CN110251801A - A kind of eyeshade reaction type microcurrent stimulating sleeping-assisting system - Google Patents
A kind of eyeshade reaction type microcurrent stimulating sleeping-assisting system Download PDFInfo
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
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- A61B5/48—Other medical applications
- A61B5/4806—Sleep evaluation
- A61B5/4812—Detecting sleep stages or cycles
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
- A61M21/00—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis
- A61M21/02—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis for inducing sleep or relaxation, e.g. by direct nerve stimulation, hypnosis, analgesia
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- A—HUMAN NECESSITIES
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- A61M21/00—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis
- A61M2021/0005—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus
- A61M2021/0072—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis by the use of a particular sense, or stimulus with application of electrical currents
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Abstract
A kind of eyeshade reaction type microcurrent stimulating sleeping-assisting system, including eyeshade ontology, include human-computer interaction module, control module, stimulation output module, sensor module and signal analysis module in eyeshade ontology, and human-computer interaction module includes the first touch-switch；Sensor module acquires user's electro-physiological signals in real time and electro-physiological signals is transmitted to signal analysis module；Signal analysis module extracts multidimensional dormant data feature；Regulating command is made after the data of control module reception signal analysis module and is sent to stimulation output module, and stimulation output module exports stimulus signal according to regulating command to promote to sleep.The present invention is based on the automatic classification and identification algorithms of artificial intelligence approach, sleep quality state is picked out from the brain of user electricity, electro-ocular signal, then suitable specific waveforms are exported, form closed loop feedback control circuit, improve abnormal brain wave, the secretion of cerebral neurotransmitters and stress hormone is adjusted with rapid recovery insomnia problem, improves the sleep quality of user.
Description
Technical field
The present invention relates to medical electronics fields, sleep and assist more particularly, to a kind of eyeshade reaction type microcurrent stimulating
System.
Background technique
Good sleep can alleviate people's fatigue in one day, promote the metabolism of human body.But with rhythm of life
Insomnia caused by many reasons such as quickening, the surge of operating pressure, has resulted in more and more crowds and is in sub-health state.According to
The World Health Organization investigates 14 two Wan Yuming of country in primary care clients and finds have 27% people to have sleeping problems.
The investigation result that China Sleep Research Association is announced shows that Chinese adult insomnia incidence is 38.2%.
Currently, insomnia mainly includes drug therapy and non-drug therapy.Medicinal treatment be easy to produce drug resistance,
Additive, interim reaction and various side effects；Non-drug therapy have the effect of it is more longlasting, be the line recommended, it is long-term
Therapeutic strategy, non-drug therapy intervenes human body by foreign object, for example utilizes sound, illumination, Neural stem cell either electricity
Stimulation etc. influences human brain, and the meeting of appropriate frequency electro photoluminescence generates certain influence to human body electroencephalogram's wave, in turn
The frequency of brain wave that human body electroencephalogram's wave is adjusted when it being made sleep state occur, so that people be allowed to rapidly enter sleep state.
It is non-medicine through cranium microcurrent stimulating therapy (Cranial Electrotherapy Stimulation, abbreviation CES)
One of object treatment method can effectively treat anxiety, depression, insomnia and children's related emotional obstacle, its main feature is that curative effect it is fast,
Without side-effects and dependence.This therapy exports the other micro-current of microampere order by the ear-clip electrodes that are clipped on ear-lobe, stimulator
Brain is stimulated, improves abnormal brain wave, adjusts the secretion of cerebral neurotransmitters and stress hormone, to reach the mesh for the treatment of insomnia
's.The therapy is authenticated by U.S. FDA, Europe CE certification and Chinese Bureau of Drugs Supervision authenticate.
But there is biggish defect currently based on the sleep assistance instrument through cranium microcurrent stimulating therapy:
1, user needs to manually select specific stimulated current mode, and this manual selection modes lack scientific finger
It leads, cannot cannot effectively help insomniac to improve sleep quality according to adaptive output adjustment is carried out the characteristics of each user.
2, lack the real-time acquisition to sleep quality physiologic information, lack closed loop feedback channel, be unable to needle brain electricity and eye electricity
Equal physiological signals adjust stimulated current in real time, and sleeping effect individual difference is big.
3, about when stop external stimulus the problem of, existing sleeping equipment generally use timing stop mode, cannot
Accomplish adaptively to be stopped according to the sleep state of user in real time, the too short or too long external stimulus time, which is all unfavorable for improving, to be used
The sleep quality at family.
Summary of the invention
The present invention provides a kind of eyeshade reaction type microcurrent stimulating sleeping-assisting system, can automatically select specific stimulation
Current-mode, in real time adjustment stimulated current and adaptive stopping stimulation.
In order to solve the above technical problems, technical scheme is as follows:
A kind of eyeshade reaction type microcurrent stimulating sleeping-assisting system, including eyeshade ontology include in the eyeshade ontology
There are human-computer interaction module, control module, stimulation output module, sensor module and signal analysis module, wherein the man-machine friendship
Mutual module includes the first touch-switch, and by short-press the first touch-switch activation system, the first touch-switch of long-pressing closes system；
The sensor module acquires user's electro-physiological signals in real time and electro-physiological signals is transmitted to signal analysis module；The signal
Analysis module uses signal processing technology and Nonlinear Dynamics, extracts effective multidimensional dormant data feature；Control mould
Regulating command is made after the data of block reception signal analysis module and is sent to stimulation output module, stimulates output module according to adjusting
Instruction exports the stimulus signal of corresponding frequency and current strength to promote to sleep.
It preferably, further include communication module and mobile terminal, the human-computer interaction module further includes the second touch-switch, short
Communication module is opened by the second touch-switch, long-pressing the second touch-switch closed communication module sets sleep mould in mobile terminal
It after formula, receives and is sent in control module through communication module, the first touch-switch and the second touch-switch told are 3*
6*2.5 touch-switch patch, parameter are as follows: insulation resistance: >=100M Ω, temperature range: -3~+70 DEG C, pressure resistance: AC250V
(50HZ)/min, rated load: 50mA, operation force: 100-350G, contact resistance :≤0.03 Ω；Communication module is logical for bluetooth
News.
Preferably, the sensor module includes brain wave acquisition unit for acquiring EEG signals and for acquiring eye
The eye electricity acquisition unit of electric signal, during acquiring electro-physiological signals, the Skin Resistance of adaptive user.
Preferably, the signal analysis module includes 50Hz trapper and IIR bandpass filter, wherein utilizing 50Hz trap
Device removes the power frequency of collected physiological signal, and IIR bandpass filter is recycled to extract brain electrical feature relevant to sleep respectively
Signal, including α wave (8~13Hz), β wave (13~30Hz), θ wave (4~8Hz), δ wave (0.5~4Hz), sleep spindle (12~
14Hz)。
Preferably, the control module includes master controller, core processor can carry out some complexity calculating and
Control, while its ADC required precision being internally integrated can satisfy the acquisition requirement for EEG signals and electro-ocular signal, so that
The processing task of huge brain electricity and electro-ocular signal can be competent at, the introducing for saving external ADC chip reduces external electrical
The complexity on road, enable circuit as far as possible reach minimum, realize that equipment is wearable.
Preferably, the sleep quality for selecting random forest integrated learning approach to establish user in the master controller is comprehensive
Assessment models are closed, the model uses gini index to divide as the selection of decision tree and belong to using decision tree as Weak Classifier
Property, 30 Weak Classifiers are formed altogether, and the period result of identification sleep is obtained using the combination strategy of ballot method；The model is with signal
The characteristic value of analysis module treated electro-ocular signal and EEG signals exports the judgement of user's sleep stage as input,
Control module carries out characteristic processing to the signal of window every 30 seconds views.
Preferably, the characteristic value that sleep quality Integrated Evaluation Model is used includes multiple on time domain, frequency domain and time-frequency domain
Feature, specific as follows:
A. temporal signatures:
Collected electro-ocular signal extracts saccadic eye movement number, frequency according to features such as amplitude and slopes；Using adopting
The original EEG signals collected, the 5 kinds of brain electrical feature signals extracted, calculate its average value, standard deviation, kurtosis, maximum value, minimum
Value, zero-crossing rate and Petrosian parting coefficient (PFD):
In formula, k is the number of samples of EEG signals, NδIt is the sign reversing number of EEG signals；
B. frequency domain character:
Fourier's variation is carried out to EEG signals and its characteristic signal, calculates separately the energy of signature waveform Yu whole segment signal
Measure ratio；
C. time and frequency domain characteristics:
EEG signals are analyzed using wavelet transform, wherein x (t) is EEG signals, and ψ is wavelet basis function,
Select symlet wavelet basis:
By wavelet transformation, show that detail coefficients and approximation coefficient, pairing approximation coefficient carry out wavelet decomposition, iteration again
It carries out 3 times, obtains 3 detail coefficients, Di(n), their average value, standard are asked to this 3 detail coefficients in 3 i=1 ... respectively
Difference, kurtosis and PFD.
Preferably, the sleep quality Integrated Evaluation Model obtains user's sleep stage, extracts its sleep quality assessment
The feature of index uses expert system as the Controlling model of stimulation output module, forms closed loop feedback control circuit, wherein
The acquisition of sleep quality assessment index is the sleep stage identified using above-mentioned sleep quality Integrated Evaluation Model, and record makes
Sleep stage historical data of the user in current sleep, from historical data, analyzing the Sleep architecture of user before the moment,
The feature of calculating include shallowly sleep, sound sleep, the ratio of rapid-eye-movement sleep and distribution, duration of always sleeping, also, according to from awakening to
Shallowly sleep, in sleep, sound sleep to the sleep cycle order for rapid-eye-movement sleep, divide sleep cycle, count the conduct of sleep cycle number
One of feature；Using the sleep characteristics extracted above as the input of expert system, the knowledge base in the expert system includes
A variety of sleep quality assessment index features correspond to the knowledge rule of optimal stimulus pulse output, the inference machine of expert system according to
Current input feature vector data, the rule of applicable boost pulse type is found with control strategy, and control module is defeated to stimulating
Module sends corresponding boost pulse type command out, the output of boost pulse is adjusted in time, so that the Sleep architecture of user
Tend to normal, increases the deep sleep time.
Preferably, it stimulates the output end of output module using voltage controlled current source, exports end in contact human body ear-lobe position group
It knits and temporal bone, to reach automatic adjusument effect, stimulation output module is one of the module directly acted on human body, this
The effect of stimulation of system is related with its stimulated current waveform and current strength, but everyone Skin Resistance is inconsistent, uses
Will lead to if constant voltage output act on human body current strength it is uncontrollable.Therefore, in order to ensure that output controlled current flow, improves stimulation
The validity of effect, output end use voltage controlled current source, control it by input voltage and export electric current, so as to avoid due to people
The uncontrollable situation of electric current is exported caused by the specificity of body and poor contact.
Preferably, the user demand and situation that the communication module is inputted by mobile terminal are conveyed to control module, together
When information can will be uploaded to cloud by way of wireless telecommunications after finish message, can store user brain electric information,
Eye information, complete documentation bedtime, time for falling asleep, depth sleeping time provide sleep quality report and brain for user
Electricity condition report, analyzes brain electrical anomaly, accomplishes that measurement, analysis, early warning, review and storage are integrated, if it find that there is sleep
Or brain electricity problem, a sleep quality report can be provided in time and brain statement-of-health feeds back to user, allow user can
Quickly understand the body state of mind.Optionally, data can be uploaded to cloud by user, and cloud can be to front end data acquisition module
Feedback control is carried out with mobile monitoring terminal, it can be achieved that the cloud of multi-user's company-data stores, data analysis result classification pushes away
It send, user's generalized information management, and comprehensive medical decision making and service can be provided by doctor according to data processed result.This
In design pattern, cloud is not only that user, doctor and hospital construct a public data pool, while also providing for three
Techno-sharing and better professional service.
Compared with prior art, the beneficial effect of technical solution of the present invention is:
1. applicability of user is strong.The Skin Resistance of user can be carried out adaptively, it can be according to real-time acquisition monitoring
The sleep quality of user is so that it is determined that specific stimulation protocol, adaptive stimulated current output, sleeping better effect, specific aim
It is stronger, suitable for different users；
2. having closed loop feedback channel.The physiology information detecting being electrically coupled using brain electricity and eye establishes closed loop feedback channel,
Adjustment stimulated current in real time, avoids single-mode from stimulating, judges that sleep state is more accurate；
3. adaptive stop output.According to the sleep quality of user, accomplish to be carried out certainly according to the sleep state of user in real time
It adapts to stop.
4. the present invention is based on wavelet transformation, nonlinear kinetics and random forest method multi-parameters based on parameter optimization to sentence
Other sleep state algorithm picks out sleep quality state from the signals such as the brain electricity of user, eye electricity, and then output is suitable specific
Waveform forms closed loop feedback control circuit, improves abnormal brain wave, adjusts the secretion of cerebral neurotransmitters and stress hormone with fast
Fast relieving insomnia problem with rapid recovery insomnia problem, and extends sleeping time, can effectively improve the sleep matter of user
Amount.It is able to detect, analyzes and records simultaneously brain electric information, intelligence accurately monitors brain electrical anomaly feelings with reference to the database of profession
Condition is suggested as a result, providing medical treatment in time for user, improves the prevention ability of brain diseases.Cloud service, Yong Huke are provided for user
To upload voluntarily upload historical information and save.EEG signals, electro-ocular signal etc. when the present invention is slept by real-time monitoring, point
The physiological activity state and sleep state of user are analysed, the different phase that control sleep assistance instrument is slept according to user exports corresponding thorn
Swash current waveform so that brain be rapidly introduced into depth loosen, the subconsciousness state of no pressure, enter back into deep sleep, greatly
The sleep quality for improving user.
Detailed description of the invention
Fig. 1 is a kind of eyeshade reaction type microcurrent stimulating sleeping-assisting system module diagram；
In figure, 1 it is eyeshade ontology, 11 is human-computer interaction module, 12 is control module, 13 is communication module, 14 is stimulation
Output module, 15 be signal analysis module, 16 be sensor module, 2 be human body, 3 be mobile terminal, 4 be cloud.
Specific embodiment
The attached figures are only used for illustrative purposes and cannot be understood as limitating the patent；
In order to better illustrate this embodiment, the certain components of attached drawing have omission, zoom in or out, and do not represent actual product
Size；
To those skilled in the art, it is to be understood that certain known features and its explanation, which may be omitted, in attached drawing
's.
The following further describes the technical solution of the present invention with reference to the accompanying drawings and examples.
Embodiment 1
The present embodiment provides a kind of eyeshade reaction type microcurrent stimulating sleeping-assisting system, such as Fig. 1, including eyeshade ontology 1,
It include human-computer interaction module 11, control module 12, stimulation output module 14,16 and of sensor module in the eyeshade ontology 1
Signal analysis module 15, wherein the human-computer interaction module 11 includes the first touch-switch, is opened by the first touch-switch of short-press
Dynamic system, the first touch-switch of long-pressing close system；The sensor module 16 acquires user's electro-physiological signals in real time and will give birth to
Electric signal transmission is managed to signal analysis module 15；The signal analysis module 15 uses signal processing technology and nonlinear kinetics
Method extracts effective multidimensional dormant data feature；Adjusting is made after the data of the reception signal analysis module 15 of control module 12
Instruction is sent to stimulation output module 14, and stimulation output module 14 exports corresponding frequency and current strength according to regulating command
Stimulus signal is to promote to sleep.It further include communication module 13 and mobile terminal 3, the human-computer interaction module 11 further includes second
Touch-switch, the second touch-switch of short-press open communication module 13, long-pressing the second touch-switch closed communication module 13, in movement
After terminal 3 sets sleep pattern, receives and be sent in control module 12 through communication module 13.
The sensor module 16 includes brain wave acquisition unit for acquiring EEG signals and for acquiring eye telecommunications
Number eye electricity acquisition unit, acquire electro-physiological signals during, the Skin Resistance of adaptive user.
The signal analysis module 15 includes 50Hz trapper and IIR bandpass filter, wherein being gone using 50Hz trapper
Except the power frequency of collected physiological signal, IIR bandpass filter is recycled to extract brain electrical feature signal relevant to sleep respectively,
Including α wave (8~13Hz), β wave (13~30Hz), θ wave (4~8Hz), δ wave (0.5~4Hz), sleep spindle (12~
14Hz)。
The control module 12 includes master controller.Random forest integrated learning approach is selected in the master controller
The sleep quality Integrated Evaluation Model of user is established, the model is made using decision tree as Weak Classifier using gini index
Attribute is divided for the selection of decision tree, forms 30 Weak Classifiers altogether, obtains identification sleep using the combination strategy of ballot method
Period result；The model using the characteristic value of treated the electro-ocular signal of signal analysis module 15 and EEG signals as input,
Control module 12 carries out characteristic processing to the signal of window every 30 seconds views.The feature that sleep quality Integrated Evaluation Model is used
Value includes multiple features on time domain, frequency domain and time-frequency domain, specific as follows:
A. temporal signatures:
Collected electro-ocular signal extracts saccadic eye movement number, frequency according to features such as amplitude and slopes；Using adopting
The original EEG signals collected, the 5 kinds of brain electrical feature signals extracted, calculate its average value, standard deviation, kurtosis, maximum value, minimum
Value, zero-crossing rate and Petrosian parting coefficient (PFD):
In formula, k is the number of samples of EEG signals, NδIt is the sign reversing number of EEG signals；
B. frequency domain character:
Fourier's variation is carried out to EEG signals and its characteristic signal, calculates separately the energy of signature waveform Yu whole segment signal
Measure ratio；
C. time and frequency domain characteristics:
EEG signals are analyzed using wavelet transform, wherein x (t) is EEG signals, and ψ is wavelet basis function,
Select symlet wavelet basis:
By wavelet transformation, show that detail coefficients and approximation coefficient, pairing approximation coefficient carry out wavelet decomposition, iteration again
It carries out 3 times, obtains 3 detail coefficients, Di(n), their average value, standard are asked to this 3 detail coefficients in 3 i=1 ... respectively
Difference, kurtosis and PFD.
The sleep quality Integrated Evaluation Model obtains user's sleep stage, extracts the spy of its sleep quality assessment index
Sign uses expert system as the Controlling model of stimulation output module 14, forms closed loop feedback control circuit, wherein sleep matter
The acquisition for measuring evaluation index is the sleep stage identified using above-mentioned sleep quality Integrated Evaluation Model, and record user exists
Sleep stage historical data in current sleep, from historical data, analyzing the Sleep architecture of user before the moment, calculating
Feature include shallowly sleep, sound sleep, the ratio of rapid-eye-movement sleep and distribution, duration of always sleeping, also, according to from awakening to shallowly sleep,
In sleep, sound sleep to the sleep cycle order for rapid-eye-movement sleep, divide sleep cycle, statistics sleep cycle number is as wherein one
A feature；Using the sleep characteristics extracted above as the input of expert system, the knowledge base in the expert system contains a variety of
Sleep quality assessment index feature corresponds to the knowledge rule of optimal stimulus pulse output, and the inference machine of expert system is according to currently
Input feature vector data, the rule of applicable boost pulse type is found with control strategy, and control module 12 exports mould to stimulation
Block 14 sends corresponding boost pulse type command, adjusts the output of boost pulse in time.
Stimulate output module 14 output end use voltage controlled current source, export 2 ear-lobe site tissue of end in contact human body and
Temporal bone.
The user demand and situation that the communication module 13 is inputted by mobile terminal 3 are conveyed to control module 12, simultaneously
Information can will be uploaded to cloud 4 by way of wireless telecommunications after finish message.
In the specific implementation process, the present embodiment has carried out 28 groups of test experiments, 28 tester's ages 20~
Between 35, male has 16, and women has 12, they have different degrees of insomnia situation.Before using the instrument, first
Investigation test carried out to them, calculate Pittsburgh Sleep Quality Index (Pittsburgh sleep quality index,
PSQI), sleep quality is divided into according to PSQI score by 5 grades: sleep quality very well (0~5 point), sleep quality can manage it (6~
10 points), sleep quality general (11~15 points), sleep quality it is very poor (16~21 points), record each tester PSQI and
Sleep quality grade, in this 26, sleep quality has 4 well, and what sleep quality can manage it has 7, and sleep quality generally has
10, sleep quality is very poor 7.Then within one month, each tester adheres to feeding back the electricity that declines using the eyeshade
Stream stimulation sleeping-assisting system is invented, and during this period, the work and rest and living habit of tester keeps being not much different with before test,
The project for needing to investigate in record PSQI daily.After one month, PSQI and sleep quality grade are calculated to everyone again,
The following table 1 illustrates tester using the sleep quality grade of present invention front and back as a result, 4 credit rating marks indicate are as follows: very well
1, it can manage it 2, general 3, very poor 4.
| Tester | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
| Before use | 1 | 4 | 3 | 3 | 1 | 2 | 2 |
| After use | 1 | 2 | 2 | 2 | 1 | 2 | 1 |
| Tester | 8 | 9 | 10 | 11 | 12 | 13 | 14 |
| Before use | 4 | 3 | 1 | 2 | 3 | 2 | 1 |
| After use | 2 | 1 | 2 | 2 | 1 | 1 | 1 |
| Tester | 15 | 16 | 17 | 18 | 19 | 20 | 21 |
| Validity period | 4 | 3 | 4 | 3 | 4 | 3 | 4 |
| After use | 2 | 2 | 3 | 2 | 1 | 2 | 2 |
| Tester | 22 | 23 | 24 | 25 | 26 | 27 | 28 |
| Before use | 3 | 4 | 2 | 2 | 3 | 3 | 2 |
| After use | 1 | 2 | 1 | 2 | 2 | 1 | 2 |
In test above, after the present invention, the number of cases that the sleep quality grade of tester improves is 20, matter of sleeping
Amount grade remains unchanged to have 7, and sleep quality decline has 1, wherein sleep quality is maintained at fine after using the present invention
Have 3, therefore all in all, the present invention has significant help to the sleep quality for improving insomnia crowd.
The same or similar label correspond to the same or similar components；
The terms describing the positional relationship in the drawings are only for illustration, should not be understood as the limitation to this patent；
Obviously, the above embodiment of the present invention be only to clearly illustrate example of the present invention, and not be pair
The restriction of embodiments of the present invention.For those of ordinary skill in the art, may be used also on the basis of the above description
To make other variations or changes in different ways.There is no necessity and possibility to exhaust all the enbodiments.It is all this
Made any modifications, equivalent replacements, and improvements etc., should be included in the claims in the present invention within the spirit and principle of invention
Protection scope within.
Claims (10)
1. a kind of eyeshade reaction type microcurrent stimulating sleeping-assisting system, including eyeshade ontology, which is characterized in that the eyeshade sheet
It in vivo include human-computer interaction module, control module, stimulation output module, sensor module and signal analysis module, wherein institute
Stating human-computer interaction module includes the first touch-switch, can start or close system by the first touch-switch；The sensor
Module acquires user's electro-physiological signals in real time and electro-physiological signals is transmitted to signal analysis module；The signal analysis module fortune
With signal processing technology and Nonlinear Dynamics, effective multidimensional dormant data feature is extracted；Control module receives signal
Regulating command is made after the data of analysis module and is sent to stimulation output module, and stimulation output module is according to regulating command output pair
The stimulus signal of the frequency and current strength answered.
2. eyeshade reaction type microcurrent stimulating sleeping-assisting system according to claim 1, which is characterized in that further include leading to
It interrogates module and mobile terminal, the human-computer interaction module further includes the second touch-switch, can be opened by the second touch-switch
Or closed communication module is received through communication module and is sent in control module after mobile terminal sets sleep pattern.
3. eyeshade reaction type microcurrent stimulating sleeping-assisting system according to claim 2, which is characterized in that the sensing
Device module includes the brain wave acquisition unit for acquiring EEG signals and the eye electricity acquisition unit for acquiring electro-ocular signal, is adopted
During collecting electro-physiological signals, the Skin Resistance of adaptive user.
4. eyeshade reaction type microcurrent stimulating sleeping-assisting system according to claim 3, which is characterized in that the signal
Analysis module includes 50Hz trapper and IIR bandpass filter, wherein removing collected physiological signal using 50Hz trapper
Power frequency, recycle IIR bandpass filter extract brain electrical feature signal relevant to sleep, including α wave (8~13Hz), β respectively
Wave (13~30Hz), θ wave (4~8Hz), δ wave (0.5~4Hz), sleep spindle (12~14Hz).
5. eyeshade reaction type microcurrent stimulating sleeping-assisting system according to claim 4, which is characterized in that the control
Module includes master controller.
6. eyeshade reaction type microcurrent stimulating sleeping-assisting system according to claim 5, which is characterized in that described
Random forest integrated learning approach is selected to establish the sleep quality Integrated Evaluation Model of user in master controller, the model utilizes
Decision tree uses gini index to divide attribute as the selection of decision tree as Weak Classifier, forms 30 Weak Classifiers, benefit altogether
The period result of identification sleep is obtained with the combination strategy of ballot method；The model is with signal analysis module treated electro-ocular signal
And the characteristic value of EEG signals, as input, control module carries out characteristic processing to the signal of window every 30 seconds views.
7. eyeshade reaction type microcurrent stimulating sleeping-assisting system according to claim 6, which is characterized in that sleep quality
The characteristic value that Integrated Evaluation Model is used includes multiple features on time domain, frequency domain and time-frequency domain, specific as follows:
A. temporal signatures:
Collected electro-ocular signal extracts saccadic eye movement number, frequency according to features such as amplitude and slopes；Using collecting
Original EEG signals, 5 kinds of brain electrical feature signals extracting, calculate its average value, standard deviation, kurtosis, maximum value, minimum value,
Zero-crossing rate and Petrosian parting coefficient (PFD):
In formula, k is the number of samples of EEG signals, NδIt is the sign reversing number of EEG signals；
B. frequency domain character:
Fourier's variation is carried out to EEG signals and its characteristic signal, calculates separately the energy ratio of signature waveform Yu whole segment signal
Value；
C. time and frequency domain characteristics:
EEG signals are analyzed using wavelet transform, wherein x (t) is EEG signals, and ψ is wavelet basis function, selection
Symlet wavelet basis:
By wavelet transformation, show that detail coefficients and approximation coefficient, pairing approximation coefficient carry out wavelet decomposition again, iteration carries out
3 times, obtain 3 detail coefficients, Di(n), their average value, standard deviation, peak are asked respectively this 3 detail coefficients in 3 i=1 ...
Degree and PFD.
8. eyeshade reaction type microcurrent stimulating sleeping-assisting system according to claim 7, which is characterized in that the sleep
Quality synthesis evaluation model obtains user's sleep stage, extracts the feature of its sleep quality assessment index, uses expert system
As the Controlling model of stimulation output module, closed loop feedback control circuit is formed, wherein the acquisition of sleep quality assessment index is
The sleep stage identified using above-mentioned sleep quality Integrated Evaluation Model, sleep rank of the record user in current sleep
Section historical data, from historical data, analyzing the Sleep architecture of user before the moment, the feature of calculating include shallowly sleep, sound sleep,
The ratio of rapid-eye-movement sleep and distribution, duration of always sleeping, also, according to from awakening to shallowly sleep, in sleep, sound sleep is to for quick eye
The sleep cycle order of dynamic sleep, divides sleep cycle, counts sleep cycle number as one of feature；What is extracted above
Input of the sleep characteristics as expert system, the knowledge base in the expert system contain a variety of sleep quality assessment index features
The knowledge rule of corresponding optimal stimulus pulse output, the inference machine of expert system is according to current input feature vector data, with control
System strategy finds the rule of applicable boost pulse type, and control module sends corresponding boost pulse kind to stimulation output module
Class instruction, adjusts the output of boost pulse in time.
9. eyeshade reaction type microcurrent stimulating sleeping-assisting system according to claim 8, which is characterized in that stimulation output
The output end of module uses voltage controlled current source, exports end in contact human body ear-lobe site tissue and temporal bone.
10. according to eyeshade reaction type microcurrent stimulating sleeping-assisting system, feature described in claim 2 to 8 any one
It is, the user demand and situation that the communication module is inputted by mobile terminal are conveyed to control module, while can will believe
Information is uploaded to cloud by way of wireless telecommunications after arranging by breath.
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Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110491498A (en) * | 2019-09-26 | 2019-11-22 | 西华师范大学 | A kind of data receiver and processing method of brain wave signal |
| CN110623664A (en) * | 2019-09-26 | 2019-12-31 | 川北医学院 | Control system and method for receiving and processing brain wave signals |
| CN110974195A (en) * | 2019-12-05 | 2020-04-10 | 珠海格力电器股份有限公司 | Method, device and storage medium for adjusting sleep environment |
| CN111528839A (en) * | 2020-05-29 | 2020-08-14 | 北京京东方健康科技有限公司 | Sleep detection method and device, sleep aid equipment and method |
| CN112545459A (en) * | 2020-12-04 | 2021-03-26 | 杭州赛翁思科技有限公司 | Drug addiction assessment correction system |
| CN113488138A (en) * | 2021-07-30 | 2021-10-08 | 山西慧虎健康科技有限公司 | Intelligent detection and targeted regulation shared sleep treasure and implementation method thereof |
| CN113662551A (en) * | 2021-08-24 | 2021-11-19 | 深圳康佳电子科技有限公司 | Sleep monitoring processing method and device based on intelligent eyeshade and intelligent eyeshade |
| CN114652938A (en) * | 2022-02-18 | 2022-06-24 | 南京安睡科技有限公司 | Intelligent closed-loop regulation and control stimulation system for promoting sleep and use method |
| CN115040754A (en) * | 2022-07-05 | 2022-09-13 | 上海全澜科技有限公司 | Sleep enhancement system based on brain activity detection |
| CN116504357A (en) * | 2023-06-28 | 2023-07-28 | 安徽星辰智跃科技有限责任公司 | Sleep periodicity detection and adjustment method, system and device based on wavelet analysis |
| CN117590770A (en) * | 2024-01-19 | 2024-02-23 | 深圳市百泰实业股份有限公司 | Intelligent sleep eye mask control method based on intelligent wearing |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2733972A1 (en) * | 2010-03-12 | 2011-09-12 | Gerard V. Sunnen | Vibrational delta and theta brain wave induction apparatus and method for stimulation of sleep |
| CN205084213U (en) * | 2015-10-20 | 2016-03-16 | 浙江神灯生物科技有限公司 | Sleep improves device |
| CN106039578A (en) * | 2016-05-11 | 2016-10-26 | 付金龙 | Wearable treatment device and device control method |
| CN206239412U (en) * | 2016-08-18 | 2017-06-13 | 中山衡思健康科技有限公司 | A kind of wearable sleep monitor eyeshade for the electric compound detection of brain electricity and eye |
| CN107693944A (en) * | 2017-10-23 | 2018-02-16 | 桂林宜康电子科技有限公司 | A kind of sleep therapy instrument |
| CN109091141A (en) * | 2018-07-25 | 2018-12-28 | 浙江理工大学 | A kind of sleep quality monitor and its monitoring method based on brain electricity and eye electricity |
| CN109316170A (en) * | 2018-11-16 | 2019-02-12 | 武汉理工大学 | Brain wave assisting sleep and wake-up system based on deep learning |
| US20190099582A1 (en) * | 2017-10-04 | 2019-04-04 | NeuroGeneces LLC | Sleep performance system and method of use |
| CN109621156A (en) * | 2019-01-04 | 2019-04-16 | 广东工业大学 | A kind of brain electricity reaction type microcurrent stimulating sleep assistance instrument and application method |
-
2019
- 2019-05-06 CN CN201910372423.9A patent/CN110251801A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2733972A1 (en) * | 2010-03-12 | 2011-09-12 | Gerard V. Sunnen | Vibrational delta and theta brain wave induction apparatus and method for stimulation of sleep |
| CN205084213U (en) * | 2015-10-20 | 2016-03-16 | 浙江神灯生物科技有限公司 | Sleep improves device |
| CN106039578A (en) * | 2016-05-11 | 2016-10-26 | 付金龙 | Wearable treatment device and device control method |
| CN206239412U (en) * | 2016-08-18 | 2017-06-13 | 中山衡思健康科技有限公司 | A kind of wearable sleep monitor eyeshade for the electric compound detection of brain electricity and eye |
| US20190099582A1 (en) * | 2017-10-04 | 2019-04-04 | NeuroGeneces LLC | Sleep performance system and method of use |
| CN107693944A (en) * | 2017-10-23 | 2018-02-16 | 桂林宜康电子科技有限公司 | A kind of sleep therapy instrument |
| CN109091141A (en) * | 2018-07-25 | 2018-12-28 | 浙江理工大学 | A kind of sleep quality monitor and its monitoring method based on brain electricity and eye electricity |
| CN109316170A (en) * | 2018-11-16 | 2019-02-12 | 武汉理工大学 | Brain wave assisting sleep and wake-up system based on deep learning |
| CN109621156A (en) * | 2019-01-04 | 2019-04-16 | 广东工业大学 | A kind of brain electricity reaction type microcurrent stimulating sleep assistance instrument and application method |
Non-Patent Citations (4)
| Title |
|---|
| GIOVANNI SANTOSTASI等: "Phase-locked loop for precisely time acoustic stimulation during sleep", 《JOURNAL OF NEUROSCIENCE METHODS》 * |
| 李斐: "基于脑电信号特征提取的睡眠分期方法研究", 《中国优秀硕士学位论文全文数据库 医药卫生科技辑》 * |
| 王保华等: "《生物医学电子学》", 31 October 1988, 高等教育出版社 * |
| 陈秉学等: "《胸科肿瘤麻醉学》", 30 November 2001, 郑州大学出版社 * |
Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110491498A (en) * | 2019-09-26 | 2019-11-22 | 西华师范大学 | A kind of data receiver and processing method of brain wave signal |
| CN110623664A (en) * | 2019-09-26 | 2019-12-31 | 川北医学院 | Control system and method for receiving and processing brain wave signals |
| CN110974195A (en) * | 2019-12-05 | 2020-04-10 | 珠海格力电器股份有限公司 | Method, device and storage medium for adjusting sleep environment |
| CN111528839A (en) * | 2020-05-29 | 2020-08-14 | 北京京东方健康科技有限公司 | Sleep detection method and device, sleep aid equipment and method |
| CN112545459A (en) * | 2020-12-04 | 2021-03-26 | 杭州赛翁思科技有限公司 | Drug addiction assessment correction system |
| CN113488138A (en) * | 2021-07-30 | 2021-10-08 | 山西慧虎健康科技有限公司 | Intelligent detection and targeted regulation shared sleep treasure and implementation method thereof |
| CN113488138B (en) * | 2021-07-30 | 2022-02-08 | 山西慧虎健康科技有限公司 | Intelligent detection and targeted regulation shared sleep treasure and implementation method thereof |
| CN113662551A (en) * | 2021-08-24 | 2021-11-19 | 深圳康佳电子科技有限公司 | Sleep monitoring processing method and device based on intelligent eyeshade and intelligent eyeshade |
| CN114652938A (en) * | 2022-02-18 | 2022-06-24 | 南京安睡科技有限公司 | Intelligent closed-loop regulation and control stimulation system for promoting sleep and use method |
| CN114652938B (en) * | 2022-02-18 | 2023-12-26 | 南京安睡科技有限公司 | Intelligent closed-loop regulation stimulation system for promoting sleep and use method |
| CN115040754A (en) * | 2022-07-05 | 2022-09-13 | 上海全澜科技有限公司 | Sleep enhancement system based on brain activity detection |
| CN115040754B (en) * | 2022-07-05 | 2024-05-07 | 上海全澜科技有限公司 | Sleep enhancement system based on brain activity detection |
| CN116504357A (en) * | 2023-06-28 | 2023-07-28 | 安徽星辰智跃科技有限责任公司 | Sleep periodicity detection and adjustment method, system and device based on wavelet analysis |
| CN116504357B (en) * | 2023-06-28 | 2024-05-10 | 安徽星辰智跃科技有限责任公司 | Sleep periodicity detection and adjustment method, system and device based on wavelet analysis |
| CN117590770A (en) * | 2024-01-19 | 2024-02-23 | 深圳市百泰实业股份有限公司 | Intelligent sleep eye mask control method based on intelligent wearing |
| CN117590770B (en) * | 2024-01-19 | 2024-04-02 | 深圳市百泰实业股份有限公司 | Intelligent sleep eye mask control method based on intelligent wearing |
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