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Intelligent wheelchair control strategies for older adults with cognitive impairment: user attitudes, needs, and preferences


Intelligent powered wheelchairs can increase mobility and independence for older adults with cognitive impairment by providing collision avoidance and navigation support. The level and/or type of control desired by this target population during intelligent wheelchair use have not been previously explored. In this paper, we present user attitudes, needs, and preferences in a study conducted with a mock intelligent wheelchair offering three different modes of user control. Users wanted to be in the loop during wheelchair operation and/or high-level decision making, and also provided specific contexts where an autonomous wheelchair would be helpful. Participants identified benefits of and concerns with intelligent wheelchairs, along with desired features and functionality. The paper presents the implication of these findings and provides specific recommendations for future intelligent wheelchair development and deployment.

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Fig. 1


  1. Participants tested a different scenario each day, and the study was not counterbalanced such that an equal number of participants tested each scenario on a day.

  2. Despite some statistically significant results, note that the lowest median QUEST 2.0 rating for each mode in all scenarios and survey items was 4.0 (“quite satisfied”). Only two ratings below 3.0 (“more or less satisfied”) were seen over all trials, suggesting that participants either felt uncomfortable to admit when they were unsatisfied, or were in fact generally quite satisfied with all modes.


  • Adhikari, B. (2014). A single subject participatory action design method for powered wheelchairs providing automated back-in parking assistance to cognitively impaired older adults: A pilot study. Vancouver: University of British Columbia.

    Google Scholar 

  • Allison, P. D., & Christakis, N. A. (1994). Logit models for sets of ranked items. Sociological Methodology, 24, 199–228. doi:10.2307/270983.

    Article  Google Scholar 

  • Baltodano, S., Sibi, S., Martelaro, N., Gowda, N., & Ju, W. (2015). RRADS: real road autonomous driving simulation. In Proceedings of the 10th annual ACM/IEEE international conference on human-robot interaction extended abstracts (p. 283). New York, NY, USA: ACM. doi:10.1145/2701973.2702099.

  • Borson, S., & Raskind, M. A. (1997). Clinical features and pharmacologic treatment of behavioral symptoms of Alzheimer’s disease. Neurology, 48(5 Suppl 6), S17–24.

    Article  Google Scholar 

  • Brandt, A., Iwarsson, S., & Stahle, A. (2004). Older people’s use of powered wheelchairs for activity and participation. Journal of Rehabilitation Medicine, 36(2), 70–77.

    Article  Google Scholar 

  • Brighton, C. (2003). Rules of the road. Rehab Managment, 16(3), 18–21.

    Google Scholar 

  • Carlson, T., & Demiris, Y. (2012). Collaborative control for a robotic wheelchair: evaluation of performance, attention, and workload. IEEE Transaction on Systems Man and Cybernetics B Cybernetics, 42(3), 876–888. doi:10.1109/tsmcb.2011.2181833.

    Article  Google Scholar 

  • Dawson, D. R., Chan, R., & Kaiserman, E. (1994). Development of the power-mobility indoor driving assessment for residents of long term care facilities. Canadian Journal of Occupational Therapy, 61(5), 269–276.

    Article  Google Scholar 

  • Demers, L., Weiss-Lambrou, R., & Ska, B. (2002). The Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST 2.0): An overview and recent progress. Technology and Disability, 14, 101–105.

    Google Scholar 

  • Fehr, L., Langbein, W. E., & Skaar, S. B. (2000). Adequacy of power wheelchair control interfaces for persons with severe disabilities: A clinical survey. Journal of Rehabilitation Research and Development, 37(3), 353–360.

    Google Scholar 

  • Foley, G., Zambalde, E. P., Viswanathan, P., & Mihailidis, A. (2014). A table-docking feature for intelligent powered wheelchairs: defining user needs. In: Toronto Rehabilitation Research Day, 2014 (Vol. Toronto). Chicago: IEEE.

  • Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12(3), 189–198.

    Article  Google Scholar 

  • Hardy, P. (2004). Examining the barriers: Powered wheelchair mobility for people with cognitive and/or sensory impairments. In ARATA 2004 National Conference, Melbourne, Australia.

  • Hart, S. G., & Staveland, L. E. (1998). Development of the NASA-TLX (Task Load Index): Results of empirical and theoretical research, Meshkati (N ed., pp. 239–250). Amsterdam: North Holland Press.

    Google Scholar 

  • How, T. V., Wang, R. H., & Mihailidis, A. (2013). Evaluation of an intelligent wheelchair system for older adults with cognitive impairments. Journal of Neuroengineering and Rehabilitation, 10, 90. doi:10.1186/1743-0003-10-90.

    Article  Google Scholar 

  • Jipp, M. (2013). Levels of automation: Effects of individual differences on wheelchair control performance and user acceptance. Theoretical Issues in Ergonomics Science, 15(5), 479–504. doi:10.1080/1463922X.2013.815829.

    Article  Google Scholar 

  • Kairy, D., Rushton, P. W., Archambault, P., Pituch, E., Torkia, C., El Fathi, A., et al. (2014). Exploring powered wheelchair users and their caregivers’ perspectives on potential intelligent power wheelchair use: a qualitative study. International Journal of Environmental Research and Public Health, 11(2), 2244–2261. doi:10.3390/ijerph110202244.

    Article  Google Scholar 

  • Lewis, C. H. (1982). Using the “thinking Aloud” method in cognitive interface design. New York: IBM T.J. Watson Research Center.

    Google Scholar 

  • Li, Q., Chen, W., & Wang, J. (2011). Dynamic shared control for humanwheelchair cooperation. In IEEE international conference on robotics and automation (ICRA) (pp. 4278–4283).

  • Lo, J., Pham, P., Viswanathan, P., & Mihailidis, A. (2014). Intelligent wheelchairs: Training & assessment. In Canadian Association of Occupational Therapists annual conference, Fredericton, NB.

  • Marcantonio, E. R. (2000). Dementia. In M. H. Beers, T. V. Jones, M. Berkwits, J. L. Kaplan, & R. Porter (Eds.), The merck manual of geriatrics (3rd ed., pp. 357–371). Whitehouse Station, NJ: Merck & Co., Inc.

    Google Scholar 

  • Masson, F., Maurette, P., Salmi, L. R., Dartigues, J. F., Vecsey, J., Destaillats, J. M., et al. (1996). Prevalence of impairments 5 years after a head injury, and their relationship with disabilities and outcome. Brain Injury, 10(7), 487–497.

    Article  Google Scholar 

  • Mitchell, I. M., Viswanathan, P., Adhikari, B., Rothfels, E., & Mackworth, A. K. (2014). Shared control policies for safe wheelchair navigation of elderly adults with cognitive and mobility impairments: Designing a wizard of oz study. In Proceedings of the American Controls Conference, Portland, OR (pp. 4087-4094).

  • Morris, J. N., Fries, B. E., Mehr, D. R., Hawes, C., Phillips, C., Mor, V., et al. (1994). MDS cognitive performance scale. Journal of Gerontology, 49(4), M174–182.

    Article  Google Scholar 

  • Mortenson, W. B., Miller, W. C., Boily, J., Steele, B., Odell, L., Crawford, E. M., et al. (2005). Perceptions of power mobility use and safety within residential facilities. Canadian Journal of Occupational Therapy, 72(3), 142–152.

    Article  Google Scholar 

  • Mosimann, U. P., Mather, G., Wesnes, K. A., O’Brien, J. T., Burn, D. J., & McKeith, I. G. (2004). Visual perception in Parkinson disease dementia and dementia with Lewy bodies. Neurology, 63(11), 2091–2096.

    Article  Google Scholar 

  • Nasreddine, Z. S., Phillips, N. A., Bedirian, V., Charbonneau, S., Whitehead, V., Collin, I., et al. (2005). The montreal cognitive assessment, MoCA: A brief screening tool for mild cognitive impairment. Journal of the American Geriatrics Society, 53(4), 695–699. doi:10.1111/j.1532-5415.2005.53221.x.

    Article  Google Scholar 

  • Parikh, S. P., Grassi, V, Jr., Kumar, V., & Okamoto, Jun, Jr. (2007). Integrating human inputs with autonomous behaviors on an intelligent wheelchair platform. IEEE Intelligent Systems, 22(2), 33–41.

    Article  Google Scholar 

  • Park, J. J. & Kuipers, B. (2015). Feedback motion planning via non-holonomic RRT* for mobile robots. IEEE/RSJ International conference on intelligent robots and systems (IROS-15).

  • Patton, M. Q. (2002). Qualitative research and evaluation methods. London: Sage Publications Inc.

    Google Scholar 

  • Peinado, G., Urdiales, C., Peula, J. M., Fernandez-Carmona, M., Annicchiarico, R.,&Sandoval, F., et al. (2011). Navigation skills based profiling for collaborative wheelchair control. In IEEE International Conference on Robotics and Automation (ICRA) (pp. 2229-2234).

  • Pineau, J., Moghaddam, A. K., Yuen, H. K., Archambault, P. S., Routhier, F., Michaud, F., et al. (2014). Automatic detection and classification of unsafe events during power wheelchair use. IEEE Journal of Translational Engineering in Health and Medicine (JTEHM), 2, 1–9. doi:10.1109/JTEHM.2014.2365773.

    Article  Google Scholar 

  • Ricker, J. H., Keenan, P. A., & Jacobson, M. W. (1994). Visuoperceptual-spatial ability and visual memory in vascular dementia and dementia of the Alzheimer type. Neuropsychologia, 32(10), 1287–1296.

    Article  Google Scholar 

  • Riek, L. D. (2012). Wizard of oz studies in hri: a systematic review and new reporting guidelines. Journal of Human-Robot Interaction, 1(1).

  • Rushton, P., Mortenson, W. B., Viswanathan, P., Wang, R. H., & Hurd Clark, L. (2014). Intelligent power wheelchairs for residents in long-term care facilities: Potential users’ experiences and perceptions. In Rehabilitation Engineering and Assistive Technology Society of North America, Indianapolis, IN.

  • Rushton, P. W., Kairy, D., Archambault, P., Pituch, E., Torkia, C., El Fathi, A., et al. (2015). The potential impact of intelligent power wheelchair use on social participation: Perspectives of users, caregivers and clinicians. Disability and Rehabilitation: Assistive Technology, 10(3), 191–197. doi:10.3109/17483107.2014.907366.

    Article  Google Scholar 

  • Simpson, R. C. (2005). Smart wheelchairs: A literature review. Journal of Rehabilitation Research and Development, 42(4), 423–436.

    Article  Google Scholar 

  • Shiomi, M., Iio, T., Kamei, K., Sharma, C., & Hagita, N. (2015). Effectiveness of social behaviors for autonomous wheelchair robot to support elderly people in Japan. PLoS One, 10(5), e0128031. doi:10.1371/journal.pone.0128031.

    Article  Google Scholar 

  • Smith, E. M., Miller, W. C., Mortenson, W. B., Mihailidis, A., Viswanathan, P., & Lo, J., et al. (2014). Interface design for shared control tele-operated power wheelchair technology. In 8th International convention on rehabilitation engineering & assistive technology (i-CREATE), Singapore.

  • Strubel, D., & Corti, M. (2008). Wandering in dementia. Psychologie & Neuropsychiatrie du Vieillissement, 6(4), 259–264. doi:10.1684/pnv.2008.0147.

    Google Scholar 

  • Urdiales, C., Peula, J. M., Fdez-Carmona, M., Barrué, C., Pérez, E. J., Sánchez-Tato, I., et al. (2011). A new multi-criteria optimization strategy for shared control in wheelchair assisted navigation. Autonomous Robots, 30(2), 179–197.

    Article  Google Scholar 

  • Viswanathan, P., Little, J., Mackworth, A., & Mihailidis, A. (2011). Navigation and obstacle avoidance help (NOAH) for older adults with cognitive impairment: A pilot study. In ACM SIGACCESS conference on computers and accessibility (ASSETS), Dundee, Scotland.

  • Viswanathan, P., Little, J. J., Mackworth, A. K., How, T. V., Wang, R. H., & Mihailidis, A. (2013a). Intelligent wheelchairs for cognitively-impaired older adults in Long-term care: A review. In Rehabilitation engineering and assistive technology society of North America, Bellevue, WA.

  • Viswanathan, P., Wang, R. H., & Mihailidis, A. (2013b). Wizard-of-Oz and mixed-methods studies to inform intelligent wheelchair design forolder adults with dementia. In Association for the advancement of assistive technology in Europe, Vilamoura, Portugal.

  • Wang, R. H. (2011). Enabling power wheelchair mobility with long-term care home residents with cognitive impairments. Toronto: University of Toronto.

    Google Scholar 

  • 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(7), 801–822.

    Article  Google Scholar 

  • Wei, Z., Chen, W., & Wang, J. (2012). 3d semantic map-based shared control for smart wheelchair. In Intelligent robotics and applications (pp. 41–51).

  • Wind, A. W., Schellevis, F. G., Van Staveren, G., Scholten, R. P., Jonker, C., & Van Eijk, J. T. (1997). Limitations of the mini-mental state examination in diagnosing dementia in general practice. International Journal of Geriatric Psychiatry, 12(1), 101–108.

    Article  Google Scholar 

  • Wood, L. E. (1997). Semi-structured interviewing for user-centered design. Interactions, 4(2), 48–61.

    Article  Google Scholar 

  • Zeng, Q., Burdet, E., & Teo, C. L. (2008). User evaluation of a collaborative wheelchair system. In Proceedings of IEEE Engineering in Medicine and Biology Society Conference (pp. 1956–1960). doi:10.1109/iembs.2008.4649571.

  • Zeng, Q., Teo, C. L., Rebsamen, B., & Burdet, E. (2008). A collaborative wheelchair system. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 16(2), 161–170. doi:10.1109/tnsre.2008.917288.

    Article  Google Scholar 

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The authors would like to acknowledge all CanWheel team members, especially Kate Keech, Pouria TalebiFard, Emma Smith, Laura Hurd Clarke, Ben Mortenson, Paula Rushton, and Eric Rothfels for their feedback and assistance in conducting the study. We would also like to thank Ellen Maki for conducting statistical analysis, as well as GF Strong, Advanced Mobility, and LTC staff (particularly Sheralyn Manning and Guylaine Desharnais) for all their support. This research was supported by CIHR CanWheel team in Wheeled Mobility for Older Adults (AMG-100925), the Collaborative Health Research Program, Alzheimer’s Society Research Program, AGE-WELL NCE Inc.—a member of the Networks of Centres of Excellence program, Science Without Borders funded by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)—Ministry of Education of Brazil, NSERC Discovery Grant #298211, an NSERC Undergraduate Student Research Award, the Canadian Foundation for Innovation (CFI) Leaders Opportunity Fund / British Columbia Knowledge Development Fund Grant #13113, the Institute for Computing, Information and Cognitive Systems (ICICS) at UBC, NSERC Grant CRDPJ 434659-12 and the ICICS/TELUS People & Planet Friendly Home Initiative at UBC.

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Correspondence to Pooja Viswanathan.

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This is one of several papers published in Autonomous Robots comprising the “Special Issue on Assistive and Rehabilitation Robotics”.

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Viswanathan, P., Zambalde, E.P., Foley, G. et al. Intelligent wheelchair control strategies for older adults with cognitive impairment: user attitudes, needs, and preferences. Auton Robot 41, 539–554 (2017).

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