CN102125429A - Alertness detection system based on electro-oculogram signal - Google Patents
Alertness detection system based on electro-oculogram signal Download PDFInfo
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Abstract
The invention discloses an alertness detection system based on an electro-oculogram signal in the technical field of signal processing. The system comprises a signal acquiring system, a signal processing system and a feedback system, wherein the signal acquiring system acquires an electro-oculogram analog signal and then outputs characteristic data to the signal processing system after performing amplification, filtration and digital-to-analogue conversion on the electro-oculogram analog signal; the signal processing system extracts characteristics from the input electro-oculogram signal, estimates an alertness state and then outputs the data to the feedback system; and the feedback system sends an alarm when an alarm condition is met. Through the alertness detection system based on the electro-oculogram signal, information more complete and accurate than an eye video can be provided; when the system is combined with the plurality of characteristics, such as low-speed eye movement, high-speed eye movement, blink and the like, which are extracted from an electro-oculogram (EOG) and a linear dynamic system supporting real-time property is adopted to de-noise, the fatigue state of a user can be timely and accurately reflected and an alarm is generated for the fatigue beyond a certain degree.
Description
Technical field
What the present invention relates to is the device in a kind of signal processing technology field, specifically is a kind of Alertness detection system based on electro-ocular signal.
Background technology
All a large amount of vehicle accidents can take place every year, cause the life and the property loss of huge amount in the world.According to incompletely statistics, the number that vehicle accident is died from the whole world every year is about 600,000, and the number injured because of traffic accident has 1,000 ten thousand every year on average approximately.The reason of vehicle accident can be divided into objective and subjective two kinds, and odjective cause mainly is the influence of natural environment and the fault of equipment, and subjective reason is then mainly from driver itself, comprise drive when intoxicated, operate miss that fatigue driving and other reasons cause.Wherein, the fatigue driving occurrence frequency is big, and is difficult to prediction and control.American National railway office is the special white paper of issuing about fatigue driving in 2006: " the tired risk control project of national railway office's railway: past, now with in the future " (The Railroad Fatigue Risk Management Program at the Federal Railroad Administration:Past, Present and Future, Nov.2006) in, specifically mentioned and wanted the strict rotation system of carrying out, control driver's working time, produce fatigue to prevent to work long hours.This shows that fatigue driving just is being subjected to suitable attention, how effectively to address this problem has also become an important research contents.
The DD850 that commercial now driver fatigue detection device has U.S. Attention Technologies company to release, and the gogo850 of Science and Technology Ltd. etc. is far driven in Nanjing.These products all are by gathering the video of driver's eye motion, analyzing the degree of fatigue that pupil and eyelid movement are judged the driver.There are many restrictions in technology based on video, just can only could normally use at night such as DD850, and its precision is not very desirable yet.
Detect in order to reach more high-precision Alertness, " with EEG power Spectral Estimation Alertness " (Estimating Alertness from the EEG Power Spectrum that people such as the Chin-Teng Lin of Taiwan university of communications and Univ California-San Diego USA deliver, EURASIP Journal, 2005) take the lead in having proposed to detect the method for Alertness in based on EEG signals (EEG).Because EEG can directly reflect the active state of brain, so the method can point-device perception people be in active still unresponsive state.Yet still have obvious defects at present based on the method for EEG: the EEG signal is too faint, disturbed easily, and the electrode that is attached to head is easy to be subjected to the hair influence, so its practicality is still waiting further raising.
Find through retrieval prior art, utilize EOG to carry out the Alertness analysis and only have some preliminary study, people such as Thurn Chia Chieh (1st International Conference on Computers in first computer in 2005, communication, signal processing international conference for example, Communications ， ﹠amp; Signal Processing with Special Track on Biomedical Engineering) " based on the tired detection system of driver of EOG " (the Development of Vehicle Driver Drowsiness Detection System Using Electrooculogram (EOG)) that delivers.But the method that this technology is used is simple, has only adopted rapid eye movement to judge fatigue strength as feature, does not bring into play EOG and has manifold strong point, does not also use any denoising method.
Summary of the invention
The present invention is directed to the prior art above shortcomings, a kind of Alertness detection system based on electro-ocular signal is provided, and (EOG) detects Alertness by electro-ocular signal, and EOG compares with EEG has high signal to noise ratio, requiring of pair amplifier and denoising is low, and electrode position does not have the hair influence.Its principle is identical with product principle based on the eye video, but EOG can provide than eye video information more comprehensively and more accurately; In conjunction with multiple features of from EOG, extracting such as SEM, rapid eye movement, nictation, and used and supported real-time linear dynamic system denoising, can reflect the fatigue state of user timely and accurately, and the fatigue that surpasses has to a certain degree been produced alarm.
The present invention is achieved by the following technical solutions, the present invention includes: signal acquiring system, signal processing system and feedback system, wherein: signal acquiring system collection eye electric analoging signal and amplify, filtering and digital-to-analogue conversion handle back output characteristic data to signal processing system, signal processing system exports feedback system to after the electro-ocular signal of importing is carried out feature extraction and estimates the Alertness state, and feedback system gives the alarm when satisfying warning condition.
Described signal acquiring system comprises: wear-type fixed mount, dried electrode and placed in-line successively amplification module, filtration module, AD modular converter and wireless sending module, wherein: several dried electrodes are arranged at and are connected in the wear-type fixed mount and with amplification module with output eye electric analoging signal, export filtration module to after the eye electric analoging signal that amplification module will be received amplifies and carry out filtering, the AD modular converter carries out filtered induced signal analog digital conversion generating feature data and exports signal processing system to by wireless sending module.
The quantity of described dried electrode is at least five, and wherein: two are positioned at eye socket and are used for horizontal electro-ocular signal collection up and down, and two are positioned at the outside, canthus and are used for vertical electro-ocular signal collection, and one is positioned at basal part of the ear top as with reference to signals collecting; The arrangement mode of another dried electrode is that four dried electrodes are positioned at forehead and are that yi word pattern arranges and carry out the electro-ocular signal collection, and on both sides a reference and the dried electrode of ground connection is set respectively.
Described signal processing system comprises: wireless receiving module, computing module, control module and display screen, wherein: wireless receiving module receives from the characteristic of signal acquiring system and exports computing module to, computing module is by signal segregant module, the feature extraction submodule, smoothing denoising submodule and feature return that submodule is formed and state that input signal is carried out handling successively of four steps and obtains Alertness will export control module to, be converted into literal or figure signal and export display screen to through control module, display screen shows the Alertness situation of change of user in real time.
The present invention is used for the driver of automobile, train, aircraft, steamer, and the work position that need focus one's attention on, when producing fatigue because of long-duration driving or operation, they in time remind, thus error and the major accident that can avoid fatigue driving or maloperation to cause.Degree of accuracy of the present invention is higher than the method based on camera collection video nictation and location pupil, practicality is higher than the method based on EEG signals, compared to high-grade video acquisition device, signal acquiring system cost of the present invention is very cheap, in sum, the present invention has far-reaching social meaning and considerable economic interests.
Description of drawings
Fig. 1 is dried electrode putting position figure;
Wherein: (a) put form for traditional electrode; (b) form for electrode is put forehead.
Fig. 2 is the signal acquiring system connection layout.
Fig. 3 is the signal processing system connection layout.
The specific embodiment
Below embodiments of the invention are elaborated, present embodiment is being to implement under the prerequisite with the technical solution of the present invention, provided detailed embodiment and concrete operating process, but protection scope of the present invention is not limited to following embodiment.
As shown in Figure 2, this enforcement comprises: signal acquiring system 1, signal processing system 2 and feedback system 3, wherein: signal acquiring system 1 gather the eye electric analoging signal and amplify, filtering and digital-to-analogue conversion handle back output characteristic data to signal processing system 2, the electro-ocular signal of 2 pairs of inputs of signal processing system exports feedback system 3 to after carrying out feature extraction and estimating the Alertness state, and feedback system 3 gives the alarm when satisfying warning condition.
Be connected by Wireless transmission mode between described signal acquiring system 1 and the signal processing system 2.
Described signal acquiring system 1 comprises: wear-type fixed mount 4, dried electrode 5 and placed in-line successively amplification module 6, filtration module 7, AD modular converter 8 and wireless sending module 9, wherein: several dried electrodes 5 are arranged at and are connected in the wear-type fixed mount 4 and with amplification module 6 with output eye electric analoging signal, export filtration module 7 to after the eye electric analoging signal that amplification module 6 will be received amplifies and carry out filtering, AD modular converter 8 carries out filtered induced signal analog digital conversion generating feature data and exports signal processing system 2 to by wireless sending module 9.
The quantity of described dried electrode 5 is at least five, and wherein: two are positioned at eye socket and are used for horizontal electro-ocular signal collection up and down, and two are positioned at the outside, canthus and are used for vertical electro-ocular signal collection, and one is positioned at basal part of the ear top as with reference to signals collecting; The arrangement mode of another dried electrode 5 is that four dried electrodes 5 are positioned at forehead and are that yi word pattern arranges and carry out the electro-ocular signal collection, and on both sides the dried electrode 5 of a reference and ground connection is set respectively.
Described amplification module 6 is that secondary amplifies, and prepositionly is enlarged into 5 times, and postposition is enlarged into 300 times;
Described filtration module 7 is the bandpass filtering of 0.1Hz～100Hz;
The sample rate of described AD modular converter 8 is greater than 500Hz, and resolution is 16bit;
The transmission speed of described wireless sending module 9 is greater than 100Kbps, and coverage is greater than 10 meters.
Described signal processing system 2 comprises: wireless receiving module 10, computing module 11, control module 12 and display screen 13, wherein: wireless receiving module 10 receives from the characteristic of signal acquiring system 1 and exports computing module 11 to, computing module 11 is by signal segregant module 14, feature extraction submodule 15, smoothing denoising submodule 16 and feature return that submodule 17 is formed and state that input signal is carried out handling successively of four steps and obtains Alertness will export control module 12 to, be converted into literal or figure signal and export display screen 13 to through control module 12, display screen 13 shows the Alertness situation of change of user in real time.
Described signal segregant module 14 is used independent component analysis (Independent Component Analysis, ICA) method: the known mixed signal that forms by the multiple source signals linear hybrid, by between the hypothesis source signal maximum separate relation being arranged, come from mixed signal, to obtain approx several the highest source signals of independent degree.This method can be isolated the electromyographic signal that occurs as noise effectively from electro-ocular signal.
Described feature extraction submodule 15 extracts respectively and obtains by rapid eye movement feature, SEM feature and eye electrical characteristic data that nictation, feature was formed, wherein: the rapid eye movement feature is meant that the time is shorter than 250ms, amplitude is greater than 1mm, angle is greater than the ocular movement of 30 degree, by earlier horizontal electro-ocular signal being made difference, get threshold value then and calculate the eye movement number of times that surpasses this threshold value; The SEM feature is meant that the time was longer than 1 second, the ocular movement of frequency between 0.2-0.6Hz, by with db4 wavelet transform decomposition level electro-ocular signal to 10 rank, get 7-10 rank subconstiuent as the SEM composition, calculate these compositions shared energy ratio in overall; Use fast fourier transform simultaneously, the part of 0-1Hz as the SEM composition, is calculated the energy ratio of this composition and 1-20Hz composition; Nictation, feature was by making difference to vertical electro-ocular signal earlier, the speed of getting two corresponding respectively catacleisises of threshold value then and opening again, with these two threshold value location signature waveforms nictation, calculate morphological characteristic then, calculate its catacleisis time, the time of reopening, in a short time every, peak velocity according to waveform nictation.
Described smoothing denoising submodule 16 uses linear dynamic system (Linear Dynamical System, LDS) method, when between the signal of Alertness characteristic signal and adjacent time point and the signal of band noise with not with the signal of noise between all have Gauss and concern, then from this two Gausses relation by known initial Alertness state, obtain all thereafter not with the Alertness state of noise.The concrete effect of the method keeps from the eye electrical feature and changes slowly and rule, the composition relevant with Alertness, remove change violent and irregular, the composition that has nothing to do with Alertness.
Described feature returns submodule 17 use support vector machine recurrence, and (Support Vector Regression, SVR) method are utilized linear supporting vector machine model training regression parameter, with assurance error minimum.Utilize the good parameter of training in advance, each eigenvalue can be carried out linear combination, draw an Alertness prediction curve.Value by this curve just can directly be judged current Alertness state.
Described feedback system 3 comprises: warning lamp 18, buzzer 19, wherein: warning lamp 18 and buzzer 19 all are connected to the control module 12 of signal processing system 2, adopt wired mode directly to connect, the signal activation of controlled module 12/close.Warning lamp 18 is used for to the user visual stimulus, and buzzer 19 is used for to user auditory stimulus.Feedback system 3 can be expanded according to concrete needs, such as changing buzzer 19 into speaker, plays one section music when activating, and may have better effect to helping user to recover Alertness.As for which kind of feedback system to recovering Alertness the most not within this patent discussion scope.
Wherein as shown in Figure 1, dried electrode 5 putting positions of acquiescence are Fig. 1 (a), because this putting position need take near the position of eye socket, so wear-type fixed mount 4 is fit to make the shape of glasses.Another kind of dried electrode 5 putting positions are Fig. 1 (b), consider that the fixed mount of shape of glasses is dressed possibility inconvenience, and this arrangement method is fit to realize fixed mount with the form of headband.The difference of these two kinds of modes of emplacements is: when adopting first kind, aforesaid signal segregant module 14 will be arranged to only electromyographic signal be separated with electro-ocular signal, and when adopting second kind, signal segregant module 14 will be configured to except to electromyographic signal with electro-ocular signal separates, also to separate with level eye electricity vertical eye electricity.
As shown in Figure 2, during use, user is worn over head (fixed mount shown in this figure is second kind of form that dried electrode 5 is put) with wear-type fixed mount 4, and guarantees that dried electrode 5 sticks skin, and opens main switch.After the electro-ocular signal of user is handled via amplification module 6, filtration module 7, AD modular converter 8 at this moment, be sent to the wireless receiving module 10 of signal processing system 2 by wireless sending module 9.
As shown in Figure 3, after signal is received by wireless receiving module 10, be changed to Alertness numerical value, be changed to view data through control module 12 then, be transferred to display screen 13 through computing module 11.At this moment, user can be learnt the alertness of oneself by display screen 13.Demonstrate the Alertness curve of variation on the screen, also can demonstrate simultaneously simple Alertness state (such as red/yellow/greenly represent that respectively Alertness from low to high).
When user enters fatigue, control module 12 will send warning lamp 18 and the buzzer 19 of activation signal to feedback system 3, user is given the alarm, and this moment, user can pass through action button, and control module 12 is ceased and desisted order to warning lamp 18 and buzzer 19 transmissions.In addition, user also can be imported personal set by action button, regulates control module 12 to a certain extent and judges the threshold value that gives the alarm.
Claims (10)
1. Alertness detection system based on electro-ocular signal, it is characterized in that, comprise: signal acquiring system, signal processing system and feedback system, wherein: signal acquiring system collection eye electric analoging signal and amplify, filtering and digital-to-analogue conversion handle back output characteristic data to signal processing system, signal processing system exports feedback system to after the electro-ocular signal of importing is carried out feature extraction and estimates the Alertness state, and feedback system gives the alarm when satisfying warning condition.
2. the Alertness detection system based on electro-ocular signal according to claim 1 is characterized in that, is connected by Wireless transmission mode between described signal acquiring system and the signal processing system.
3. the Alertness detection system based on electro-ocular signal according to claim 1, it is characterized in that, described signal acquiring system comprises: the wear-type fixed mount, dried electrode and placed in-line successively amplification module, filtration module, AD modular converter and wireless sending module, wherein: several dried electrodes are arranged at and are connected in the wear-type fixed mount and with amplification module with output eye electric analoging signal, export filtration module to after the eye electric analoging signal that amplification module will be received amplifies and carry out filtering, the AD modular converter carries out filtered induced signal analog digital conversion generating feature data and exports signal processing system to by wireless sending module.
4. the Alertness detection system based on electro-ocular signal according to claim 1, it is characterized in that, the quantity of described dried electrode is at least five, wherein: two are positioned at eye socket and are used for horizontal electro-ocular signal collection up and down, two are positioned at the canthus outside and are used for vertical electro-ocular signal collection, and one is positioned at basal part of the ear top as with reference to signals collecting; The arrangement mode of another dried electrode is that four dried electrodes are positioned at forehead and are that yi word pattern arranges and carry out the electro-ocular signal collection, and on both sides a reference and the dried electrode of ground connection is set respectively.
5. the Alertness detection system based on electro-ocular signal according to claim 3 is characterized in that, described amplification module is that secondary amplifies, and prepositionly is enlarged into 5 times, and postposition is enlarged into 300 times; Described filtration module is the bandpass filtering of 0.1Hz～100Hz; The sample rate of described AD modular converter is greater than 500Hz, and resolution is 16bit; The transmission speed of described wireless sending module is greater than 100Kbps, and coverage is greater than 10 meters.
6. the Alertness detection system based on electro-ocular signal according to claim 1, it is characterized in that, described signal processing system comprises: wireless receiving module, computing module, control module and display screen, wherein: wireless receiving module receives from the characteristic of signal acquiring system and exports computing module to, computing module is by signal segregant module, the feature extraction submodule, smoothing denoising submodule and feature return that submodule is formed and state that input signal is carried out handling successively of four steps and obtains Alertness will export control module to, be converted into literal or figure signal and export display screen to through control module, display screen shows the Alertness situation of change of user in real time.
7. the Alertness detection system based on electro-ocular signal according to claim 1, it is characterized in that, described signal segregant module is according to the known mixed signal that is formed by the multiple source signals linear hybrid, by between the hypothesis source signal maximum separate relation being arranged, come from mixed signal, to obtain approx several the highest source signals of independent degree.
8. the Alertness detection system based on electro-ocular signal according to claim 1 is characterized in that, described feature extraction submodule extracts respectively and obtains by rapid eye movement feature, SEM feature and eye electrical characteristic data that nictation, feature was formed.
9. the Alertness detection system based on electro-ocular signal according to claim 1, it is characterized in that, described rapid eye movement feature is meant that the time is shorter than 250ms, amplitude is greater than 1mm, angle is greater than the ocular movement of 30 degree, by earlier horizontal electro-ocular signal being made difference, get threshold value then and calculate the eye movement number of times that surpasses this threshold value; The SEM feature is meant that the time was longer than 1 second, the ocular movement of frequency between 0.2-0.6Hz, by with db4 wavelet transform decomposition level electro-ocular signal to 10 rank, get 7-10 rank subconstiuent as the SEM composition, calculate these compositions shared energy ratio in overall; Use fast fourier transform simultaneously, the part of 0-1Hz as the SEM composition, is calculated the energy ratio of this composition and 1-20Hz composition; Nictation, feature was by making difference to vertical electro-ocular signal earlier, the speed of getting two corresponding respectively catacleisises of threshold value then and opening again, with these two threshold value location signature waveforms nictation, calculate morphological characteristic then, calculate its catacleisis time, the time of reopening, in a short time every, peak velocity according to waveform nictation.
10. the Alertness detection system based on electro-ocular signal according to claim 1, it is characterized in that, described smoothing denoising submodule according between the signal of Alertness characteristic signal and adjacent time point and the signal of band noise with not with passing through known initial Alertness state between the signal of noise, obtain all thereafter not with the Alertness state of noise.
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