CHARACTERIZATION OF YOUNG CHILDREN WITH PREFERRED AND NON-PREFERRED GRAPHIC RULE DURING DRAWING
DOI:
https://doi.org/10.11113/jt.v78.9455Keywords:
Handwriting, electroencephalogram, partial directed coherence, fast fourier transform, principal component analysisAbstract
This paper aims to investigate the functional connectivity in brain among young children during employment of preferred and non-preferred rule when drawing basic drawing task using Partial Directed Coherence (PDC) and to determine the most significant parameter in differentiating the two groups using handwriting dynamic features and brain activity based on statistical analysis and principle component analysis (PCA). Twelve subjects between 5 and 6 years old were selected randomly. All subjects were asked to gaze and trace four different unlined shapes. The brain signals were recorded using an electroencephalogram (EEG) machine during drawing tasks. Result showed that subjects who employed preferred graphic rule (Control) when performing gazing and tracing tasks were better at visual processing when compared to those that used graphic rule in haphazard fashion. Besides, significant difference was found in frequency domain when subjects used graphic rule in rule governed fashion when compared to relaxing activity. The contrast was found when subject used graphic rule in haphazard fashion. Results from PCA showed most significant parameter (gamma/high gamma) in differentiating between the two groups (employed graphic rule vs. non-graphic) was found in tracing task.
References
Khalid, P. I., J. Yunos, and R. Adnan 2010. Extraction of Dynamic Features from Hand Drawn Data for the Identification of Children with Handwriting Difficulty. Research in Developmental Disabilities. 31: 256-262.
Yusof, U. K. M. 2012. The Screening Tool for Handwriting Difficulty. Graduate Report Project, Universiti Teknologi Malaysia, Skudai. 1-2.
Feder, K.P. and A. Majnemer 2003. Handwriting Development, Competency, and Intervention. Development Medicine and Child Neurology. 49: 312-317.
Rosenblum, S., P. L. Weiss, S. Parush 2003. Product and Process Evaluation of Handwriting Difficulties. Educational Psychology Review. 15: 41-8.
Zwicker, J. G. 2005. Effectiveness of Occupational Therapy in Remediating Handwriting Difficulties in Primary Students: Cognitive Versus Multisensory Interventions. University of Victoria. M. A. Thesis. 17-20.
Hammerschimdt, S. L. and P. Sudsawad 2004. Teacher’s Survey on Problems with Handwriting: Referral, Evaluation and Outcomes. American Occupational Therapy Journal. 58 (2). 185-92.
Gillespie, H. M. 2003. Component Handwriting Skills among Early Elementary Children with Average and Below Average Printing Ability. Northwestern University. PhD Thesis. 12-18.
Tseng, M.H. and E. A. Murray 1994. Differences in Perceptual-Motor Measures in Children with Good and Poor Handwriting. Occupational Therapy Journal of Research. 14: 19-36.
Khalid, P. I., J. Yunos, R. Adnan, M. Harun, R. Sudirman and N. H. Mahmood 2010. The Use of Graphic Rules in Grade One to Help Identify Children at Risk of Handwriting Difficulties. Research in Development Disabilities. 31: 1685-1693.
Summers, J. 2001. Joint Laxity in the Index Finger and Thumb and its Relationship to Pencil Grasps Used by Children. Australian Occupational Therapy Journal. 48(3): 132-141.
Berry, K. E. 1989. The Development Test of Visual Motor Integration. 3rd. ed. Cleveland, OH: Modern Curriculum Press.
Goodnow, J. J. and R. Levine 1973. The Grammar of Action: Sequence and Syntax in Children’s Copying. Cognitive Psychology. 4: 82-98.
Meulenbroek, R. G. J. and A. J. W. M. Thomassen 1991. Stroke-Direction Preferences in Drawing and Handwriting. Human Movement Science. 10: 247-270.
Baccala, L.A. and K. Sameshima 2001. Partial Directed Coherence: A New Concept in Neural Structure Determination. Biological cybernetics. 84: 463-474.
Hashim, S., N. M. Safri, P. I. Khalid, M. A. Othman and J. Yunus 2014. Differences in Cortico-Corticol Functional Connections between Children with Good and Poor Handwriting: A Case Study. IEEE Region 10 Symposium. 34-38.
Meulenbroek, R. G. J., A. J. W. M., Thomassen, J. J. Schilings, and D. A. Rosenbaum 1996. Synergies and Sequencing in Copying L-Shaped Patterns in Handwriting and Drawing Research: Basic and Applied Issues, M. L. Simner and C. G. Leedham, Eds. Amsterdam, Netherlands: IOS Press. 41-55.
Ziviani, J. and M. Wallen 2006. The Development of Graph Motor Skills in Hand Function in the Child. In A. Henderson and C. Pehoski. Foundation for remediation. Philadelphia USA: Eds Elsevier. 217-236.
Chiang, J., Z. J. Wang, M. J. and McKeown 2009. Sparse Multivariate Autoregressive (mAR)-Based Partial Directed Coherence (PDC) for Electroencephalogram (EEG) Analysis. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 457-460.
Brillinger, D. 1996. Remarks Concerning Graphical Model for Time Series and Point Process. Revista de econometrical. 16: 1-23.
Tanaka, N., N. A. Zakaria, N. K. Kibinge, S. Kanaya, T. Tamura, and M. Yoshida 2014. Fall-Risk Classification of the Timed Up-and-Go Test with Principle Component Analysis. International Journal of Neurorehabilitation. 1: 106.
Downloads
Published
Issue
Section
License
Copyright of articles that appear in Jurnal Teknologi belongs exclusively to Penerbit Universiti Teknologi Malaysia (Penerbit UTM Press). This copyright covers the rights to reproduce the article, including reprints, electronic reproductions, or any other reproductions of similar nature.
