Brain Computer Interaction of Indian Facial Expressions Recognition Through Digital Electroencephalography
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(IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 2, February 2011 Brain Computer Interaction Of Indian Facial Expressions Recognition Through Digital Electroencephalography Mr.Dinesh Chandra Jain Dr. V.P Pawar Univ. of RGPV, Dept. Of Computer-Sc & Engineering Univ. of Pune, Dept. of Computer App. Shri Vaishnav Inst. of Technology Director of Siddhant Inst. of Comp-App Indore, India Pune, India firstname.lastname@example.org email@example.com Abstract— The brain computer interaction could be the interface so expression may consider as a vector in the seven medium of the future, instead of using peripheral input output devices dimensional field. In anatomical FACS , the subject have .So The brain computer interaction is a path way in which through been made to express expressions which will have anatomical digital EEG technique the brain signals of human subject have been aspects of the face. The facial expression are controlled by the recorded under different poses by using Digital brain so it is useful to correlate the expression with the Electroencephalograph (EEG) 2400NP instrument. Under experimental setup The subjects have given different expressions brain. Today’s there are so many techniques available for corresponding brain signals that have been recorded through a direct contact with neural as Electroencephalography(EEG), popular technique Digital EEG. An attempt has been done to Magneto encephalography (MEG) and FMRI. correlate these results to the facial action coding System (FACS). II. BCI THROUGH EEG In brain computer interaction electroencephalography Keywords- Bci, Eeg, Expression, Facial coding System. technique is an approximation of the cumulative All standard paper components have been specified for electrical activity of neurons and is a measure of the three reasons: (1) ease of use when formatting individual brain's voltage fluctuations as detected from scalp papers, (2) automatic compliance to electronic requirements electrodes. This technology is to augment human that facilitate the concurrent or later production of electronic capabilities by enabling human subject to interact with a products, and (3) conformity of style throughout a conference computer through a conscious and spontaneous proceedings. Margins, column widths, line spacing, and type modulation of their brain waves after a short training styles are built-in; examples of the type styles are provided period. A brain computer interaction has been developed throughout this document and are identified in italic type, cerebral electric activity is recorded via the within parentheses, following the example. Some components, Electroencephalography: electrodes , attached on the scalp such as multi-leveled equations, graphics, and tables are not and measure the electric signal of the brain . The prescribed, although the various table text styles are provided. signals are amplified and transmitted to the computer The formatter will need to create these components, which transform them into device control command. The incorporating the applicable criteria that follow. crucial requirement for the successful functioning of the brain computer interaction is that the electric activity in I. INTRODUCTION the scalp surface. The most important challenging application of brain computer interaction is to enables direct interaction between human and computer by directly receiving and transmitting signals to and from the brain of human subject. In the Computer system the Recognition of Facial expression of human subject is a great challenging task. During expression recognition of human face there are so many complex issue arises like: neuromedical ,anatomical and psychological. This is dependent on the social behavior of human.. Basically, one human being may have different expression under different -2 conditions. The human subject may have seven type of universal facial expressions like: happiness, sadness, fear, anger, surprise, disgust, and neutral Fig1. Brain computer Interaction Identify applicable sponsor/s here. (sponsors) 212 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 2, February 2011 EEG frequency band There are Five rhythms as: 1) Gamma ϒ: 30-50 Hz 2) Beta β: 13-30 Hz 3) Alpha α: 8- 13 Hz 4) Theta θ: 4-8 Hz 5) Delta δ: 0.5-4 Hz. EEG Characteristics • It measures directly brain function. • It has a high temporal resolution, in the range of milliseconds. • The spatial resolution is in the range of centimeters for scalp electrodes, while implanted electrodes can measure Fig 4:The international 10-20 system the activity of single neurons. • Scalp electrodes are non-invasive while implanted The test was conducted for ten minutes and each participant electrodes are invasive. was asked to give the different expressions while imaging the • The required equipment is portable. particular situations portraying different emotions simultaneously. The lower filter of the Neuro portable EEG Experimental method and procedure was set at 1Hz, High filter at 70Hz; sensitivity at 7μV, channels 20, sweep speed 30mm/sec, Montage set 1 for all During eeg test the subject should be prepared to give experiment. The resultant facial expressions of the different type of facial expressions. To conduct test , the participants were also captured photographically with the help scalp must be free from oil now tie The electrode cap over of a digital camera. At the same time, the signals of the head with the use of electrode cream and finally check all the different regions of the brain were mapped. The different electrodes are connected with subject head, now said to position of connection for signal monitoring is shown in fig subject to give six universal face expression and on 4. An example of mapped signal is shown in fig 5. The behalf of expression see the signal fluctuation and record it experiment was conducted in the sound proof environment. with the four different regions of the brain. Fig2: Electrode connected on head. Fig 3 . Four region of brain Fig5 : signal of different -different brain area. In our experimental setup we have to selected fifteen male persons in the age group of 6 to 30 year with non-psychiatric history have been selected for our experiment. The electrode cap was placed on the different regions of each person EEG was recorded at sites of brain region for all frontal lobe and parietal lobe are put together FP2-F4(R), FP1-F3 (L) and Occipital lobe (C4-P4(R), C3-P3 (L)/Temporal lobe are kept separate. FP1, FP2, F3, F4, F7, F8, FTC1, FTC2, C3, C4, T3, T4, TCP1, TCP2, T5, T6, P3, P4, PZ, O1, O2,A1,A2. The fig 4 contains details of connection for left and right portion of the brain in 10-20 international system. Fig 6: Eeg signal window during test 213 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 2, February 2011 The signals corresponding to different expressions were The description of the apparatus used as Electrode cable, GND recorded and stored in the computer .The four regions of plug wire, Phonetic wire, EEG conducting paste, Absorbent the brain with left, right, front and back positions are identified cotton wool I.P., Sony digital camera HD 5X. corresponding to these positions, the average frequency and the average peak voltage are determined through commercial III. Result and Conclusion software available with the system The signals were recorded three times for each expression corresponding to all different The goal of the present research work is to represent the seven subjects. The average values are mentioned in the Table experimental work towards bci direction. In our experimental 1.The EEG 24/NP channel unit used was from Digital setup, A portable Electroencephalograph system has been used Neurocompact Medicaid System. for brain. It has been found that in the human subject there are twenty six muscles are responsible for the overall movement of the face. The photographic expressions for each experiment are shown in fig (7). Happy Sad Angry Fear Disgust Surprise Fig 7. Six Facial Expression All Four Brain Positions Regions Position 1 Position 2 Result FL FL PL OL TL +PL+OL+TL Left Right Left Right Left & Right Avg. Avg. of of Expressions F PV F PV F PV F PV F PV 1.Neutral 24.5 38.6 22.5 34.0 21.5 34.5 20.5 37 23.0 35.15 2.Happy 24 44.5 21.9 42.1 24.5 36.2 23.1 32.9 23.37 42.75 3.Sad 22.5 34.3 26.3 39.6 20.2 33.0 22.1 36.8 25.35 35.92 4.Anger 19.6 35 26.1 35.6 23.4 31.1 20.4 33.4 22.37 33.77 5.Fear 19.7 36.8 18.9 34.9 16.6 27.0 16.9 36.1 19.11 35.37 6.Disgust 19.5 40.2 20.1 35.2 18.5 30.2 19.6 38.2 19.42 35.95 7.Surprise 13.1 32.4 17.9 34.7 13.9 32.8 13.8 34.7 14.67 33.65 Table 1. Results for different facial expression 214 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 2, February 2011 References . Desney S. Tan, Anton Nijholt(Eds.)” Brain computer . Clinical application of an EEG-based brain-computer interaction applying our minds to HCI”,springer interface: a case study . 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Davidson and Tomarken , A.J.1993, Frontal brain asymmetry and emotional reactivity: Author Profile biology substrate of affective style, psychophysiology ,82-89. . P.Ekman,”Recognition of six basic facial expression and their strength by neural “International workshop in IEEE 1992. Mr. Dinesh Chandra Jain has completed B.E . Cohn, J.A., Allen J.J.B and Harmon- Jones, 2001, (Comp-Sc) in 2004 and M.Tech (IT) degree in 2007. He is presently working as Voluntary facial Expression and hemispheric asymmetry Assistant Professor in the Department of Comp. over the frontal cortex, Psychoysiology, 38, 912-925 . Science & Engg. at SVITS, Indore. and He is  .Terzo poulous, D. & Waters, K. (1993). Analysis and pursuing PhD in the field of Digital Image synthesis of facial image sequences using physical and Processing & Neural Network Anatomical models. IEEE Trans.Pattern analysisNetwork. Neural and machine intelligence 15, 6: 569-579.  Blundell, G. G. The meaning of EEG. London: Audio Ltd. Dr.Vrushsen Pawar received MS, . Frances M.Dyro,”The EEG Handbook” clinical Ph.D.(Computer) Degree from Dept .CS neurophysiology,LaboratoryMassachusetts, London,1989. & IT, Dr.B.A.M. University & PDF from transactions on neural system. ES, University of Cambridge, UK. Also .Ying-li Tian,Takeo Kanade J.F. Cohn “Recognizing Received MCA (SMU), MBA (VMU) Action Unit for facial expression analysis”, IEEE degrees respectively. He has received prestigious fellowship from DST, UGRF (UGC), Sakaal transactions on Pattern analysis & machine intelligence, Feb(vol-23,no.2) pp. 97-115,2001 London, ABC (USA) etc. He has published 90 and more foundation, ES .Delorme and S.Makieig,”EEg changes accompanying research papers in reputed national international Journals & learned regulation of 12-43 EEG – activity “ IEEE conferences. He has recognize Ph.D Guide from University of . The "10-20 System" of Electrode Placement University & Sighaniya University (India). He is senior IEEE une, SRTM member and other reputed society member. Currently working http://faculty.washington.edu/chudler/1020.html as a Professor & Director in SICA institute is affiliated to University of P pune. . Gupta, S.; Singh, H. Preprocessing EEG signals for direct human-system interface. Intelligence and Systems, 1996., IEEE International Joint Symposia on , 1996 Page(s): 32 –37. . T.M. Vaughan, J.R. Wolpaw, and E. Donchin, "EEG- Based Communication: Prospects and Problems", IEEE Trans. on Rehabilitation Engineering,4:4,pp. 425—430,1996. 215 http://sites.google.com/site/ijcsis/ ISSN 1947-5500