Jason R. Wilson
Skip Abstract Section
Abstract
Assistive robots are becoming an increasingly important application platform for research in robotics, AI, and HRI, as there is a pressing need to develop systems that support the elderly and people with disabilities, with a clear path to market. Yet, what remains unclear is whether current autonomous systems are already up to the task or whether additional HRI work is needed to make these systems acceptable and useful.
In this article, we report our efforts of developing and evaluating an architecture for a fully autonomous robot designed to assist older adults with Parkinson’s disease (PD) in sorting their medications. The main goal for the robot is to aid users in a manner that maintains the autonomy of the user by providing cognitive and social support with varying levels of assistance. We first evaluated the robot with subjects drawn from a pool of university students, which is common practice in experimental work in psychology and HRI. As the results were very positive, we followed up with an evaluation using people with Parkinson’s disease, who surprisingly had mostly negative outcomes. We thus report our analysis of the differences in the evaluations and discuss the challenges for HRI posed by the sources of the negative evaluations: (1) designing a robot to adapt to the many routines the participants use at home, (2) unique needs of participants with PD not present in student participants, and (3) the role of familiar technologies in designing and evaluating a new technology. While it is unlikely, given the current state of technology, that fully autonomous assistive robots for older adults will be available in the near term, we believe that our work exposes a critical need in HRI to involve the target population as early as possible in the design process.
- H. R. Lee, Šabanović, W. L. Chang, S. Nagata, J. Piatt, C. Bennett, and D. Hakken. 2017. Steps toward participatory design of social robots: mutual learning with older adults with depression. In Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction. 244--253Google Scholar
- Ronald C. Arkin, Matthias Scheutz, and Linda Tickle-Degnen. 2014. Preserving dignity in patient caregiver relationships using moral emotions and robots. In Proceedings of the IEEE International Symposium on Ethics in Science, Technology and Engineering. 1--5.Google ScholarCross Ref
- American Occupational Therapy Association et al. 2015. Occupational therapy code of ethics (2015). Amer. J. Occup. Ther. 69, 3 (2015). https://ajot.aota.org/article.aspx?articleid=2442685.Google Scholar
- Jacquelyn L. Bainbridge and J. Mark Ruscin. 2009. Challenges of treatment adherence in older patients with Parkinson’s disease. Drugs Aging 26, 2 (2009), 145--155.Google ScholarCross Ref
- Elliot Baum. 2006. Pill dispenser. U.S. Patent 7,100,793.Google Scholar
- Priscilla Briggs, Matthias Scheutz, and Linda Tickle-degnen. 2015. Are robots ready for administering health status surveys? First results from an HRI study with subjects with Parkinson’s disease. In Proceedings of the 10th Annual ACM/IEEE International Conference on Human-Robot Interaction. ACM, 327--334.Google Scholar
- Susan A. Brown and Viswanath Venkatesh. 2005. Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle. MIS Quart. 29, 3 (2005).Google Scholar
- Praminda Caleb-Solly, Sanja Dogramadzi, David Ellender, Tina Fear, and Herjan van den Heuvel. 2014. A mixed-method approach to evoke creative and holistic thinking about robots in a home environment. In Proceedings of the ACM/IEEE International Conference on Human-robot Interaction. ACM, 374--381.Google Scholar
- Vicki S. Conn, Adam R. Hafdahl, Pamela S. Cooper, Todd M. Ruppar, David R. Mehr, and Cynthia L. Russell. 2009. Interventions to improve medication adherence among older adults: Meta-analysis of adherence outcomes among randomized controlled trials. Gerontologist 49, 4 (2009), 447--462.Google ScholarCross Ref
- Chandan Datta, H. Yul Yang, Priyesh Tiwari, I. Han Kuo, and Bruce A. MacDonald. 2011. End user programming to enable closed-loop medication management using a healthcare robot. In Proceedings of Australasian Conference on Robotics and Automation.Google Scholar
- Lindsey Dayer, Seth Heldenbrand, Paul Anderson, Paul O. Gubbins, and Bradley C. Martin. 2013. Smartphone medication adherence apps: Potential benefits to patients and providers. J. Amer. Pharm. Assoc. 53, 2 (2013), 172--181.Google ScholarCross Ref
- E. R. Foster. 2014. Instrumental activities of daily living performance among people with Parkinson’s disease without dementia. Amer. J. Occup. Ther. 68, 3 (2014), 353--362.Google ScholarCross Ref
- Donald Grosset, Angelo Antonini, Margherita Canesi, Gianni Pezzoli, Andrew Lees, Karen Shaw, Esther Cubo, Pablo Martinez-Martin, Olivier Rascol, Laurence Negre-Pages, et al. 2009. Adherence to antiparkinson medication in a multicenter european study. Movement Disorders 24, 6 (2009), 826--832.Google ScholarCross Ref
- Jörg W. Haslbeck and Doris Schaeffer. 2009. Routines in medication management: The perspective of people with chronic conditions. Chronic Illness 5, 3 (2009), 184--196.Google ScholarCross Ref
- Leah M. Haverhals, Courtney A. Lee, Katie A. Siek, Carol A. Darr, Sunny A. Linnebur, J. Mark Ruscin, and Stephen E. Ross. 2011. Older adults with multi-morbidity: Medication management processes and design implications for personal health applications. J. Med. Internet Res. 13, 2 (2011), e44.Google ScholarCross Ref
- Tamara L. Hayes, John M. Hunt, Andre Adami, and Jeffrey A. Kaye. 2006. An electronic pillbox for continuous monitoring of medication adherence. In Proceedings of the International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 6400--6403.Google Scholar
- Timothy J. Hazen and Issam Bazzi. 2001. A comparison and combination of methods for OOV word detection and word confidence scoring. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP’01), Vol. 1. IEEE, 397--400.Google Scholar
- Amanda R. Hemmesch. 2011. The Stigmatizing Effects of Facial Masking and Abnormal Bodily Movement on Older Adults’ First Impressions of Individuals with Parkinson’s Disease. Brandeis University.Google Scholar
- Judith E. Hertz and Cynthia A. Anschutz. 2002. Relationships among perceived enactment of autonomy, self-care, and holistic health in community-dwelling older adults. J. Holistic Nurs. 20, 2 (2002), 166--186.Google ScholarCross Ref
- Hsiu-Fang Hsieh and Sarah E. Shannon. 2005. Three approaches to qualitative content analysis. Qualitat. Health Res. 15, 9 (2005), 1277--1288.Google ScholarCross Ref
- Almar A. L. Kok, Marja J. Aartsen, Dorly J. H. Deeg, and Martijn Huisman. 2015. Capturing the diversity of successful aging: An operational definition based on 16-year trajectories of functioning. Gerontologist 57, 2 (2015), 240--251.Google Scholar
- Amit S. Kulkarni, Rajesh Balkrishnan, Roger T. Anderson, Heather M. Edin, Jeff Kirsch, and Mark A. Stacy. 2008. Medication adherence and associated outcomes in medicare health maintenance organization-enrolled older adults with Parkinson’s disease. Movement Disorders 23, 3 (2008), 359--365.Google ScholarCross Ref
- Paul Lamere, Philip Kwok, Evandro Gouvea, Bhiksha Raj, Rita Singh, William Walker, Manfred Warmuth, and Peter Wolf. 2003. The CMU SPHINX-4 speech recognition system. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP’03), Vol. 1. Citeseer, 2--5.Google Scholar
- Chaiwoo Lee and Joseph F. Coughlin. 2015. PERSPECTIVE: Older adults’ adoption of technology: An integrated approach to identifying determinants and barriers. J. Product Innovat. Manage. 32, 5 (2015), 747--759.Google ScholarCross Ref
- Hee Rin Lee and Laurel D. Riek. 2018. Reframing assistive robots to promote successful aging. ACM Trans. Hum.-Robot Interact. 7, 1 (2018), 11.Google ScholarDigital Library
- Matthew L. Lee and Anind K. Dey. 2011. Reflecting on pills and phone use: Supporting awareness of functional abilities for older adults. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 2095--2104.Google Scholar
- Wendy Levinson, Audiey Kao, Alma Kuby, and Ronald A. Thisted. 2005. Not all patients want to participate in decision making: A national study of public preferences. J. Gen. Internal Med. 20, 6 (2005), 531--535.Google ScholarCross Ref
- Jamy Li. 2015. The benefit of being physically present: A survey of experimental works comparing copresent robots, telepresent robots and virtual agents. Int. J. Hum. Comput. Studies 77 (Jan. 2015), 23--27.Google ScholarDigital Library
- Eric J. MacLaughlin, Cynthia L. Raehl, Angela K. Treadway, Teresa L. Sterling, Dennis P. Zoller, and Chester A. Bond. 2005. Assessing medication adherence in the elderly: Which tools to use in clinical practice? Drugs Aging 22, 3 (2005), 231--255.Google ScholarCross Ref
- C. Marras, J. C. Beck, J. H. Bower, E. Roberts, B. Ritz, G. W. Ross, R. D. Abbott, R. Savica, S. K. Van Den Eeden, A. W. Willis et al. 2018. Prevalence of Parkinson’s disease across North America. NPJ Parkinson’s Dis. 4, 1 (2018), 21.Google Scholar
- Bonnie M. Muir and Neville Moray. 1996. Trust in automation. Part II. Experimental studies of trust and human intervention in a process control simulation. Ergonomics 39, 3 (1996), 429--460.Google ScholarCross Ref
- Alan Naditz. 2008. Medication complianceâhelping patients through technology: Modern “smart” pillboxes keep memory-short patients on their medical regimen. Telemed. e-Health 14, 9 (2008), 875--880.Google ScholarCross Ref
- Lennart Nordenfelt. 2004. The varieties of dignity. Health Care Anal. 12, 2 (2004), 69--81.Google ScholarCross Ref
- Lars Osterberg and Terrence Blaschke. 2005. Adherence to medication. New Engl. J. Med. 353, 5 (2005), 487--497.Google ScholarCross Ref
- T. J. Parker. 2014. Prescribing design. Design Manage. Rev. 25, 3 (2014), 30--33.Google Scholar
- Jürgen Pripfl, Tobias Körtner, Daliah Batko-Klein, Denise Hebesberger, Markus Weninger, Christoph Gisinger, Susanne Frennert, Hakan Eftring, Margarita Antona, Ilia Adami, et al. 2016. Results of a real world trial with a mobile social service robot for older adults. In Proceedings of the 11th ACM/IEEE International Conference on Human Robot Interaction. IEEE Press, 497--498.Google ScholarCross Ref
- Ireen M. Proot, Harry F. J. M. Crebolder, Huda Huijer Abu-Saad, Ton H. G. M. Macor, and Ruud H. J. Ter Meulen. 2000. Facilitating and constraining factors on autonomy: The views of stroke patients on admission into nursing homes. Clin. Nurs. Res. 9, 4 (2000), 460--478.Google ScholarCross Ref
- Islam Qudah, Peter Leijdekkers, and Valerie Gay. 2010. Using mobile phones to improve medication compliance and awareness for cardiac patients. In Proceedings of the 3rd International Conference on PErvasive Technologies Related to Assistive Environments. ACM, 36.Google ScholarDigital Library
- M. V. Radomski and C. A. Trombly (Eds.). 2013. Occupational Therapy for Physical Dysfunction (7th ed.). Lippincott Williams 8 Wilkins.Google Scholar
- J. C. Rogers and M. B. Holm. 1994. Performance Assessment of Self-Care Skills (PASS-Home) Version 3.1 [Unpublished assessment tool]. University of Pittsburgh, Pittsburgh, PA.Google Scholar
- Richard M. Ryan, Jennifer G. La Guardia, Jessica Solky-Butzel, Valery Chirkov, and Youngmee Kim. 2005. On the interpersonal regulation of emotions: Emotional reliance across gender, relationships, and cultures. Personal Relation. 12, 1 (2005), 145--163.Google ScholarCross Ref
- Anil Sahai, Stephen K. Breede, Roger O. Topliffe, and Douglas A. Topliffe. 1999. Medication dispensing system. U.S. Patent 5,971,594.Google Scholar
- Matthias Scheutz. 2006. ADE—Steps towards a distributed development and runtime environment for complex robotic agent architectures. Appl. Artific. Intell. 20, 4--5 (2006).Google ScholarCross Ref
- Matthias Scheutz, Gordon Briggs, Rehj Cantrell, Evan Krause, Tom Williams, and Richard Veale. 2013. Novel mechanisms for natural human-robot interactions in the DIARC architecture. In Proceedings of the AAAI Workshop on Intelligent Robotic Systems.Google Scholar
- Ju Young Shin, Barbara Habermann, and Ingrid Pretzer-Aboff. 2015. Challenges and strategies of medication adherence in Parkinson’s disease: A qualitative study. Geriatr. Nurs. 36, 3 (2015), 192--196.Google ScholarCross Ref
- Candace L. Sidner, Christopher Lee, Cory D. Kidd, Neal Lesh, and Charles Rich. 2005. Explorations in engagement for humans and robots. Artific. Intell. 166, 1--2 (Aug. 2005), 140--164.Google ScholarCross Ref
- Cory-ann Smarr, Akanksha Prakash, Jenay M. Beer, Tracy L. Mitzner, Charles C. Kemp, and Wendy A. Rogers. 2012. Older adults’ preferences for and acceptance of robot assistance for everyday living tasks. In Proceedings of the Human Factors and Ergonomics Society 56th Annual Meeting. 153--157.Google Scholar
- Craig A. Smith and Phoebe C. Ellsworth. 1985. Patterns of cognitive appraisal in emotion. J. Personal. Soc. Psychol. 48, 4 (1985), 813--838.Google ScholarCross Ref
- Michael A. Steinman and Joseph T. Hanlon. 2010. Managing medications in clinically complex elders: “There’s got to be a happy medium.” J. Amer. Med. Assoc. 304, 14 (2010), 1592--1601.Google ScholarCross Ref
- Carol S. Stilley, Catherine M. Bender, Jacqueline Dunbar-Jacob, Susan Sereika, and Christopher M. Ryan. 2010. The impact of cognitive function on medication management: Three studies. Health Psychol. 29, 1 (2010), 50.Google ScholarCross Ref
- P. Tiwari, J. Warren, K. Day, and C. Datta. 2011. Comprehensive support for self management of medications by a networked robot for the elderly. In Proceedings of the Health Informatics New Zealand 10th Annual Conference and Exhibition.Google Scholar
- Martijn van der Eijk, Frouke A. P. Nijhuis, Marjan J. Faber, and Bastiaan R. Bloem. 2013. Moving from physician-centered care towards patient-centered care for Parkinson’s disease patients. Parkinson. Relat. Disord. 19, 11 (2013), 923--927.Google ScholarCross Ref
- Kazuyoshi Wada, Takanori Shibata, Tomoko Saito, Kayoko Sakamoto, and Kazuo Tanie. 2005. Psychological and social effects of one year robot assisted activity on elderly people at a health service facility for the aged. In Proceedings of the IEEE International Conference on Robotics and Automation, Vol. 2005. 2785--2790.Google ScholarCross Ref
- R. L. Wade, B. Clancey, and J. Michaeli. 2016. Improvement in antihypertensive and cholesterol-lowering medication persistence using a mobile technology application. Value Health 19, 3 (2 2016), A306.Google Scholar
- Kieran Walsh and Aoife Callan. 2011. Perceptions, preferences, and acceptance of information and communication technologies in older-adult community care settings in Ireland: A case-study and ranked-care program analysis. Ageing Int. 36, 1 (2011), 102--122.Google ScholarCross Ref
- Ilene Warner. 1998. Telemedicine in home health care: The current status of practice. Home Health Care Manage. Pract. 10, 2 (1998), 62--68.Google Scholar
- Netta Weinstein, Andrew K. Przybylski, and Richard M. Ryan. 2012. The index of autonomous functioning: Development of a scale of human autonomy. J. Res. Personal. 46, 4 (2012), 397--413.Google ScholarCross Ref
- Jason R. Wilson, Nah Young Lee, Annie Saechao, Sharon Hershenson, Matthias Scheutz, and Linda Tickle-Degnen. 2017. Hand gestures and verbal acknowledgments improve human-robot rapport. In Proceedings of the International Conference on Social Robotics. Springer, 334--344.Google ScholarCross Ref
- Jason R. Wilson, Nah Young Lee, Annie Saechao, and Matthias Scheutz. 2016. Autonomy and dignity : Principles in designing effective social robots to assist in the care of older adults. In Proceedings of the Workshop on Using Social Robots to Improve the Quality of Life in the Elderly (ICSR’16).Google Scholar
- Jason R. Wilson, Nah Young Lee, Annie Saechao, Linda Tickle-Degnen, and Matthias Scheutz. 2016. Designing a social robot to assist in medication sorting. In Social Robotics (ICSR’16), A. Agah, J. J. Cabibihan, A. Howard, M. Salichs, and H. He (Eds.). Lecture Notes in Computer Science, vol. 9979. Springer, Cham. https://link.springer.com/chapter/10.1007/978-3-319-47437-3_21.Google Scholar
- Jason R. Wilson, Linda Tickle-Degnen, and Matthias Scheutz. 2016. Designing a social robot to assist in medication sorting. In Proceedings of the International Conference on Social Robotics. Springer International Publishing, 211--221.Google ScholarCross Ref
- Jason R. Wilson, Michael Wransky, and Jorge Tierno. 2018. General approach to automatically generating need-based assistance. In Proceedings of the 6th Annual Conference on Advances in Cognitive Systems.Google Scholar
Index Terms
- Challenges in Designing a Fully Autonomous Socially Assistive Robot for People with Parkinson’s Disease
Recommendations
Navigating Real-World Challenges: A Quadruped Robot Guiding System for Visually Impaired People in Diverse Environments
CHI '24: Proceedings of the CHI Conference on Human Factors in Computing SystemsBlind and Visually Impaired (BVI) people find challenges in navigating unfamiliar environments, even using assistive tools such as white canes or smart devices. Increasingly affordable quadruped robots offer us opportunities to design autonomous guides ...
A review of assistive technologies for people with Parkinson's disease
Smart Environments: Technology to Support HealthcareThe population is aging and with this, the incidence of age related diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD) are increasing. Assistive Technology (AT) is viewed as one of the possible solutions which can be used to meet the ...
Evaluation of Human Robot Interaction Factors of a Socially Assistive Robot Together with Older People
CISIS '12: Proceedings of the 2012 Sixth International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS)This paper describes the evaluation of human-robot-interaction (HRI) related to the future use of a humanoid robotic system as interface in intelligent home environments. The core motivation was to enhance the user interaction between smart home systems ...
Comments