EEG ELECTRODE LOCALIZATION FOR READING-WRITING NEUROPATHWAY: SPECTRAL ANALYSIS APPROACH
DOI:
https://doi.org/10.11113/jt.v78.9088Keywords:
Electroencephalogram (EEG), writing, spectral analysisAbstract
Writing is a survival skill in schools and many children are reported to have suffered from writing disorder. Emerging technology enables this disorder detectable through monitoring of EEG signals. However, in working with EEG, the lack of methodological approach would lead to gargantuan of data and thus wastage in resources and time. Furthermore, placing of a large number of electrodes on the recording cap will cause discomfort to the subject, with data being more liable to false readings and artifacts. Recognizing the number of electrodes through proper localization plays a fundamental role in improving the overall performance of an EEG acquisition system, thus the objective of this research. This study involves the following phases: Data Collection, Data Acquisition and Data Analysis. Target population are normal and healthy subjects of age between 18 and 25. The EEG signals are recorded with electrodes at activation areas along the documented signal pathway of the brain (C3, C4, P3, P4, O1, O2, T7, FC5) during reading and writing. Fast Fourier Transform (FFT) is applied to transform the EEG in time domain into frequency domain so that signature features in frequency content during relaxation and sentence writing can be extracted. Results showed that relaxation drew on one dominant peak and the frequency content resides in the alpha sub-band while writing activity drew on two dominant peaks, one in alpha and the other in beta sub-band. The frequency range of EEG recorded during relaxation is 8-13 Hz while that during writing is 13-29 Hz, well within the alpha and beta sub-band for the different neuro-activity accordingly. Hence, it can be concluded from experimental results and findings from previous works that electrodes C3/C4, P3/P4, O1/O2, T7 and FC5 are suitable as optimal localized EEG electrode placement for neuro-pathway for reading-writing.
References
Coppin, P. and Hockema, S. A. 2009. Learning from the Information Workspace of an Information Professional with Dyslexia and ADHD. IEEE Toronto International Conference Science and Technology for Humanity (TIC-STH). 801-807.
Gomez, C. 2004. Dyslexia in Malaysia. International Book of Dyslexia: A Guide to Practice and Resources. L. John Wiley & Sons, Ed.
Department of Education for Special Needs. 2013. Ministry of Education, Malaysia.
Idris, T. H. M. 2012. Statistik Bilangan Sekolah, Murid dan Guru di Malaysia. Majlis Guru Besar Daerah Muar. [Online]. Available: http://mgbmuar.blogspot.com/2012/12/bilangan-sekolah-murid-dan-guru.html.
Breteler, M. H. M. Arns, M. Peters, S. Giepmans, I. and Verhoeven, L. 2010. Improvements in Spelling after QEEG-based Neurofeedback in Dyslexia: A Randomized Controlled Treatment Study. Appl. Psychophysiol. Biofeedback. 35(1): 5-11.
Dobrea, M.-C. Dobrea, D. M. and Alexa, D. 2010. Spectral EEG Features and Tasks Selection Process: Some Considerations Toward BCI Applications. IEEE International Workshop on Multimedia Signal Processing. 150-155.
Galin, D. Raz, J. Fein, G. Johnstone, J. Herron, J. and Yingling, C. 1992. EEG Spectra in Dyslexic and Normal Readers During Oral And Silent Reading. Electroencephalogr. Clin. Neurophysiol. 82(2): 87-101.
Cososchi, S. Strungaru, R. Ungureanu, A. and Ungureanu, M. 2006. EEG Features Extraction for Motor Imagery. 28th IEEE EMBS Annual International Conference. 1142-1145.
Glass, A. and Riding, R. J. EEG Differences and Cognitive Style. Biol. Psychol. 51(1): 23-41.
Cincotti, F. Pichiorri, F. Aricò, P. Aloise, F. Leotta, F. Vico Fallani, F. Millán, J. D. R. Molinari, M. and Mattia, D. 2012. EEG-based Brain-Computer Interface to Support Post-Stroke Motor Rehabilitation of the Upper Limb. 34th Annual International Conference of the IEEE EMBS. 4112-4115.
Santos, T. O. Caetano, R. Moniz, J. Rosa, A. C. Ist, L. I. S. R. and Pais, A. V. R. 1999. Classification of Movement Cognitive Potentials from EEG. Proceedings of the First Joint BMES/EMBS Conference. 449-450.
Xiaoxia, L. Guizhi, X. Xiukui, S. Yang, S. and Yufang, W. 2008. Development of Acupuncture-Reading with EEG, MRI and PET. 5th International Conference on Information Technology and Application in Biomedicine. 592-595.
Fadzal, C. W. N. F. C. W. Mansor, W. and Khuan, L. Y. 2011. Review of Brain Computer Interface application in Diagnosing Dyslexia. IEEE Control and System Graduate Research Colloquium Review. 124-128.
Lauer, R. T. Peckham, P. H. and Kilgore, K. L. 1999. EEG-based Control of a Hand Grasp Neuroprosthesis. Neuroreport. 10(8): 1767-1771.
Karim, I. Abdul, W. and Kamaruddin, N. 2013. Classification of Dyslexic and Normal Children During Resting Condition using KDE and MLP. 5th International Conference on Information and Communication Technology for the Muslim World (ICT4M). 1-5.
Seitz, R. J. and Dusseldorf. 2009. Brain Representations Of Writing. GFL-Journal. 2(3): 65-82.
Hashim, S. Safri, N. M. Khalid, P. I. Othman, M. A. and Yunus, J. 2014. Differences in Cortico-Cortical Functional Connections between Children with Good and Poor Handwriting : A Case Study. IEEE Region 10 Symposium. 34-38.
Menon, V. and Desmond, J. E. 2001. Left Superior Parietal Cortex Involvement in Writing: Integrating fMRI with Lesion Evidence. Cogn. Brain Res. 12(2): 337-340.
Fadzal, C. W. N. F. C. W. Mansor, W. Khuan, L. Y. Mohamad, N. B. Mahmoodin, Z. Mohamad, S. and Amirin, S. 2014. Welch Power Spectral Density of EEG Signal Generated from Dyslexic Children. IEEE Region 10 Symposium. 560-562.
Flynn, J. M. Deering, W. M. Goldstein, M. and Rahbar, M. H. 1992. Electrophysiological Correlates of Dyslexic Subtypes. J. Learn. Disabil. 25: 133-141.
Sklar, B. Hanley, J. and Simmons, W. W. 1973. A Computer Analysis of EEG Spectral Signatures from Normal and Dyslexic Children. IEEE Transactions on Biomedical Engineering. 49(1): 20-26.
Florea, B.-F. and Grigore, O. 2011. Reading Detection Based On EEG Signal Analysis. 7th International Symposium on Advanced Topics in Electrical Engineering. 1-6.
Rippon, G. and Brunswick, N. 2000. Trait and State EEG Indices of Information Processing in Developmental Dyslexia. Int. J. Psychophysiology. 36: 251-265.
Bogdanowicz, K. M. Lockiewicz, M. Bogdanowicz, M. and PÄ…chalska, M. 2013. Characteristics of Cognitive Deficits and Writing Skills of Polish Adults with Developmental Dyslexia. Int. J. Psychophysiol. 93(1): 78-83.
Behnam, H. Sheikhani, A. Mohammadi, M. R. Noroozian, M. and Pari, G. 2007. Analysis of EEG Background Activity in Autism Disorders with Fast Fourier Transform and Short Time Fourier Measure. International Conference on Intelligent and Advanced Systems (ICIAS 2007). 1240-1244.
Bhople, A. D. and Tijare, P. A. 2012. Fast Fourier Transform Based Classification of Epileptic Seizure Using Artificial Neural Network. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 2(4): 228-231.
Lenartowicz, A. Walshaw, P. D. Bookheimer, S. McCracken, J. and Loo, S. K. 2010. ICA and fusion of EEG & fMRI Functional Connectivity Of Attention Control in Children with ADHD. 2nd New Horizons in Human Brain Imaging Meeting. 1-2.
Allahverdy, A. Nasrabadi, A. M. and Mohammadi, M. R. 2011. Detecting ADHD Children Using Symbolic Dynamic of Nonlinear Features of EEG. 19th Iranian Conference on Electrical Engineering (ICEE). 1-4.
Wang, D. Kochiyama, T. Wu, and J. I. 2005. Measurement and Analysis of electroencephalogram (EEG) using Directional Visual Stimuli for Brain Computer Interface. Proceedings of the 2005 International Conference on Active Media Technology (AMT 2005). 34-39.
Horovitz, S. G. Gallea, C.’Ali Najee-Ullah, M. and Hallett, M. 2013. Functional Anatomy of Writing with the Dominant Hand. PLoS One. 8(7): 1-10.
Lakany, H. and Conway, B. A. 2005. Comparing EEG Patterns of Actual and Imaginary Wrist Movements-A Machine Learning Approach. 1st ICGST International Conference on Artificial Intelligence and Machine Learning AIML 05. 124-127.
Lakany, H. and Conway, B. A. 2005. Classification of Wrist Movements using EEG-based Wavelets Features. IEEE Engineering in Medicine and Biology 27th Annual Conference. 5404-5407.
Ismail, K. A. Mansor, W. Khuan, L. Y. and Fadzal, C. W. N. F. C. W. 2012. Spectral Analysis of EEG Signals Generated from Imagined Writing. IEEE 8th International Colloquium on Signal Processing and its Applications. 510-513.
Hamadicharef, B. Zhang, H. Guan, C. Phua, K. S. Tee, K. P. and Ang, K. K. 2009. Learning EEG-Based Spectral-Spatial Patterns for Attention Level Measurement. IEEE International Symposium on Circuits and Systems. 1465-1468.
Walker, J. E. and Norman, C. A. 2004. Normal Adult Readers Recruit Increasing Beta Power at T3 as Reading Difficulty Increases. 12th Annual Scientific Conference of the International Society for Neuronal Regulation. 1-4.
Tian, Y. J. Tai, Y. H. Kuo, T. H. and Sun, K. T. 2013. Reactions of Brain in English Reading Tests. 2013 Fourth Global Congress on Intelligent Systems. 309-313.
Kunze, K. Shiga, Y. Ishimaru, S. and Kise, K. 2013. Reading Activity Recognition using an Off-the-Shelf EEG- Detecting Reading Activities and Distinguishing Genres of Documents. 12th International Conference on Document Analysis and Recognition. 96-100.
Klimesch, W. Doppelmayr, M. Wimmer, H. Gruber, W. Ro¨hm, D. and Schwaiger, J. 2001. Alpha and Beta Band Power Changes in Normal and Dyslexic Children. Clin. Neurophysiol. 112: 1186-1195.
Chesnutt, C. 2012. Feature Generation of EEG Data using Wavelet Analysis. Master Thesis, Austin, Texas: Department of Electrical Engineering, Texas Tech. University.
Fourier, J. 1878. The Analytical Theory of Heat. 1st ed. Cambridge at the University Press.
Duhamel, P. and Vetterli, M. 1990. Fast Fourier Transforms: A Tutorial Review and a State of the Art. Signal Processing. 19(4): 259-299.
Saidi, A. 1994. Decimation-In-Time-Frequency FFT Algorithm. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP-94). 453-456.
Tower, F. 2012. 10 / 20 System Positioning. Manual, Wanchai, Hong Kong: Trans Cranial Technologies ldt.
Truchard, J. 2013. Biomedical Engineering Education Portal. Manual, National Instruments.
Pfurtscheller, G. Stancák, A. and Neuper, C. 1996. Event-Related Synchronization (ERS) in the Alpha Band - An Electrophysiological Correlate of Cortical Idling: A Review. Int. J. Psychophysiol. 24(1-2): 39-46.
Pfurtscheller, G. 1992. Event-Related Synchronization (ERS): an Electrophysiological Correlate of Cortical Areas at Rest. Electroencephalogr. Clin. Neurophysiol. 83(1): 62-69.
Damoiseaux, J. S. Rombouts, S. A. R. B. Barkhof, F. Scheltens, P. Stam, C. J. Smith, S. M. and Beckmann, C. F. 2006. Consistent Resting-State Networks. Proc. Natl. Acad. Sci. United States Am. 103(37): 13848-13853.
Beckmann, C. F. DeLuca, M. Devlin, J. T. and Smith, S. M. 2005. Investigations into Resting-State Connectivity using Independent Component Analysis. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 360(1457): 1001-1013.
Schurz, M. Wimmer, H. Richlan, F. Ludersdorfer, P. Klackl, J. and Kronbichler, M. 2014. Resting-State and Task-Based Functional Brain Connectivity in Developmental Dyslexia. Cereb. Cortex. 1-13.
Fadzal, C. W. N. F. C. W. Mansor, W., and Khuan, L. Y. 2011. An Analysis of EEG Signal Generated From Grasping and Writing. International Conference on Computer Applications and Industrial Electronics (ICCAIE 2011). 535-537.
Pfurtscheller, G. Stancák Jr., A. and Edlinger, G. 1997. On the Existence of Different Types of Central Beta Rhythms Below 30 Hz. Electroencephalogr. Clin. Neurophysiol. 102(4): 316-325.
Spironelli, C. Penolazzi, B. and Angrilli, A. 2008. Dysfunctional Hemispheric Asymmetry Of Theta And Beta EEG Activity During Linguistic Tasks In Developmental Dyslexia. Biol. Psychol. 77(2): 123-31.
Fadzal, C. W. N. F. C. W. Mansor, W. and Khuan, L. Y. 2012. Analysis of EEG Signal from Right and Left Hand Writing Movements. IEEE Control and System Graduate Research Colloquium (ICSGRC 2012). 354-358.
Klimesch, W. Doppelmayr, M. Wimmer, H. Schwaiger, J. and Ro, D. 2001. Theta Band Power Changes in Normal and Dyslexic Children. Cinical Neurophysiol. 112: 1174-1185.
Chen, Z. Zhou, H. and Zhao, L. 2011. Decoding Human Right and Left Hand Motor Imagery from EEG Single Trials using Sample Entropy. Proceedings of 2011 International Conference on Electronics and Optoelectronics. 353-356.
Richards, T. L. Berninger, V. W. Stock, P. Altemeier, L. Trivedi, P. and Maravilla, K. R. 2011. Differences Between Good and Poor Child Writers on fMRI Contrasts for Writing Newly Taught and Highly Practiced Letter Forms. Read. Writ. 24(5): 493-516.
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