Publication: Long-Term Social Human-Robot Interaction for Neurorehabilitation: Robots as a Tool to Support Gait Therapy in the Pandemic
Abstract (Spanish)
Abstract (English)
Extent
Collections
Collections
References
Agrigoroaie, R. M., and Tapus, A. (2016). “Developing a healthcare robot with personalized behaviors and social skills for the elderly,” in International Conference on Human Robot Interaction (Christchurch). doi: 10.1109/HRI.2016.7451870
Aymerich-Franch, L. (2020). Why it is time to stop ostracizing social robots. Nat. Mach. Intell. 2:364. doi: 10.1038/s42256-020-0202-5
Bickmore, T. W., and Picard, R. W. (2005). Establishing and maintaining long-term human- computer relationships. ACM Trans. Comput. Hum. Interact. 2, 617–638. doi: 10.1145/1067860. 1067867
Campa, R., and Campa, R. (2016). The rise of social robots: a review of the recent literature. J. Evol. Technol. 26, 106–113.
Carrillo, F. M., Butchart, J., Knight, S., Scheinberg, A., Wise, L., Sterling, L., et al. (2017). Adapting a general purpose social robot for paediatric rehabilitation through in-situ design. ACM Trans. Hum. Robot Interact. 7, 1–30. doi: 10.1145/3203304
Casas, J., Senft, E., Gutierrez, L., Rincon-Roncancio, M., Munera, M., Belpaeme, T., et al. (2020). Social assistive robots: assessing the impact of a training assistant robot in cardiac rehabilitation. Int. J. Soc. Robot. 12, 1–15. doi: 10.1007/s12369-020-00708-y
Casas, J. A., Céspedes, N., Cifuentes, C. A., Gutierrez, L. F., RincónRoncancio, M., and Múnera, M. (2019). Expectation vs. reality: attitudes towards a socially assistive robot in cardiac rehabilitation. Appl. Sci. 9:4651. doi: 10.3390/app9214651
Cespedes, N., Munera, M., Gomez, C., and Cifuentes, C. A. (2020). Social humanrobot interaction for gait rehabilitation. IEEE Trans. Neural Syst. Rehabil. Eng. 18, 1299–1307. doi: 10.1109/TNSRE.2020.2987428
Cifuentes, C. A., Pinto, M. J., Céspedes, N., and Múnera, M. (2020). Social robots in therapy and care. Curr. Robot. Rep. 28, 1–16. doi: 10.1007/s43154-020-00009-2
Compagnant, M., Daviet, J. C., Mandigout, S., Lcroix, J., Vuillerme, N., and Salle, J. Y. (2017). Reliability of the rating of perceived exertion (Borg Scale) in post-stroke during 2 tasks of daily life. Ann. Phys. Rehabil. Med. 60, e1–e2. doi: 10.1016/j.rehab.2017.07.017
Daroff, R. (2016). Bradley’s Neurology in Clinical Practice. London: Elsevier.
Duffy, B. R., Rooney, C. F. B., Hare, G. M. P. O., and Donoghue, R. P. S. O. (1999). “What is a social robot?” in 10th Irish Conference on Artificial Intelligence Cognitive Science (Ireland), 1–3
Fasola, J., and Mataric, M. J. (2010). “Robot exercise instructor: a socially assisti ´ ve robot system to monitor and encourage physical exercise for the elderly,” in Proceedings - IEEE International Workshop on Robot and Human Interactive Communication (Viareggio), 416–421. doi: 10.1109/ROMAN.2010.5598658
Feil-Seifer, D., and Mataric, M. J. (2011). Socially assistive robotics. ´ IEEE Robot. Automat. Mag. 18, 24–31. doi: 10.1109/MRA.2010.940150
Gittler, M., and Andrew, M. D. (2018). Guidelines for adult stroke rehabilitation and recovery. JAMA 319, 820–821. doi: 10.1001/jama.2017.22036
Heerink, M., Kröse, B., Evers, V., and Wielinga, B. (2010). Assessing acceptance of assistive social agent technology by older adults: the almere model. Int. J. Soc. Robot. 2, 361–375. doi: 10.1007/s12369-010-0068-5
Heerink, M., Vanderborght, B., Broekens, J., and Albo-Canals, J. (2016). New friends: social robots in therapy and education. Int. J. Soc. Robot. 8, 443–444. doi: 10.1007/s12369-016-0374-7
Hollander, J. E., and Carr, B. G. (2020). Virtually perfect? Telemedicine for Covid-19. N. Engl. J. Med. 382, 1679–1681. doi: 10.1056/NEJMp2003539
Jarvis, C. I., Van Zandvoort, K., Gimma, A., Prem, K., Auzenbergs, M., O’Reilly, K., et al. (2020). Quantifying the impact of physical distance measures on the transmission of COVID-19 in the UK. BMC Med. 18:124. doi: 10.1186/s12916-020-01597-8
Kasap, Z., and Magnenat-Thalmann, N. (2012). Building long-term relationships with virtual and robotic characters: the role of remembering. Vis. Comput. 28, 87–97. doi: 10.1007/s00371-011-0630-7
Khaleghi, A., Mohammadi, M. R., Jahromi, G. P., and Zarafshan, H. (2020). New ways to manage pandemics: using technologies in the era of COVID-19, a narrative review. Iran J. Psychiatry 15, 236–242. doi: 10.18502/ijps.v15i3.3816
Kozyavkin, V., Kachmar, O., and Ablikova, I. (2014). “Humanoid social robots in the rehabilitation of children with cerebral palsy,” in Proceedings - REHAB 2014 (Tomar), 430–431. doi: 10.4108/icst.pervasivehealth.2014.255323
Leocani, L., Diserens, K., Moccia, M., and Caltagirone, C. (2020). Disability through COVID-19 pandemic: neurorehabilitation cannot wait. Eur. J. Neurol. 27, 50–51. doi: 10.1111/ene.14320
Libin, A. V., and Libin, E. V. (2004). Person-robot interactions from the robopsychologists’ point of view: the robotic psychology and robotherapy approach. Proc. IEEE 92, 1789–1803. doi: 10.1109/JPROC.2004.835366
Martín, A., Pulido, J. C., González, J. C., García-Olaya, Á., and Suárez, C. (2020). A framework for user adaptation and profiling for social robotics in rehabilitation. Sensors 20, 1–23. doi: 10.3390/s20174792
Mataric, M. J., Eriksson, J., Feil-Seifer, D. J., and Winstein, C. J. ( ´ 2007). Socially assistive robotics for post-stroke rehabilitation. J. Neuroeng. Rehabil. 4:5. doi: 10.1186/1743-0003-4-5
Peleka, G., Kargakos, A., Skartados, E., Kostavelis, J., Giakoumis, D., Sarantopoulos, I., et al. (2018). “RAMCIP - a service robot for MCI patients at home,” in 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (Madrid), 1–9
Polak, R. F., and Levy-Tzedek, S. (2020). “A social robot for rehabilitation: expert clinicians and post-stroke patients’ evaluation following a longterm intervention,” in ACM/IEEE International Conference on Human-Robot Interaction (New York, NY: IEEE Computer Society), 151–160.
Pulido, J. C., González, J. C., Suárez-Mejías, C., Bandera, A., Bustos, P., and Fernández, F. (2017). Evaluating the child-robot interaction of the NAOTherapist platform in pediatric rehabilitation. Int. J. Soc. Robot. 9, 343–358. doi: 10.1007/s12369-017-0402-2
Robinson, H., MacDonald, B., Kerse, N., and Broadbent, E. (2013). The psychosocial effects of a companion robot: a randomized controlled trial. J. Am. Med. Direct. Assoc. 14, 661–667. doi: 10.1016/j.jamda.2013.02.007
Russo, L., and Trabacca, A. (2020). The ethic of care, disability and rehabilitation during the Covid-19 pandemic. Pediatr. Neurol. 111:39. doi: 10.1016/j.pediatrneurol.2020.06.006
Sabelli, A., Way, M., and Hagita, N. (2011). “A conversational robot in an elderly care center: an ethnographic study,” in HRI 2011 - Proceedings of the 6th ACM/IEEE International Conference on Human-Robot Interaction (Lausanne), 37–44. doi: 10.1145/1957656.1957669
Sakel, M., Saunders, K., Chandi, J., Haxha, S., and Faruqui, R. (2020). Neurorehabilitation service during COVID-19 pandemic: best practices from UK. J. Pakistan Med. Assoc. 70, S136–S140. doi: 10.5455/JPMA.33
Sante, H. A. D. (2012). Accident Vasculaire Cerebral: Methodes de Reeducation de la fonction Motrice chez l’adulte. Haute Autorite de Sante, Saint-Denis La Plaine Cedex.
Scassellati, B., and Vázquez, M. (2020). The potential of socially assistive robots during infectious disease outbreaks. Sci. Robot. 5:eabc9014. doi: 10.1126/scirobotics.abc9014
Swinnen, E., Lefeber, N., Willaert, W., De Neef, F., Bruyndonckx, L., Spooren, A., et al. (2017). Motivation, expectations, and usability of a driven gait orthosis in stroke patients and their therapists. Top. Stroke Rehabil. 24, 299–308. doi: 10.1080/10749357.2016.1266750
Tavakoli, M., Carriere, J., and Torabi, A. (2020). Robotics, smart wearable technologies, and autonomous intelligent systems for healthcare during the COVID-19 pandemic: an analysis of the state of the art and future vision. Adv. Intell. Syst. 2:2000071. doi: 10.1002/aisy.202000071
Weaver, L. J., and Ferg, A. L. (2020). Therapeutic measurement and testing. Clifton Park, NY: Delmar Cengage Learning
WHO (2020). Coronavirus Disease 2019, Situation Report-192. doi: 10.1213/XAA.0000000000001218
Wilcoxon, F. (1945). Individual comparisons by ranking methods. Biometr. Bull. 1:80. doi: 10.2307/3001968
Winkle, K., Caleb-Solly, P., Turton, A., and Bremner, P. (2018). “Social robots for engagement in rehabilitative therapies: design implications from a study with therapists,” in Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction (HRI ’18) (New York, NY: Association for Computing Machinery), 289–297. doi: 10.1145/3171221.3171273
Yang, L., Cheng, H., Hao, J., Ji, Y., and Kuang, Y. (2015). “A survey on media interaction in social robotics,” in Lecture Notes in Computer Science (Gwangju: Springer Verlag), 181–190. doi: 10.1007/978-3-319-24078-7_18
Zhang, J., Litvinova, M., Liang, Y., Wang, Y., Wang, W., Zhao, S., et al. (2020). Changes in contact patterns shape the dynamics of the COVID-19 outbreak in China. Science 368, 1481–1486. doi: 10.1126/science.abb8001