Design of an Affordable Socially Assistive Robot for Remote Health and Function Monitoring and Prognostication
To address shortages in rehabilitation clinicians and provide for the growing numbers of elder and disabled patients needing rehabilitation, we have been working towards developing an affordable socially assistive robot for remote therapy and health monitoring. Our system is being designed to initially work via remote control, while addressing some of the challenges of traditional telepresence. To understand how to design a system to meet the needs of elders, we created a mobile therapy robot prototype from two commercial robots and demonstrated this system to clinicians in two types of rehabilitation care settings: a daycare setting and a inpatient rehabilitation setting. We propose to introduce the prototype as a social and therapy agent into clinician-patient interactions with the aim of improving the quality of information transfer between the clinician and the patient. This paper describes an investigative effort to understand how clinicians who work with elders accept this prototype. Clinicians from each setting differed in their needs for the robot. Those in daycare settings preferred a more social robot to encourage and motivate elders to exercise
as well as monitor their health. Clinicians in the inpatient rehabilitation setting desired a robot with more therapeutic and treatment capabilities. Both groups wanted a robot with some autonomy that was portable, maintainable, affordable, and durable. We discuss these results in detail along with the ethical implications of increasing the robot’s autonomy and suggest additional requirements for achieving a smarter robot that can meet the clinicians’ social, health monitoring and prognostication desires.
Intelligent Health Monitoring, Socially Assistive Robotics, Rehabilitation Robotics, Telepresence, Human-centered computing
Breazeal, C. (2003). Toward sociable robots. In Robotics and autonomous systems (Vol. 42, pp. 167–175). doi: 10.1016/S0921-8890(02)00373-1
Brown, D., Boden-Albala, B., Langa, K., Lisabeth, L., Fair, M., Smith, M., . . . Morgenstern, L. (2006). Projected costs of ischemic stroke in the
united states. Neurology, 67(8), 1390-1395. doi: 10.1212/01.wnl.0000237024.16438.20
Calderita, L., Bustos, P., Suarez Mejias, C., Fernandez, F., & Bandera, A. (2013). Therapist: Towards an autonomous socially interactive robot for motor and neurorehabilitation therapies for children. In Proceedings of the 2013 7th international conference on pervasive computing technologies for healthcare and workshops, pervasivehealth 2013 (p. 374-377). doi: 10.4108/icst.pervasivehealth.2013.252348
Christensen, K., Doblhammer, G., Rau, R., & Vaupel, J. (2009). Ageing populations: the challenges ahead. The Lancet, 374(9696), 1196-1208. doi: 10.1016/S0140-6736(09)61460-4
Demaerschalk, B. M., Hwang, H. M., & Leung, G. (2010). US cost burden of ischemic stroke: A systematic literature review. American Journal of Managed Care. doi: 12684 [pii]
Eng, C., Pedulla, J., Eleazer, G., McCann, R., & Fox, N. (1997). Program of all-inclusive care for the elderly (pace): An innovative model of integrated geriatric care and financing. Journal of the American Geriatrics Society, 45(2), 223-232. doi: 10.1111/j.1532-5415.1997.tb04513.x
Fasola, J., & Mataric, M. (2013). A socially assistive robot exercise coach for the elderly. Journal of Human-Robot Interaction, 2(2), 3–32.
Freedman, V. A., & Spillman, B. C. (2014). The residential continuum from home to nursing home: size, characteristics and unmet needs of older adults. The journals of gerontology. Series B, Psychological sciences and social sciences, 69, S42–S50. doi: 10.1093/geronb/gbu120
González, J. C., Pulido, J. C., & Fernández, F. (2017, June). A three-layer planning architecture for the autonomous control of rehabilitation therapies based on social robots. Cognitive Systems Research, 43, 232–249. doi: 10.1016/j.cogsys.2016.09.003
Hirth, V., Baskins, J., & Dever-Bumba, M. (2009). Program of all-inclusive care (pace): Past, present, and future. Journal of the American Medical Directors Association, 10(3), 155-160. doi: 10.1016/j.jamda.2008.12.002
Jesus, T., Landry, M., Dussault, G., & Fronteira, I. (2017). Human resources for health (and rehabilitation): Six rehab-workforce challenges for the century. Human Resources for Health, 15(1). doi: 10.1186/s12960-017-0182-7
Jette, D., Latham, N., Smout, R., Gassaway, J., Slavin, M., & Horn, S. (2005). Physical therapy interventions for patients with stroke in inpatient rehabilitation facilities. Physical Therapy, 85(3), 238-248.
Johnson, M. J., Johnson, M. A., Sefcik, J. S., Cacchione, P. Z., Mucchiani, C., Lau, T., & Yim, M. (2017). Task and design requirements for an affordable mobile service robot for elder care in an all-inclusive care for elders assisted-living setting. International Journal of Social Robotics, 1–20.
Kuwamura, K., Yamazaki, R., Nishio, S., & Ishiguro, H. (2014). Elderly care using teleoperated android telenoid. Gerontechnology, 13(2), 226. doi:
Lin, V., Zhang, X., & Dixon, P. (2015). Occupational therapy workforce in the united states: Forecasting nationwide shortages. PM and R, 7(9), 946-954. doi: 10.1016/j.pmrj.2015.02.012
López Recio, D., Márquez Segura, L., Márquez Segura, E., & Waern, A. (2013). The nao models for the elderly. In Acm/ieee international conference
on human-robot interaction (p. 187-188). doi: 10.1109/HRI.2013.6483564
Mast, M., Burmester, M., Graf, B., Weisshardt, F., Arbeiter, G., Španěl, M., . . . Kronreif, G. (2015). Design of the human-robot interaction for a semi-autonomous service robot to assist elderly people. In Ambient assisted living (pp. 15–29). Springer.
Miskam, M., Hamid, M., Yussof, H., Shamsuddin, S., Malik, N., & Basir, S. (2013). Study on social interaction between children with autism and humanoid robot nao. Applied Mechanics and Materials, 393, 573-578. doi: 10.4028/www.scientific.net/AMM.393.573
Mitzner, T., Chen, T., Kemp, C., & Rogers, W. (2014). Identifying the potential for robotics to assist older adults in different living environments. International Journal of Social Robotics, 6(2), 213-227. doi: 10.1007/s12369-013-0218-7
Ovbiagele, B., Goldstein, L., Higashida, R., Howard, V., Johnston, S., Khavjou, O., . . . Trogdon, J. (2013). Forecasting the future of stroke in the united states: A policy statement from the american heart association and american stroke association. Stroke, 44(8), 2361-2375. doi: 10.1161/STR.0b013e31829734f2
Oyeyemi, A. (2001). Job satisfaction traits of nigerian physical therapists. Physiotherapy Theory and Practice, 17(4), 257-268. doi: 10.1080/095939801753385753
Patoglu, V., Ertek, G., Oz, O., Zoroglu, D., & Kremer, G. (2010). Design requirements for a tendon rehabilitation robot: Results from a survey of engineers and health professionals. In Proceedings of the asme design engineering technical conference (Vol. 6, p. 85-94). doi:
Rathore, F., New, P., & Iftikhar, A. (2011). A report on disability and rehabilitation medicine in pakistan: Past, present, and future directions. Archives of Physical Medicine and Rehabilitation, 92(1), 161-166. doi: 10.1016/j.apmr.2010.10.004
Reynolds, E. M., Grujovski, A., Wright, T., Foster, M., & Reynolds, H. N. (2012). Utilization of robotic “remote presence” technology within north american intensive care units. Telemedicine and e-Health, 18(7), 507–515.
Rutledge, C., Haney, T., Bordelon, M., Renaud, M., & Fowler, C. (2014). Telehealth: Preparing advanced practice nurses to address healthcare needs in rural and underserved populations. International Journal of Nursing Education Scholarship, 11(1). doi: 10.1515/ijnes-2013-0061
Scassellati, B., Admoni, H., & Matari´c, M. (2012). Robots for use in autism research. Annual Review of Biomedical Engineering, 14, 275-294. doi: 10.1146/annurevbioeng-071811-150036
Schulz, R., Wahl, H.-W., Matthews, J., De Vito Dabbs, A., Beach, S., & Czaja, S. (2015). Advancing the aging and technology agenda in gerontology. Gerontologist, 55(5), 724-734. doi: 10.1093/geront/gnu071
Schwabacher, M., & Goebel, K. (2007). A Survey of Artificial Intelligence for Prognostics. The Intelligence Report. In Association for the advancement of artificial intelligence aaai fall symposium 2007.
Seelye, A., Wild, K., Larimer, N., Maxwell, S., Kearns, P., & Kaye, J. (2012). Reactions to a remote-controlled video-communication robot in seniors’ homes: A pilot study of feasibility and acceptance. Telemedicine and e-Health, 18(10), 755-759. doi: 10.1089/tmj.2012.0026
Sefcik, J., Johnson, M., Yim, M., Lau, T., Vivio, N., Mucchiani, C., & Cacchione, P. (2018). Stakeholders’ perceptions sought to inform the development of a low-cost mobile robot for older adults: A qualitative descriptive study. Clinical Nursing Research, 27(1), 61-80. doi: 10.1177/1054773817730517
Smarr, C.-A., Mitzner, T., Beer, J., Prakash, A., Chen, T., Kemp, C., & Rogers, W. (2014). Domestic robots for older adults: Attitudes, preferences, and potential. International Journal of Social Robotics, 6(2), 229-247. doi: 10.1007/s12369-013-0220-0
Sorbello, R., Chella, A., Calí, C., Giardina, M., Nishio, S., & Ishiguro, H. (2014). Telenoid android robot as an embodied perceptual social regulation medium engaging natural human-humanoid interaction. Robotics and Autonomous Systems, 62(9), 1329–1341. doi: 10.1016/j.robot.2014.03.017
Torta, E., Oberzaucher, J.,Werner, F., Cuijpers, R. H., & Juola, J. F. (2012). Attitudes towards socially assistive robots in intelligent homes: results from laboratory studies and field trials. Journal of Human-Robot Interaction, 1(2), 76–99.
Tsui, K., Norton, A., Brooks, D., McCann, E., Medvedev, M., Allspaw, J., . . . Yanco, H. (2014). Iterative design of a semi-autonomous social telepresence robot research platform: A chronology. Intelligent Service Robotics, 7(2), 103-119. doi: 10.1007/s11370-014-0148-8
Van Den Berg, N., Schumann, M., Kraft, K., & Hoffmann, W. (2012). Telemedicine and telecare for older patients - a systematic review. Maturitas, 73(2), 94-114. doi: 10.1016/j.maturitas.2012.06.010
Vermeersch, P., Sampsel, D., & Kleman, C. (2015). Acceptability and usability of a telepresence robot for geriatric primary care: A pilot. Geriatric Nursing, 36(3), 234-238. doi: 10.1016/j.gerinurse.2015.04.009
VGo Communication. (2011). Extending the reach of care - vgo com (Tech. Rep.).
Wilk, R., & Johnson, M. J. (2014). Usability feedback of patients and therapists on a conceptual mobile service robot for inpatient and home-based stroke rehabilitation. In Biomedical robotics and biomechatronics (2014 5th ieee ras & embs international conference on (pp. 438–443).
Zimbelman, J., Juraschek, S., Zhang, X., & Lin, V.-H. (2010). Physical therapy workforce in the united states: Forecasting nationwide shortages. PM and R, 2(11), 1021-1029. doi: 10.1016/j.pmrj.2010.06.015