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Software with Biofeedback to Assist People with Down Syndrome

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
D. Lima, M. Sousa, R. Araújo, J. Hannum, A. Da Rocha, T. Barbosa
10.5120/ijca2017912847

D Lima, M Sousa, R Araújo, J Hannum, Da A Rocha and T Barbosa. Software with Biofeedback to Assist People with Down Syndrome. International Journal of Computer Applications 158(5):31-37, January 2017. BibTeX

@article{10.5120/ijca2017912847,
	author = {D. Lima and M. Sousa and R. Araújo and J. Hannum and A. Da Rocha and T. Barbosa},
	title = {Software with Biofeedback to Assist People with Down Syndrome},
	journal = {International Journal of Computer Applications},
	issue_date = {January 2017},
	volume = {158},
	number = {5},
	month = {Jan},
	year = {2017},
	issn = {0975-8887},
	pages = {31-37},
	numpages = {7},
	url = {http://www.ijcaonline.org/archives/volume158/number5/26906-2017912847},
	doi = {10.5120/ijca2017912847},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Down syndrome is caused by the presence of three chromosomes 21 in all or most cells of a person [1]. A person with Down syndrome has different chronological and functional age, so the same response is not expected as those without the syndrome [2]. This deficiency stems from brain damage and functional imbalances of the nervous system, resulting in some learning difficulties, which can vary from basic literacy to performing daily activities. The applications developed in this work are intended to help these people in their literacy, while monitoring their attention levels and detecting their expressions. The assistance is provided through activities such as pairing vowels and matching words with corresponding images and sounds. On the other hand, a biofeedback algorithm called Attention Meter runs in parallel with the activities, monitoring the user’s attention during the execution. This algorithm is implemented as a framework that can be used by any application running Android or RemixOS. Finally, a performance report of the student engagement and learning is generated for a professional analysis, according to the attention level.

References

  1. O que é? Síndrome de Down. Online: http://www.movimentodown.org.br/sindrome-de- down/o-que- e/.
  2. Bissoto ML. Desenvolvimento Cognitivo e o Processo de Aprendizagem do Portador de Síndrome de Down: Revelando Concepções e Perspectivas Educacionais. Ciências e Cognição, 200.
  3. Picard Rosalind W., Affective Computing in Cambridge: MIT press, Vol. 252. 1997.
  4. Projeto Participar, Expressar. Online: http://www.projetoparticipar.unb.br/expressar.
  5. Livox, Livox. Online: http://www.livox.com.br/.
  6. Hayed G.R, Hirano S., Monibi M., Nguyen D.H., Yeganyan M. Interactive visual supports for children autism in Pers Ubiquit, 2010.
  7. Android Studio. Online: https://developer.android.com/studio/index.html.
  8. Pivetta, E. M. Aplicação do software hot potatoes como ferramenta de apoio ao ensino/aprendizagem para pessoas com síndrome de Down. (2009).
  9. Leite D. A. & Baptista N. M. G. Aprendizagem da criança de quatro a seis anos com Síndrome de Down em uma escola especial. (2006).
  10. Herrera, A. R. C., Dickie, I. B. & Schulenburg, H. R. W. Design inclusivo: Interface Gráfica Voltada para Crianças com Síndrome de Down [electronic version]. (2014). Ergodesign & HCI, 2, 1-8.
  11. Martin G. & Pear J. Modificação de comportamento: o que é e como fazer [Translation Noreen Campbell de Aguirre. Scientific Revision Hélio José Guilhard]. - 8. ed. - [Reprint]. (2009) - São Paulo: Roca.
  12. Douglas F. de M. Santos Edson, “ELViS: Enhanced for Limited Vision System.”, International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868 Foundation of Computer Science FCS, New York, USA Volume 9 – No.8, October 2015.
  13. C. J. Lee, “Externalizing and Interpreting Autonomic Arousal in People Diagnosed with Autism”, Program of Media Arts and Sciences, School of Architetural and Planning in partial fulfillment of the requirements for the degree of Doctor of Philosophi, Massachusetts Institute of Technology, September 2011.
  14. Sommerville, Ian. Engenharia de Software. Tradução Selma Shin Shimizu Melnikoff; Reginaldo Arakaki; Edilson de Andrade Barbosa. 8. ed. São Paulo: Addison Wesley
  15. LEE, Chia-Hsun Jackie et al. Attention meter: a vision-based input toolkit for interaction designers. In: CHI'06 extended abstracts on Human factors in computing systems. ACM, 2006.
  16. Viola, P., and Jones Michael. "Robust Real-time Object Detection." Second International Workshop on Statistical and Computational Theories of Vision-Modeling, Learning, Computing, and Sampling. 2004. 
  17. Belhumeur, Peter N.; Hespanha, João P.; KRIEGMAN, David J. Eigenfaces vs. fisherfaces: Recognition using class specific linear projection. IEEE Transactions on pattern analysis and machine intelligence, v. 19, n. 7, p. 711-720, 1997.
  18. I Tuytelaars T. Mikolajczyk K. Local Invariant Feature Detectors: A Survey, Foundations and Trends in Computer Graphics and Vision Vol. 3, No. 3. 2007
  19. Ramírez-Gutierrez, K., Cruz-Pérez, D., and Pérez-Meana, H. (2011). A face recognition algorithm using eigenphases and histogram equalization. International Journal of Computers, 5:34–41.

Keywords

Biofeedback, OpenCV, Attention, Activity, Framework