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Development of an Assistive Robotic System with Virtual Assistance to Enhance Play for Children with Disabilities: A Preliminary Study

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Abstract

Children with disabilities typically have fewer opportunities for manipulation and play, due to their physical limitations, resulting in delayed cognitive and perceptual development. A switched-controlled device can remotely do tasks for a child or a human helper can mediate the child’s interaction with the environment during play. However, these approaches disconnect children from the environment and limit their opportunities for interactive play with objects. This paper presents a novel application of a robotic system with virtual assistance, implemented by virtual fixtures, to enhance interactive object play for children in a set of coloring tasks. The assistance conditions included zero assistance (No-walls), medium level assistance (Soft-walls) and high level assistance (Rigid-walls), which corresponded to the magnitude of the virtual fixture forces. The system was tested with fifteen able-bodied adults and results validated the effectiveness of the system in improving the user’s performance. The Soft- and Rigid-walls conditions significantly outperformed the No-walls condition and led to relatively the same performance improvements in terms of: (a) a statistically significant reduction in the ratio of the colored area outside to the colored area inside the region of interest (with large effect sizes, Cohen’s d > .8), (b) and a substantial reduction in the travelled distance outside the borders (with large effect sizes). The developed platform will next be tested with typically developing children and then children with disabilities. Future development will include adding artificial intelligence to adaptively tune the level of assistance according to the user’s level of performance (i.e. providing more assistance only when the user is committing more errors).

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Notes

  1. http://dl.geomagic.com/binaries/support/downloads/Sensable/3DS/Premium1.0_1.5_HF_Device_guide.pdf.

References

  1. Harkness, L. B. A. (1993). The test of playfulness and children with physical disabilities. Occupational Therapy Journal Research, 21(2), 73–89.

    Article  Google Scholar 

  2. Klatzky, R. L., Loomis, J. M., Lederman, S. J., Wake, H., & Fujita, N. (1993). Haptic identification of objects and their depictions. Perception & Psychophysics, 54, 170–178.

    Article  Google Scholar 

  3. Lederman, S. J., & Klatzky, R. L. (2004). Haptic identification of common objects: Effects of constraining the manual exploration process. Perception & Psychophysics, 66, 618–628.

    Article  Google Scholar 

  4. BS EN ISO 9241-910. (2011). Ergonomics of human–system interaction. Framework for tactile haptic interactions [Ergon. l’interaction homme-système. Cadre pour les Interact. tactiles haptiques].

  5. Power, T. G. (2000). Play and exploration in children and animals. Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  6. Taylor, M. M., Lederman, S. J., & Gibson, R. H. (1973). Tactual perception of texture. In Biology of perceptual systems (Chap. 12). Amsterdam: Elsevier.

  7. Cook, A. M., Hoseit, P., Liu, K. M., Lee, R. Y., & Zenteno-Sanchez, C. M. (1988). Using a robotic arm system to facilitate learning in very young disabled children. IEEE Transactions on Biomedical Engineering, 35, 132–137.

    Article  Google Scholar 

  8. Kronreif, G., & Prazak-Aram, B. (2008). Robot and play—from assistance to mediation. In ACM/IEEE human–robot interaction conference, Amsterdam.

  9. Smith, J., & Topping, M. (1996). The introduction of a robotic aid to drawing into a school for physically handicapped children: A case study. British Journal of Occupational Therapy, 59, 565–569.

    Article  Google Scholar 

  10. Rios-Rincon, A. M., Adams, K., Magill-Evans, J., & Cook, A. (2015). Playfulness in children with limited motor abilities when using a robot. Physical & Occupational Therapy in Pediatrics, 2638, 1–15. doi:10.3109/01942638.2015.1076559.

    Google Scholar 

  11. Tsotsos, J. K., Verghese, G., Dickinson, S., Jenkin, M., Jepson, A., Milios, E., et al. (1998). PLAYBOT a visually-guided robot for physically disabled children. Image and Vision Computing, 16, 275–292. doi:10.1016/S0262-8856(97)00088-7.

    Article  Google Scholar 

  12. Robins, B., Dautenhahn, K., Ferrari, E., Kronreif, G., Prazak-Aram, B., Marti, P., et al. (2012). Scenarios of robot-assisted play for children with cognitive and physical disabilities. Interaction studies, 13, 189–234. doi:10.1075/is.13.2.03rob.

    Article  Google Scholar 

  13. Jafari, N., Adams, K., & Tavakoli, M. (2015). Haptic telerobotics: Application to assistive technology for children with disabilitie. North Am: Rehabil. Eng. Assist. Technol. Soc.

    Google Scholar 

  14. Crespo, L. M., Reinkensmeyer, D. J., Marchal-Crespo, L. M., & Reinkensmeyer, D. J. (2008). Haptic guidance can enhance motor learning of a steering task. Journal of Motor Behavior, 40, 545–557.

    Article  Google Scholar 

  15. Wang, R. H., Mihailidis, A., Dutta, T., & Fernie, G. R. (2011). Usability testing of multimodal feedback interface and simulated collision-avoidance power wheelchair for long-term-care home residents with cognitive impairments. Journal of Rehabilitation Research and Development, 48, 801. doi:10.1682/JRRD.2010.08.0147.

    Article  Google Scholar 

  16. Langdon, P., Keates, S., Clarkson, P. J., & Robinson, P. (2000) Using haptic feedback to enhance computer interaction for motion-impaired users. In P. Sharkey (Ed.), Virtual reality and associated technologies (pp. 25–32). Reading: University of Reading.

  17. Xiaolong, Z. (2010). Adaptive haptic exploration of geometrical structures in map navigation for people with visual impairment. In IEEE international symposium on haptic audio visual environments and games 1.

  18. Sjöström, C. (2001). Using haptics in computer interfaces for blind people. Chi, 2001, 245–246. doi:10.1145/634211.634213.

    Google Scholar 

  19. Sjostrom, C. (2001). Virtual haptic search tools—the white cane in a haptic computer interface. In C. Marincek (Ed.), Assistive technology: Added value to quality of life, AAATE’01 (pp. 124–128). Amsterdam: IOS.

  20. Rozario, S. V., Housman, S., Kovic, M., Kenyon, R. V., & Patton, J. L. (2009). Therapist-mediated post-stroke rehabilitation using haptic/graphic error augmentation. In Annual international conference of the IEEE engineering in medicine and biology society (pp. 1151–1156). doi:10.1109/IEMBS.2009.5333875.

  21. Atashzar, F., Jafari, N., Shahbazi, M., Janz, H., Tavakoli, M., Patel, R. V., et al. (2016). Telerobotics-assisted platform for enhancing interaction with physical environments for people living with cerebral palsy. Journal of Medical Robotics Research, 2(2), 1740001.

    Article  Google Scholar 

  22. Abbott, J. J., Marayong, P., & Okamura, A. M. (2007). Haptic virtual fixtures for robot-assisted manipulation. Springer Tracts in Advanced Robotics, 28, 49–64. doi:10.1007/978-3-540-48113-3_5.

    Article  MATH  Google Scholar 

  23. Asque, C. T., Day, A. M., & Laycock, S. D. (2012). Haptic-assisted target acquisition in a visual point-and-click task for computer users with motion impairments. IEEE Transactions on Haptics, 5, 120–130. doi:10.1109/TOH.2011.55.

    Article  Google Scholar 

  24. Abbott, J. J., Hager, G. D., & Okamura, A. M. (2003). Steady-hand teleoperation with virtual fixtures. In Proceedings of IEEE international symposium on robot and human interactive communication (pp. 145–151). doi:10.1109/ROMAN.2003.1251824

  25. Wrock, M. R., & Nokleby, S. B. (2011). Haptic teleoperation of a manipulator using virtual fixtures and hybrid position-velocity control. In 13th World congress on mechanism and machine science A12_342.

  26. Bettini, A., Marayong, P., Lang, S., Okamura, A. M., & Hager, G. D. (2004). Vision-assisted control for manipulation using virtual fixtures. IEEE Transactions on Robotics, 20, 953.

    Article  Google Scholar 

  27. Rosenberg, L. (1993). The use of virtual fixtures to enhance telemanipulation with time delay. In Proceedings of ASME advances in robotics, mechatronics and haptic interfaces (DSC, Vol. 49).

  28. Covarrubias, M., Bordegoni, M., Cugini, U., Milano, P., Via, M., & Masa, G. L. (2011). Sketching haptic system based on point-based approach for assisting people with down syndrome. Communications in Computer and Information Science, 173, 378–382. doi:10.1007/978-3-642-22098-2_76.

    Article  Google Scholar 

  29. Covarrubias, M., Gatti, E., Mansutti, A., Bordegoni, M., & Cugini, U. (2012, July). Multimodal guidance system for improving manual skills in disabled people. In International conference on computers for handicapped persons (pp. 227–234). Berlin: Springer.

  30. Covarrubias, M., Gatti, E., Bordegoni, M., Cugini, U., & Mansutti, A. (2014). Improving manual skills in persons with disabilities (PWD) through a multimodal assistance system. Disability and Rehabilitation: Assistive Technology, 9, 335–343. doi:10.3109/17483107.2013.799238.

    Article  Google Scholar 

  31. Covarrubias, M., Bordegoni, M., & Cugini, U. (2014). Haptic trajectories for assisting patients during rehabilitation of upper extremities. Computer-Aided Design and Application, 12, 218–225. doi:10.1080/16864360.2014.962434.

    Article  Google Scholar 

  32. Covarrubias, M., Bordegoni, M., & Cugini, U. (2015). Haptic trajectories for assisting patients during rehabilitation of upper extremities. Computer-Aided Design and Applications, 12(2), 218–225.

    Article  Google Scholar 

  33. Bettini, A., Lang, S., Okamura, A., & Hager, G. (2001). Vision assisted control for manipulation using virtual fixtures. In IEEE/RSJ international conference on intelligent robots and systems (pp 1171–1176).

  34. Sayers, C. P., & Paul, R. P. (1994). An operator interface for teleprogramming employing synthetic fixtures. Presence (Cambridge), 3, 309–320.

    Article  Google Scholar 

  35. Blanche, E. I. (2008). Play in children with cerebral palsy: Doing with-not doing to. In D. Parham & L. Fazio (Eds.), Play in occupational therapy for children (pp. 375–393). St. Louis: Mosby Elsevier.

    Chapter  Google Scholar 

  36. Gruber, E. J., & McNinch, G. W. (1994). Young children’s interpretations of coloring activities. The Journal of Pediatric Psychology, 21, 347–350.

    Google Scholar 

  37. Mayesky, M. (2009). Creative activities for young children (9th ed.). New York: Delmar Publishing Company.

    Google Scholar 

  38. McGee, L. M., & Richgels, D. J. (2011). Literacy’s beginnings: Supporting young readers and writers (6th ed.). Boston: Pearson/Allyn Bacon.

    Google Scholar 

  39. Bandura, A., & Adams, N. E. (1977). Analysis of self-efficacy theory of behavioral change. Cognitive Therapy and Research, 1, 287–310.

    Article  Google Scholar 

  40. Dweck, C. S. (2002). The development of ability conceptions. In Development of achievement motivation. San Diego: Academic Press.

  41. Schell, Barbara. A., Gillen, Glen., & Marjorie Scaffa, E. S. C. (2014). Willard and Spackman’s occupational therapy (12th ed.). Philadelphia: Lippincott Williams & Wilkins.

    Google Scholar 

  42. Field, A. (2011). Discovering statistics using SPSS (3rd ed.). Thousand Oaks, CA: SAGE.

    MATH  Google Scholar 

  43. Likert, R. (1932). A technique for the measturement of attitudes. Archiv fur Psychologie, 22, 1–55.

    Google Scholar 

  44. Brooke, J. (1996). SUS—A “quick and dirty” usability scale. In Usability evaluation in industry. London: Taylor and Francis.

  45. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.

    MATH  Google Scholar 

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Acknowledgements

This research was supported by a Collaborative Health Research Project (CHRP), a joint initiative of the National Sciences and Engineering Research Council (NSERC) and Canadian Institutes of Health Research (CIHR), Grants #462227-14 and #134744, and the Glenrose Foundation.

Author information

Authors and Affiliations

  1. Faculty of Rehabilitation Medicine, University of Alberta, Assistive Technology Labs, 3-48 Corbett Hall, Edmonton, AB, T6G 2G4, Canada

    Nooshin Jafari & Kim D. Adams

  2. Glenrose Rehabilitation Hospital, Edmonton, AB, T5G 0B7, Canada

    Kim D. Adams

  3. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, T6G 1H9, Canada

    Mahdi Tavakoli

  4. Department of Psychology, University of Alberta, Edmonton, AB, T6G 2R3, Canada

    Sandra Wiebe

Authors
  1. Nooshin Jafari
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  2. Kim D. Adams
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  3. Mahdi Tavakoli
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  4. Sandra Wiebe
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Corresponding author

Correspondence to Nooshin Jafari.

Appendix

Appendix

See Figs. 6, 7, 8, 9.

Fig. 6
figure 6

Illustration of the color-coded movement trajectories of participant #1 inside and outside the ROI under No-walls (left plot), Soft-walls (middle plot) and Rigid-walls (right plot) assistance conditions

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Fig. 7
figure 7

Visualization of analysis of the movement trajectories of participant #1 inside and outside the ROI under No-walls (left plot), Soft-walls (middle plot) and Rigid-walls (right plot) assistance conditions

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Fig. 8
figure 8

Illustration of the color-coded movement trajectories of participant #1 inside and outside the ROI under No-walls (left plot), Soft-walls (middle plot) and Rigid-walls (right plot) assistance conditions

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Fig. 9
figure 9

Visualization of analysis of the movement trajectories of participant #1 inside and outside the ROI under No-walls (left plot), oft-walls (middle plot) and Rigid-walls (right plot) assistance conditions

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Jafari, N., Adams, K.D., Tavakoli, M. et al. Development of an Assistive Robotic System with Virtual Assistance to Enhance Play for Children with Disabilities: A Preliminary Study. J. Med. Biol. Eng. 38, 33–45 (2018). https://doi.org/10.1007/s40846-017-0305-6

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