[go: up one dir, main page]

CN105212924A - A kind of based on brain wave method for detecting fatigue driving and device thereof - Google Patents

A kind of based on brain wave method for detecting fatigue driving and device thereof Download PDF

Info

Publication number
CN105212924A
CN105212924A CN201510658894.8A CN201510658894A CN105212924A CN 105212924 A CN105212924 A CN 105212924A CN 201510658894 A CN201510658894 A CN 201510658894A CN 105212924 A CN105212924 A CN 105212924A
Authority
CN
China
Prior art keywords
brain wave
ripple
brain
driver
value
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201510658894.8A
Other languages
Chinese (zh)
Inventor
杨彬
王宣
汤宝文
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Anhui Sunshine Sealing Electronic Technology Co Ltd
Original Assignee
Anhui Sunshine Sealing Electronic Technology Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Anhui Sunshine Sealing Electronic Technology Co Ltd filed Critical Anhui Sunshine Sealing Electronic Technology Co Ltd
Priority to CN201510658894.8A priority Critical patent/CN105212924A/en
Publication of CN105212924A publication Critical patent/CN105212924A/en
Pending legal-status Critical Current

Links

Landscapes

  • Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)
  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)

Abstract

A kind of based on brain wave method for detecting fatigue driving and device thereof, relate to fatigue detecting technology field, it is characterized in that: comprise the following steps, acquiring brain waves: often gather θ ripple, α ripple, the β ripple in brain wave respectively simultaneously in each 0.6 ~ 2 second, continue more than three seconds; Brain wave transmits: be passed in computer by the θ ripple in above-mentioned brain wave, α ripple, β wavelength-division supplementary biography; Brain wave is analyzed: analyzed by the time of P value and driving, described P value=(θ value+α is worth)/β value, the described time is daytime and night respectively; Comprise acquiring brain waves module, brain wave processing module and judge warning module, described acquiring brain waves module sends the brain wave of collection to brain wave processing module by bluetooth, and described brain wave processing module sends the signal of collection to judgement warning module.By brain wave, the present invention judges whether driver is in fatigue state, easy to detect, reliability is high, is conducive to reducing security incident.<!-- 2 -->

Description

A kind of based on brain wave method for detecting fatigue driving and device thereof
Technical field:
The present invention relates to fatigue detecting technology field, specifically a kind of based on brain wave method for detecting fatigue driving and device thereof.
Background technology:
Brain wave (Electroencephalogram, EEG) be brain when activity, the postsynaptic potential that a large amount of neuron synchronously occurs is formed after summation.Electric wave change during its record cerebral activity is overall anti-in cerebral cortex or scalp surface of the bioelectrical activity of cranial nerve cell.Brain wave derives from the postsynaptic potential of pyramidal cell top dendron.The formation of the synchronization of brain wave rhythm and pace of moving things is also relevant with the activity of cortex thalamic nonspecific projection system.Brain wave is that some spontaneous rhythmic neuroelectricities are movable, its frequency variation scope is between 1-30 time per second, four wave bands can be divided into, i.e. δ (1-3Hz), θ (4-7Hz), α (8-13Hz), β (14-30Hz).In addition, when awakening and be absorbed in a certain thing, the γ ripple that a kind of frequency of Chang Kejian is higher compared with β ripple, its frequency is 30 ~ 80Hz, and wave amplitude scope is indefinite; And also can there is the normal brain activity electric wave that other waveforms are comparatively special, as hump ripple, σ ripple, λ ripple, κ-complex wave, μ ripple etc. when sleeping.Also not do not detect based on brain wave the method and apparatus whether driver is in fatigue state in prior art, or whether to be in the reliability of the method for fatigue state poor for detecting driver.
Summary of the invention:
Technical problem to be solved by this invention is to provide a kind of easy to detect, reliability high based on brain wave method for detecting fatigue driving and device thereof.
Technical problem to be solved by this invention realizes by the following technical solutions:
One, based on brain wave method for detecting fatigue driving, is characterized in that: comprise the following steps,
Acquiring brain waves: often gather θ ripple, α ripple, the β ripple in brain wave respectively simultaneously in each 0.6 ~ 2 second, continue more than three seconds;
Brain wave transmits: be passed in computer by the θ ripple in above-mentioned brain wave, α ripple, β wavelength-division supplementary biography;
Brain wave is analyzed: analyzed by the time of P value and driving, described P value=(θ value+α is worth)/β value, the described time is daytime and night respectively;
Tired judgement:
Daytime:
Represent that driver is in waking state as P<=1.2;
Represent that driver is in fatigue state as 1.2<P<=1.5;
Represent that as P>1.5 driver will enter sleep state;
Night:
Represent that driver is in waking state as P<=1.05;
Represent that driver is in fatigue state as 1.05<P<=1.35;
Represent that as P>1.35 driver will enter sleep state.
A kind of based on brain wave method for detecting fatigue driving and device thereof, comprise acquiring brain waves module, brain wave processing module and judge warning module, described acquiring brain waves module sends the brain wave of collection to brain wave processing module by bluetooth, and described brain wave processing module sends the signal of collection to judgement warning module.
Brain wave is that some spontaneous rhythmic neuroelectricities are movable, its frequency variation scope is between 1-30 time per second, four wave bands can be divided into, i.e. δ (1-3Hz), θ (4-7Hz), α (8-13Hz), β (14-30Hz).
δ wave frequency is 0.5 ~ 3Hz, and amplitude is 20 ~ 200 μ V.When people at infancy stage or intelligent development is immature, adult under extremely tired and lethargy or narcotism, this wave band can be recorded at temporal lobe and top.
θ wave frequency is 4 ~ 7Hz, and amplitude is 100 ~ 150 μ V.Adult when wish suffers setbacks and is depressed and this ripple of psychotic very remarkable.But this ripple is the main component in the electroencephalogram of juvenile (10-17 year).
α wave frequency is 8 ~ 13Hz (average is 10Hz), and amplitude is 20 ~ 100 μ V.It is the basilic rhythm of normal brain electric wave, if do not have additional stimulation, its frequency is quite constant.People clear-headed, quiet and when closing one's eyes this rhythm and pace of moving things the most obvious, open eyes (being subject to photostimulation) or accept other when stimulating, α ripple disappears at once.
β wave frequency is 14 ~ 30Hz, and amplitude is 5 ~ 20 μ V.When psychentonia and excited or excited time there is this ripple, when people wakes from a nightmare with a start, the slow wave rhythm and pace of moving things originally can immediately substitute by this rhythm and pace of moving things.
Acquiring brain waves module can gather E.E.G frequency spectrum, EEG signals quality, original brain wave and three eSense parameters: focus, allowance and detecting nictation.
Acquiring brain waves module is the eeg signal of captured in real time experiencer.The eeg signal acquisition module that we use is ThinkGearAM module or TGAM module, and the current potential at forehead electrode and ear-lobe place is obtained brain wave data by this module as a reference.Under TG_BAND_9600 baud rate, every 0.6s acquiring brain waves module acquires to the information maximum probability that can change, namely between 0 to 0.6s acquiring brain waves module acquires to information be identical, for avoiding other factors to disturb, we use the information once collected to carry out processing and the degree of fatigue judging experiencer every 1s.
Brain wave processing module is that we utilize acquiring brain waves module to catch the eeg signal of user, then process, filter out the E.E.G frequency spectrum of our needs, EEG signals quality, original brain wave and eSense parameter and transmitted it in computer by the blue-tooth device that acquisition module is built-in.After acquisition signal, we pass to exe program by the signal that bluetooth receives by serial port communication technology, and this program carrys out extraction and analysis by the function library (data stream parser API) calling acquiring brain waves module and provide and packet, and we need signal to be processed.
Judge warning module: the brain wave that we use is θ, α, β ripple, δ ripple is because have more present infancy stage or intelligent development immature period, so we do not go to use.Detect through great many of experiments that known fatigue state α ripple can rise, β ripple can decline when people is in; When people enters sleep state from fatigue state, θ ripple can increase, so we judge the fatigue strength of driver by P=(θ+α)/β formula.This money software is divided into two kinds of patterns: day mode and Night.Wherein, the attention level requirement of day mode to driver is lower, and the requirement of Night to driver is higher.According to driver, within a period of time, the change of (3 seconds) P value carrys out voice reminder driver and concentrates on.In addition, software also has warning function, and it is predicted according to the P value decline curve of driver, driver be about to enter the fatigue phase before remind driver to stop rest.
The invention has the beneficial effects as follows: by brain wave, the present invention judges whether driver is in fatigue state, easy to detect, reliability is high, be conducive to reducing security incident.
Detailed description of the invention:
The technological means realized to make the present invention, creation characteristic, reaching object and effect is easy to understand, below in conjunction with instantiation, setting forth the present invention further.
One, based on brain wave method for detecting fatigue driving and device thereof, comprises the following steps,
Acquiring brain waves: often gather θ ripple, α ripple, the β ripple in brain wave respectively simultaneously in each 1 second, continue more than three seconds;
Brain wave transmits: be passed in computer by the θ ripple in above-mentioned brain wave, α ripple, β wavelength-division supplementary biography;
Brain wave is analyzed: analyzed by the time of P value and driving, described P value=(θ value+α is worth)/β value, the described time is daytime and night respectively;
Tired judgement:
Daytime:
Represent that driver is in waking state as P<=1.2;
Represent that driver is in fatigue state as 1.2<P<=1.5;
Represent that as P>1.5 driver will enter sleep state;
Night:
Represent that driver is in waking state as P<=1.05;
Represent that driver is in fatigue state as 1.05<P<=1.35;
Represent that as P>1.35 driver will enter sleep state.
A kind of based on brain wave method for detecting fatigue driving and device thereof, comprise acquiring brain waves module, brain wave processing module and judge warning module, acquiring brain waves module sends the brain wave of collection to brain wave processing module by bluetooth, and brain wave processing module sends the signal of collection to judgement warning module.
More than show and describe ultimate principle of the present invention and principal character and advantage of the present invention.The technical staff of the industry should understand; the present invention is not restricted to the described embodiments; what describe in above-described embodiment and description just illustrates principle of the present invention; without departing from the spirit and scope of the present invention; the present invention also has various changes and modifications, and these changes and improvements all fall in the claimed scope of the invention.Application claims protection domain is defined by appending claims and equivalent thereof.

Claims (2)

1. based on a brain wave method for detecting fatigue driving, it is characterized in that: comprise the following steps,
Acquiring brain waves: often gather θ ripple, α ripple, the β ripple in brain wave respectively simultaneously in each 0.6 ~ 2 second, continue more than three seconds;
Brain wave transmits: be passed in computer by the θ ripple in above-mentioned brain wave, α ripple, β wavelength-division supplementary biography;
Brain wave is analyzed: analyzed by the time of P value and driving, described P value=(θ value+α is worth)/β value, the described time is daytime and night respectively;
Tired judgement:
Daytime:
Represent that driver is in waking state as P<=1.2;
Represent that driver is in fatigue state as 1.2<P<=1.5;
Represent that as P>1.5 driver will enter sleep state;
Night:
Represent that driver is in waking state as P<=1.05;
Represent that driver is in fatigue state as 1.05<P<=1.35;
Represent that as P>1.35 driver will enter sleep state.
2. one according to claim 1 is based on brain wave fatigue driving detection device, it is characterized in that: comprise acquiring brain waves module, brain wave processing module and judge warning module, described acquiring brain waves module sends the brain wave of collection to brain wave processing module by bluetooth, and described brain wave processing module sends the signal of collection to judgement warning module.
CN201510658894.8A 2015-10-10 2015-10-10 A kind of based on brain wave method for detecting fatigue driving and device thereof Pending CN105212924A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201510658894.8A CN105212924A (en) 2015-10-10 2015-10-10 A kind of based on brain wave method for detecting fatigue driving and device thereof

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201510658894.8A CN105212924A (en) 2015-10-10 2015-10-10 A kind of based on brain wave method for detecting fatigue driving and device thereof

Publications (1)

Publication Number Publication Date
CN105212924A true CN105212924A (en) 2016-01-06

Family

ID=54982475

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201510658894.8A Pending CN105212924A (en) 2015-10-10 2015-10-10 A kind of based on brain wave method for detecting fatigue driving and device thereof

Country Status (1)

Country Link
CN (1) CN105212924A (en)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105701973A (en) * 2016-04-26 2016-06-22 成都远控科技有限公司 Fatigue detection and early warning method based on brain wave acquisition and system thereof
CN108418959A (en) * 2018-02-11 2018-08-17 广东欧珀移动通信有限公司 Electronic device, method for outputting prompt information and related product
CN108877150A (en) * 2018-07-05 2018-11-23 张屹然 A kind of tired driver driving monitoring device based on biological brain electrical chip and tired distinguished number

Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102274032A (en) * 2011-05-10 2011-12-14 北京师范大学 Driver fatigue detection system based on electroencephalographic (EEG) signals
CN102835964A (en) * 2012-08-31 2012-12-26 漳州师范学院 Glasses for acquiring fatigue driving physiological signal transmitted via Bluetooth
CN103530986A (en) * 2012-07-02 2014-01-22 内蒙古大学 Brain wave and Zigbee-based fatigue driving early-warning system
CN103815900A (en) * 2013-11-22 2014-05-28 刘志勇 Hat and method for measuring alertness based on EEG frequency-domain feature indexing algorithm
EP2752157A1 (en) * 2013-01-08 2014-07-09 Nihon Kohden Corporation Biological signal averaging processing device
CN103919565A (en) * 2014-05-05 2014-07-16 重庆大学 Fatigue driving electroencephalogram signal feature extraction and identification method
CN203898306U (en) * 2014-06-06 2014-10-29 上海理工大学 Brain wave collecting device based on wireless transmission
CN104305964A (en) * 2014-11-11 2015-01-28 东南大学 Head mounted fatigue detector and method
CN204440609U (en) * 2015-03-12 2015-07-01 西安科技大学 A kind of fatigue driving monitoring terminal based on brain-computer interface
CN104825256A (en) * 2015-04-30 2015-08-12 南京信息工程大学 Artificial limb system with perception feedback function
CN204636626U (en) * 2015-04-30 2015-09-16 南京信息工程大学 A kind of artificial limb system with perceptible feedback function

Patent Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102274032A (en) * 2011-05-10 2011-12-14 北京师范大学 Driver fatigue detection system based on electroencephalographic (EEG) signals
CN103530986A (en) * 2012-07-02 2014-01-22 内蒙古大学 Brain wave and Zigbee-based fatigue driving early-warning system
CN102835964A (en) * 2012-08-31 2012-12-26 漳州师范学院 Glasses for acquiring fatigue driving physiological signal transmitted via Bluetooth
EP2752157A1 (en) * 2013-01-08 2014-07-09 Nihon Kohden Corporation Biological signal averaging processing device
CN103815900A (en) * 2013-11-22 2014-05-28 刘志勇 Hat and method for measuring alertness based on EEG frequency-domain feature indexing algorithm
CN103919565A (en) * 2014-05-05 2014-07-16 重庆大学 Fatigue driving electroencephalogram signal feature extraction and identification method
CN203898306U (en) * 2014-06-06 2014-10-29 上海理工大学 Brain wave collecting device based on wireless transmission
CN104305964A (en) * 2014-11-11 2015-01-28 东南大学 Head mounted fatigue detector and method
CN204440609U (en) * 2015-03-12 2015-07-01 西安科技大学 A kind of fatigue driving monitoring terminal based on brain-computer interface
CN104825256A (en) * 2015-04-30 2015-08-12 南京信息工程大学 Artificial limb system with perception feedback function
CN204636626U (en) * 2015-04-30 2015-09-16 南京信息工程大学 A kind of artificial limb system with perceptible feedback function

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
HONG J ETAC: "《Electroencephalographic Study of Drowsiness in Simulated Driving with Sleep Deprivation》", 《INTERNATIONAL JOURNAL OF INDUSTRIAL ERGONOMICS》 *
杨才坤: "《疲劳驾驶检测方法的研究及其嵌入式实现》", 《中国优秀硕士学位论文全文数据库 信息科技辑》 *
殷艳红: "《基于脑电波与眨眼的驾驶员疲劳模拟实验研究》", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105701973A (en) * 2016-04-26 2016-06-22 成都远控科技有限公司 Fatigue detection and early warning method based on brain wave acquisition and system thereof
CN108418959A (en) * 2018-02-11 2018-08-17 广东欧珀移动通信有限公司 Electronic device, method for outputting prompt information and related product
CN108877150A (en) * 2018-07-05 2018-11-23 张屹然 A kind of tired driver driving monitoring device based on biological brain electrical chip and tired distinguished number

Similar Documents

Publication Publication Date Title
CN103111020B (en) System and method for detecting and relieving driving fatigue based on electrical acupoint stimulation
CN104965584B (en) Mixing brain-machine interface method based on SSVEP and OSP
CN105701973A (en) Fatigue detection and early warning method based on brain wave acquisition and system thereof
CN106388818B (en) Method and system for extracting characteristic information of sleep state monitoring model
CN111870813A (en) Electroencephalogram stimulation memory enhancement system based on portable EEG equipment
CN104574818B (en) Fatigue driving detection and elimination method applied to mobile phone
CN106473705B (en) Electroencephalogram signal processing method and system for sleep state monitoring
CN106691474A (en) Brain electrical signal and physiological signal fused fatigue detection system
CN103021134A (en) Monitoring and alarm device for fatigue driving of automobile
KR20150082322A (en) Systems and methods for evaluation of neuropathologies
Petersen et al. Generic single-channel detection of absence seizures
CN102274032A (en) Driver fatigue detection system based on electroencephalographic (EEG) signals
CN106388778B (en) Electroencephalogram signal preprocessing method and system in sleep state analysis
CN106128032A (en) A kind of fatigue state monitoring and method for early warning and system thereof
WO2001045554A3 (en) Method and apparatus for assessing susceptibility to stroke
CN103690163A (en) ICA (independent component analysis) and HHT (Hilbert-Huang transform) fusion based automatic electrooculogram interference eliminating method
CN105212924A (en) A kind of based on brain wave method for detecting fatigue driving and device thereof
Hallum et al. Surround suppression supports second-order feature encoding by macaque V1 and V2 neurons
CN106341750A (en) Bluetooth earphone capable of monitoring driver fatigue state and carrying out fatigue early warning
US20240172977A1 (en) Automatic detection system for depressive disorder based on high frequency auditory steady-state response
CN111921062A (en) Sound wave intervention memory enhancement system based on portable EEG equipment
Hu et al. A real-time electroencephalogram (EEG) based individual identification interface for mobile security in ubiquitous environment
CN107280665A (en) Brain evoked potential signal acquisition method
CN117064409A (en) Method, device and terminal for evaluating transcranial direct current intervention stimulation effect in real time
US11944445B2 (en) Method for detecting elements of interest in electrophysiological signals and detector

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication

Application publication date: 20160106

RJ01 Rejection of invention patent application after publication