state of mind assess
With the head wearable device of adjusting, it is characterised in that: include:
Audio playing module for playing out audio source file；
For acquiring the physiological signal collection module of subject's physiological signal；
For assessing to obtain to physiological signal collection module collected physiological signal progress Emotion identification and the state of mind
State of mind assessment result is simultaneously fed back to audio playing module to adjust the state of mind of the audio source file of broadcasting and assess mould
Block.
Head wearable device of the present invention can acquire the state of mind of the physiological signal assessment subject of subject, and in real time
Feedback adjustment plays audio to adjust broadcasting content, to influence in real time on the mood of subject, and then to the state of mind
It is adjusted；The equipment is easy to use, fast and effeciently carries out state of mind assessment to subject and intervenes adjusting.
It preferably, further include wearable frame body；The wearable frame body includes forehead frame and is connected to forehead frame two sides
Locating rack；Locating rack includes the extension body of rod connecting with forehead frame, and is connected to the audio extended below the body of rod and plays pedestal；
The audio plays the positioning region of pedestal and the formation of extension rod body for being located on human body ear；The audio playing module is set
It sets and is played on pedestal in audio；Physiological signal collection module is electroencephalogramsignal signal acquisition module；Electroencephalogramsignal signal acquisition module setting exists
On forehead frame；State of mind evaluation module is arranged on locating rack；The electroencephalogramsignal signal acquisition module, state of mind evaluation module
Successively signal connects with audio playing module.
State of mind evaluation module and audio playing module are arranged on locating rack head wearable device of the present invention, make
Light rear weight, to make forehead frame be fitted on human body forehead by gravity, is conducive to make before the wearable device weight of head
Electroencephalogramsignal signal acquisition module effectively obtains physiology signal；Extend the body of rod and audio plays the locating rack of pedestal formation in " T "
Shape, " T " shaped rear side are erected on human body ear, it can be achieved that consolidating, easily positioning and fix, while having good wearing
Comfort.
Preferably, the electroencephalogramsignal signal acquisition module includes the antinion middle line brain wave acquisition list being arranged on the inside of forehead frame
Member, and it is arranged on the inside of forehead frame and is located at the antinion brain wave acquisition unit of antinion middle line brain wave acquisition unit two sides.This hair
The bright EEG signals that can effectively acquire one lead of human body to multi-lead.
It preferably, further include wireless communication module；The wireless communication module is arranged on locating rack；State of mind assessment
Module is connect module with cloud platform signal by wireless communication.
The above-mentioned working method assessed for the state of mind with the head wearable device adjusted, it is characterised in that: including
Following steps:
S1 step, audio playing module play out audio source file, carry out auditory stimulation to subject；
S2 step, physiological signal collection module acquire the physiological signal of subject；Physiological signal includes EEG signals, heart rate letter
Number, any one of electromyography signal, skin electric signal and voice signal or two or more；
S3 step, state of mind evaluation module pre-processes physiological signal, feature extraction and Emotion identification, to subject
The state of mind assessed, obtain state of mind assessment result；
S4 step, state of mind evaluation module feed back state of mind assessment result to audio playing module, to adjust audio
Source file.
Preferably, in the S1 step, audio playing module plays out audio source file, carries out sense of hearing thorn to subject
Swash, refer to: audio playing module is loudspeaker or In-Ear Headphones or bone conduction earphone；Loudspeaker or In-Ear Headphones or bone pass
Guide lug machine plays out audio source file, carries out auditory stimulation to subject.
Preferably, in the S2 step, physiological signal collection module acquires the physiological signal of subject, refers to: physiological signal
The EEG signals of acquisition module acquisition subject；
In S3 step, state of mind evaluation module pre-processes physiological signal, feature extraction and Emotion identification, right
The state of mind of subject is assessed, and is obtained state of mind assessment result, is referred to: state of mind evaluation module is to EEG signals
It is pre-processed, and feature extraction and mood knowledge is carried out using Dynamic Graph convolutional neural networks algorithm combination width learning system
Not, the state of mind of subject is assessed, obtains state of mind assessment result.
Preferably, the state of mind evaluation module pre-processes EEG signals, and using Dynamic Graph convolution mind
Feature extraction and Emotion identification are carried out through network algorithm combination width learning system, the state of mind of subject is assessed,
State of mind assessment result is obtained, is referred to: using in independent composition analysis algorithm and Principal Component Analysis Algorithm removal EEG signals
Eye electricity, electrocardio, electromagnetic interference artefact with realize pretreatment；EEG signals are extracted using Dynamic Graph convolutional neural networks algorithm
Feature, EEG signals are mapped to feature space, then in feature space using width learning system be used as classifier, general
EEG signals carry out mood Classification and Identification, obtain the intensity value of each mood classification；It is commented according to the intensity value of each mood classification
Estimate the state of mind of subject.
Preferably, the mood classification includes tired, depressed, dejected and boring；According to the intensity value of each mood classification
The state of mind for assessing subject, refers to: tired normal value, depressed normal value, dejected normal value and boring normal value are set, point
Do not judge the ratio of fatigue strength values and tired normal value, the ratio of depressed intensity value and depressed normal value, dejected intensity value with
The ratio of dejected normal value and boring intensity value assess the state of mind of subject with boring normal value.
Preferably, in the S4 step, state of mind evaluation module, which feeds back state of mind assessment result to audio, plays mould
Block is referred to adjusting audio source file: using one of following three kinds of schemes:
One, state of mind evaluation module is according to state of mind assessment result from the broadcasting audio in state of mind evaluation module
Library recalls corresponding audio source file, and audio source file is sent to audio playing module, and audio playing module is to receiving
Audio source file play out to adjust broadcasting audio；
Two, state of mind evaluation module generates corresponding generation audio signal according to state of mind assessment result and instructs,
And it is sent to audio playing module；Audio playing module instructs the broadcasting audio repository from audio playing module according to audio signal
Corresponding audio source file is recalled to play out to adjust broadcasting audio；
Three, state of mind assessment result is sent to exterior terminal equipment, exterior terminal equipment by state of mind evaluation module
Corresponding audio source file is recalled from the broadcasting audio repository in exterior terminal equipment according to state of mind assessment result, and audio
Source file is sent to audio playing module, and audio playing module plays out to adjust broadcasting sound the audio source file received
Frequently.
Preferably, in the S4 step, also module is connect state of mind evaluation module with cloud platform signal by wireless communication,
To send cloud platform for physiological signal and state of mind assessment result.
Compared with prior art, the invention has the advantages that with the utility model has the advantages that
1, head wearable device of the present invention can acquire the state of mind of the physiological signal assessment subject of subject, and real
When feedback adjustment play audio and adjust broadcasting content, to be influenced in real time on the mood of subject, and then to spiritual shape
State is adjusted；It is easy to use, state of mind assessment fast and effeciently is carried out to subject and intervenes adjusting；
2, head wearable device of the present invention can consolidate, easily be fixed on human body head, have good comfortable wearing
Sense；Effectively acquire the EEG signals of one lead of human body to multi-lead；
3, the method for the present invention can acquire the state of mind of the physiological signal assessment subject of subject, and Real-time Feedback adjusts
Audio is played to adjust broadcasting content, to be influenced in real time on the mood of subject, and then the state of mind is adjusted；
4, the method for the present invention is in state of mind evaluation module, using Dynamic Graph convolutional neural networks algorithm (Dynamical
Graph Convolutional Neural Networks, DGCNN) and width learning system (Broad Learning
System, BLS), i.e. the algorithm of DGCNN+BLS realizes the assessment of the state of mind；Dynamic Graph convolutional neural networks algorithm is volume
The extension of product neural network algorithm (CNN) on the diagram；The research object of traditional CNN is mainly in rule space structure
Data, and DGCNN uses the thought of map, realizes the method for carrying out deep learning to the data of Anomalistic space structure；Dynamically
Picture scroll product neural network algorithm may be implemented to learn end to end, learn spy complicated out automatically from original EEG signals
Sign；Width learning system is a kind of incremental learning system for not needing depth structure, it can be used as a classifier to carry out
The classification and identification of mood, effect is good and speed is very fast；Therefore this deep learning+width study algorithm is to the state of mind
Assessment it is more accurate；
5, the method for the present invention not only can play audio using loudspeaker and In-Ear Headphones, can also use bone conduction earphone
To play audio；Bone conduction earphone converts sound to the mechanical oscillation signal of different frequency, passes through the skull, human body and mind of people
It is transmitted through organizing；The sound conduction mode of sound wave is generated by vibrating diaphragm relative to tradition, osteoacusis eliminates many sound waves
The step of transmitting；And clearly sound-reducing can be realized in a noisy environment, compared to traditional In-Ear Headphones and is raised
Sound device has outstanding audio result of broadcast, and sound wave will not influence other people because of spreading in air；
6, state of mind evaluation module ties collected physiological signal and the assessment of the obtained state of mind in the present invention
Fruit is sent to cloud platform, facilitates data storage, processing and the data analysis operation for realizing cloud platform, is convenient for model correction.
Detailed description of the invention
Fig. 1 is the system block diagram of head wearable device of the present invention；
Fig. 2 is the structural schematic diagram of head wearable device of the present invention；
Fig. 3 is the block diagram of the electroencephalogramsignal signal acquisition module in head wearable device of the present invention；
Fig. 4 is the block diagram of state of mind evaluation module in head wearable device of the present invention；
Fig. 5 is the block diagram of wearable device sound intermediate frequency playing module in head of the present invention；
Wherein, 1 it is forehead frame, 1.1 be antinion middle line brain wave acquisition unit, 1.2 be antinion brain wave acquisition unit, 2 is fixed
Position frame, 2.1 be extend the body of rod, 2.2 be audio broadcasting pedestal, 2.3 be positioning region, 3 be scalable adjustment section.
Specific embodiment
The present invention is described in further detail with specific embodiment with reference to the accompanying drawing.
Embodiment one
A kind of head wearable device assessed for the state of mind with adjusting of the present embodiment, structure such as Fig. 1, comprising:
Audio playing module for playing out audio source file；
For acquiring the physiological signal collection module of subject's physiological signal；
For assessing to obtain to physiological signal collection module collected physiological signal progress Emotion identification and the state of mind
State of mind assessment result is simultaneously fed back to audio playing module to adjust the state of mind of the audio source file of broadcasting and assess mould
Block.
Head wearable device of the present invention can acquire the state of mind of the physiological signal assessment subject of subject, and in real time
Feedback adjustment plays audio to adjust broadcasting content, to influence in real time on the mood of subject, and then to the state of mind
It is adjusted.
Head wearable device can be intelligent helmet, smart cap, intelligent headband etc.；The present embodiment is by taking intelligent headband as an example
It is illustrated.As shown in Fig. 2, head wearable device further includes wearable frame body；Wearable frame body includes forehead frame 1 and connection
Locating rack in 1 two sides of forehead frame；Locating rack 2 includes that the extension body of rod 2.1 connecting with forehead frame 1 and audio play pedestal
2.2；Audio plays pedestal 2.2 and is connected to the positioning region 2.3 for extending and being formed below the body of rod 2.1 for being located on human body ear；
Audio playing module setting plays on pedestal 2.2 in audio；Physiological signal collection module is electroencephalogramsignal signal acquisition module, brain telecommunications
Number acquisition module is arranged on forehead frame 1；State of mind evaluation module is arranged on locating rack 2；Electroencephalogramsignal signal acquisition module, essence
Successively signal connects refreshing state estimation module with audio playing module.
State of mind evaluation module is arranged to be referred on locating rack 2, the printed circuit board and electricity of state of mind evaluation module
Sub- component is arranged in extension rod body, or setting plays in pedestal in audio, or setting plays seat in the extension body of rod and audio
In vivo.
State of mind evaluation module and audio playing module are arranged on locating rack 2 head wearable device of the present invention,
It gently weighs before making head wearable device weight, to make forehead frame 1 be fitted on human body forehead by gravity, is conducive to afterwards
Electroencephalogramsignal signal acquisition module is set effectively to obtain human body electroencephalogram's signal；Extend the body of rod 2.1 and audio plays the positioning that pedestal 2.2 is formed
Frame 2 is " T " shape, and " T " shaped rear side is positioning region 2.3, is erected on human body ear, it can be achieved that consolidating, easily positioning and consolidate
It is fixed, while there is good wear comfort.
Forehead frame 1 has arc.The forehead frame 1 of arc can realize flexible deformation to match convenient for being bonded with human body forehead
Close human body head size.Extend the body of rod 2.1 to connect by scalable adjustment section 3 with forehead frame 1.Can according to human body head size,
It is adjusted by adjusting scalable adjustment section 3 and extends the body of rod 2.1 at a distance from forehead frame 1, so that locating rack 2 be made preferably to wear
On human body ear, and be conducive to audio playing module and preferably positioned, further increases the comfort of human body wearing.
Electroencephalogramsignal signal acquisition module is for obtaining human body electroencephalogram's signal, the antinion middle line including 1 inside of forehead frame is arranged in
Brain wave acquisition unit 1.1, and 1 inside of forehead frame is set and is located at the antinion of 1.1 two sides of antinion middle line brain wave acquisition unit
Brain wave acquisition unit 1.2.The present invention can effectively acquire the EEG signals of one lead of human body to multi-lead.In the present embodiment, antinion
Brain wave acquisition unit 1.2 is two, can acquire the EEG signals of three lead of human body.Also more volumes can be set in practical application
Pole brain wave acquisition unit acquires the EEG signals of human body multi-lead.
The working method of the present embodiment head wearable device, characterized by the following steps:
S1 step, audio playing module play out audio source file, carry out auditory stimulation to subject；
S2 step, physiological signal collection module acquire the physiological signal of subject；Physiological signal includes EEG signals, heart rate letter
Number, any one of electromyography signal, skin electric signal and voice signal or two or more；
S3 step, state of mind evaluation module pre-processes physiological signal, feature extraction and Emotion identification, to subject
The state of mind assessed, obtain state of mind assessment result；
S4 step, state of mind evaluation module feed back state of mind assessment result to audio playing module, to adjust audio
Source file.
The method of the present invention can acquire the state of mind of the physiological signal assessment subject of subject, and Real-time Feedback adjustment is broadcast
Playback adjusts broadcasting content frequently, to influence in real time on the mood of subject, and then the state of mind is adjusted.
In the S1 step, audio playing module plays out audio source file, carries out auditory stimulation to subject, is
Refer to: audio playing module is loudspeaker or In-Ear Headphones or bone conduction earphone；Loudspeaker or In-Ear Headphones or osteoacusis ear
Machine plays out audio source file, carries out auditory stimulation to subject.The method of the present invention using loudspeaker and can not only enter
Aural headphone plays audio, can also play audio with bone conduction earphone；Bone conduction earphone as shown in Figure 3 converts sound to
The mechanical oscillation signal of different frequency is transmitted by the skull, human body and nerve fiber of people；Relative to tradition by vibrating diaphragm come
The sound conduction mode of sound wave is generated, osteoacusis eliminates the step of many sound waves transmit；And it can be real in a noisy environment
Now clearly sound-reducing has outstanding audio result of broadcast compared to traditional In-Ear Headphones and loudspeaker, and
Sound wave will not influence other people because of spreading in air.When audio playing module is bone conduction earphone, extend the body of rod
2.1 one end is connect with forehead frame 1, and the other end is for extending to human body ear rear, and audio broadcasting pedestal 2.2 is used for and human body
Fitting on front side of ear mastoid process.
In the S2 step, physiological signal collection module acquires the physiological signal of subject, refers to: physiological signal collection module
Acquire the EEG signals of subject；
In S3 step, state of mind evaluation module pre-processes physiological signal, feature extraction and Emotion identification, right
The state of mind of subject is assessed, and is obtained state of mind assessment result, is referred to: as shown in figure 4, state of mind evaluation module
EEG signals are pre-processed, and feature extraction is carried out using Dynamic Graph convolutional neural networks algorithm combination width learning system
And Emotion identification, the state of mind of subject is assessed, state of mind assessment result is obtained.
The state of mind evaluation module pre-processes EEG signals, and is calculated using Dynamic Graph convolutional neural networks
Method combination width learning system carries out feature extraction and Emotion identification, assesses the state of mind of subject, obtains spirit
Condition evaluation results refer to: using eye electricity, the heart in independent composition analysis algorithm and Principal Component Analysis Algorithm removal EEG signals
Electricity, electromagnetic interference artefact are to realize pretreatment；The feature of EEG signals is extracted using Dynamic Graph convolutional neural networks algorithm, it will
EEG signals are mapped to feature space, then use width learning system as classifier in feature space, by EEG signals
Mood Classification and Identification is carried out, the intensity value of each mood classification is obtained；Subject is assessed according to the intensity value of each mood classification
The state of mind.
The method of the present invention is in state of mind evaluation module, using Dynamic Graph convolutional neural networks algorithm (Dynamical
Graph Convolutional Neural Networks, DGCNN) and width learning system (Broad Learning
System, BLS), i.e. the algorithm of DGCNN+BLS realizes the assessment of the state of mind；Dynamic Graph convolutional neural networks algorithm is volume
The extension of product neural network algorithm (CNN) on the diagram；The research object of traditional CNN is mainly in rule space structure
Data, and DGCNN uses the thought of map, realizes the method for carrying out deep learning to the data of Anomalistic space structure；Dynamically
Picture scroll product neural network algorithm may be implemented to learn end to end, learn spy complicated out automatically from original EEG signals
Sign；Width learning system is a kind of incremental learning system for not needing depth structure, it can be used as a classifier to carry out
The classification and identification of mood, effect is good and speed is very fast；Therefore this deep learning+width study algorithm is to the state of mind
Assessment it is more accurate.
The mood classification includes tired, depressed, dejected and boring；It is assessed and is tested according to the intensity value of each mood classification
The state of mind of person, refers to: setting tired normal value, depressed normal value, dejected normal value and boring normal value, judges respectively tired
The ratio of labor intensity value and tired normal value, the ratio of depressed intensity value and depressed normal value, dejected intensity value and dejected normal
The ratio of value and boring intensity value assess the state of mind of subject with boring normal value.
In the S4 step, state of mind evaluation module feeds back state of mind assessment result to audio playing module, to adjust
Whole audio source file, refers to: as shown in figure 5, state of mind assessment result is sent to exterior terminal by state of mind evaluation module
Equipment, exterior terminal equipment recall corresponding sound from the broadcasting audio repository in exterior terminal equipment according to state of mind assessment result
Frequency source file, and audio source file is sent to audio playing module, audio playing module to the audio source file received into
Row is played to adjust broadcasting audio.Exterior terminal equipment adjusts the audio that audio playing module plays；Exterior terminal equipment refers to
The equipment such as mobile phone, tablet computer, PC.
Preferable scheme is that: head wearable device further includes wireless communication module, and state of mind evaluation module also passes through
Wireless communication module is connect with cloud platform signal, sends cloud platform for physiological signal and state of mind assessment result.This hair
Collected physiological signal and obtained state of mind assessment result are sent to cloud platform by bright middle state of mind evaluation module,
Facilitate data storage, processing and the data analysis operation for realizing cloud platform, is convenient for model correction.
Head wearable device of the present invention both can be used for medical field, the auxiliary equipment as diagnosing and treating；It can also
To be used for normal life health keeping products field, for adjusting Mood during everyday life.
Embodiment two
The difference of the working method and embodiment one of the present embodiment head wearable device is: described in the present embodiment
In S3 step, state of mind evaluation module pre-processes physiological signal, feature extraction and Emotion identification, to the spirit of subject
State is assessed, and state of mind assessment result is obtained, and is referred to using the prior art, such as wavelet analysis, double-spectrum analysis.This reality
Remaining step for applying a working method is the same as example 1.
Embodiment three
The difference of the working method and embodiment one of the present embodiment head wearable device is: described in the present embodiment
In S4 step, state of mind evaluation module feeds back state of mind assessment result to audio playing module, to adjust audio source file,
Refer to: state of mind evaluation module is recalled according to state of mind assessment result from the broadcasting audio repository in state of mind evaluation module
Corresponding audio source file, and audio source file is sent to audio playing module, audio playing module is to the audio received
Source file is played out to adjust broadcasting audio；
Either state of mind evaluation module generates corresponding generation audio signal according to state of mind assessment result and refers to
It enables, and is sent to audio playing module；Audio playing module instructs the broadcasting sound from audio playing module according to audio signal
Frequency library recalls corresponding audio source file and plays out to adjust broadcasting audio.Remaining step of the present embodiment working method with
Embodiment one is identical.
The above embodiment is a preferred embodiment of the present invention, but embodiments of the present invention are not by above-described embodiment
Limitation, other any changes, modifications, substitutions, combinations, simplifications made without departing from the spirit and principles of the present invention,
It should be equivalent substitute mode, be included within the scope of the present invention.
Claims (10)
1. a kind of head wearable device assessed for the state of mind with adjusting, it is characterised in that: include:
Audio playing module for playing out audio source file；
For acquiring the physiological signal collection module of subject's physiological signal；
For assessing to obtain spirit to physiological signal collection module collected physiological signal progress Emotion identification and the state of mind
Condition evaluation results simultaneously feed back the state of mind evaluation module that the audio source file of broadcasting is adjusted to audio playing module.
2. the head wearable device according to claim 1 assessed for the state of mind with adjusting, it is characterised in that: also
Including wearable frame body；The wearable frame body includes forehead frame and the locating rack for being connected to forehead frame two sides；Locating rack includes
The extension body of rod being connect with forehead frame, and be connected to the audio extended below the body of rod and play pedestal；The audio plays pedestal
The positioning region for being located on human body ear is formed with extension rod body；The audio playing module setting plays pedestal in audio
On；Physiological signal collection module is electroencephalogramsignal signal acquisition module；Electroencephalogramsignal signal acquisition module is arranged on forehead frame；The state of mind
Evaluation module is arranged on locating rack；The electroencephalogramsignal signal acquisition module, state of mind evaluation module and audio playing module according to
Secondary signal connection.
3. the head wearable device according to claim 2 assessed for the state of mind with adjusting, it is characterised in that: institute
Stating electroencephalogramsignal signal acquisition module includes the antinion middle line brain wave acquisition unit being arranged on the inside of forehead frame, and is arranged in forehead frame
Inside and the antinion brain wave acquisition unit for being located at antinion middle line brain wave acquisition unit two sides.
4. the working method according to claim 1 assessed for the state of mind with the head wearable device adjusted,
It is characterized in that: including the following steps:
S1 step, audio playing module play out audio source file, carry out auditory stimulation to subject；
S2 step, physiological signal collection module acquire the physiological signal of subject；Physiological signal include EEG signals, heart rate signal,
Any one of electromyography signal, skin electric signal and voice signal or two or more；
S3 step, state of mind evaluation module pre-processes physiological signal, feature extraction and Emotion identification, to the essence of subject
Refreshing state is assessed, and state of mind assessment result is obtained；
S4 step, state of mind evaluation module feed back state of mind assessment result to audio playing module, to adjust audio source document
Part.
5. working method according to claim 4, it is characterised in that: in S1 step, audio playing module is by audio-source
File plays out, and carries out auditory stimulation to subject, refers to: audio playing module is that loudspeaker or In-Ear Headphones or bone pass
Guide lug machine；Loudspeaker or In-Ear Headphones or bone conduction earphone play out audio source file, carry out sense of hearing thorn to subject
Swash.
6. working method according to claim 4, it is characterised in that: in the S2 step, the acquisition of physiological signal collection module
The physiological signal of subject, refers to: the EEG signals of physiological signal collection module acquisition subject；
In S3 step, state of mind evaluation module pre-processes physiological signal, feature extraction and Emotion identification, to subject
The state of mind of person is assessed, and is obtained state of mind assessment result, is referred to: state of mind evaluation module carries out EEG signals
Pretreatment, and feature extraction and Emotion identification are carried out using Dynamic Graph convolutional neural networks algorithm combination width learning system, it is right
The state of mind of subject is assessed, and state of mind assessment result is obtained.
7. working method according to claim 6, it is characterised in that: the state of mind evaluation module is to EEG signals
It is pre-processed, and feature extraction and mood knowledge is carried out using Dynamic Graph convolutional neural networks algorithm combination width learning system
Not, the state of mind of subject is assessed, obtains state of mind assessment result, refers to: using independent composition analysis algorithm
The eye electricity in EEG signals, electrocardio, electromagnetic interference artefact are removed with Principal Component Analysis Algorithm to realize pretreatment；Using Dynamic Graph
Convolutional neural networks algorithm extracts the features of EEG signals, EEG signals is mapped to feature space, then in feature space
It is middle that EEG signals progress mood Classification and Identification is obtained as classifier by the strong of each mood classification using width learning system
Angle value；The state of mind of subject is assessed according to the intensity value of each mood classification.
8. working method according to claim 7, it is characterised in that: the mood classification include it is tired, depressed, dejected and
It is boring；The state of mind that subject is assessed according to the intensity value of each mood classification, refers to: setting tired normal value, depression just
Constant value, dejected normal value and boring normal value, judge respectively the ratio of fatigue strength values and tired normal value, depressed intensity value with
The ratio of depressed normal value, the ratio of dejected intensity value and dejected normal value and boring intensity value assess quilt with boring normal value
The state of mind of examination person.
9. working method according to claim 4, it is characterised in that: in the S4 step, state of mind evaluation module will be smart
Refreshing condition evaluation results feedback is referred to audio playing module with adjusting audio source file: using one of following three kinds of schemes:
One, state of mind evaluation module is according to state of mind assessment result from the broadcasting audio repository tune in state of mind evaluation module
Corresponding audio source file out, and audio source file is sent to audio playing module, audio playing module is to the sound received
Frequency source file is played out to adjust broadcasting audio；
Two, state of mind evaluation module generates corresponding generation audio signal according to state of mind assessment result and instructs, concurrently
It send to audio playing module；Audio playing module instructs the broadcasting audio repository from audio playing module to recall according to audio signal
Corresponding audio source file is played out to adjust broadcasting audio；
Three, state of mind assessment result is sent to exterior terminal equipment by state of mind evaluation module, exterior terminal equipment according to
State of mind assessment result recalls corresponding audio source file from the broadcasting audio repository in exterior terminal equipment, and audio source document
Part is sent to audio playing module, and audio playing module plays out to adjust broadcasting audio the audio source file received.
10. working method according to claim 4, it is characterised in that: in the S4 step, state of mind evaluation module is also logical
It crosses wireless communication module to connect with cloud platform signal, sends cloud platform for physiological signal and state of mind assessment result.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811430882.XA CN109350051B (en) | 2018-11-28 | 2018-11-28 | Head wearable device for mental state assessment and adjustment and working method thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811430882.XA CN109350051B (en) | 2018-11-28 | 2018-11-28 | Head wearable device for mental state assessment and adjustment and working method thereof |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109350051A true CN109350051A (en) | 2019-02-19 |
| CN109350051B CN109350051B (en) | 2023-12-29 |
Family
ID=65343322
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811430882.XA Active CN109350051B (en) | 2018-11-28 | 2018-11-28 | Head wearable device for mental state assessment and adjustment and working method thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109350051B (en) |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110348299A (en) * | 2019-06-04 | 2019-10-18 | 上海交通大学 | The recognition methods of three-dimension object |
| CN110464344A (en) * | 2019-08-16 | 2019-11-19 | 兰州大学 | The method for collecting the device of eeg signal acquisition and music and its playing music |
| CN110811648A (en) * | 2019-11-20 | 2020-02-21 | 阿呆科技（北京）有限公司 | Depression tendency evaluation system based on residual convolutional neural network |
| CN110947076A (en) * | 2019-11-27 | 2020-04-03 | 华南理工大学 | Intelligent brain wave music wearable device capable of adjusting mental state |
| CN110947075A (en) * | 2019-11-27 | 2020-04-03 | 华南理工大学 | Personalized mental state adjusting system and method based on brainwave music |
| CN111358475A (en) * | 2020-03-16 | 2020-07-03 | 国网安徽省电力有限公司 | Mental state assessment method and system for high-risk operating personnel in power system |
| CN112515680A (en) * | 2019-09-19 | 2021-03-19 | 中国科学院半导体研究所 | Wearable brain electrical fatigue monitoring system |
| CN112596273A (en) * | 2020-12-30 | 2021-04-02 | 华南理工大学 | Intelligent color-changing glasses with electroencephalogram emotion assessment and adjustment functions and control method |
| CN114052734A (en) * | 2021-11-24 | 2022-02-18 | 西安电子科技大学 | Electroencephalogram emotion recognition method based on progressive graph convolution neural network |
| CN115363585A (en) * | 2022-09-04 | 2022-11-22 | 北京中科心研科技有限公司 | Standardized group depression risk screening system and method based on habituation removal and film watching tasks |
| CN116671881A (en) * | 2023-08-03 | 2023-09-01 | 北京九叁有方物联网科技有限公司 | Head-wearing brain body operation capability assessment device and method based on graph neural network |
Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110222724A1 (en) * | 2010-03-15 | 2011-09-15 | Nec Laboratories America, Inc. | Systems and methods for determining personal characteristics |
| CN104463218A (en) * | 2014-12-16 | 2015-03-25 | 重庆邮电大学 | sEMG self-adaptive mode recognition method based on on-line SVM and application of method on intelligent wheelchair |
| CN205029825U (en) * | 2015-08-10 | 2016-02-10 | 湖北工业大学 | Intelligence accuse sleep earphone |
| CN205051851U (en) * | 2015-10-30 | 2016-02-24 | 深圳创达云睿智能科技有限公司 | Intelligent earphone of brain electricity |
| CN105893780A (en) * | 2016-05-10 | 2016-08-24 | 华南理工大学 | Mental and psychological assessment method based on VR interaction and brain wave and cerebral blood flow monitoring |
| CN106267514A (en) * | 2016-10-19 | 2017-01-04 | 上海大学 | Feeling control system based on brain electricity feedback |
| WO2017069644A2 (en) * | 2015-10-22 | 2017-04-27 | MBRAINTRAIN LLC Belgrade | Wireless eeg headphones for cognitive tracking and neurofeedback |
| CN106620990A (en) * | 2016-11-24 | 2017-05-10 | 深圳创达云睿智能科技有限公司 | Method and device for monitoring mood |
| CN106725532A (en) * | 2016-12-13 | 2017-05-31 | 兰州大学 | Depression automatic evaluation system and method based on phonetic feature and machine learning |
| US20170337438A1 (en) * | 2010-06-07 | 2017-11-23 | Affectiva, Inc. | Mental state analysis using blink rate for vehicles |
| US20170339484A1 (en) * | 2014-11-02 | 2017-11-23 | Ngoggle Inc. | Smart audio headphone system |
| US20170352283A1 (en) * | 2016-06-07 | 2017-12-07 | Cerekinetic, Inc. | Self-administered evaluation and training method to improve mental state |
| CN107595302A (en) * | 2017-09-06 | 2018-01-19 | 西安交通大学 | A kind of device and method that user's state of mind is monitored using EEG signals |
| WO2018129211A1 (en) * | 2017-01-04 | 2018-07-12 | StoryUp, Inc. | System and method for modifying biometric activity using virtual reality therapy |
| CN108363978A (en) * | 2018-02-12 | 2018-08-03 | 华南理工大学 | Using the emotion perception method based on body language of deep learning and UKF |
| CN108461126A (en) * | 2018-03-19 | 2018-08-28 | 傅笑 | In conjunction with virtual reality（VR）The novel intelligent psychological assessment of technology and interfering system |
| CN108564011A (en) * | 2017-08-01 | 2018-09-21 | 南京邮电大学 | A kind of personal identification method that normal form being presented based on brain electricity Rapid Speech |
| CN108888281A (en) * | 2018-08-16 | 2018-11-27 | 华南理工大学 | State of mind appraisal procedure, equipment and system |
-
2018
- 2018-11-28 CN CN201811430882.XA patent/CN109350051B/en active Active
Patent Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110222724A1 (en) * | 2010-03-15 | 2011-09-15 | Nec Laboratories America, Inc. | Systems and methods for determining personal characteristics |
| US20170337438A1 (en) * | 2010-06-07 | 2017-11-23 | Affectiva, Inc. | Mental state analysis using blink rate for vehicles |
| US20170339484A1 (en) * | 2014-11-02 | 2017-11-23 | Ngoggle Inc. | Smart audio headphone system |
| CN104463218A (en) * | 2014-12-16 | 2015-03-25 | 重庆邮电大学 | sEMG self-adaptive mode recognition method based on on-line SVM and application of method on intelligent wheelchair |
| CN205029825U (en) * | 2015-08-10 | 2016-02-10 | 湖北工业大学 | Intelligence accuse sleep earphone |
| WO2017069644A2 (en) * | 2015-10-22 | 2017-04-27 | MBRAINTRAIN LLC Belgrade | Wireless eeg headphones for cognitive tracking and neurofeedback |
| CN205051851U (en) * | 2015-10-30 | 2016-02-24 | 深圳创达云睿智能科技有限公司 | Intelligent earphone of brain electricity |
| CN105893780A (en) * | 2016-05-10 | 2016-08-24 | 华南理工大学 | Mental and psychological assessment method based on VR interaction and brain wave and cerebral blood flow monitoring |
| US20170352283A1 (en) * | 2016-06-07 | 2017-12-07 | Cerekinetic, Inc. | Self-administered evaluation and training method to improve mental state |
| CN106267514A (en) * | 2016-10-19 | 2017-01-04 | 上海大学 | Feeling control system based on brain electricity feedback |
| CN106620990A (en) * | 2016-11-24 | 2017-05-10 | 深圳创达云睿智能科技有限公司 | Method and device for monitoring mood |
| CN106725532A (en) * | 2016-12-13 | 2017-05-31 | 兰州大学 | Depression automatic evaluation system and method based on phonetic feature and machine learning |
| WO2018129211A1 (en) * | 2017-01-04 | 2018-07-12 | StoryUp, Inc. | System and method for modifying biometric activity using virtual reality therapy |
| CN108564011A (en) * | 2017-08-01 | 2018-09-21 | 南京邮电大学 | A kind of personal identification method that normal form being presented based on brain electricity Rapid Speech |
| CN107595302A (en) * | 2017-09-06 | 2018-01-19 | 西安交通大学 | A kind of device and method that user's state of mind is monitored using EEG signals |
| CN108363978A (en) * | 2018-02-12 | 2018-08-03 | 华南理工大学 | Using the emotion perception method based on body language of deep learning and UKF |
| CN108461126A (en) * | 2018-03-19 | 2018-08-28 | 傅笑 | In conjunction with virtual reality（VR）The novel intelligent psychological assessment of technology and interfering system |
| CN108888281A (en) * | 2018-08-16 | 2018-11-27 | 华南理工大学 | State of mind appraisal procedure, equipment and system |
Non-Patent Citations (3)
| Title |
|---|
| C. L. PHILIP CHEN ET.AL: "Broad Learning System: a new learning paradigm and system without going deep", 2017 32ND YOUTH ACADEMIC ANNUAL CONFERENCE OF CHINESE ASSOCIATION OF AUTOMATION (YAC) * |
| TENGFEI SONG ET.AL: "EEG Emotion Recognition Using Dynamical Graph Convolutional Neural Networks", IEEE TRANSACTIONS ON AFFECTIVE COMPUTING, pages 532 * |
| 陈萌;李幼军;刘岩;: "脑电信号与个人情绪状态关联性分析研究", 计算机科学与探索, no. 05 * |
Cited By (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110348299B (en) * | 2019-06-04 | 2022-06-10 | 上海交通大学 | Method for recognizing three-dimensional object |
| CN110348299A (en) * | 2019-06-04 | 2019-10-18 | 上海交通大学 | The recognition methods of three-dimension object |
| CN110464344A (en) * | 2019-08-16 | 2019-11-19 | 兰州大学 | The method for collecting the device of eeg signal acquisition and music and its playing music |
| CN112515680A (en) * | 2019-09-19 | 2021-03-19 | 中国科学院半导体研究所 | Wearable brain electrical fatigue monitoring system |
| CN112515680B (en) * | 2019-09-19 | 2023-03-31 | 中国科学院半导体研究所 | Wearable brain electrical fatigue monitoring system |
| CN110811648A (en) * | 2019-11-20 | 2020-02-21 | 阿呆科技（北京）有限公司 | Depression tendency evaluation system based on residual convolutional neural network |
| WO2021103829A1 (en) * | 2019-11-27 | 2021-06-03 | 华南理工大学 | Personalized mental state adjustment system and method based on brainwave music |
| CN110947076B (en) * | 2019-11-27 | 2021-07-16 | 华南理工大学 | Intelligent brain wave music wearable device capable of adjusting mental state |
| CN110947075A (en) * | 2019-11-27 | 2020-04-03 | 华南理工大学 | Personalized mental state adjusting system and method based on brainwave music |
| GB2608690A (en) * | 2019-11-27 | 2023-01-11 | Univ South China Tech | Personalized mental state adjustment system and method based on brainwave music |
| CN110947076A (en) * | 2019-11-27 | 2020-04-03 | 华南理工大学 | Intelligent brain wave music wearable device capable of adjusting mental state |
| CN111358475A (en) * | 2020-03-16 | 2020-07-03 | 国网安徽省电力有限公司 | Mental state assessment method and system for high-risk operating personnel in power system |
| CN112596273A (en) * | 2020-12-30 | 2021-04-02 | 华南理工大学 | Intelligent color-changing glasses with electroencephalogram emotion assessment and adjustment functions and control method |
| CN114052734A (en) * | 2021-11-24 | 2022-02-18 | 西安电子科技大学 | Electroencephalogram emotion recognition method based on progressive graph convolution neural network |
| CN115363585A (en) * | 2022-09-04 | 2022-11-22 | 北京中科心研科技有限公司 | Standardized group depression risk screening system and method based on habituation removal and film watching tasks |
| CN115363585B (en) * | 2022-09-04 | 2023-05-23 | 北京中科心研科技有限公司 | Standardized group depression risk screening system and method based on habit removal and film watching tasks |
| CN116671881A (en) * | 2023-08-03 | 2023-09-01 | 北京九叁有方物联网科技有限公司 | Head-wearing brain body operation capability assessment device and method based on graph neural network |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109350051B (en) | 2023-12-29 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109350051A (en) | The head wearable device and its working method with adjusting are assessed for the state of mind | |
| US11185257B2 (en) | Hearing assistance device with brain computer interface | |
| CN109620257B (en) | Mental state intervention and regulation system based on biofeedback and working method thereof | |
| CN109992113B (en) | MI-BCI system based on multi-scene induction and control method thereof | |
| US10660537B2 (en) | Headgear with displaceable sensors for electrophysiology measurement and training | |
| US10178952B2 (en) | Bi-hemispheric brain wave system and method of performing bi-hemispherical brain wave measurements | |
| CN106994013A (en) | Wearable physiology resonance stimulating system, electrical stimulation device and physiological activity sensing device further | |
| CN110947076B (en) | Intelligent brain wave music wearable device capable of adjusting mental state | |
| WO2020186651A1 (en) | Smart sports earphones based on eeg thoughts and implementation method and system thereof | |
| WO2020187109A1 (en) | User sleep detection method and system | |
| GB2608690A (en) | Personalized mental state adjustment system and method based on brainwave music | |
| Looney et al. | Ear-EEG: user-centered and wearable BCI | |
| CN109391891A (en) | For running the method and hearing device of hearing device | |
| US20220141601A1 (en) | Portable system for gathering and processing data from eeg, eog, and/or imaging sensors | |
| CN110368005A (en) | A kind of intelligent earphone and mood and physiological health monitoring method based on intelligent earphone | |
| CN107184205B (en) | Automatic knowledge memory traction method based on memory scale and induction capture of brain | |
| CN114081511B (en) | Binaural frequency-division hearing-induced brain-computer interface device and method | |
| WO2021167866A1 (en) | Control of parameters of hearing instrument based on ear canal deformation and concha emg signals | |
| CN112156319A (en) | Bone conduction music helps dormancy system | |
| CN209932734U (en) | Head wearable equipment | |
| DE202017006910U1 (en) | Cardiac activity sensor integrated with wired earbuds | |
| Athavipach et al. | Development of low-cost in-the-ear eeg prototype | |
| EP3409319B1 (en) | System for neural hearing stimulation integrated with a pair of glasses | |
| Pollard et al. | Morphological differences affect speech transmission over bone conduction | |
| CN212623357U (en) | Helmet for virtual reality |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |