Relations between Touch Target Size and Drag Distance in Mobile Applications for Users with Autism Spectrum Disorders
- 110 Downloads
In recent years, the development of mobile applications for people within the autism spectrum has proliferated to help enhance skills that could be diminished in users with this condition. However, the usability of these applications does not appear to be the focus of development because users with autism can have difficulty with fine motor skills. This article focuses on evaluating the optimal drag distance and the sizes of the interaction elements for users with Autism Spectrum Disorder. To accomplish this goal, a case study was conducted that involved 20 users with Autism Spectrum Disorder and 30 users with typical development, using a prototype generated and two applications for commercial use on 7-in. tablets. For both developed applications, a slight variation can be observed between the different groups of participants. In the interaction with Proyect@ Habilidades, the application has pictograms of 65 pixels and it has a maximum trailing distance of 340 pixels. Moreover, in Proyect@ Retratos, where there is a minimum deviation between users with levels of autism 1 and 2, it also has pictograms of 65 pixels but with a drag distance of 110 pixels. For this reason, according to the results, we suggest that in order to obtain better results in the interaction with applications aimed at users diagnosed with autism spectrum disorders, the applications should have pictograms of a range of 65 pixels with a drag interaction between 110 and 340 pixels. Considering in context a 7-in. tablet with a resolution of 1280 × 800 pixels.
KeywordsAutism Interaction Dragging Mobile applications
We appreciate the support of the National Council of Science and Technology (CONACYT) and the Autonomous University of Baja California for the resources provided to develop this research. Roberto Muñoz was supported by the INF PUCV 2105 Doctoral Scholarship. Finally, Rodolfo Villarroel and Roberto Munoz thanks the DOC INNOVA 2018 CORFO (14ENI2-26905) project.
Compliance with Ethical Standards
The manuscript does not contain clinical studies or patient data.
Conflict of Interest
The authors declare that they have no conflict of interest.
- 1.APA, “American Psychiatric Association,” 2013. [Online]. Available: http://www.apa.org/pi/disability/resources/publications/newsletter/2016/09/autism-spectrum-disorder.aspx.
- 2.P. Fitzpatrick, J. A. Frazier, D. M. Cochran, T. Mitchell, C. Coleman, and R. C. Schmidt, “Impairments of social motor synchrony evident in autism spectrum disorder,” Front. Psychol., vol. 7, no. AUG, pp. 1–13, 2016.Google Scholar
- 5.Munoz-Soto, R. et al., Proyect@ matemáticas: A learning object for supporting the practitioners in autism spectrum disorders. Proc. - 2016 11th Lat. Am. Conf. Learn. Objects Technol. LACLO 2016, 2016.Google Scholar
- 6.Chen, C., Developing a tablet computer game with visual-spatial concept jigsaw puzzles for autistic children. pp. 5522–5532, 2013.Google Scholar
- 7.Muñoz, R., Barcelos, T., Noël, R., and Kreisel, S., Development of software that supports the improvement of the empathy in children with autism spectrum disorder. Proc. - Int. Conf. Chil. Comput. Sci. Soc. SCCC, pp. 223–228, 2013.Google Scholar
- 8.Mejia-Figueroa, A., De Los Angeles Quezada Cisnero, M., and Juarez-Ramirez, J.R., Developing usable software applications for users with autism: User analysis, user interface design patterns and interface components. Proceedings - 2016 4th International Conference in Software Engineering Research and Innovation, CONISOFT 2016. pp. 195–203, 2016.Google Scholar
- 9.Card, A., Moran, S. and Newell T., The Psychology of Human-Computer Interaction.. Book, 1983.Google Scholar
- 10.Rice, A.D., Lartigue, J.W., Touch-level model ( TLM ): Evolving KLM-GOMS for touchscreen and mobile devices categories and subject descriptors. ACM trans. Access. Comput. 1–6, 2014.Google Scholar
- 11.A. Lee, K. Song, H. B. Ryu, J. Kim, and G. Kwon, “Fingerstroke time estimates for touchscreen-based mobile gaming interaction,” Hum. Mov. Sci., vol. 44, no. 2016, pp. 211–224, 2015.Google Scholar
- 12.Quezada, A., Juárez-Ramírez, R., Jiménez, S., Ramírez-Noriega, A., Inzunza, S., and Munoz, R., Assessing the target’ size and drag distance in mobile applications for users with autism. Adv. Intell. Syst. Comput. 746:1–10, 2018.Google Scholar
- 13.El Batran, K., and Dunlop, M. D., Enhancing KLM (keystroke-level model) to fit touch screen mobile devices. Proc. 16th Int. Conf. Human-computer Interact. with Mob. devices Serv. - MobileHCI 14:283–286, 2014.Google Scholar
- 14.Holleis, P., Otto, F., Hussmann, H., and Schmidt, A., Keystroke-level model for advanced mobile phone interaction. CHI ‘07 Proc. SIGCHI Conf. Hum. factors Comput. Syst., 1505–1514, 2007.Google Scholar
- 15.H. Li, Y. Liu, J. Liu, X. Wang, Y. Li, and P.-L. P. Rau, “Extended KLM for mobile phone interaction,” Proc. 28th Int. Conf. Ext. Abstr. Hum. factors Comput. Syst. - CHI EA ‘10, p. 3517, 2010.Google Scholar
- 17.Motti, L. G., Vigouroux, N., and Gorce, P., Drag-and-drop for older adults using touchscreen devices: Effects of screen sizes and interaction techniques on accuracy. 26th French-Speaking Conf. Human-Machine Interact. HMI 2014:139–146, 2014.Google Scholar
- 18.F. Vella, N. Vigouroux, and P. Rumeau, “Investigating drag and drop techniques for older people with cognitive impairment,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 6764 LNCS, no. PART 4, pp. 530–538, 2011.Google Scholar
- 19.Anthony, L., Brown, Q., Nias, J., Tate, B., and Mohan, S., Interaction and recognition challenges in interpreting children’s touch and gesture input on mobile devices. Proc. 2012 ACM Int. Conf. Interact. Tabletops Surf. - ITS 12:225, 2012.Google Scholar