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Well the link I posted were for companies who are compliant with SEC rules.....Not sure what kind of notice ECT would have to give...
Any news Mcchoochoo? Are you ready for a shareholder Meeting?
http://www.ehow.com/how_2039474_sec-compliance-shareholder.html
double down?
I am surprised more people are not talking about the document that France101 posted......
Regards, ;)
On the good buys.....
close.....William......
I have no clue...Do you know? Is there a phantom amigo?
In the states William=Bill, Richard=Dick....actually I go by my middle name & not my first name......
Wow! I look tonight and see all of these messages and wonder what happened. After reading all of the messages from today I see the topic is patents.
Hmmm, here is the info from USPTO as of 7:36pm today:
Application Number: 61/071,966 Status: Provisional Application Expired
Until the patent application has completed examination and the patent has been issued and assigned to someone other than the inventor it belongs to the inventor, who in this case is Mr. Farbos. ECT may have filed the application but they 'own' nothing yet.
France,
Nice find & Thanks for posting this. I had to chance to take a look at this "registar of companies" which is in french, this evening. (been busy with the snowflakes falling) There are some nice little tidbits in here & information here that I think is good to share with the board which shows recent activity with the 5 AMIGOS.
1)2009-12-10 LE REGISTRAIRE DES ENTREPRISES
H:22:06:18 SYSTÈME CIDREQ
On December 12, 2009 @ 10:06 there was a registration/modification of the business. (I have no clue what system cidreq is)
Number 1164656630 Effective Control Transport. It appears they have updated the business to bring it current to the edfice of Business for Quebec
2)DESTINATAIRE : GUY FAUCHER
ADRESSE : 1600, RUE DU MONT CODE POSTAL: J3V 4L5
SAINT-BRUNO-DE-MONTARVILLE (QUÉBEC)
It appears they are using the address of Guy Faucher at this time for the business address
3)PERSONNES LIÉES
===============
PERSONNES MANQUANTES: NON
NOM ET ADRESSE CODE POSTAL DÉTAIL PERSONNE
====================================== =========== ====================
CHARLES SCHWAB TRUST CO LTÉE ACTIONNAIRE
TROISIÈME ACTIONNAIR
837, WHISPER FALLS LN
MENASHA (WISCONSIN)
ÉTATS-UNIS
------------------------------------------------------------------BÉLANGER, ALPHONSE ACTIONNAIRE
PREMIER ACTIONNAIRE
2070, AVENUE DE LA RIVIÈRE-JAUNE G2N 1T2
QUÉBEC (QUÉBEC)
-----------------------------------------------------------------COUPAL, PIERRE-YVES ACTIONNAIRE
DEUXIÈME ACTIONNAIRE
1360, ROUTE ÉDOUARD VII J0L 2K0
SAINT-PHILIPPE (QUÉBEC)
This is intresting. A "actionnaire" is a shareholder.. They list 3 shareholders as the 1st, 2nd & 3rd
#1 Alphonse Belanger-Quebec
#2 Pierre Coupal-Quebec
#3 Charles Schwab-USA
Any IHUBERS want to fess up? I dont think these listed are Ihubbers.....
4)FAUCHER, GUY ADMINISTRATEUR
PRÉSIDENT 1600, DUMONT J3V 4L5
SAINT-BRUNO-DE-MONTARVILLE (QUÉBEC)
NAIM, MARIO ADMINISTRATEUR
SECRÉTAIRE 10429, AVENUE PÉLOQUIN H2C 2K2
MONTRÉL (QUÉBEC)
GAUTHIER, JEAN-PAUL ADMINISTRATEUR
TRÉSORIER 895, RUE D'ALENÇON G7A 4B6
SAINT-NICOLAS (QUÉBEC)
DE MEDEIROS, EGBERTO ADMINISTRATEUR
VICE-PRÉSIDENT 417, BOULEVARD BEACONSFIELD H9W 4B4
BEACONSFIELD (QUÉBEC)
GUY, BENOIT ADMINISTRATEUR
VICE-PRÉSIDENT 427, RUE DES PLATEAUX J3H 6E6
MONT-SAINT-HILAIRE (QUÉBEC)
1, 2, 3, 4 & 5. I count 5 Amigos! The 5 amigos are listed for the update. Again here are the bios' as per the solitication document.
Dr. Guy J.C. Benoit, M.Sc., D.D.S., age 42, is the founder of the dentistry clinics CliniquesDentaires Benoit & Associés. A longtime shareholder of Effective Control Transport, Mr. Benoit has completed degrees in microbiology and immunology (1989) from McGill University and in biology from University on Montreal (1990). He was awarded a master immunology in 1992 and finally completed his doctoral studies in dentistry in 1996. He is a certified implantologist and has also received a
certification to perform bone grafts.
Guy Faucher, C.A., age 60, had advised Effective Control Transport from August 2008 to March 2009. He is the co-founder and senior partner of the accounting firm Faucher, Daviault and Partners, fromwhich he has retired in 2000. Throughout his career he has served as director or held senior executivepositions in many business ventures, including Orex Exploration Inc., Paraiso Del Sol Beach Resort Hotel, Dynamak Inc., Progicar Inc. and Provilub S.A.
Guy-Paul Gauthier, age 47, worked at Effective Control Transport from April 2008 to March 2009 as Vice-President of corporate development. He is the President and director of Aquagenex Inc., a development-stage company that manufactures a portable self-contained water treatment system especially designed for emergency use and remote locations. He is also the former President and cofounder of Securcap Corporation, a closely-held holding company that operated in the Health and Environmental sectors.
Gib de Medeiros, B.Sc. Eng., Ph.D., age 48, Mr. de Medeiros worked at Effective Control Transport from august 2007 to April 2009 as Vice-President of Sales, with responsibilities for Latin America Business Development, Marketing & Sales, and also Strategic Planning. He cumulates twenty nine years of progressive international experience as a senior executive and consultant in large multinational corporations, as well as direct entrepreneurial involvement in start-ups. Prior to joining
Effective Control Transport, Mr. de Medeiros worked as a new ventures developer and entrepreneur, having developed and headed the implementation of venture capital backed companies, privately help start-ups, spin-offs and new business units. Mr. de Medeiros has also worked for multinational companies like Microsoft, Editora Abril S.A. and IBM Global Business Services, in the sectors of consumer goods, engineering, services, software, publishing, media and telecom, acquiring skills and competences in
business general management, business development, marketing & sales, distribution, human resources, product development and customer support. Mr. de Medeiros also has academic experience both teaching and participating in research projects at universities. He obtained a Ph.D. in Human-Computer Interaction
and Cognitive Ergonomics in 1992 from the Conservatoire National des Arts et Métiers (CNAM) in Paris(France), an Advanced Management Program (AMP) diploma in business management in 1997 from the INSEAD in Fontainebleau (France), and an Industrial Engineering diploma in 1985 from the Polytechnic
School of the University of São Paulo, (Brazil). He has successfully finished a Project Management specialization at McGill University, Montreal, Canada (2009).
Mario Naim, Esq., age 42, had worked as counsel to Effective Control Transport between September 23rd, 2008 and April 13, 2009. Prior to joining Effective Control Transport, Mr. Naim had specialized in the areas of mergers and acquisitions, banking and securities law. He has notably been involved in U.S. and cross-border transactions, and worked with Canadian and U.S. clients in the 21 acquisition of businesses in the U.S., Europe, the Middle East and Latin America. Mr. Naim received a
B.A. in Philosophy from the University of Québec in Montreal, his LL.B. from the University of Québec in Montreal, and his LL.M. (Banking Law) at Boston University School of Law. He was admitted to the Quebec bar in 1996 and to the New York bar in 2003.
What does all this mean? It appears the ECT Recovery team is doing some behind the scenes work...or plain english...Getting their ducks in a row....
PS: France, Seems there were 2 modifications:
19 DÉCLARATION MODIFICATIVE 2009-12-09 0 000 (listed above)
19 DÉCLARATION MODIFICATIVE 2009-11-11 0 000
Can you find out & post what "modificative" happened on 11/11/2009?
Were you one of the scoffers on the "patent pending"?
How does this abstract PCT patent compare with Biocognifsafe stripped down version?
I would wait to all things are worked out. There will be alot of FUD (fear, uncertainty & doubt)(crainte, incertitude et doute) here until we here from the team. The un-official word out of Quebec is the injunction was lifted on Thursday. The un-official word from Deleware is the judge ruled in favor of the shareholder vote. We know that RH Tried the raise the AS & perform a 12-1 RS. We know that paper worked has been filed (admendents) & the AS is 250 million & the RS is not happening. The team has been doing some work behind the scenes.
You are now chatting with 'Christina' with the Delaware Division of Corporations Information Center.
Christina: Hello, Please hold as I review your question.
Christina: 250,000,000
BF: ok, a few weeks back it was 600 million, & I believe the last filing was OCtober 9th
BF: Has there been any filings/admendments since then?
BF: There was also a admendmentfor a 12-1 R/S...has that changed as well?
Christina: there was a cert. of corrections filed on 11-12-2009
BF: Thank you again for your help! Was that the last filing?
Christina: Yes,
BF: thanks again...have a great day!
Christina: You are welcome.,
We know now we have a patent pending. Many on this board scoffed at that claim. Well, it is out there & it would seem, Bruno has worked hard on this patent. You must remember that this belongs to ECT. The abstracts on this patent seem solid. Read closely concerning the eyelid claims. If you have shares, you helped in funding this research project. If you are like myself, you may feel excited about this opportunity & revolutionizing product called the CRAM. You may want to but Bruno a drink in 6 months. Thank you Bruno!
All this being said, It is important to hear from the team, before all the rumors & accusations are thrown all over the place, especially here on IHUB.
I am not looking for all the answers, the final plan to market the CRAM, production schedules, LOI's or even contracts at this point. Frankly speaking, these all have to be worked out. The CRAM needs to be field tested. The team needs to examen the product & see how much work is left to do on the product. This will take some time. I would like to hear from the team & be updated on the following:
the court process (since the RH injunction in July)
the share counts
the team structure
Update on financing
Initiating/redeveloping old contacts (Robert & others)
Bruno Update
Patent Process Update
Shareholder meeting (I would be willing to host it at my business)
They need to say we are in charge & will begin the process outlined in the solicitation that we voted upon. If Guy Faucher is the guy in charge as posted, you as a shareholder can vote him out if you wish, at the shareholder meeting. We voted for the transparency, & hopefully we hear form the amigos next week! It may be a small pop for flippers, but for longs it would be the beginning of a steady rise to those who believe in the CRAM.
The sooner we hear the better. As a shareholder & one who likes to see PPS appreciation, I think you could see some buying with an updated agenda from the team.
REASONS FOR OUR SOLICITATION
We are significant stockholders of the Company. As of June 2, 2009, the mailing date in connection with the solicitation, the Committee owns in the aggregate a total of 9,917,700 shares of
Common Stock, or approximately 4% of the Common Stock outstanding. As significant stockholders of
Effective Control Transport, the Committee has a vested financial interest in the maximization of the value of the Company’s Common Stock. Our interests are aligned with the interests of all stockholders:
we have one simple goal – to maximize the value of the Common Stock for all stockholders, complete
the CRAM’s development, bring it to market, and operate the Company with honesty, competency
and transparency.
Transparency. Accountability. Competency. It is Time for a True Change!
The ECT Recovery Committee has a plan to right the ship and put the Company back on course
towards transparency, accountability and competency.
In light of the depth of our past experience, we are uniquely positioned to help turn Effective
Control Transport around. We will do everything within our power to save the Company that we worked
so hard to build during our tenure. With your support and a lot of hard work by a passionate and dedicated
team, we are committed to complete the development of the CRAM and bring it to market so that it can
start saving lives!
We have nominated five highly qualified nominees who will constitute the entire Board
if the Board Removal Proposal and Election Proposal are approved by stockholders. The Nominees if
elected will aggressively pursue the following initiatives designed to restore stockholder value.
- Appoint a new executive management team;
- Apply modern principles of corporate governance;
- Obtain bridge financing;
- Complete CRAM testing and development;
-Restore relations with clients in the transportation industry based on mutual trust;
- Elaborate a long term plan; and
-Convene a shareholder meeting.
The Nominees understand that, if elected as directors of Effective Control Transport, each of
them will have an obligation under Delaware law to discharge his duties as a director in good faith,
consistent with his fiduciary duties to the Company and the stockholders.
There can be no assurance that the actions the Nominees intend to take as described above will be
implemented if they are elected or that the election of the Nominees will improve the Company’s business
or otherwise enhance stockholder value. Your vote to elect the Nominees does not constitute a vote in
favor of the Committee’s value-enhancing plans for Effective Control Transport. Your vote for the
Removal Proposal and to elect the Nominees will have the legal effect of replacing five incumbent
directors of Effective Control Transport with the Nominees. There can be no assurance that stockholder
value will be maximized as a result of this solicitation or the election of the Nominees.
RELEASE THE UPDATE!
Publication
18 months after the filing date or the priority date if any, the international application is published by the International Bureau (IB) of WIPO, based at Geneva, Switzerland, in one of the ten "languages of publication": Arabic, Chinese, English, French, German, Japanese, Korean, Portuguese, Russian, and Spanish. [27] There is an exception to this general rule however: if 18 months after the priority date, the international application only designates the United States, then the application is not automatically published.
I don't have L's at work...anybody? Where is 4-kids when you need her!
I believe that was a good buy! Wonder who sold? Now you can't even find a seller!
LOL..go figure...a few days back 500k go through at the bid......I am sitting at 1 yesterday after the big volume, no sellers, no sellers today @ .0095......MUST BE a good sign?....
I would be happy for it to run, & Miss it & have to paint it at 25 cents! :)
I am not looking for a full-out plan, just a few updates at this point to inform shareholders.....
Or maybe the ECT Friends Website?.....
I have been looking at the abstact for the patent....I think we have a good patent...the eyelid closure part is interesting.......let's see how long it takes to it to be granted......
Back a few months ago, posters saying Patent Pending, was a lie, well, touche on that....RH managed to get it done..somehow...
United States Patent Application 20090299209
Kind Code A1
Farbos; Bruno December 3, 2009
--------------------------------------------------------------------------------
METHOD AND DEVICE FOR THE DETECTION OF MICROSLEEP EVENTS
Abstract
Disclosed herein is a method of detecting a microsleep event in a subject. The method includes determining a number of eye openness factors by measuring a number of distances between an upper eyelid and a lower eyelid of at least one eye over a time period. Graphical representations of the eye openness factors are then generated. Changes in the eye openness factors over the time period are correlated with a reference eye closure pattern indicative of the microsleep event. Also disclosed is a microsleep event detection device.
--------------------------------------------------------------------------------
Inventors: Farbos; Bruno; (Montreal, CA)
Correspondence Name and Address: EDWARDS ANGELL PALMER & DODGE LLP
P.O. BOX 55874
BOSTON
MA
02205
US
Assignee Name and Adress: Effective Control Transport, Inc.
Quebec
CA
Serial No.: 340017
Series Code: 12
Filed: December 19, 2008
U.S. Current Class: 600/544; 600/558
U.S. Class at Publication: 600/544; 600/558
Intern'l Class: A61B 5/0476 20060101 A61B005/0476; A61B 3/00 20060101 A61B003/00
--------------------------------------------------------------------------------
Claims
--------------------------------------------------------------------------------
1. A method of detecting a microsleep event in a subject, the method comprising:determining a plurality of eye openness factors by measuring a plurality of distances between an upper eyelid and a lower eyelid of at least one eye over a time period;generating graphical representations of the eye openness factors; andcorrelating changes in the eye openness factors over the time period with a reference eye closure pattern indicative of the microsleep event.
2. The method, according to claim 1, further comprising: illuminating the face of the subject; and recording a facial image.
3. The method, according to claim 2, in which a digital camera having an infra-red source is used to illuminate the face and to record the facial image.
4. The method, according to claim 1, further comprising: identifying the eye and the eyelids by using a facial feature recognition algorithm.
5. The method, according to claim 1, further comprising: verifying the presence of microsleep characteristic eye openness factor levels by measuring the eye openness factors as a function of time for a blink cycle of the eye.
6. The method, according to claim 5, in which the eye openness factors levels include at least one eye openness level.
7. The method, according to claim 5, in which the eye openness factors include one or more eye openness levels and five or less eye openness levels.
8. The method, according to claim 5, in which the eye openness factors include five eye openness levels.
9. The method, according to claim 5, in which the eye openness levels are associated with an open eye, the closure of the eyelids, partial or closed eye, and opening of the eyelids
10. The method, according to claim 1, in which the eye openness factors include five successive eye openness levels, the sequential detection of the five levels being indicative of microsleep characteristics.
11. The method, according to claim 10, further comprising: determining additional eye openness factors if less than five successive eye openness factor levels are detected.
12. The method, according to claim 5, further comprising: computing eye opening and eye closure representative curves.
13. The method, according to claim 12, in which the eye closure representative curves are computed using a negative slope and a second order polynomial regression applied to the eye openness factors of the first and second eye openness factor levels.
14. The method, according to claim 12, in which the eye opening factors are computed using a positive slope and a second order polynomial regression applied to the eye openness factors of the fourth and fifth eye openness factor levels.
15. The method, according to claim 12, further comprising: verifying the presence of microsleep eye opening and closing representative curves by computing the Pearson coefficient of the eye closure representative curves with regard to the first and second eye openness factor levels and the eye opening representative curves with regard to the fourth and fifth eye factor levels.
16. The method, according to claim 15, in which the subject is informed when the Pearson coefficients are greater than or equal to a predetermined threshold value.
17. The method, according to claim 3, in which images of the face are sampled at a frequency of between 10 Hz and 60 Hz.
18. The method, according to claim 5, further comprising: a sub-process for detecting microsleep characteristic eye openness factor levels at an image sampling frequency of 20 Hz.
19. The method, according to claim 18, in which the sub-process comprises: verifying that a first level is detected by confirming the presence of a series six or more successive eye openness factors corresponding to an open eye.
20. The method, according to claim 19, further comprising: verifying that a second level is detected by confirming the presence of a series four or more successive decreasing eye openness factors.
21. The method, according to claim 20, further comprising: verifying that a third level is detected by confirming the presence of a series of a minimum of five and a maximum of one-hundred and twenty successive eye openness factors.
22. The method, according to claim 21, further comprising: verifying that a fourth level is detected by confirming the presence of a series of a minimum of four successive eye openness factors.
23. The method, according to claim 22, further comprising: verifying that a fifth level is detected by confirming the presence of a series of a minimum of six successive eye openness factors corresponding to the open eye.
24. The method, according to claim 1, further comprising: alerting the subject to the presence of the microsleep event.
25. A microsleep event detection device, the device comprising:a facial image sampler for sampling facial images over time of a subject, the sampler having an infra red source for illuminating one or more eyes of the subject;a microprocessor having electronically stored therein an electronically executable microsleep detection process, the microprocessor being connected to the sampler for receiving the sampled facial images, the images being electronically converted to graphical representations of eye openness factors; anda memory associated with the microprocessor, the memory having stored therein a plurality of reference eye closure patterns for electronically correlating the eye openness factors with the reference eye closure patterns.
26. The device, according to claim 25, further comprising an alert connected to the microprocessor for alerting the subject to the microsleep event.
27. A method of alerting a vehicle operator to a microsleep event, the method comprising:determining a plurality of eye openness factors by measuring a plurality of distances between an upper eyelid and a lower eyelid of at least one eye over a time period;generating graphical representations of the eye openness factors;correlating changes in the eye openness factors over the time period with a reference eye closure pattern indicative of the microsleep event; andtriggering an alarm so as to alert the operator to the microsleep event.
28. A method of correlating EEG and EOG microsleep patterns with eye closure patterns, the method comprising:measuring EEG and EOG microsleep patterns in a subject;determining a plurality of eye openness factors by measuring a plurality of distances between an upper eyelid and a lower eyelid of at least one eye over a time period;generating graphical representations of the eye openness factors; andcorrelating changes in the eye openness factors with the EEG and EOG microsleep patterns.
--------------------------------------------------------------------------------
Description
--------------------------------------------------------------------------------
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001]This application claims the benefit of previously filed U.S. Provisional Patent Application Ser. No. 61/071,966, filed on May 28, 2008, the contents of which are incorporated herein by reference.
TECHNICAL FIELD
[0002]The present invention concerns a method and device for the detection of microsleep events.
BACKGROUND
[0003]Methods for quantifying driving performance errors associated with sleep onset are of key importance for reducing the number of sleep related crashes. In the US, driver sleepiness is a major cause of motor vehicle crashes and is responsible for approximately 40,000 injuries and 1500 deaths each year. In one study, 55% of 1000 drivers surveyed indicated that they had driven while drowsy and 23% had fallen asleep at the wheel. This confirms other studies that sleepiness or sleep onset may play a role in vehicle crashes that are erroneously attributed to other causes.
[0004]Microsleep events are a useful indicator of sleep onset. A microsleep event often occurs as a result of sleep deprivation, or mental fatigue, sleep apnea, narcolepsy, or hypersomnia.
[0005]There are standardized methods for monitoring microsleep, which include: monitoring the electroencephalogram (EEG) and electrooculogram (EOG), video, test of performance, and the like. Of all these methods, the EEG is considered the most reliable for measuring sleepiness. However, both EEG and EOG, require the use of electrodes, which are attached to the subject, thereby making these methods inappropriate to routinely monitor any operators conducting fatigue prone tasks, such as, for example, vehicle drivers. The other methods are impractical because they are both difficult to set-up and because they require intensive data analysis by humans thereby making data treatment difficult to automate.
[0006]There are various ways by which microsleep episodes can be identified. Some experts define microsleep according to behavioral criteria (eyelids closure), while others rely on electroencephalogram markers such as a 3-15 second episode (shorter durations would be difficult to visually detect and longer times would qualify as sleep onset.) during which 4-7 Hz (theta wave) activity replaced the waking 14-20 Hz (alpha wave) background rhythm.
[0007]Microsleep, subjectively related to the sensation of "nodding off", is associated with the interruption of the blinking artifacts characteristic of full wakefulness. During microsleep events, attention lapses can impair the ability to detect and respond to crucial stimuli and events. For example, microsleeps (or microsleep episodes) can become extremely dangerous when occurring during situations which require continual alertness, such as driving a motor vehicle or operating machinery. People who experience microsleeps usually remain unaware of them, instead believing themselves to have been awake the whole time, or feeling a sensation of `spacing out`. The sleepy driver is at very high risk of having an accident during a microsleep episode. Many accidents have occurred because of microsleep episodes.
[0008]Clearly, the ability to detect microsleep events would be useful as a means of alerting and warning drowsy drivers of such events.
[0009]Several studies have used "quantitative" EEG methods to identify driver sleepiness. Theta power (EEG waves), and the frequency of theta bursts typically increase during prolonged driving, and are associated with poor driving performance. Disadvantageously, these techniques typically average EEG activity over several seconds (up to 1 minute), and therefore could not be used to detect brief microsleep events of between 3 seconds and 15 seconds.
[0010]A variety of physiological measures have been proposed to alert drivers to the onset of drowsiness.
[0011]One of the most investigated is PERCLOS (or PERcent CLOSure), which measures drowsiness as the percent of time a driver's eyes are closed over a time period. When a sufficient number of open/closed patterns are obtained, PERCLOS will trigger an alarm. PERCLOS works at percentages greater than 80%, which typically means that within 1 minute, the eyes of the individual must be closed for 48 seconds before an alarm is triggered. Clearly, this delay in unacceptable in tasks such as driving a vehicle because by the time PERCLOS activates the alarm, the driver will already have either fallen asleep, or be on the verge of falling asleep. Therefore, disadvantageously PERCLOS is too slow a system to allow preventive actions to be taken before an individual, such as a driver, experiences the first signs of sleepiness.
[0012]EOG records, which are made to exclude potential artifacts during EEG records, also show that normal eye blinks often continue during microsleep events, indicating that the eyes are at least partially open.
[0013]Another physiological measure, which is based on measurements of eye closure and which supposedly alerts drivers to the onset of drowsiness, is the measurement of peak blink velocities, as described in U.S. Pat. No. 7,071,831B2. The system described therein includes a pair of glasses or spectacle frames that must be worn by the individuals in order to monitor the occurrence of eye blinks. However, this kind of device must be carried or worn by operators (i.e. portable devices).
[0014]Thus, there is a need for a detection method and device for the detection of microsleep events in a subject as an indicator of sleep onset that is able to detect brief microsleep events, at early stages, not requiring the use of electrodes or other portable devices.
SUMMARY
[0015]We have unexpectedly discovered that microsleep events can be easily and readily detected by measuring the closing and opening patterns of the eyelids over time using a microsleep detection process, converting the raw data collected from the measurements into graphs and comparing the graphs to those of stored, standardized microsleep patterns.
[0016]Accordingly, in one aspect there is provided a method of detecting a microsleep event in a subject, the method comprising:--determining a plurality of eye openness factors by measuring a plurality of distances between an upper eyelid and a lower eyelid of at least one eye over a time period;--generating graphical representations of the eye openness factors; and--correlating changes in the eye openness factors over the time period with a reference eye closure pattern indicative of the microsleep event.
[0017]The method, as described above, further comprising: illuminating the face of the subject; and recording a facial image. A digital camera having an infra-red source is used to illuminate the face and to record the facial image.
[0018]The method, as described above, further comprising: identifying the eye and the eyelids by using a facial feature recognition algorithm.
[0019]The method, as described above, further comprising: verifying the presence of microsleep characteristic eye openness factor levels by measuring the eye openness factors as a function of time for a blink cycle of the eye. The eye openness factors levels include at least one eye openness level. The eye openness factors include one or more eye openness levels and five or less eye openness levels. The eye openness factors include five eye openness levels. The eye openness levels are associated with an open eye, the closure of the eyelids, partial or closed eye, and opening of the eyelids.
[0020]The method, as described above, in which the eye openness factors include five successive eye openness levels, the sequential detection of the five levels being indicative of microsleep characteristics. The method further comprising: determining additional eye openness factors if less than five successive eye openness factor levels are detected.
[0021]The method, as described above, further comprising: computing eye opening and eye closure representative curves. The eye closure representative curves are computed using a negative slope and a second order polynomial regression applied to the eye openness factors of the first and second eye openness factor levels. The eye opening factors are computed using a positive slope and a second order polynomial regression applied to the eye openness factors of the fourth and fifth eye openness factor levels. The method further comprising: verifying the presence of microsleep eye opening and closing representative curves by computing the Pearson coefficient of the eye closure representative curves with regard to the first and second eye openness factor levels and the eye opening representative curves with regard to the fourth and fifth eye factor levels. The subject is informed when the Pearson coefficients are greater than or equal to a predetermined threshold value.
[0022]The method, as described above, in which images of the face are sampled at a frequency of between 10 Hz and 60 Hz.
[0023]The method, as described above, further comprising: a sub-process for detecting microsleep characteristic eye openness factor levels at an image sampling frequency of 20 Hz. The sub-process comprises: verifying that a first level is detected by confirming the presence of a series six or more successive eye openness factors corresponding to an open eye.
[0024]The method, as described above, further comprising: verifying that a second level is detected by confirming the presence of a series four or more successive decreasing eye openness factors. The method, as described above, further comprising: verifying that a third level is detected by confirming the presence of a series of a minimum of five and a maximum of one-hundred and twenty successive eye openness factors.
[0025]The method, as described above, further comprising: verifying that a fourth level is detected by confirming the presence of a series of a minimum of four successive eye openness factors.
[0026]The method, as described above, further comprising: verifying that a fifth level is detected by confirming the presence of a series of a minimum of six successive eye openness factors corresponding to the open eye.
[0027]The method, as described above, further comprising: alerting the subject to the presence of the microsleep event.
[0028]According to another aspect, there is provided a microsleep event detection device, the device comprising:
[0029]a facial image sampler for sampling facial images over time of a subject, the sampler having an infra red source for illuminating one or more eyes of the subject;
[0030]a microprocessor having electronically stored therein an electronically executable microsleep detection process, the microprocessor being connected to the sampler for receiving the sampled facial images, the images being electronically converted to graphical representations of eye openness factors; and
[0031]a memory associated with the microprocessor, the memory having stored therein a plurality of reference eye closure patterns for electronically correlating the eye openness factors with the reference eye closure patterns.
The device, as described above further comprises an alert connected to the microprocessor for alerting the subject to the microsleep event.
[0032]Accordingly, in another aspect there is provided a method of alerting a vehicle operator to a microsleep event, the method comprising: [0033]determining a plurality of eye openness factors by measuring a plurality of distances between an upper eyelid and a lower eyelid of at least one eye over a time period;
[0034]generating graphical representations of the eye openness factors;
[0035]correlating changes in the eye openness factors over the time period with a reference eye closure pattern indicative of the microsleep event; and
[0036]triggering an alarm so as to alert the operator to the microsleep event.
[0037]Accordingly, in yet another aspect, there is provided a method of correlating EEG and EOG microsleep patterns with eye closure patterns, the method comprising: [0038]measuring EEG and EOG microsleep patterns in a subject; [0039]determining a plurality of eye openness factors by measuring a plurality of distances between an upper eyelid and a lower eyelid of at least one eye over a time period; [0040]generating graphical representations of the eye openness factors; and [0041]correlating changes in the eye openness factors with the EEG and EOG microsleep patterns.
BRIEF DESCRIPTION OF THE FIGURES
[0042]Embodiments of the invention will be described by way of example only with reference to the accompany drawings, in which:
[0043]FIG. 1 is a block diagram of a microsleep detection device according to an illustrative embodiment of the present invention, the device being used on a subject;
[0044]FIG. 2 is a flow diagram of a microsleep event detection process that may be used by the device of FIG. 1;
[0045]FIGS. 3A and 3B are schematic views of the fully open eye (FIG. 3A) and the fully closed eye (FIG. 3B) with their associated eye openness factor;
[0046]FIG. 4 is a series of schematic views of an example of the variation of the eye openness factor as a function of time for a blink cycle;
[0047]FIG. 5 is an illustrative example of the fully closed eye (period L4 and L5), at the moment of a microsleep; and
[0048]FIG. 6 is a flow diagram of a microsleep characteristic eye openness factor levels detection sub-process that may be used with the microsleep event detection process of FIG. 2 for an image sampling frequency of 20 Hz.
DETAILED DESCRIPTION
[0049]Generally stated, the non-limitative illustrative embodiment of the present invention provides a method and device for the detection of microsleep events in a human subject based on the analysis of eye closure patterns of at least one eye, typically both eyes, which occur during microsleep events.
[0050]During microsleep events, measured by EEG and EOG, we observed a progressive variation of the distance between an upper eyelid and a lower eyelid of a human subject over time. We now describe hereinbelow a method and device, which provides complementary evidence of impending sleep in drowsy operators, such as vehicle drivers, airplane pilots, air traffic controllers and the like, using eye closure patterns, which when detected, alerts sleepy operators to unsafe situations before eyelid closure occurs, thereby correlating EEG and EOG microsleep patterns with eye closure patterns.
[0051]Also described is a method for the analysis of eye closure patterns allowing the differentiation between a normal eyelid closure and one due to drowsiness.
[0052]Referring to FIG. 1, there is shown an example of a microsleep event detection device 100, which generally comprises facial image sampler such as a digital camera 102 with an associated infrared source 104, a microprocessor 106 with an associated memory 108 and either or both an alarm/display 110 and input/output interface 112.
[0053]Thus, in one example, there is described a method using the device 100 for detecting a microsleep event in a human subject. The method comprises: determining a plurality of eye openness factors by measuring a plurality of distances between an upper eyelid and a lower eyelid of at least one eye, typically both eyes, over a time period; generating graphical representations of the eye openness factors; and correlating changes in the eye openness factors over the time period with a reference eye closure pattern indicative of the microsleep event.
[0054]In operation, the digital camera 102 is aimed at the face of a subject 10 and illuminates his or her eyes 12 using the infrared source 104 in order to determine the eye openness factor, i.e. a value representative of the distance between the upper 14a and lower 14b eyelids. The images taken by the digital camera 102 are then processed by the processor 106 which executes a microsleep event detection process stored on its associated memory 108. Upon detection of a microsleep event, the microsleep event detection device 100 may inform the user of a microsleep event by triggering an integrated alarm and/or display 110 or provide the information to a further process or device via the input/output interface 112. It is to be understood that other components may be added to the microsleep event detection device 100 such as, for example, a user interface and a wireless communication device.
[0055]Referring now to FIG. 2, there is shown a flow diagram of a microsleep event detection process 200 that may be electronically executed by the processor 106 of the microsleep event detection device 100 of FIG. 1. The steps of the process 200 are indicated by blocks 202 to 212. The process 200 starts at block 202 by sampling an image of the face of a subject 10 using the digital camera 102. The digital camera 102 may sample images at a frequency between about 10 and 60 Hz (i.e. sampling frequency). At block 204, the process 200 identifies, in the sampled digital image, the eye 12 and eyelids 14a, 14b of the subject 10. This may be accomplished using a facial feature recognition algorithm executed by the processor 106. Then, the eye openness factor is computed.
[0056]Referring now to FIGS. 3A and 3B, the eye openness factor may be expressed as .delta. having a value between 1, representing a fully open eye 12 (see FIG. 3A), and 0, representing a fully closed eye 12 (see FIG. 3B). The value of .delta. may be computed, for example, by dividing the measured distance between the upper 14a and lower 14b eyelids positions in a Cartesian representation (X,Y) by a reference measure of the fully open eye D. Thus:
.delta.=(upper lid position (x.sub.u,y.sub.u)-lower lid position (x.sub.l,y.sub.l))/D,
where D=upper lid position (x.sub.U,y.sub.U)-lower lid position (x.sub.L,y.sub.L) and (x.sub.u,y.sub.u)=instant upper lid position, (x.sub.l,y.sub.l)=instant lower lid position, (x.sub.U,y.sub.U)=upper lid position at maximum eye opening and (x.sub.L,y.sub.L)=lower lid position at maximum eye opening.
[0057]Referring again to FIG. 2 at block 206, the process verifies if the microsleep characteristic eye openness factor levels are present.
[0058]Referring to FIG. 4, there is shown an illustrative example of the variation of the eye openness factor as a function of time for a blink cycle. The blink cycle starts at time t.sub.1 with a fully open eye 12 (eye openness factor .delta.=1.00), at t.sub.2 the eye openness factor remains at .delta.=1.00, then decreases, going through .delta.=0.80 and .delta.=0.50 at times t.sub.1 and t.sub.1+1, until it reaches .delta.=0.00 at time t.sub.j (fully closed eye 12), and then increases, going through .delta.=0.50 and .delta.=0.80 at times t.sub.k and t.sub.k+1, until it reaches .delta.=1.00 again at t.sub.n. It is to be understood that the blink cycle illustrated in FIG. 4 for illustrative purpose only and that an actual cycle would comprise a number of sample times depending the sample frequency.
[0059]Referring now to FIG. 5, these computed eye openness factors, as a function of time, can be represented in a graph which may be generally characterized by five successive levels, L1 to L5. The first and last levels, L1 and L5, are associated with the open eye (i.e. .delta.=1.00), the second level, L2, with the closure of the eyelids, 14a, 14b (i.e. 0.00>.delta.>0.00, .delta. decreasing), the third level L3, with the partial or closed eye (i.e. 0.00<.delta.<0.5 for example) and fourth level, L4, with the opening of the eyelids 14a, 14b (i.e. 0.00<.delta.<1.00, .delta. increasing).
[0060]Referring again to FIG. 2, the process 200 detects all five levels, i.e. L1 to L5, it then proceeds to block 208. If not, it proceeds back to block 202 for the next image sample. At block 208, the process computes the eye closure 21 or 26 and eye opening 25 or 27 representative curves. The eye closure representative curve 21 or 26 is computed using negative slope second order polynomial regression (parabolic curve), i.e.
Y=d.sub.0+d.sub.1.X+d.sub.2.X.sup.2.
where Y is the predicted outcome value for the polynomial model with regression coefficients d.sub.1 to .sub.2 for each degree and Y intercept d1; [0061]which is applied to the eye openness factors composing the first and second eye openness factor levels, i.e. L1 and L2. As for the eye opening representative curve 25 or 27, it is computed using positive slope second order polynomial regression applied to the eye openness factors composing the fourth and fifth eye openness factor levels, i.e. L4 and L5. Then, at block 210, the process 220 verifies if the microsleep eye opening and closing representative curves are present. This is accomplished by computing the Pearson coefficient, r:
[0061] r = XY - X Y N ( X 2 - ( X ) 2 N ) ( Y 2 - ( Y ) 2 N ) ##EQU00001##
where X and Y are positions in a Cartesian representation; [0062]of the eye closure representative curve 21 or 26 with regard to the eye openness factors composing eye openness factor levels L1 and L2, and of the eye opening representative curve 25 or 27 with regard to the eye openness factors composing the eye openness factor levels L4 and L5. If both Pearson coefficients are greater or equal to a given threshold such as, for example, 0.9, then the process 200 proceeds to block 212. If not, it proceeds back to block 202 for next image sample. Finally, at block 212, the microsleep event detection device 100 may inform the user 10 of the detection of a microsleep event state via the integrated alarm and/or display 110 or provide the information to a further process or device via the input/output interface 112 (see FIG. 1) using, for instance, a wired or wireless telecommunication link such as, for example, Bluetooth, WiFi and the like.
[0063]It is to be understood that the Pearson coefficient threshold is not meant to be restricted to 0.9 and may be adjusted to suit a desired confidence level. It may also vary depending on the resolution of the digital camera 102 (see FIG. 1).
[0064]The eye closure pattern is based on these particular observations closing, duration of the eyelid complete or partial closure and re-opening. More precisely, the eye closure pattern indicates a progressive decreasing followed by a baseline period where the eyelids are fully closed and then a reopening. If all the above occur, then a microsleep is detected.
Example of Microsleep Characteristic Eye Openness Factor Levels at an Image Sampling Frequency of 20 GHz
[0065]Referring now to FIG. 6, there is shown a flow diagram a microsleep characteristic eye openness factor levels detection sub-process 300 that may be executed at block 206 of process 200 in order to detect the presence of the five microsleep characteristic eye openness factor levels, i.e. L1 to L5 (see FIG. 5) for an image sampling frequency of 20 Hz. The steps of the sub-process 300 are indicated by blocks 301 to 305.
[0066]At block 301, the sub-process 300 verifies if the first level L1 is detected. To that end, the sub-process 300 checks if a series of a minimum of six (6) successive eye openness factors having a value of .delta.=1.00 is present. If so, the sub-process 300 proceeds to block 302, if not, it goes back to block 202 of process 200 (see FIG. 2).
[0067]At block 302, the sub-process 300 verifies if the second level L2 is detected. To that end, the sub-process 300 checks if a series of a minimum of four (4) successive decreasing eye openness factors having values between of .delta.=0.99 and .delta.=0.01 is present. If so, the sub-process 300 proceeds to block 303, if not, it goes back to block 202 of process 200 (see FIG. 2).
[0068]Then, at block 303, the sub-process 300 verifies if the third level L3 is detected. To that end, the sub-process 300 checks if a series of a minimum of five (5) and a maximum of 120 successive eye openness factors having a value of .delta.=0.00 is present. If so, the sub-process 300 proceeds to block 304, if not, it goes back to block 202 of process 200 (see FIG. 2).
[0069]At block 304, the sub-process 300 verifies if the fourth level L4 is detected. To that end, the sub-process 300 checks if a series of a minimum of four (4) successive increasing eye openness factors having values between of .delta.=0.01 and .delta.=0.99 is present. If so, the sub-process 300 proceeds to block 305, if not, it goes back to block 202 of process 200 (see FIG. 2).
[0070]Finally, at block 305, the sub-process 300 verifies if the fifth level L5 is detected. To that end, the sub-process 300 checks if a series of a minimum of six (6) successive eye openness factors having a value of .delta.=1.00 is present. If so, the sub-process 300 proceeds to block 208 of process 200 (see FIG. 2), the presence of all five (5) microsleep characteristic eye openness factor levels. If not, the sub-process 300 goes back to block 202 of process 200 (see FIG. 2). It is to be understood that the number of eye openness factors used to detect the presence of each microsleep characteristic eye openness factor level may vary, for example according to the image sampling frequency and are meant as illustrative examples only.
[0071]It is to be understood that the memory associated with the microprocessor as described above, contains a plurality of reference eye closure patterns stored therein. The graphs as illustrated in FIG. 5 are compared to the reference eye closure patterns. Once a match is found, a microsleep event is verified and the alarm is activated
[0072]Although the present invention has been described by way of a particular embodiment and examples thereof, it should be noted that it will be apparent to persons skilled in the art that modifications may be applied to the present particular embodiment without departing from the scope of the present invention.
I think the Amigos may become chatter boxes......
probably examining patents...I am surprised he did not post the ECT patent....
Anyway good day here! up 29% .011.....
I will take a few pops here & there...not selling just would like to see some MOMO.....
How high do we go? I am going to read up on the Bruno's work on the patent this evening.......
Are you buying more? If you do, you can probably be the majority shareholder.....:)
1)Actually, I would like to look at that patent (biocognifsafe) here on the board as well & have a discussion on the merits..I know we had a discussion on the patent, which seemed to be a stripped down version earlie on this board.......I do think we have a good patent though...Can it be confirmed that it is a worldwide patent?
2)When we do have a shareholders meeting, I am going to ask the powers to be to have Rosebud & Doogie sit at the same table....that means Doogie needs to become a shareholder....:)
V in M?
.01 bid uptick.....
We could be on a GOLDMINE!
Is this a $100.00 stock? :)
The shareholders here paid Bruno's salary & the some of the amigo's as well, the past few years as the CRAM was being developed....
It makes sense to have it equitable for all parties......Both in taking care of BRUNO, and making sure the shareholders will be well awarded.....
You do know that most of the amigos have the same vested interest as me & other shareholders...they own shares in the company....
WIN WIN!
RELEASE THE BEAST!
That why we invest...RISK VS REWARD!
KABOOM big time with Bruno back, & finanacing in place!....I will take that risk!
I wonder what is going on in a snowy downtown Montreal courtroom.....
pre-market....@ ..009 25k
kinda...for now....
.0085 x .009...
worth it..risk vs reward...if you have some loose change to buy a few here......
There was a discussion on this yesterday, the court date was not yesterday....Word is that the injunction date is today........
WOW! Rosebud digging deep in the old posts......Hopefully, this is another step...a step forward.....Let's hope we all make some money here in 2010! (with some stocking stuffers for Christmas)....
It would appear that RH was being truthful concerning the patent pending....got to give him credit on that one.....
RELEASE THE AMIGOS!
I like that..a GAME CHANGER....I am looking forward to hearing Rosebud's comments on the patent:
The device, as described above further comprises an alert connected to the microprocessor for alerting the subject to the microsleep event.
Accordingly, in another aspect there is provided a method of alerting a vehicle operator to a microsleep event, the method comprising: Accordingly, in another aspect there is provided a method of alerting a vehicle operator to a microsleep event, the method comprising:
- determining a plurality of eye openness factors by measuring a plurality of distances between an upper eyelid and a lower eyelid of at least one eye over a time period; - generating graphical representations of the eye openness factors; - Determining a plurality of eye openness factors by measuring a plurality of distances between an upper eyelid and a lower eyelid of at least one eye over a time period; - generating graphical representations of the eye openness factors;
- correlating changes in the eye openness factors over the time period with a reference eye closure pattern indicative of the microsleep event; and - Correlating changes in the eye openness factors over the time period with a reference eye closure pattern indicative of the microsleep event; and
- triggering an alarm so as to alert the operator to the microsleep event. - Triggering an alarm so as to alert the operator to the microsleep event.
Accordingly, in yet another aspect, there is provided a method of correlating EEG and EOG microsleep patterns with eye closure patterns, the method comprising: Accordingly, in yet another aspect, there is provided a method of correlating EEG and EOG microsleep patterns with eye closure patterns, the method comprising:
- measuring EEG and EOG microsleep patterns in a subject; - Measuring EEG and EOG microsleep patterns in a subject;
- determining a plurality of eye openness factors by measuring a plurality of distances between an upper eyelid and a lower eyelid of at least one eye over a time period; - Determining a plurality of eye openness factors by measuring a plurality of distances between an upper eyelid and a lower eyelid of at least one eye over a time period;
- generating graphical representations of the eye openness factors; and - Generating graphical representations of the eye openness factors; and
- correlating changes in the eye openness factors with the EEG and EOG microsleep patterns. - Correlating changes in the eye openness factors with the EEG and EOG microsleep patterns.
BRIEF DESCRIPTION OF THE DRAWINGS BRIEF DESCRIPTION OF THE DRAWINGS
Embodiments of the invention will be described by way of example only with reference to the accompany drawings, in which: Embodiments of the invention will be described by way of example only with reference to the accompany drawings, in which:
Figure 1 is a block diagram of a microsleep detection device according to an illustrative embodiment of the present invention, the device being used on a subject; Figure 1 is a block diagram of a microsleep detection device according to an illustrative embodiment of the present invention, the device being used on a subject;
Figure 2 is a flow diagram of a microsleep event detection process that may be used by the device of Figure 1 ; Figure 2 is a flow diagram of a microsleep event detection process that may be used by the device of Figure 1;
Figure 3A and 3B are schematic views of the fully open eye (Figure 3A) and the fully closed eye (Figure 3B) with their associated eye openness factor; Figure 3A and 3B are schematic views of the fully open eye (Figure 3A) and the fully closed eye (Figure 3B) with their associated eye openness factor;
Figure 4 is a series of schematic views of an example of the variation of the eye openness factor as a function of time for a blink cycle; Figure 4 is a series of schematic views of an example of the variation of the eye openness factor as a function of time for a blink cycle;
Figure 5 is an illustrative example of the fully closed eye (period L4 and L5), at the moment of a microsleep; and Figure 5 is an illustrative example of the fully closed eye (period L4 and L5), at the moment of a microsleep; and
Figure 6 is a flow diagram of a microsleep characteristic eye openness factor levels detection sub-process that may be used with the microsleep event detection process of Figure 2 for an image sampling frequency of 20 Hz. Figure 6 is a flow diagram of a microsleep characteristic eye openness factor levels detection sub-process that may be used with the microsleep event detection process of Figure 2 for an image sampling frequency of 20 Hz.
DETAILED DESCRIPTION Generally stated, the non-limitative illustrative embodiment of the present invention provides a method and device for the detection of microsleep events in a human subject based on the analysis of eye closure patterns of at least one eye, typically both eyes, which occur during microsleep events. DETAILED DESCRIPTION Generally stated, the non-limitative illustrative embodiment of the present invention provides a method and device for the detection of microsleep events in a human subject based on the analysis of eye closure patterns of at least one eye, typically both eyes, which occur during microsleep events.
During microsleep events, measured by EEG and EOG, we observed a progressive variation of the distance between an upper eyelid and a lower eyelid of a human subject over time. We now describe hereinbelow a method and device, which provides complementary evidence of impending sleep in drowsy operators, such as vehicle drivers, airplane pilots, air traffic controllers and the like, using eye closure patterns, which when detected, alerts sleepy operators to unsafe situations before eyelid closure occurs, thereby correlating EEG and EOG microsleep patterns with eye closure patterns. During microsleep events, measured by EEG and EOG, we observed a progressive variation of the distance between an upper eyelid and a lower eyelid of a human subject over time. We now describe hereinbelow a method and device, which provides complementary evidence of impending sleep in drowsy operators, such as vehicle drivers, airplane pilots, air traffic controllers and the like, using eye closure patterns, which when detected, alerts sleepy operators to unsafe situations before eyelid closure occurs, thereby correlating EEG and EOG microsleep patterns with eye closure patterns.
Also described is a method for the analysis of eye closure patterns allowing the differentiation between a normal eyelid closure and one due to drowsiness. Also described is a method for the analysis of eye closure patterns allowing the differentiation between a normal eyelid closure and one due to drowsiness.
Referring to Figure 1 , there is shown an example of a microsleep event detection device 100, which generally comprises facial image sampler such as a digital camera 102 with an associated infrared source 104, a microprocessor 106 with an associated memory 108 and either or both an alarm/display 110 and input/output interface 112. Referring to Figure 1, there is shown an example of a microsleep event detection device 100, which generally comprises facial image sampler such as a digital camera 102 with an associated infrared source 104, a microprocessor 106 with an associated memory 108 and either or both an alarm / display 110 and input / output interface 112.
Thus, in one example, there is described a method using the device 100 for detecting a microsleep event in a human subject. The method comprises: determining a plurality of eye openness factors by measuring a plurality of distances between an upper eyelid and a lower eyelid of at least one eye, typically both eyes, over a time period; generating graphical representations of Thus, in one example, there is described a method using the device 100 for detecting a microsleep event in a human subject. The method comprises: determining a plurality of eye openness factors by measuring a plurality of distances between an upper eyelid and a lower eyelid of at least one eye, typically both eyes, over a time period; generating graphical representations of
the eye openness factors; and correlating changes in the eye openness factors over the time period with a reference eye closure pattern indicative of the microsleep event. the eye openness factors; and correlating changes in the eye openness factors over the time period with a reference eye closure pattern indicative of the microsleep event.
In operation, the digital camera 102 is aimed at the face of a subject 10 and illuminates his or her eyes 12 using the infrared source 104 in order to determine the eye openness factor, ie a value representative of the distance between the upper 14a and lower 14b eyelids. The images taken by the digital camera 102 are then processed by the processor 106 which executes a microsleep event detection process stored on its associated memory 108. Upon detection of a microsleep event, the microsleep event detection device 100 may inform the user of a microsleep event by triggering an integrated alarm and/or display 110 or provide the information to a further process or device via the input/output interface 112. It is to be understood that other components may be added to the microsleep event detection device 100 such as, for example, a user interface and a wireless communication device. In operation, the digital camera 102 is aimed at the face of a subject 10 and illuminates his or her eyes 12 using the infrared source 104 in order to determine the eye openness factor, ie a value representative of the distance between the upper 14a and lower 14b eyelids. The images taken by the digital camera 102 are then processed by the processor 106 which executes a microsleep event detection process stored on its associated memory 108. Upon detection of a microsleep event, the microsleep event detection device 100 may inform the user of a microsleep event by triggering an integrated alarm and / or display 110 or provide the information to a further process or device via the input / output interface 112. It is to be understood that other components may be added to the microsleep event detection device 100 such as, for example, a user interface and a wireless communication device.
Referring now to Figure 2, there is shown a flow diagram of a microsleep event detection process 200 that may be electronically executed by the processor 106 of the microsleep event detection device 100 of Figure 1. The steps of the process 200 are indicated by blocks 202 to 212. The process 200 starts at block 202 by sampling an image of the face of a subject 10 using the digital camera 102. The digital camera 102 may sample images at a frequency between about 10 and 60Hz (ie sampling frequency). At block 204, the process 200 identifies, in the sampled digital image, the eye 12 and eyelids 14a, 14b of the subject 10. This may be accomplished using a facial feature recognition algorithm executed by the processor 106. Then, the eye openness factor is computed. Referring now to Figure 2, there is shown a flow diagram of a microsleep event detection process 200 that may be electronically executed by the processor 106 of the microsleep event detection device 100 of Figure 1. The steps of the process 200 are indicated by blocks 202 to 212. The process 200 starts at block 202 by sampling an image of the face of a subject 10 using the digital camera 102. The digital camera 102 may sample images at a frequency between about 10 and 60Hz (ie sampling frequency). At block 204, the process 200 identifies, in the sampled digital image, the eye 12 and eyelids 14a, 14b of the subject 10. This may be accomplished using a facial feature recognition algorithm executed by the processor 106. Then, the eye openness factor is computed .
Referring now to Figures 3A and 3B, the eye openness factor may be expressed as d having a value between 1 , representing a fully open eye 12 (see Figure 3A), and 0, representing a fully closed eye 12 (see Figure 3B). The value of d may be computed, for example, by dividing the measured distance between the upper Referring now to Figures 3A and 3B, the eye openness factor may be expressed as d having a value between 1, representing a fully open eye 12 (see Figure 3A), and 0, representing a fully closed eye 12 (see Figure 3B). The value of d may be computed, for example, by dividing the measured distance between the upper
14a and lower 14b eyelids positions in a Cartesian representation (X 1 Y) by a reference measure of the fully open eye D. Thus: 14a and lower 14b eyelids positions in a Cartesian representation (X 1 Y) by a reference measure of the fully open eye D. Thus:
d =(upper lid position (x u ,y u ) - lower lid position (xi,y?))/D A d = (upper lid position (x u, y u) - lower lid position (xi, y?)) / D A
where D = upper lid position (xu,yu) - lower lid position (xL.yO and (x u ,y u ) = instant upper lid position, (x?,y?) = instant lower lid position, (xu,yu) = upper lid position at maximum eye opening and (xL.yO = lower lid position at maximum eye opening. where D = upper lid position (xu, yu) - lower lid position (xL.yO and (x u, y u) = instant upper lid position, (x?, y?) = instant lower lid position, (xu, yu) = upper lid position at maximum eye opening and (xL.yO = lower lid position at maximum eye opening.
Referring again to Figure 2 at block 206, the process verifies if the microsleep characteristic eye openness factor levels are present. Referring again to Figure 2 at block 206, the process verifies if the microsleep characteristic eye openness factor levels are present.
Referring to Figure 4, there is shown an illustrative example of the variation of the eye openness factor as a function of time for a blink cycle. The blink cycle starts at time ti with a fully open eye 12 (eye openness factor d = 1.00), at t 2 the eye openness factor remains at d = 1.00, then decreases, going through d = 0.80 and d = 0.50 at times t, and t,+i , until it reaches d = 0.00 at time t j (fully closed eye 12), and then increases, going through d = 0.50 and d = 0.80 at times t k and t k +i, until it reaches d = 1.00 again at t n It is to be understood that the blink cycle illustrated in Figure 4 for illustrative purpose only and that an actual cycle would comprise a number of sample times depending the sample frequency. Referring to Figure 4, there is shown an illustrative example of the variation of the eye openness factor as a function of time for a blink cycle. The blink cycle starts at time ti with a fully open eye 12 (eye openness factor d = 1.00) , at t 2 the eye openness factor remains at d = 1.00, then decreases, going through d = 0.80 and d = 0.50 at times t, and t, + i, until it reaches d = 0.00 at time t j (fully closed eye 12), and then increases, going through d = 0.50 and d = 0.80 at times t k and t k + i, until it reaches d = 1.00 again at t n It is to be understood that the blink cycle illustrated in Figure 4 for illustrative purpose only and that an actual cycle would comprise a number of sample times depending the sample frequency.
Referring now to Figure 5, these computed eye openness factors, as a function of time, can be represented in a graph which may be generally characterized by five successive levels, L1 to L5. The first and last levels, L1 and L5, are associated with the open eye (ie d = 1.00), the second level, L2, with the closure of the eyelids, 14a, 14b (ie 0.00 > d > 0.00, d decreasing), the third level L3, with the partial or closed eye (ie 0.00 < d < 0.5 for example) and fourth level, L4, with the opening of the eyelids 14a, 14b (ie 0.00 < d < 1.00, d increasing). Referring now to Figure 5, these computed eye openness factors, as a function of time, can be represented in a graph which may be generally characterized by five successive levels, L1 to L5. The first and last levels, L1 and L5, are associated with the open eye (ie d = 1.00), the second level, L2, with the closure of the eyelids, 14a, 14b (ie 0.00> d> 0.00, d decreasing), the third level L3, with the partial or closed eye (ie 0.00 <d <0.5 for example) and fourth level, L4, with the opening of the eyelids 14a, 14b (ie 0.00 <d <1.00, d increasing).
Referring again to Figure 2, the process 200 detects all five levels, ie L1 to L5, it then proceeds to block 208. If not, it proceeds back to block 202 for the next Referring again to Figure 2, the process 200 detects all five levels, ie L1 to L5, it then proceeds to block 208. If not, it proceeds back to block 202 for the next
image sample. At block 208, the process computes the eye closure 21 or 26 and eye opening 25 or 27 representative curves. The eye closure representative curve 21 or 26 is computed using negative slope second order polynomial regression (parabolic curve), ie image sample. At block 208, the process computes the eye closure 21 or 26 and eye opening 25 or 27 representative curves. The eye closure representative curve 21 or 26 is computed using negative slope second order polynomial regression (parabolic curve), ie
Y = d o + d 1 .X + d 2 .X 2 . Y = d o + d 1. X + d 2. X 2.
where Y is the predicted outcome value for the polynomial model with regression coefficients di to 2 for each degree and Y intercept d1 ; where Y is the predicted outcome value for the polynomial model with regression coefficients di to 2 for each degree and Y intercept d1;
which is applied to the eye openness factors composing the first and second eye openness factor levels, ie L1 and L2. As for the eye opening representative curve 25 or 27, it is computed using positive slope second order polynomial regression applied to the eye openness factors composing the fourth and fifth eye openness factor levels, ie L4 and L5. Then, at block 210, the process 220 verifies if the microsleep eye opening and closing representative curves are present. This is accomplished by computing the Pearson coefficient, r: which is applied to the eye openness factors composing the first and second eye openness factor levels, ie L1 and L2. As for the eye opening representative curve 25 or 27, it is computed using positive slope second order polynomial regression applied to the eye openness factors composing the fourth and fifth eye openness factor levels, ie L4 and L5. Then, at block 210, the process 220 verifies if the microsleep eye opening and closing representative curves are present. This is accomplished by computing the Pearson coefficient, r:
where X and Y are positions in a Cartesian representation; where X and Y are positions in a Cartesian representation;
of the eye closure representative curve 21 or 26 with regard to the eye openness factors composing eye openness factor levels L1 and L2, and of the eye opening representative curve 25 or 27 with regard to the eye openness factors composing the eye openness factor levels L4 and L5. If both Pearson coefficients are greater or equal to a given threshold such as, for example, 0.9, then the process 200 proceeds to block 212. If not, it proceeds back to block 202 for next image sample. Finally, at block 212, the microsleep event detection device 100 may inform the user 10 of the detection of a microsleep event state via the integrated alarm and/or display 110 or provide the information to a further process or device via the input/output interface 112 (see Figure 1) using, for instance, a wired or of the eye closure representative curve 21 or 26 with regard to the eye openness factors composing eye openness factor levels L1 and L2, and of the eye opening representative curve 25 or 27 with regard to the eye openness factors composing the eye openness factor levels L4 and L5. If both Pearson coefficients are greater or equal to a given threshold such as, for example, 0.9, then the process 200 proceeds to block 212. If not, it proceeds back to block 202 for next image sample. Finally, at block 212 , the microsleep event detection device 100 may inform the user 10 of the detection of a microsleep event state via the integrated alarm and / or display 110 or provide the information to a further process or device via the input / output interface 112 (see Figure 1 ) using, for instance, a wired or
wireless telecommunication link such as, for example, Bluetooth, WiFi and the like. wireless telecommunication link such as, for example, Bluetooth, WiFi and the like.
It is to be understood that the Pearson coefficient threshold is not meant to be restricted to 0.9 and may be adjusted to suit a desired confidence level. It may also vary depending on the resolution of the digital camera 102 (see Figure 1). It is to be understood that the Pearson coefficient threshold is not meant to be restricted to 0.9 and may be adjusted to suit a desired confidence level. It may also vary depending on the resolution of the digital camera 102 (see Figure 1).
The eye closure pattern is based on these particular observations closing, duration of the eyelid complete or partial closure and re-opening. More precisely, the eye closure pattern indicates a progressive decreasing followed by a baseline period where the eyelids are fully closed and then a reopening. If all the above occur, then a microsleep is detected. The eye closure pattern is based on these particular observations closing, duration of the eyelid complete or partial closure and re-opening. More precisely, the eye closure pattern indicates a progressive decreasing followed by a baseline period where the eyelids are fully closed and then a reopening. If all the above occur, then a microsleep is detected.
Example of microsleep characteristic eye openness factor levels at an image sampling frequency of 20GHz Example of microsleep characteristic eye openness factor levels at an image sampling frequency of 20GHz
Referring now to Figure 6, there is shown a flow diagram a microsleep characteristic eye openness factor levels detection sub-process 300 that may be executed at block 206 of process 200 in order to detect the presence of the five microsleep characteristic eye openness factor levels, ie L1 to L5 (see Figure 5) for an image sampling frequency of 20 Hz. The steps of the sub-process 300 are indicated by blocks 301 to 305. Referring now to Figure 6, there is shown a flow diagram a microsleep characteristic eye openness factor levels detection sub-process 300 that may be executed at block 206 of process 200 in order to detect the presence of the five microsleep characteristic eye openness factor levels, ie L1 to L5 (see Figure 5) for an image sampling frequency of 20 Hz. The steps of the sub-process 300 are indicated by blocks 301 to 305.
At block 301 , the sub-process 300 verifies if the first level L1 is detected. To that end, the sub-process 300 checks if a series of a minimum of six (6) successive eye openness factors having a value of d = 1.00 is present. If so, the sub-process 300 proceeds to block 302, if not, it goes back to block 202 of process 200 (see Figure 2). At block 301, the sub-process 300 verifies if the first level L1 is detected. To that end, the sub-process 300 checks if a series of a minimum of six (6) successive eye openness factors having a value of d = 1.00 is present. If so, the sub-process 300 proceeds to block 302, if not, it goes back to block 202 of process 200 (see Figure 2).
At block 302, the sub-process 300 verifies if the second level L2 is detected. To that end, the sub-process 300 checks if a series of a minimum of four (4) successive decreasing eye openness factors having values between of d = 0.99 At block 302, the sub-process 300 verifies if the second level L2 is detected. To that end, the sub-process 300 checks if a series of a minimum of four (4) successive decreasing eye openness factors having values between of d = 0.99
and d = 0.01 is present. If so, the sub-process 300 proceeds to block 303, if not, it goes back to block 202 of process 200 (see Figure 2). and d = 0.01 is present. If so, the sub-process 300 proceeds to block 303, if not, it goes back to block 202 of process 200 (see Figure 2).
Then, at block 303, the sub-process 300 verifies if the third level L3 is detected. To that end, the sub-process 300 checks if a series of a minimum of five (5) and a maximum of 120 successive eye openness factors having a value of d = 0.00 is present. If so, the sub-process 300 proceeds to block 304, if not, it goes back to block 202 of process 200 (see Figure 2). Then, at block 303, the sub-process 300 verifies if the third level L3 is detected. To that end, the sub-process 300 checks if a series of a minimum of five (5) and a maximum of 120 successive eye openness factors having a value of d = 0.00 is present. If so, the sub-process 300 proceeds to block 304, if not, it goes back to block 202 of process 200 (see Figure 2).
At block 304, the sub-process 300 verifies if the fourth level L4 is detected. To that end, the sub-process 300 checks if a series of a minimum of four (4) successive increasing eye openness factors having values between of d = 0.01 and d = 0.99 is present. If so, the sub-process 300 proceeds to block 305, if not, it goes back to block 202 of process 200 (see Figure 2). At block 304, the sub-process 300 verifies if the fourth level L4 is detected. To that end, the sub-process 300 checks if a series of a minimum of four (4) successive increasing eye openness factors having values between of d = 0.01 and d = 0.99 is present. If so, the sub-process 300 proceeds to block 305, if not, it goes back to block 202 of process 200 (see Figure 2).
Finally, at block 305, the sub-process 300 verifies if the fifth level L5 is detected. To that end, the sub-process 300 checks if a series of a minimum of six (6) successive eye openness factors having a value of d = 1.00 is present. If so, the sub-process 300 proceeds to block 208 of process 200 (see Figure 2), the presence of all five (5) microsleep characteristic eye openness factor levels. If not, the sub-process 300 goes back to block 202 of process 200 (see Figure 2). It is to be understood that the number of eye openness factors used to detect the presence of each microsleep characteristic eye openness factor level may vary, for example according to the image sampling frequency and are meant as illustrative examples only. Finally, at block 305, the sub-process 300 verifies if the fifth level L5 is detected. To that end, the sub-process 300 checks if a series of a minimum of six (6) successive eye openness factors having a value of d = 1.00 is present. If so, the sub-process 300 proceeds to block 208 of process 200 (see Figure 2), the presence of all five (5) microsleep characteristic eye openness factor levels. If not, the sub-process 300 goes back to block 202 of process 200 (see Figure 2). It is to be understood that the number of eye openness factors used to detect the presence of each microsleep characteristic eye openness factor level may vary, for example according to the image sampling frequency and are meant as illustrative examples only.
It is to be understood that the memory associated with the microprocessor as described above, contains a plurality of reference eye closure patterns stored therein. The graphs as illustrated in Figure 5 are compared to the reference eye closure patterns. Once a match is found, a microsleep event is verified and the alarm is activated It is to be understood that the memory associated with the microprocessor as described above, contains a plurality of reference eye closure patterns stored therein. The graphs as illustrated in Figure 5 are compared to the reference eye closure patterns. Once a match is found, a microsleep event is verified and the alarm is activated
Although the present invention has been described by way of a particular embodiment and examples thereof, it should be noted that it will be apparent to Although the present invention has been described by way of a particular embodiment and examples thereof, it should be noted that it will be apparent to
persons skilled in the art that modifications may be applied to the present particular embodiment without departing from the scope of the present invention. persons skilled in the art that modifications may be applied to the present particular embodiment without departing from the scope of the present invention
The method, as described above, further comprising: illuminating the face of the subject; and recording a facial image. A digital camera having an infra-red source is used to illuminate the face and to record the facial image.
The method, as described above, further comprising: identifying the eye and the eyelids by using a facial feature recognition algorithm. The method, as described above, further comprising: identifying the eye and the eyelids by using a facial feature recognition algorithm.
The method, as described above, further comprising: verifying the presence of microsleep characteristic eye openness factor levels by measuring the eye openness factors as a function of time for a blink cycle of the eye. The eye openness factors levels include at least one eye openness level. The eye openness factors include one or more eye openness levels and five or less eye openness levels. The eye openness factors include five eye openness levels. The eye openness levels are associated with an open eye, the closure of the eyelids, partial or closed eye, and opening of the eyelids. The method, as described above, further comprising: verifying the presence of microsleep characteristic eye openness factor levels by measuring the eye openness factors as a function of time for a blink cycle of the eye. The eye openness factors levels include at least one eye openness level. The eye openness factors include one or more eye openness levels and five or less eye openness levels. The eye openness factors include five eye openness levels. The eye openness levels are associated with an open eye, the closure of the eyelids, partial or closed eye, and opening of the eyelids.
The method, as described above, in which the eye openness factors include five successive eye openness levels, the sequential detection of the five levels being indicative of microsleep characteristics. The method further comprising: determining additional eye openness factors if less than five successive eye openness factor levels are detected. The method, as described above, in which the eye openness factors include five successive eye openness levels, the sequential detection of the five levels being indicative of microsleep characteristics. The method further comprising: determining additional eye openness factors if less than five successive eye openness factor levels are detected.
The method, as described above, further comprising: computing eye opening and eye closure representative curves. The eye closure representative curves are computed using a negative slope and a second order polynomial regression applied to the eye openness factors of the first and second eye openness factor The method, as described above, further comprising: computing eye opening and eye closure representative curves. The eye closure representative curves are computed using a negative slope and a second order polynomial regression applied to the eye openness factors of the first and second eye openness factor
levels. The eye opening factors are computed using a positive slope and a second order polynomial regression applied to the eye openness factors of the fourth and fifth eye openness factor levels. The method further comprising: verifying the presence of microsleep eye opening and closing representative curves by computing the Pearson coefficient of the eye closure representative curves with regard to the first and second eye openness factor levels and the eye opening representative curves with regard to the fourth and fifth eye factor levels. The subject is informed when the Pearson coefficients are greater than or equal to a predetermined threshold value. levels. The eye opening factors are computed using a positive slope and a second order polynomial regression applied to the eye openness factors of the fourth and fifth eye openness factor levels. The method further comprising: verifying the presence of microsleep eye opening and closing representative curves by computing the Pearson coefficient of the eye closure representative curves with regard to the first and second eye openness factor levels and the eye opening representative curves with regard to the fourth and fifth eye factor levels. The subject is informed when the Pearson coefficients are greater than or equal to a predetermined threshold value.
The method, as described above, in which images of the face are sampled at a frequency of between 10 Hz and 60Hz. The method, as described above, in which images of the face are sampled at a frequency of between 10 Hz and 60Hz.
Need a little explaining ROSEBUD....I guess this is why I show some excitement at times.....
There are various ways by which microsleep episodes can be identified. Some experts define microsleep according to behavioral criteria (eyelids closure), while others rely on electroencephalogram markers such as a 3-15 second episode (shorter durations would be difficult to visually detect and longer times would qualify as sleep onset.) during which 4-7 Hz (theta wave) activity replaced the waking 14-20 Hz (alpha wave) background rhythm.
Microsleep, subjectively related to the sensation of "nodding off', is associated with the interruption of the blinking artifacts characteristic of full wakefulness. During microsleep events, attention lapses can impair the ability to detect and respond to crucial stimuli and events. For example, microsleeps (or microsleep episodes) can become extremely dangerous when occurring during situations which require continual alertness, such as driving a motor vehicle or operating machinery. People who experience microsleeps usually remain unaware of them, instead believing themselves to have been awake the whole time, or feeling a sensation of 'spacing out'. The sleepy driver is at very high risk of having an accident during a microsleep episode. Many accidents have occurred because of microsleep episodes. Microsleep, subjectively related to the sensation of "nodding off ', is associated with the interruption of the blinking artifacts characteristic of full wakefulness. During microsleep events, attention lapses can impair the ability to detect and respond to crucial stimuli and events. For example, microsleeps (or microsleep episodes) can become extremely dangerous when occurring during situations which require continual alertness, such as driving a motor vehicle or operating machinery. People who experience microsleeps usually remain unaware of them, instead believing themselves to have been awake the whole time, or feeling a sensation of 'spacing out'. The sleepy driver is at very high risk of having an accident during a microsleep episode. Many accidents have occurred because of microsleep episodes.
Clearly, the ability to detect microsleep events would be useful as a means of alerting and warning drowsy drivers of such events. Clearly, the ability to detect microsleep events would be useful as a means of alerting and warning drowsy drivers of such events.
Several studies have used "quantitative" EEG methods to identify driver sleepiness. Theta power (EEG waves), and the frequency of theta bursts typically increase during prolonged driving, and are associated with poor driving performance. Disadvantageously, these techniques typically average EEG activity over several seconds (up to 1 minute), and therefore could not be used to detect brief microsleep events of between 3 seconds and 15 seconds. Several studies have used "quantitative" EEG methods to identify driver sleepiness. Theta power (EEG waves), and the frequency of theta bursts typically increase during prolonged driving, and are associated with poor driving performance. Disadvantageously, these techniques typically average EEG activity over several seconds (up to 1 minute), and therefore could not be used to detect brief microsleep events of between 3 seconds and 15 seconds.
A variety of physiological measures have been proposed to alert drivers to the onset of drowsiness. A variety of physiological measures have been proposed to alert drivers to the onset of drowsiness.
One of the most investigated is PERCLOS (or PERcent CLOSure), which measures drowsiness as the percent of time a driver's eyes are closed over a One of the most investigated is PERCLOS (or PERcent CLOSure), which measures drowsiness as the percent of time a driver's eyes are closed over a
time period. When a sufficient number of open/closed patterns are obtained, PERCLOS will trigger an alarm. PERCLOS works at percentages greater than 80%, which typically means that within 1 minute, the eyes of the individual must be closed for 48 seconds before an alarm is triggered. Clearly, this delay in unacceptable in tasks such as driving a vehicle because by the time PERCLOS activates the alarm, the driver will already have either fallen asleep, or be on the verge of falling asleep. Therefore, disadvantageously PERCLOS is too slow a system to allow preventive actions to be taken before an individual, such as a driver, experiences the first signs of sleepiness. time period. When a sufficient number of open / closed patterns are obtained, PERCLOS will trigger an alarm. PERCLOS works at percentages greater than 80%, which typically means that within 1 minute, the eyes of the individual must be closed for 48 seconds before an alarm is triggered. Clearly, this delay in unacceptable in tasks such as driving a vehicle because by the time PERCLOS activates the alarm, the driver will already have either fallen asleep, or be on the verge of falling asleep. Therefore, disadvantageously PERCLOS is too slow a system to allow preventive actions to be taken before an individual, such as a driver, experiences the first signs of sleepiness.
IBOX UPDATED!
PCT/CA2009/000732
LOL....I am sure Bruno will like that....more info...might see the buyers in the morning!
Designated Countries:
AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, BH, BR, BW, BY, BZ, CA, CH, CN, CO, CR, CU, CZ, DE, DK, DM, DO, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IS, JP, KE, KG, KM, KN, KP, KR, KZ, LA, LC, LK, LR, LS, LT, LU, LY, MA, MD, ME, MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, OM, PG, PH, PL, PT, RO, RS, RU, SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW.
African Regional Intellectual Property Org. (ARIPO) (BW, GH, GM, KE, LS, MW, MZ, NA, SD, SL, SZ, TZ, UG, ZM, ZW) African Regional Intellectual Property Org. (ARIPO) (BW, GH, GM, KE, LS, MW, MZ, NA, SD, SL, SZ, TZ, UG, ZM, ZW)
Eurasian Patent Organization (EAPO) (AM, AZ, BY, KG, KZ, MD, RU, TJ, TM) Eurasian Patent Organization (EAPO) (AM, AZ, BY, KG, KZ, MD, RU, TJ, TM)
European Patent Office (EPO) (AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, IE, IS, IT, LT, LU, LV, MC, MK, MT, NL, NO, PL, PT, RO, SE, SI, SK, TR) European Patent Office (EPO) (AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, IE, IS, IT, LT, LU, LV , MC, MK, MT, NL, NO, PL, PT, RO, SE, SI, SK, TR)
African Intellectual Property Organization (OAPI) (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, ML, MR, NE, SN, TD, TG). African Intellectual Property Organization (OAPI) (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, ML, MR, NE, SN, TD, TG).
CLAIMS
1. A method of detecting a microsleep event in a subject, the method comprising: - determining a plurality of eye openness factors by measuring a plurality of distances between an upper eyelid and a lower eyelid of at least one eye over a time period;
- generating graphical representations of the eye openness factors; and
- correlating changes in the eye openness factors over the time period with a reference eye closure pattern indicative of the microsleep event.
2. The method, according to claim 1 , further comprising: illuminating the face of the subject; and recording a facial image.
3. The method, according to claim 2, in which a digital camera having an infra-red source is used to illuminate the face and to record the facial image.
4. The method, according to claim 1 , further comprising: identifying the eye and the eyelids by using a facial feature recognition algorithm.
5. The method, according to claim 1 , further comprising: verifying the presence of microsleep characteristic eye openness factor levels by measuring the eye openness factors as a function of time for a blink cycle of the eye.
6. The method, according to claim 5, in which the eye openness factors levels include at least one eye openness level.
7. The method, according to claim 5, in which the eye openness factors include one or more eye openness levels and five or less eye openness levels.
8. The method, according to claim 5, in which the eye openness factors include five eye openness levels.
9. The method, according to claim 5, in which the eye openness levels are associated with an open eye, the closure of the eyelids, partial or closed eye, and opening of the eyelids
10. The method, according to claim 1 , in which the eye openness factors include five successive eye openness levels, the sequential detection of the five levels being indicative of microsleep characteristics.
11. The method, according to claim 10, further comprising: determining additional eye openness factors if less than five successive eye openness factor levels are detected.
12. The method, according to claim 5, further comprising: computing eye opening and eye closure representative curves.
13. The method, according to claim 12, in which the eye closure representative curves are computed using a negative slope and a second order polynomial regression applied to the eye openness factors of the first and second eye openness factor levels.
14. The method, according to claim 12, in which the eye opening factors are computed using a positive slope and a second order polynomial regression applied to the eye openness factors of the fourth and fifth eye openness factor levels.
15. The method, according to claim 12, further comprising: verifying the presence of microsleep eye opening and closing representative curves by computing the Pearson coefficient of the eye closure representative curves with
regard to the first and second eye openness factor levels and the eye opening representative curves with regard to the fourth and fifth eye factor levels.
16. The method, according to claim 15, in which the subject is informed when the Pearson coefficients are greater than or equal to a predetermined threshold value.
17. The method, according to claim 3, in which images of the face are sampled at a frequency of between 10 Hz and 60Hz.
18. The method, according to claim 5, further comprising: a sub-process for detecting microsleep characteristic eye openness factor levels at an image sampling frequency of 20Hz.
19. The method, according to claim 18, in which the sub-process comprises: verifying that a first level is detected by confirming the presence of a series six or more successive eye openness factors corresponding to an open eye.
20. The method, according to claim 19, further comprising: verifying that a second level is detected by confirming the presence of a series four or more successive decreasing eye openness factors.
21. The method, according to claim 20, further comprising: verifying that a third level is detected by confirming the presence of a series of a minimum of five and a maximum of one-hundred and twenty successive eye openness factors.
22. The method, according to claim 21 , further comprising: verifying that a fourth level is detected by confirming the presence of a series of a minimum of four successive eye openness factors.
23. The method, according to claim 22, further comprising: verifying that a fifth level is detected by confirming the presence of a series of a minimum of six successive eye openness factors corresponding to the open eye.
24. The method, according to claim 1 , further comprising: alerting the subject to the presence of the microsleep event.
25. A microsleep event detection device, the device comprising:
- a facial image sampler for sampling facial images over time of a subject, the sampler having an infra red source for illuminating one or more eyes of the subject;
- a microprocessor having electronically stored therein an electronically executable microsleep detection process, the microprocessor being connected to the sampler for receiving the sampled facial images, the images being electronically converted to graphical representations of eye openness factors; and
- a memory associated with the microprocessor, the memory having stored therein a plurality of reference eye closure patterns for electronically correlating the eye openness factors with the reference eye closure patterns.
26. The device, according to claim 25, further comprising an alert connected to the microprocessor for alerting the subject to the microsleep event.
27. A method of alerting a vehjcle operator to a microsleep event, the method comprising:
- determining a plurality of eye openness factors by measuring a plurality of distances between an upper eyelid and a lower eyelid of at least one eye over a time period;
- generating graphical representations of the eye openness factors; - correlating changes in the eye openness factors over the time period with a reference eye closure pattern indicative of the microsleep event; and
- triggering an alarm so as to alert the operator to the microsleep event.
28. A method of correlating EEG and EOG microsleep patterns with eye closure patterns, the method comprising:
- measuring EEG and EOG microsleep patterns in a subject;
- determining a plurality of eye openness factors by measuring a plurality of distances between an upper eyelid and a lower eyelid of at least one eye over a time period;
- generating graphical representations of the eye openness factors; and
- correlating changes in the eye openness factors with the EEG and EOG microsleep patterns.
METHOD AND DEVICE FOR THE DETECTION OF MICROSLEEP EVENTS
Disclosed herein is a method of detecting a microsleep event in a subject. The method includes determining a number of eye openness factors by measuring a number of distances between an upper eyelid and a lower eyelid of at least one eye over a time period. Graphical representations of the eye openness factors are then generated. Changes in the eye openness factors over the time period are correlated with a reference eye closure pattern indicative of the microsleep event. Also disclosed is a microsleep event detection device.
AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, BH, BR, BW, BY, BZ, CA, CH, CN, CO, CR, CU, CZ, DE, DK, DM, DO, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IS, JP, KE, KG, KM, KN, KP, KR, KZ, LA, LC, LK, LR, LS, LT, LU, LY, MA, MD, ME, MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, OM, PG, PH, PL, PT, RO, RS, RU, SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW.
African Regional Intellectual Property Org. (ARIPO) (BW, GH, GM, KE, LS, MW, MZ, NA, SD, SL, SZ, TZ, UG, ZM, ZW)
Eurasian Patent Organization (EAPO) (AM, AZ, BY, KG, KZ, MD, RU, TJ, TM)
European Patent Office (EPO) (AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, IE, IS, IT, LT, LU, LV, MC, MK, MT, NL, NO, PL, PT, RO, SE, SI, SK, TR)
African Intellectual Property Organization (OAPI) (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, ML, MR, NE, SN, TD, TG).