CN108852304A - Sleeping quality analyzing device and method based on EEG signals - Google Patents
Sleeping quality analyzing device and method based on EEG signals Download PDFInfo
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- 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
- 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
- A61B5/25—Bioelectric electrodes therefor
- A61B5/279—Bioelectric electrodes therefor specially adapted for particular uses
- A61B5/291—Bioelectric electrodes therefor specially adapted for particular uses for electroencephalography [EEG]
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- 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]
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- A—HUMAN NECESSITIES
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- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
- A61B5/6802—Sensor mounted on worn items
- A61B5/6803—Head-worn items, e.g. helmets, masks, headphones or goggles
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Abstract
The invention discloses sleeping quality analyzing devices and method based on EEG signals, overcome passively improves user's sleep quality and expensive, inconvenient to use and be not able to use the problem of family understands the sleep quality of oneself and improved at present, which includes electroencephalogramsignal signal analyzing instrument and user mobile phone client；Electroencephalogramsignal signal analyzing instrument includes electrode for encephalograms group, EEG Processing module, FPGA microcontroller, bluetooth module, the helmet and power module；Electrode for encephalograms group is mounted on the helmet, electrode for encephalograms group is connect with EEG Processing module electric wire, EEG Processing module is connect with FPGA microcontroller electric wire, FPGA microcontroller is connect with bluetooth module electric wire, and power module is connect with EEG Processing module, FPGA microcontroller with bluetooth module electric wire respectively；Electroencephalogramsignal signal analyzing instrument is connect with user mobile phone client using communication.The Analysis of sleeping quality method based on EEG signals that the present invention also provides a kind of.
Description
Technical field
The present invention relates to a kind of methods for belonging to Cognitive Neuroscience and information technology field, more precisely, of the invention
It is related to a kind of sleeping quality analyzing device and method based on EEG signals.
Background technique
With the continuous development of society, people are faced with more and more pressure, and the state of mind of people is more or less
It is affected.Sleep be relieve stress, adjust the best way of spirit, and it to the reparation of function of human body, promote human brain
Memory, reduce illness rate, strengthen immunity etc. suffers from important function, therefore people increasingly pay close attention to oneself sleep quality and
Sleep quality.
EEG signals are the autonomous potential activities for being generated by brain neurological motion and being present in always central nervous system,
Sleep cerebral electricity signal is acquired in cerebral cortex by brain-computer interface technology, sleep can be studied, to improve sleeping for people
Dormancy quality provides effective means.2007, American National sleep medicine association made new unified sleep stage interpretation
Guide, they are respectively lucid interval, rapid-eye-movement sleep phase REM and NREM sleep phase NREM, wherein non-rapid eye
Dynamic sleep period NREM is divided into S1 phase (drowsy state), S2 phase (rapid eye movement sleep), S3 phase (moderate sleep period) and S4 phase (deep sleep again
Phase).Normal person's sleep initially enters NREM sleep phase NREM by lucid interval, and sequentially enters the S2 phase by the S1 phase rapidly,
S3 phase, S4 phase simultaneously continue；There is first time rapid eye movement after NREM sleep phase NREM continues 80-120 minutes
Sleep period REM enters NREM sleep phase NREM next time after continuing a few minutes, forms NREM sleep phase NREM
With rapid-eye-movement sleep phase REM cycle period, the average rapid eye movement REM sleep of appearance in every 90 minutes, closer to sleep
The later period rapid-eye-movement sleep phase REM duration gradually extends, 10-30 minutes sustainable every time.Normal person is in S1, S2 phase, brain
The α wave of electric wave is gradually replaced by θ wave；In rapid-eye-movement sleep phase REM, muscle is fully relaxed, body metabolism rate rise close to
Wakefulness level, 80% or more people have a dream in rapid-eye-movement sleep phase REM, i.e. rapid-eye-movement sleep phase REM and the close phase of dream
It closes, it is seen that mixed frequency electroencephalogram, rapid eye movement, Muscle tensility disappear.Normal person is in S1, S2 phase and rapid-eye-movement sleep phase REM
The stimulation of different degrees of sound and light can be experienced.Studies have shown that accounting for S1, S2 phase pair of entire sleeping time about 55%
Relieving fatigue effect is little, and only enters sound sleep phase and rapid-eye-movement sleep phase REM, just has larger effect to relieving fatigue.
That is, the quality of sleep depends on the depth that the depth that nerve inhibits namely is slept.It entirely sleeps shared by deep sleep
The ratio of time is bigger, and sleep quality is better.Studies have shown that eeg data plays vital work to research sleep stage
With.
The existing sleeping apparatus product based on brain wave is mostly specific by broadcasting music, transmission in user's sleep period
Band signal promotes user's sleep, but this method can only passively improve user's sleep quality, and expensive, using not
It is convenient.Or user's sleep quality is only simply recorded, targetedly sleep quality analysis is not carried out, without intuitive
User is showed, do not achieve the purpose that user is made to understand the sleep quality of oneself in depth and is improved.
Summary of the invention
The technical problem to be solved by the present invention is to overcome it is of the existing technology can only passively improve user sleep
Quality and expensive, inconvenient to use and do not reach and make user understand the sleep quality of oneself in depth and improve
The problem of, provide a kind of sleeping quality analyzing device and method based on EEG signals.
In order to solve the above technical problems, the present invention adopts the following technical scheme that realization：It is described based on EEG signals
Sleeping quality analyzing device include electroencephalogramsignal signal analyzing instrument and user mobile phone client；
The electroencephalogramsignal signal analyzing instrument includes electrode for encephalograms group, EEG Processing module, FPGA microcontroller, bluetooth
Module, the helmet and power module；
The electrode for encephalograms group is mounted on the helmet, and is connected between electrode for encephalograms and EEG Processing module using electric wire
It connects, adopts and run wires between EEG Processing module and FPGA microcontroller, between FPGA microcontroller and bluetooth module
It adopts and runs wires to, connected between power module and EEG Processing module, FPGA microcontroller and bluetooth module using electric wire
It connects；
Electroencephalogramsignal signal analyzing instrument, which passes through, to be connected between bluetooth module and user mobile phone client using communication.
Electrode for encephalograms group described in technical solution uses the bioelectric measurement silver-silver chloride solid of 16 model CX
Powder sintered electrode is fixedly mounted on the inside of the helmet, that is, is respectively and fixedly installed to the left side that international 10-20 system placement methods define
Antinion Fp1, right antinion Fp2, left volume F3, right volume F4, left front temporo F7, it is right before temporo F8, left centre C3, right median C4, left ear-lobe A1,
Auris dextra hang down A2, left top P3, right top P4, left back temporo T5, it is right after temporo T6, left pillow O1, right pillow O2 electrode position at, wherein left ear-lobe
A1, left ear-lobe A2 are at installation reference electrode.
EEG Processing module described in technical solution include preamplifier, high-pass filtering circuit, trap circuit,
Low-pass filter circuit, post amplifier and analog-digital converter；
The preamplifier selects the instrument amplifier for acquiring biological electric signals of model INA128；It is described
High-pass filtering circuit lower-cut-off frequency be 0.3Hz；The trap circuit selects the 50HZ trapper of model F42N50,
The model trapper center trap frequency has been set；The low-pass filter circuit cutoff frequency is 50HZ；After described
Set the instrument amplifier for acquiring biological electric signals that amplifier selects model INA128；The analog-digital converter uses
The A/D converter for bioelectric measurement of model ADS1298；The preamplifier of the model INA128 draws
The pin Vi of foot VO and high-pass filtering circuit, which is adopted, to be run wires to, and the pin VO's and model F42N50 of high-pass filtering circuit falls into
The pin VIN of wave circuit, which is adopted, to be run wires to, the pin Vo of the trap circuit of model F42N50 and drawing for low-pass filter circuit
Foot Vi, which is adopted, to be run wires to, and the pin In of the post amplifier of the pin Vo and model INA128 of low-pass filter circuit is using electricity
Line connection, the pin Vo of the post amplifier of model INA128 are adopted with the pin VIN of the analog-digital converter of model ADS1298
It runs wires to.
High-pass filtering circuit described in technical solution is by resistance R1, resistance R2, capacitor C1, capacitor C2 and model
The operational amplifier of TLC2252AID forms；One end of pin Vi and capacitor C1, which is adopted, to be run wires to, the other end of capacitor C1 with
One end of capacitor C2, which is adopted, to be run wires to, and the other end of capacitor C1 and one end of resistance R2 are adopted and run wires to, and resistance R2's is another
No. 1 pin of one end and the operational amplifier of model TLC2252AID, which is adopted, to be run wires to, the other end and model of capacitor C2
It adopts and runs wires to for No. 3 pins of the operational amplifier of TLC2252AID, one end of the other end and resistance R1 of capacitor C2 is adopted
It runs wires to, the other end of resistance R1 is adopted with pin GND to be run wires to, the operational amplifier of model TLC2252AID
No. 1 pin of No. 2 pins and the operational amplifier of model TLC2252AID, which is adopted, to be run wires to, model TLC2252AID's
No. 4 pins of operational amplifier are adopted with pin GND to be run wires to, and No. 8 of the operational amplifier of model TLC2252AID are drawn
Foot is adopted with pin VCC and is run wires to, and No. 1 pin and pin Vo of the operational amplifier of model TLC2252AID use electric wire
Connection；
The low-pass filter circuit by resistance R1, resistance R2, capacitor C1, capacitor C2 and model TLC2252AID fortune
Calculate amplifier composition；One end of pin Vi and capacitor C1, which is adopted, to be run wires to, and one end of the other end and capacitor C2 of capacitor C1 is adopted
It runs wires to, the other end of capacitor C1 and one end of resistance R2 are adopted and run wires to, the other end and model of resistance R2
No. 1 pin of the operational amplifier of TLC2252AID, which is adopted, to be run wires to, the other end and model TLC2252AID of capacitor C2
No. 3 pins of operational amplifier adopt and run wires to, the other end of capacitor C2 and one end of resistance R1 are adopted and are run wires to, electricity
The other end of resistance R1 is adopted with pin GND to be run wires to, No. 2 pins and model of the operational amplifier of model TLC2252AID
It adopts and runs wires to for No. 1 pin of the operational amplifier of TLC2252AID, the 4 of the operational amplifier of model TLC2252AID
Number pin is adopted with pin GND to be run wires to, and No. 8 pins and the pin VCC of the operational amplifier of model TLC2252AID are adopted
It runs wires to, No. 1 pin of the operational amplifier of model TLC2252AID is adopted with pin Vo to be run wires to.
It is adopted between EEG Processing module and FPGA microcontroller described in technical solution and runs wires to refer to：Institute
The EEG Processing module stated uses electric wire by the analog-digital converter and FPGA microcontroller of model ADS1298 therein
Connection：
The FPGA microcontroller of the pin D0 and model EP2C5Q208 of the analog-digital converter of the model ADS1298
The pin A0 electric wire of device connects, and the pin D1 and the FPGA of model EP2C5Q208 of the analog-digital converter of model ADS1298 are micro-
The pin A1 electric wire of controller connects, the pin D2's and model EP2C5Q208 of the analog-digital converter of model ADS1298
The pin A2 electric wire of FPGA microcontroller connects, the pin D3 and model of the analog-digital converter of model ADS1298
The pin A3 electric wire of the FPGA microcontroller of EP2C5Q208 connects, the pin D4 and type of the analog-digital converter of model ADS1298
Number for EP2C5Q208 FPGA microcontroller pin A4 electric wire connection, the pin D5 of the analog-digital converter of model ADS1298
It is connect with the pin A5 electric wire of the FPGA microcontroller of model EP2C5Q208, the analog-digital converter of model ADS1298 draws
Foot D6 is connect with the pin A6 electric wire of the FPGA microcontroller of model EP2C5Q208, the analog-digital converter of model ADS1298
Pin D7 connect with the pin A7 electric wire of the FPGA microcontroller of model EP2C5Q208.
It is adopted between FPGA microcontroller and bluetooth module described in technical solution and runs wires to refer to：The FPGA
Microcontroller uses the FPGA microcontroller of model EP2C5Q208, and bluetooth module uses the bluetooth module of model HC05；Two
It adopts and runs wires between person：
The bluetooth module of the pin RXD1 and model HC05 of the FPGA microcontroller of the model EP2C5Q208
The connection of pin TXD electric wire, the bluetooth module of the pin TXD1 and model HC05 of the FPGA microcontroller of model EP2C5Q208
Pin RXD electric wire connection.
Between power module described in technical solution and EEG Processing module, FPGA microcontroller and bluetooth module
It adopts and runs wires to refer to：The power module is the power module using model LH20-10B03；Model LH20-
The power module of 10B03 passes through the pin V+ of pin Vo+ and preamplifier, pin VCC, the trap circuit of high-pass filtering circuit
Pin VIN, the pin VCC of low-pass filter circuit, the pin V+ of post amplifier, pin VDD, FPGA of analog-digital converter it is micro-
The pin VCCIO of controller and the pin VDD electric wire of bluetooth module connect；The power module of model LH20-10B03 is by drawing
The pin V- of foot Vo- and preamplifier, the pin GND of high-pass filtering circuit, the pin GND of trap circuit, low-pass filtering electricity
The pin GND on road, the pin V- of post amplifier, the pin GND of pin GND, FPGA microcontroller of analog-digital converter and blue
The pin GND electric wire of tooth module connects；
The power module of the pin VCCIO and model LH20-10B03 of the FPGA microcontroller of model EP2C5Q208
Pin Vo+ electric wire connection；The power module of the pin VDD and model LH20-10B03 of the bluetooth module of model HC05
The connection of pin Vo+ electric wire；The electricity of the pin GND and model LH20-10B03 of the FPGA microcontroller of model EP2C5Q208
The pin Vo- electric wire of source module connects；The power supply of the pin GND and model LH20-10B03 of the bluetooth module of model HC05
The pin Vo- electric wire of module connects.
A kind of Analysis of sleeping quality method based on EEG signals, including steps are as follows：
1) starting electroencephalogramsignal signal analyzing instrument and electroencephalogramsignal signal analyzing instrument initialize：
The electroencephalogramsignal signal analyzing instrument initial method is electrification reset, is resetted when being initially powered, makes brain telecommunications
FPGA microcontroller output state in number analyzer is reset, into original state；
2) electroencephalogramsignal signal analyzing instrument and user mobile phone client carry out Bluetooth pairing：
The electroencephalogramsignal signal analyzing instrument and user mobile phone client carries out Bluetooth pairing and refers to upon initialization, brain electricity
The bluetooth in bluetooth module and user mobile phone client in signal analyzer is wirelessly connected；
3) electrode for encephalograms group acquires user's EEG signals：
User correctly wears the helmet, and 16 electrodes of the electrode for encephalograms group being mounted on the helmet are individually positioned in international 10-
Left antinion Fp1 that 20 system placement methods define, right antinion Fp2, left volume F3, right volume F4, left front temporo F7, it is right before temporo F8, left centre
C3, right median C4, left ear-lobe A1, auris dextra hang down A2, left top P3, right top P4, left back temporo T5, it is right after temporo T6, left pillow O1, right pillow O2
User's EEG signals are acquired at electrode position；
4) EEG signals are sent in FPGA microcontroller after EEG Processing resume module；
5) FPGA microcontroller analyzes EEG signals, sends user hand passenger through bluetooth module for analysis result
Family end；
6) user mobile phone client receives data and storage records：
User mobile phone client passes through the data that bluetooth real-time reception electroencephalogramsignal signal analyzing instrument transmits, when by data receiver
Between, user's sleep stage information stores to database；
7) user mobile phone client judges that user sleeps so that whether the bluetooth module of electroencephalogramsignal signal analyzing instrument interrupts transmission
Whether terminate, if transmission ending, determine that user wakes up, stops receiving data；Otherwise user is determined to continue in sleep
Analyze data；
8) user mobile phone client analyzes sleep quality, draws sleep curve and will analyze as the result is shown to user.
FPGA microcontroller described in technical solution analyzes EEG signals, and analysis result is sent out through bluetooth module
User mobile phone client is sent to refer to：
1) FPGA microcontroller receives digital brain electrical signal；
2) amplitude-frequency analysis is carried out to digital EEG signals, judges sleep period locating for user, the judgement user institute
The specific judgment method of the sleep period at place is as follows：
(1) when 8~13 times per second α waves disappear, when 2~7 times per second θ waves occur, it is believed that sleep enters the drowsy state；
(2) when there is the automatic amplitude modulated phenomenon of α wave, i.e., a burst of α wave starts that amplitude is smaller, and centre becomes larger, and amplitude becomes again later
Greatly, in spindle and when there is specific κ wave, it is believed that sleep enters rapid eye movement sleep；
(3) when δ wave is more than 20%, but it is no more than 50%, when amplitude is more than 74 μ V, it is believed that sleep enters moderate and sleeps
Phase；
(4) when δ wave accounts for 50% or more, it is believed that sleep enters the deep sleep phase；
(5) when there is low wave amplitude, mixed frequency E.E.G, the θ for showing as the low-voltage that frequency is 3-7Hz involved compared with lucid interval
When the slow 1-2Hz of α wave low frequency α wave, there is typical sawtooth wave occur, it is believed that sleep enters rapid-eye-movement sleep phase REM；
(6) since drowsy state, rapid eye movement sleep are little to relieving fatigue effect, only enter deep sleep phase and rapid eye movement
Sleep period REM just has larger effect to relieving fatigue, its sleep quality is judged in order to facilitate user, herein by rapid-eye-movement sleep
Phase REM playback moderate sleep period；Think that user is in lucid interval except above situation；
3) sleep period locating for user is transmitted to user mobile phone client by bluetooth module.
User mobile phone client described in technical solution analyzes sleep quality, draws sleep curve and shows analysis result
Show and refers to user：
1) according to user's that night each stage sleep duration in database, unit is minute, according to formula：Sleep scores=
[deep sleep duration/duration of always sleeping × 0.5+ moderate sleep duration/always sleeps duration × 0.4+ (shallowly when sleep duration+sleep
It is long)/duration × 0.1 of always sleeping] × 100, calculate user every night before sleep scores, with user 7 days sleep scores variation tendencies into
Row compares, and draws nearly 7 days change curves, and user can intuitively check the variation of oneself sleep quality, and user is facilitated to be directed to certainly
Oneself work and rest is adjusted, and improves sleep quality；
2) according to user's dormant data in database, using the time as horizontal axis, initial time is that user wears EEG signals point
1 time of analyzer, the termination time is user's recovery time, using sleep stage as the longitudinal axis, draws user's sleep curve, user can be straight
The variation for checking oneself daily sleep quality seen facilitates user to be adjusted for the work and rest of oneself, improves sleep quality；
3) according to user's dormant data in database, according to certain stage sleep duration/duration of always sleeping, calculating each stage sleeps
Dormancy duration accounting draws sleep quality pie chart, and user is facilitated to be adjusted for the work and rest of oneself, improves sleep quality；
4) according to user's dormant data in database, according to user when time each stage sleep accounting, with preceding 7 days proportions
It compares, if 7 days proportion average values are more than 5% to certain sleep stage earlier above, user mobile phone client prompt is used
Family：Certain stage sleep is abnormal, it is noted that movement, diet of keeping fit keep good work and rest；If each stage accounting amplitude of variation is equal
Within 5%, then user mobile phone client prompts user：This sleep is without exception, continuing with holding.
Compared with prior art the beneficial effects of the invention are as follows：
It is slept 1. EEG signals are applied to by the sleeping quality analyzing device and method of the present invention based on EEG signals
It in dormancy Stage Classification, and is combined with user mobile phone, EEG signals are analyzed when sleeping to user, judge the locating sleep of user
Stage, and real-time Transmission is to user mobile phone client；
It is slept 2. the sleeping quality analyzing device and method of the present invention based on EEG signals is targetedly drawn out
Dormancy curve, nearly 7 days sleep scores change curves, sleep stage accounting pie chart, and compare user nearly 7 days daily each sleep stages
Accounting informs the information such as the variation of its sleep quality of user, intuitively uses information by user mobile phone client output information
The variation of oneself daily sleep quality is checked at family, and user is facilitated to be adjusted for the work and rest of oneself, improves sleep quality.
Detailed description of the invention
The present invention will be further described below with reference to the drawings：
Fig. 1 is the schematic block diagram of the sleeping quality analyzing device structural principle of the present invention based on EEG signals；
Fig. 2 is to be placed in electroencephalogramsignal signal analyzing instrument in the sleeping quality analyzing device of the present invention based on EEG signals
In electrode for encephalograms group laying method schematic diagram；
Fig. 3 is that the electricity of EEG signals analyzer in the sleeping quality analyzing device of the present invention based on EEG signals is former
Reason figure；
Fig. 4 is the brain electricity of EEG signals analyzer in the sleeping quality analyzing device of the present invention based on EEG signals
The circuit diagram of the high-pass filtering circuit of signal processing module；
Fig. 5 is the brain electricity of EEG signals analyzer in the sleeping quality analyzing device of the present invention based on EEG signals
The circuit diagram of the low-pass filter circuit of signal processing module；
Fig. 6 is the Analysis of sleeping quality method flow schematic block diagram of the present invention based on EEG signals；
Fig. 7 is EEG Processing employed in the Analysis of sleeping quality method of the present invention based on EEG signals
The workflow schematic block diagram of resume module EEG signals；
Fig. 8 is FPGA microcontroller employed in the Analysis of sleeping quality method of the present invention based on EEG signals
Analyze the workflow schematic block diagram of EEG signals；
In figure：1. electroencephalogramsignal signal analyzing instrument, 2. user mobile phone clients, 1-1. electrode for encephalograms group, at 1-2. EEG signals
Manage module, 1-3.FPGA microcontroller, 1-4. bluetooth module.
Specific embodiment
The present invention is explained in detail with reference to the accompanying drawing：
Refering to fig. 1, the sleeping quality analyzing device based on EEG signals includes electroencephalogramsignal signal analyzing instrument 1 and user
Cell phone client 2.
The electroencephalogramsignal signal analyzing instrument 1 is multichannel brain electric acquisition device, and electroencephalogramsignal signal analyzing instrument 1 includes electrode for encephalograms
Group 1-1, EEG Processing module 1-2, FPGA microcontroller 1-3, bluetooth module 1-4, power module and the helmet.
The number of electrodes that the electrode for encephalograms group 1-1 is used is 16, is individually positioned in international 10-20 system placement methods
The electrode position of definition：Left antinion Fp1, right antinion Fp2, left volume F3, right volume F4, left front temporo F7, it is right before temporo F8, left centre C3,
Right median C4, left ear-lobe A1, auris dextra hang down temporo T6, left pillow O1 behind A2, left top P3, right top P4, left back temporo T5, the right side, at right pillow O2,
It is reference electrode at middle A1, A2.
The electrode that the electrode for encephalograms group 1-1 is used is the biology of the model CX produced by Chinese Green Imtech
Electrical measurement silver-silver chloride solid powder sintered electrode, is fixed on the inside of the helmet, which has strong antijamming capability, be not easy
Polarization, measurement accuracy is high, and noise is small, and reusable advantage ensure that the accuracy and sensitivity of eeg signal acquisition；It uses
The bioelectric measurement of model CX is applied to by the sleep cerebral electricity conductive paste of the model GT-20 of Chinese Green Imtech production
The side contacted with silver-silver chloride solid powder sintered electrode with scalp.
For the helmet (shell) by having the hard material of certain elasticity to constitute, inside makes wearer with flexible material
Be comfortable on, under the support of the helmet, wearer using when can lie low or lie on one's side, make without influencing electrode for encephalograms group 1-1
With.There is hole on the inside of the helmet, hole is for placing electrode for encephalograms, the electrode that the position in hole and world 10-20 system placement methods define
Position：Temporo F8, left centre C3, right median C4, a left side before left antinion Fp1, right antinion Fp2, left volume F3, right volume F4, left front temporo F7, the right side
Temporo T6, left pillow O1, right pillow O2 are corresponding behind the vertical A2 of ear-lobe A1, auris dextra, left top P3, right top P4, left back temporo T5, the right side.
Referring to Fig.2, the international 10-20 system electrode placement methods are that normal electrode as defined in international electroencephalography meeting is put
Set method.It is the top view looked down from the crown in figure, shown line segment is the space curve along the connection of curved surface each point.International 10-
20 system electrode placement methods define 25 points.The position for being arranged in left hemisphere is marked using odd number, is arranged in the position of right hemisphere
It sets and is marked using even number；A1 and A2 represents left and right ear-lobe, and the electrode for encephalograms being placed on A1 and A2 is reference electrode；Nz and Lz generation
At the table nasion and external occipital protuberance；Curved surface includes front and back sagittal line, transverse presentation line, side bit line；
The front and back sagittal line is to take a space line from Lz from nasion Nz to external occipital protuberance along curved surface, on this line,
Each point is marked from front to back, antinion midpoint Fpz, metopion Fz, central point Cz, vertex Pz, pillow point Oz is successively named as, in antinion
The distance of point Fpz to nasion Nz and the distance of pillow point Oz to external occipital protuberance Lz respectively account for the 10% of this line overall length, remaining each point is equal
It is separated by with the 20% of this line overall length；
The transverse presentation line is to hang down A2 from roots of zygoma recess before left tragus, that is, left ear-lobe A1 by central point Cz to auris dextra
Take a space line along curved surface, the left and right sides of this line symmetrically mark T3 in left temporo, T4 in right temporo, left centre C3, in the right side
C4 is entreated, T3 in left temporo, T4 point and left ear-lobe A1, auris dextra hang down and respectively account for the 10% of transverse presentation line overall length at a distance from A2 in right temporo, remaining is respectively
Point is separated by with the 20% of transverse presentation line overall length；
The side bit line be gone backward through from antinion midpoint Fpz T3 in left temporo, in right temporo T4 point to pillow point Oz along curved surface
Left and right side space line is taken respectively, symmetrically marks left antinion Fp1, right antinion Fp2, a left side from front to back on left and right side line
Preceding temporo F7, it is right before temporo F8, left back temporo T5, it is right after temporo T6, left pillow O1, right pillow O2 each point；Left antinion Fp1, right antinion Fp2 point to volume
The distance of pole midpoint Fpz respectively accounts for the 10% of this line overall length at a distance from left pillow O1, right pillow O2 point to pillow point Oz point, remaining is each
T3 in point, including left temporo, T4 point in right temporo are separated by between adjacent two o'clock with the 20% of this line overall length；It is logical from left front temporo F7
It crosses before metopion Fz to the right side temporo F8 and takes a space line along curved surface, left volume F3 is located at left front temporo F7 and metopion Fz space curve
Middle position, right volume F4 point are located at the middle position of temporo F8 space curve before metopion Fz and the right side；Pass through vertex from left back temporo T5
Temporo T6 takes a space line along curved surface after Pz to the right side, and left top P3 is located at the middle position of left back temporo T5 and vertex Pz space curve,
Right top P4 is located at the middle position of temporo T6 space curve behind vertex Pz and the right side.
Refering to Fig. 3, the electrode for encephalograms group 1-1 in the electroencephalogramsignal signal analyzing instrument 1 acquires EEG signals, passes through electrode wires
It is connect with EEG Processing module 1-2；EEG Processing module 1-2 handles EEG signals, output port with
It adopts and runs wires between the input port of FPGA microcontroller 1-3；FPGA microcontroller 1-3 to treated EEG signals into
Row analysis, adopts between bluetooth module 1-4 and runs wires to, and bluetooth module 1-4 is sent to user mobile phone client for result is analyzed
End 2.
The EEG Processing module 1-2 includes preamplifier, high-pass filtering circuit, trap circuit, low pass filtered
Wave circuit, post amplifier and analog-digital converter.
The preamplifier selects putting dedicated for the instrument of acquiring biological electric signals for U.S. boolean company production
Big device INA128；
Refering to Fig. 4, the lower-cut-off frequency of the high-pass filtering circuit is 0.3Hz, by resistance R1, resistance R2, capacitor
The operational amplifier of C1, capacitor C2 and model TLC2252AID form；One end of pin Vi and capacitor C1, which is adopted, to be run wires to,
One end of the other end of capacitor C1 and capacitor C2, which are adopted, to be run wires to, and the other end of capacitor C1 and one end of resistance R2 use electric wire
Connection, the other end of resistance R2 are adopted with No. 1 pin of the operational amplifier of model TLC2252AID and are run wires to, capacitor C2
The other end and No. 3 pins of the operational amplifier of model TLC2252AID adopt and run wires to, the other end of capacitor C2 with
One end of resistance R1, which is adopted, to be run wires to, and the other end of resistance R1 is adopted with pin GND to be run wires to, model TLC2252AID
No. 2 pins of operational amplifier adopt and run wires to No. 1 pin of the operational amplifier of model TLC2252AID, model
It adopts and runs wires to pin GND for No. 4 pins of the operational amplifier of TLC2252AID, the operation of model TLC2252AID
No. 8 pins of amplifier are adopted with pin VCC to be run wires to, No. 1 pin of the operational amplifier of model TLC2252AID with
Pin Vo, which is adopted, to be run wires to；
The trap circuit selects the 50HZ trapper of model F42N50, and the model trapper center trap frequency is
It is set, is directly used without debugging, peripheral circuit is simple；
Refering to Fig. 5, the low-pass filter circuit cutoff frequency is 50HZ, by resistance R3, resistance R4, capacitor C3, capacitor
The operational amplifier of C4 and model TLC2252AID composition；One end of pin Vi and resistance R3, which is adopted, to be run wires to, resistance R3
The other end and one end of resistance R4 adopt and run wires to, the other end of resistance R3 and one end of capacitor C4 are adopted and are run wires to,
No. 1 pin of the other end of capacitor C4 and the operational amplifier of model TLC2252AID, which is adopted, to be run wires to, and resistance R4's is another
No. 3 pins of one end and the operational amplifier of model TLC2252AID, which are adopted, to be run wires to, the other end and capacitor of resistance R4
One end of C3, which is adopted, to be run wires to, and the other end of capacitor C3 is adopted with pin GND to be run wires to, the fortune of model TLC2252AID
No. 1 pin of No. 2 pins and the operational amplifier of model TLC2252AID of calculating amplifier, which is adopted, to be run wires to, model
The pin GND of the operational amplifier of No. 4 pins and model TLC2252AID of the operational amplifier of TLC2252AID is using electricity
Line connection, No. 8 pins of the operational amplifier of model TLC2252AID are adopted with pin VCC to be run wires to, model
No. 1 pin of the operational amplifier of TLC2252AID is adopted with pin Vo to be run wires to；
The post amplifier selects putting dedicated for the instrument of acquiring biological electric signals for U.S. boolean company production
Big device INA128；
The analog-digital converter uses the A/D converter dedicated for bioelectric measurement designed by TI company
ADS1298；
The power module selects the power module of the model LH20-10B03 of GODSEND production, and input voltage is
220V, output voltage 3.3V.
The electrode for encephalograms group 1-1 is connect by electrode wires with EEG Processing module 1-2, more precisely, type
Number preceding storing for passing through the model INA128 in electrode wires and EEG Processing module 1-2 for the electrode for encephalograms group 1-1 of CX
The pin IN connection of big device；
The pin VO of the preamplifier of the model INA128 and the pin Vi of high-pass filtering circuit use electric wire
Connection；The pin VO of the high-pass filtering circuit is adopted with the pin VIN of the trap circuit of model F42N50 and is run wires to；
The pin Vo of the trap circuit of the model F42N50 and the pin Vi of low-pass filter circuit are adopted and are run wires to；Described
The pin Vo of low-pass filter circuit is adopted with the pin In of the post amplifier of model INA128 and is run wires to；The model
It adopts and runs wires to the pin VIN of the analog-digital converter of model ADS1298 for the pin Vo of post amplifier of INA128；
The FPGA microcontroller of the pin D0 and model EP2C5Q208 of the analog-digital converter of the model ADS1298
The pin A0 electric wire of device 1-3 connects, the pin D1's and model EP2C5Q208 of the analog-digital converter of model ADS1298
The pin A1 electric wire of FPGA microcontroller 1-3 connects, the pin D2 and model of the analog-digital converter of model ADS1298
The pin A2 electric wire of the FPGA microcontroller 1-3 of EP2C5Q208 connects, the pin D3 of the analog-digital converter of model ADS1298
It is connect with the pin A3 electric wire of the FPGA microcontroller 1-3 of model EP2C5Q208, the analog-digital converter of model ADS1298
Pin D4 connect with the pin A4 electric wire of the FPGA microcontroller 1-3 of model EP2C5Q208, the mould of model ADS1298
The pin A5 electric wire of the FPGA microcontroller 1-3 of the pin D5 and model EP2C5Q208 of number converter are connect, model
The pin A6 electric wire of the FPGA microcontroller 1-3 of the pin D6 and model EP2C5Q208 of the analog-digital converter of ADS1298 connect
It connects, the pin of the FPGA microcontroller 1-3 of the pin D7 and model EP2C5Q208 of the analog-digital converter of model ADS1298
The connection of A7 electric wire；
It is adopted between the bluetooth module 1-4 of the FPGA microcontroller 1-3 and model HC05 of the model EP2C5Q208
It runs wires to, more precisely, the pin RXD1 and model HC05 of the FPGA microcontroller 1-3 of model EP2C5Q208
Bluetooth module 1-4 pin TXD electric wire connection, the pin TXD1 and type of the FPGA microcontroller 1-3 of model EP2C5Q208
Number for HC05 bluetooth module 1-4 pin RXD electric wire connection；The pin of the FPGA microcontroller 1-3 of model EP2C5Q208
VCCIO is connect with the pin Vo+ electric wire of the power module of model LH20-10B03；The bluetooth module 1-4's of model HC05
Pin VDD is connect with the pin Vo+ electric wire of the power module of model LH20-10B03；The FPGA of model EP2C5Q208 is micro-
The pin GND of controller 1-3 is connect with the pin Vo- electric wire of the power module of model LH20-10B03；Model HC05's
The pin GND of bluetooth module 1-4 is connect with the pin Vo- electric wire of the power module of model LH20-10B03.
The pin ACL and ACN of the power module of the model LH20-10B03 respectively with the firewire of standard household AC electrical
It is connect with zero curve by electric wire, pin GND ground connection；The power module of model LH20-10B03 passes through pin Vo+ and preceding storing
The big pin V+ of device, the pin VCC of high-pass filtering circuit, the pin VIN of trap circuit, low-pass filter circuit pin VCC, after
Set the pin VCCIO and bluetooth module 1-4 of the pin V+ of amplifier, pin VDD, FPGA microcontroller 1-3 of analog-digital converter
Pin VDD electric wire connection；The power module of model LH20-10B03 by the pin V- of pin Vo- and preamplifier,
The pin GND of high-pass filtering circuit, the pin GND of trap circuit, the pin GND of low-pass filter circuit, post amplifier draw
Foot V-, analog-digital converter pin GND, FPGA microcontroller 1-3 pin GND and bluetooth module 1-4 pin GND electric wire connect
It connects, for powering to each circuit and device.
Electroencephalogramsignal signal analyzing instrument 1 is by using wireless communication between bluetooth module 1-4 therein and user mobile phone client 2
Mode connects.
After brain control signal analyzer 1 initializes, bluetooth module 1-4 needs to complete bluetooth with user mobile phone client 2 and matches
It is right.Electroencephalogramsignal signal analyzing instrument 1 is completed with after the transmission of the data of user mobile phone client 2, and user mobile phone client 2 is according to received
Information draws user's sleep curve, and analyzes user's sleep quality, gives analysis to user as the result is shown.
Refering to Fig. 6, the Analysis of sleeping quality method based on EEG signals includes the following steps：
1. starting electroencephalogramsignal signal analyzing instrument 1 and electroencephalogramsignal signal analyzing instrument 1 initializing：
1 initial method of electroencephalogramsignal signal analyzing instrument is electrification reset, is resetted when being initially powered, makes brain telecommunications
FPGA microcontroller 1-3 output state in number analyzer 1 is reset, into original state；
2. electroencephalogramsignal signal analyzing instrument 1 and user mobile phone client 2 carry out Bluetooth pairing：
The electroencephalogramsignal signal analyzing instrument 1 and user mobile phone client 2 carries out Bluetooth pairing and refers to upon initialization, brain
The bluetooth module in bluetooth module 1-4 and user mobile phone client 2 in electric signal analyzer 1 is wirelessly connected；
3. electrode for encephalograms group 1-1 acquires user's EEG signals：
The number of electrodes that the electrode for encephalograms group 1-1 is used is 16, and the electrode used is dry-type electrode, is placed respectively
In the left antinion Fp1 of electrode position, right antinion Fp2, left volume F3, right volume F4, left front temporo that international 10-20 system placement methods define
Temporo behind the vertical A2 of temporo F8, left centre C3, right median C4, left ear-lobe A1, auris dextra, left top P3, right top P4, left back temporo T5, the right side before F7, the right side
T6, left pillow O1, at right pillow O2；
4. EEG signals are sent in FPGA microcontroller after EEG Processing module 1-2 processing refering to Fig. 7：
1) electrode for encephalograms group 1-1 acquires user's EEG signals first；
2) preamplifier carries out 10 times of amplifications to EEG signals；
3) EEG signals are set as 0.3Hz, are filtered out low-frequency d component and caused by high-pass filtering circuit, cutoff frequency
Interference；
4) EEG signals filter out 50Hz Hz noise by trap circuit；
5) EEG signals filter out High-frequency Interference by low-pass filter circuit；
6) post amplifier carries out 100 times of amplifications to EEG signals；
7) EEG signals are converted by the A/D of analog-digital converter, are converted to digital brain electrical signal；
8) digital brain electrical signal is transmitted to FPGA microcontroller 1-3；
5. FPGA microcontroller 1-3 analyzes EEG signals refering to Fig. 8, analysis result is sent out through bluetooth module 1-4
It is sent to user mobile phone client 2：
1) FPGA microcontroller (1-3) receives digital brain electrical signal；
2) amplitude-frequency analysis is carried out to digital EEG signals, judges sleep period locating for user, the judgement user institute
The specific judgment method of the sleep period at place is as follows：
(1) when 8~13 times per second α waves disappear, when 2~7 times per second θ waves occur, it is believed that sleep enters the drowsy state；
(2) when there is the automatic amplitude modulated phenomenon of α wave, i.e., a burst of α wave starts that amplitude is smaller, and centre becomes larger, and amplitude becomes again later
Greatly, in spindle and when there is specific κ wave, it is believed that sleep enters rapid eye movement sleep；
(3) when δ wave is more than 20%, but it is no more than 50%, when amplitude is more than 74 μ V, it is believed that sleep enters moderate and sleeps
Phase；
(4) when δ wave accounts for 50% or more, it is believed that sleep enters the deep sleep phase；
(5) when there is low wave amplitude, mixed frequency E.E.G, θ wave (3-7Hz) and the low frequency α wave for showing as low-voltage are (relatively awake
The slow 1-2Hz of α wave when the phase), there is typical sawtooth wave occur, it is believed that sleep enters rapid-eye-movement sleep phase REM；
(6) since drowsy state, rapid eye movement sleep are little to relieving fatigue effect, only enter deep sleep phase and rapid eye movement
Sleep period REM just has larger effect to relieving fatigue, its sleep quality is judged in order to facilitate user, herein by rapid-eye-movement sleep
Phase REM playback moderate sleep period；Think that user is in lucid interval except above situation；
3) sleep period locating for user is transmitted to user mobile phone client 2 by bluetooth module 1-4；
6. user mobile phone client 2 receives data, storage record：
User mobile phone client 2 passes through the data that bluetooth real-time reception electroencephalogramsignal signal analyzing instrument transmits, when by data receiver
Between, the information such as user's sleep stage store to database；
7. user mobile phone client 2 with electroencephalogramsignal signal analyzing instrument 1 whether interrupted bluetooth transmission come judge user sleep whether
Terminate.If transmission ending, determine that user wakes up, stops receiving data；Otherwise user is determined to continue to analyze in sleep
Data.
8. user mobile phone client 2 analyzes sleep quality, draws sleep curve and will analyze as the result is shown to user：
1) according to user's that night each stage sleep duration (unit in database：Minute), according to formula：Sleep scores=
[deep sleep duration/duration of always sleeping × 0.5+ moderate sleep duration/always sleeps duration × 0.4+ (shallowly when sleep duration+sleep
It is long)/duration × 0.1 of always sleeping] × 100, calculate user every night before sleep scores, with user 7 days sleep scores variation tendencies into
Row compares, and draws nearly 7 days change curves, and user can intuitively check the variation of oneself sleep quality, and user is facilitated to be directed to certainly
Oneself work and rest is adjusted, and improves sleep quality；
2) according to user's dormant data in database, using the time as horizontal axis, initial time is that user wears EEG signals point
1 time of analyzer, the termination time is user's recovery time, using sleep stage as the longitudinal axis, draws user's sleep curve, user can be straight
The variation for checking oneself daily sleep quality seen facilitates user to be adjusted for the work and rest of oneself, improves sleep quality；
3) according to user's dormant data in database, according to certain stage sleep duration/duration of always sleeping, calculating each stage sleeps
Dormancy duration accounting draws sleep quality pie chart, and user is facilitated to be adjusted for the work and rest of oneself, improves sleep quality；
4) according to user's dormant data in database, according to user when time each stage sleep accounting, with preceding 7 days proportions
It compares, if 7 days proportion average values are more than 5% to certain sleep stage earlier above, the prompt of user mobile phone client 2 is used
Family：Certain stage sleep is abnormal, it is noted that movement, diet of keeping fit keep good work and rest；If each stage accounting amplitude of variation is equal
Within 5%, then user mobile phone client 2 prompts user：This sleep is without exception, continuing with holding；
Analysis is simultaneously included as the result is shown drafting to user and shows user's sleep curve, meter by the drafting sleep curve
It calculates and shows user's sleep scores and the nearly 7 days change curves of sleep scores, drafting and show user's sleep quality pie chart, aobvious
Show prompt information.
Although disclosed herein embodiment it is as above, the content is only to facilitate understanding the present invention and adopting
Embodiment, and the non-limiting present invention.It should be pointed out that not departing from the present invention for those skilled in the art
Under the premise of spirit disclosed by embodiment, it can make an amendment and change in the formal and details of implementation, but the present invention
Scope of patent protection, still should be subject to the scope of the claims as defined in the appended claims.
Claims (10)
1. a kind of sleeping quality analyzing device based on EEG signals, it is characterised in that, the sleep based on EEG signals
Quality analysis apparatus includes electroencephalogramsignal signal analyzing instrument (1) and user mobile phone client (2)；
The electroencephalogramsignal signal analyzing instrument (1) includes electrode for encephalograms group (1-1), EEG Processing module (1-2), FPGA micro-control
Device (1-3), bluetooth module (1-4), the helmet and power module processed；
The electrode for encephalograms group (1-1) is mounted on the helmet, electrode for encephalograms (1-1) and EEG Processing module (1-2) it
Between adopt and run wires to, adopt and run wires between EEG Processing module (1-2) and FPGA microcontroller (1-3), FPGA
It adopts and runs wires between microcontroller (1-3) and bluetooth module (1-4), power module and EEG Processing module (1-2),
It adopts and runs wires between FPGA microcontroller (1-3) and bluetooth module (1-4)；
Electroencephalogramsignal signal analyzing instrument (1), which passes through, uses communication between bluetooth module (1-4) and user mobile phone client (2)
Connection.
2. the sleeping quality analyzing device described in accordance with the claim 1 based on EEG signals, it is characterised in that, the brain electricity
Electrode group (1-1) uses the bioelectric measurement silver-silver chloride solid powder sintered electrode of 16 model CX, is fixedly mounted on
The inside of the helmet is respectively and fixedly installed to left antinion Fp1, right antinion Fp2, left volume that international 10-20 system placement methods define
Temporo F8, left centre C3, right median C4, left ear-lobe A1, auris dextra vertical A2, left top P3, You Ding before F3, right volume F4, left front temporo F7, the right side
Behind P4, left back temporo T5, the right side at the electrode position of temporo T6, left pillow O1, right pillow O2, wherein left ear-lobe A1, left ear-lobe A2 are that installation is joined
It examines at electrode.
3. the sleeping quality analyzing device described in accordance with the claim 1 based on EEG signals, it is characterised in that, the brain electricity
Signal processing module (1-2) includes preamplifier, high-pass filtering circuit, trap circuit, low-pass filter circuit, post amplifier
With analog-digital converter；
The preamplifier selects the instrument amplifier for acquiring biological electric signals of model INA128；
The high-pass filtering circuit lower-cut-off frequency is 0.3Hz；
The trap circuit selects the 50HZ trapper of model F42N50, which has set
It sets；
The low-pass filter circuit cutoff frequency is 50HZ；
The post amplifier selects the instrument amplifier for acquiring biological electric signals of model INA128；
The analog-digital converter uses the A/D converter for bioelectric measurement of model ADS1298；
The pin VO of the preamplifier of the model INA128 and the pin Vi of high-pass filtering circuit are adopted and are run wires to,
The pin VO of high-pass filtering circuit is adopted with the pin VIN of the trap circuit of model F42N50 and is run wires to, model
The pin Vo of the trap circuit of F42N50 and the pin Vi of low-pass filter circuit are adopted and are run wires to, the pin of low-pass filter circuit
The pin In of Vo and the post amplifier of model INA128, which is adopted, to be run wires to, and the post amplifier of model INA128 draws
The pin VIN of foot Vo and the analog-digital converter of model ADS1298, which is adopted, to be run wires to.
4. the sleeping quality analyzing device described in accordance with the claim 3 based on EEG signals, it is characterised in that, the high pass
The operational amplifier composition of filtered electrical routing resistance R1, resistance R2, capacitor C1, capacitor C2 and model TLC2252AID；Pin
One end of Vi and capacitor C1, which is adopted, to be run wires to, and the other end of capacitor C1 and one end of capacitor C2 are adopted and run wires to, capacitor C1
The other end and one end of resistance R2 adopt and run wires to, the other end of resistance R2 and the operation amplifier of model TLC2252AID
No. 1 pin of device, which is adopted, to be run wires to, No. 3 pins of the operational amplifier of the other end and model TLC2252AID of capacitor C2
It adopts and runs wires to, the other end of capacitor C2 and one end of resistance R1 are adopted and run wires to, the other end and pin GND of resistance R1
It adopts and runs wires to, the operation of No. 2 pins and model TLC2252AID of the operational amplifier of model TLC2252AID is put
No. 1 pin of big device, which is adopted, to be run wires to, and No. 4 pins and pin GND of the operational amplifier of model TLC2252AID use
Electric wire connection, No. 8 pins of the operational amplifier of model TLC2252AID are adopted with pin VCC to be run wires to, model
No. 1 pin of the operational amplifier of TLC2252AID is adopted with pin Vo to be run wires to；
The low-pass filter circuit is put by the operation of resistance R1, resistance R2, capacitor C1, capacitor C2 and model TLC2252AID
Big device composition；One end of pin Vi and capacitor C1, which is adopted, to be run wires to, and the other end of capacitor C1 and one end of capacitor C2 are using electricity
Line connection, the other end of capacitor C1 and one end of resistance R2 are adopted and are run wires to, the other end and model of resistance R2
No. 1 pin of the operational amplifier of TLC2252AID, which is adopted, to be run wires to, the other end and model TLC2252AID of capacitor C2
No. 3 pins of operational amplifier adopt and run wires to, the other end of capacitor C2 and one end of resistance R1 are adopted and are run wires to, electricity
The other end of resistance R1 is adopted with pin GND to be run wires to, No. 2 pins and model of the operational amplifier of model TLC2252AID
It adopts and runs wires to for No. 1 pin of the operational amplifier of TLC2252AID, the 4 of the operational amplifier of model TLC2252AID
Number pin is adopted with pin GND to be run wires to, and No. 8 pins and the pin VCC of the operational amplifier of model TLC2252AID are adopted
It runs wires to, No. 1 pin of the operational amplifier of model TLC2252AID is adopted with pin Vo to be run wires to.
5. the sleeping quality analyzing device described in accordance with the claim 1 based on EEG signals, it is characterised in that, the brain electricity
It is adopted between signal processing module (1-2) and FPGA microcontroller (1-3) and runs wires to refer to：
The analog-digital converter and FPGA micro-control that the EEG Processing module (1-2) passes through model ADS1298 therein
Device (1-3) processed, which is adopted, to be run wires to：
FPGA microcontroller (the 1- of the pin D0 and model EP2C5Q208 of the analog-digital converter of the model ADS1298
3) pin A0 electric wire connection, the pin D1 and the FPGA of model EP2C5Q208 of the analog-digital converter of model ADS1298 are micro-
The pin A1 electric wire of controller (1-3) connects, the pin D2 and model of the analog-digital converter of model ADS1298
The pin A2 electric wire of the FPGA microcontroller (1-3) of EP2C5Q208 connects, the pin of the analog-digital converter of model ADS1298
D3 is connect with the pin A3 electric wire of the FPGA microcontroller (1-3) of model EP2C5Q208, and the modulus of model ADS1298 turns
The pin A4 electric wire of the FPGA microcontroller (1-3) of the pin D4 and model EP2C5Q208 of parallel operation is connect, model
The pin A5 electric wire of the FPGA microcontroller (1-3) of the pin D5 and model EP2C5Q208 of the analog-digital converter of ADS1298 connects
It connects, FPGA microcontroller (1-3's) of the pin D6 and model EP2C5Q208 of the analog-digital converter of model ADS1298 draws
The connection of foot A6 electric wire, the FPGA microcontroller of the pin D7 and model EP2C5Q208 of the analog-digital converter of model ADS1298
The pin A7 electric wire of (1-3) connects.
6. the sleeping quality analyzing device described in accordance with the claim 1 based on EEG signals, it is characterised in that, the FPGA
It is adopted between microcontroller (1-3) and bluetooth module (1-4) and runs wires to refer to：
The FPGA microcontroller (1-3) uses the FPGA microcontroller of model EP2C5Q208, and bluetooth module (1-4) is adopted
With the bluetooth module of model HC05；It adopts and runs wires between the two：
The bluetooth module of the pin RXD1 and model HC05 of the FPGA microcontroller (1-3) of the model EP2C5Q208
The pin TXD electric wire of (1-4) connects, the pin TXD1 and model of the FPGA microcontroller (1-3) of model EP2C5Q208
The pin RXD electric wire of the bluetooth module (1-4) of HC05 connects.
7. the sleeping quality analyzing device described in accordance with the claim 1 based on EEG signals, it is characterised in that, the power supply
It adopts and runs wires between module and EEG Processing module (1-2), FPGA microcontroller (1-3) and bluetooth module (1-4)
Refer to：
The power module is the power module using model LH20-10B03；
The power module of model LH20-10B03 passes through the pin V+ of pin Vo+ and preamplifier, high-pass filtering circuit
Pin VCC, the pin VIN of trap circuit, the pin VCC of low-pass filter circuit, post amplifier pin V+, analog-digital converter
The pin VCCIO of pin VDD, FPGA microcontroller (1-3) connect with the pin VDD electric wire of bluetooth module (1-4)；Model
The power module of LH20-10B03 by the pin V- of pin Vo- and preamplifier, high-pass filtering circuit pin GND, fall into
The pin GND of wave circuit, the pin GND of low-pass filter circuit, the pin V- of post amplifier, analog-digital converter pin GND,
The pin GND of FPGA microcontroller (1-3) is connect with the pin GND electric wire of bluetooth module (1-4)；
The power module of the pin VCCIO and model LH20-10B03 of the FPGA microcontroller (1-3) of model EP2C5Q208
Pin Vo+ electric wire connection；The power supply of the pin VDD and model LH20-10B03 of the bluetooth module (1-4) of model HC05
The pin Vo+ electric wire of module connects；The pin GND and model of the FPGA microcontroller (1-3) of model EP2C5Q208
The pin Vo- electric wire of the power module of LH20-10B03 connects；The pin GND and type of the bluetooth module (1-4) of model HC05
Number for LH20-10B03 power module pin Vo- electric wire connection.
8. a kind of Analysis of sleeping quality method based on EEG signals, it is characterised in that, the sleep based on EEG signals
Mass analysis method includes that steps are as follows：
1) starting electroencephalogramsignal signal analyzing instrument and electroencephalogramsignal signal analyzing instrument initialize：
Electroencephalogramsignal signal analyzing instrument (1) initial method is electrification reset, is resetted when being initially powered, makes EEG signals
FPGA microcontroller (1-3) output state in analyzer (1) is reset, into original state；
2) electroencephalogramsignal signal analyzing instrument and user mobile phone client carry out Bluetooth pairing：
The electroencephalogramsignal signal analyzing instrument (1) and user mobile phone client (2) carries out Bluetooth pairing and refers to upon initialization, brain
The bluetooth in bluetooth module (1-4) and user mobile phone client (2) in electric signal analyzer (1) is wirelessly connected；
3) electrode for encephalograms group acquires user's EEG signals：
User correctly wears the helmet, and 16 electrodes of the electrode for encephalograms group (1-1) being mounted on the helmet are individually positioned in international 10-
Left antinion Fp1 that 20 system placement methods define, right antinion Fp2, left volume F3, right volume F4, left front temporo F7, it is right before temporo F8, left centre
C3, right median C4, left ear-lobe A1, auris dextra hang down A2, left top P3, right top P4, left back temporo T5, it is right after temporo T6, left pillow O1, right pillow O2
User's EEG signals are acquired at electrode position；
4) EEG signals are sent in FPGA microcontroller (1-3) after EEG Processing module (1-2) processing；
5) FPGA microcontroller (1-3) analyzes EEG signals, sends user through bluetooth module (1-4) for analysis result
Cell phone client (2)；
6) user mobile phone client receives data and storage records：
User mobile phone client (2) passes through the data that bluetooth real-time reception electroencephalogramsignal signal analyzing instrument (1) transmits, when by data receiver
Between, user's sleep stage information stores to database；
7) user mobile phone client (2) judges to use so that whether the bluetooth module (1-4) of electroencephalogramsignal signal analyzing instrument (1) interrupts transmission
Whether family sleep terminates, if transmission ending, determines that user wakes up, and stops receiving data；Otherwise in determining user to sleep, after
Continued access contracture analyses data；
8) user mobile phone client (2) analyzes sleep quality, draws sleep curve and will analyze as the result is shown to user.
9. the Analysis of sleeping quality method based on EEG signals according to claim 8, it is characterised in that, the FPGA
Microcontroller (1-3) analyzes EEG signals, sends user mobile phone client through bluetooth module (1-3) for analysis result
(2) refer to：
1) FPGA microcontroller (1-3) receives digital brain electrical signal；
2) amplitude-frequency analysis is carried out to digital EEG signals, judges sleep period locating for user, described judges locating for user
The specific judgment method of sleep period is as follows：
(1) when 8~13 times per second α waves disappear, when 2~7 times per second θ waves occur, it is believed that sleep enters the drowsy state；
(2) when there is the automatic amplitude modulated phenomenon of α wave, i.e., a burst of α wave starts that amplitude is smaller, and centre becomes larger, and amplitude becomes larger again later, is in
When spindle and the specific κ wave of appearance, it is believed that sleep enters rapid eye movement sleep；
(3) when δ wave is more than 20%, but it is no more than 50%, when amplitude is more than 74 μ V, it is believed that sleep enters moderate sleep period；
(4) when δ wave accounts for 50% or more, it is believed that sleep enters the deep sleep phase；
(5) it when there is low wave amplitude, mixed frequency E.E.G, shows as when frequency involves for the θ of the low-voltage of 3-7Hz compared with lucid interval
The low frequency α wave of the slow 1-2Hz of α wave has typical sawtooth wave occur, it is believed that sleep enters rapid-eye-movement sleep phase REM；
(6) since drowsy state, rapid eye movement sleep are little to relieving fatigue effect, only enter deep sleep phase and rapid-eye-movement sleep
Just there is larger effect in phase REM to relieving fatigue, its sleep quality is judged in order to facilitate user, herein by the rapid-eye-movement sleep phase
REM playback moderate sleep period；Think that user is in lucid interval except above situation；
3) sleep period locating for user is transmitted to user mobile phone client (2) by bluetooth module (1-4).
10. the Analysis of sleeping quality method based on EEG signals according to claim 8, it is characterised in that, the use
Family cell phone client (2) analyzes sleep quality, draws sleep curve and refers to analysis to user as the result is shown：
1) according to user's that night each stage sleep duration in database, unit is minute, according to formula：Sleep scores=[depth
Duration/duration of always sleeping of sleeping × 0.5+ moderate sleep duration/duration × 0.4+ that always sleeps (duration+sleep duration of shallowly sleeping)/
Total sleep duration × 0.1] × 100, calculating user, 7 days sleep scores variation tendencies compare before sleep scores, with user every night
It is right, nearly 7 days change curves are drawn, user can intuitively check the variation of oneself sleep quality, and user is facilitated to be directed to oneself
Work and rest is adjusted, and improves sleep quality；
2) according to user's dormant data in database, using the time as horizontal axis, initial time is that user wears electroencephalogramsignal signal analyzing instrument 1
Time, the termination time is user's recovery time, using sleep stage as the longitudinal axis, draws user's sleep curve, user can be intuitive
The variation for checking oneself daily sleep quality facilitates user to be adjusted for the work and rest of oneself, improves sleep quality；
3) according to user's dormant data in database, according to certain stage sleep duration/duration of always sleeping, when calculating each stage sleep
Long accounting draws sleep quality pie chart, and user is facilitated to be adjusted for the work and rest of oneself, improves sleep quality；
4) it is carried out according to user when time each stage sleep accounting with preceding 7 days proportions according to user's dormant data in database
Comparison, if 7 days proportion average values are more than 5% to certain sleep stage earlier above, user mobile phone client (2) prompt is used
Family：Certain stage sleep is abnormal, it is noted that movement, diet of keeping fit keep good work and rest；If each stage accounting amplitude of variation is equal
Within 5%, then user mobile phone client (2) prompts user：This sleep is without exception, continuing with holding.
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| CN110584658A (en) * | 2019-08-22 | 2019-12-20 | 西安八水健康科技有限公司 | Electroencephalogram acquisition system for transcranial electrical stimulation and vagus nerve stimulation |
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| CN113908397A (en) * | 2021-09-04 | 2022-01-11 | 武汉左点科技有限公司 | Insomnia treatment method and device based on brain wave monitoring technology |
| CN114668947A (en) * | 2021-12-21 | 2022-06-28 | 北京师范大学 | Operating system and method for sleep TMR based on EEG |
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