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Paladyn, Journal of Behavioral Robotics

Editor-in-Chief: Schöner, Gregor


Covered by SCOPUS


CiteScore 2018: 2.17

SCImago Journal Rank (SJR) 2018: 0.336
Source Normalized Impact per Paper (SNIP) 2018: 1.707

ICV 2018: 120.52

Open Access
Online
ISSN
2081-4836
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Differences between young and old users when interacting with a humanoid robot: a qualitative usability study

Ronit Feingold-Polak
  • Recanati School for Community Health Professions, Department of Physical Therapy, Ben Gurion University of the Negev, Beer-Sheva, Israel
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Avital Elishay / Yonat Shahar / Maayan Stein / Yael Edan / Shelly Levy-Tzedek
  • Corresponding author
  • Recanati School for Community Health Professions, Department of Physical Therapy, Ben Gurion University of the Negev, Beer-Sheva, Israel and Zlotowski Center for Neuroscience, Ben Gurion University of the Negev, Beer-Sheva, Israel
  • Email
  • Other articles by this author:
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Published Online: 2018-08-22 | DOI: https://doi.org/10.1515/pjbr-2018-0013

Abstract

With the aging of the population worldwide, humanoid robots are being used with an older population, e.g., stroke patients and people with dementia. There is a growing body of knowledge on how people interact with robots, but limited information on the difference between young and old adults in their preferences when interacting with humanoid robots and what factors influence these preferences.We developed a gamified robotic platform of a cognitive-motor task.We conducted two experiments with the following aims: to test how age, location of touch interaction (touching the robot’s tablet or hand), and embodied presence of a humanoid robot affect the motivation of different age-group users to continue performing a cognitive-motor task. A total of 60 participants (30 old adults and 30 young adults) took part in two experiments with the humanoid Pepper robot (Softbank robotics). Both old and young adults reported they enjoyed the interaction with the robot as they found it engaging and fun, and preferred the embodied robot over the non-embodied computer screen. This study highlights that in order for the experience of the user to be positive a personalization of the interaction according to the age, the needs of the user, the characteristics, and the pace of the task is needed.

Keywords: socially assistive robots; human-robot interaction; old adults; young adults; aging; gamification; presence; embodiment; timing

References

  • [1] OECD, Population statistics, Organization for Economic Cooperation and Development, 2004, http://www.oecd.orgGoogle Scholar

  • [2] H. I. Krebs, B. T. Volpe, Rehabilitation robotics, Handbook of Clinical Neurology, 2013, 110, 283-294, DOI:10.1016/B978-0- 444-52901-5.00023-XCrossrefGoogle Scholar

  • [3] D. J. Feil-Seifer, M. J. Mataric, Defining socially assistive robotics, 9th International Conference on Rehabilitation Robotics (ICORR 2005), 2005, 465-468, DOI: 10.1109/ICORR.2005.1501143CrossrefGoogle Scholar

  • [4] J. Fassola, M. J. Mataric, Using socially assistive human-robot interaction to motivate physical exercise for older adults, In: Proceedings of the IEEE, 2012, 100(8), 2512-2526, DOI: 10.1109/JPROC.2012.2200539Google Scholar

  • [5] S. Šabanović, C. C. Bennett, W. L. Chang, L. Huber, PARO robot affects diverse interaction modalities in group sensory therapy for older adults with dementia, 2013 IEEE 13th International Conference on Rehabilitation Robotics (ICORR), Seattle, WA, 2013, 1-6, DOI: 10.1109/ICORR.2013.6650427CrossrefGoogle Scholar

  • [6] W-Y. G. Louie, D. McColl, G. Nejat, Acceptance and attitudes toward a human-like socially assistive robot by older adults, Assistive Technology, 2014, 26(3), 140-150, DOI: 10.1080/10400435.2013.869703Web of ScienceCrossrefGoogle Scholar

  • [7] M. J. Mataric, J. Eriksson, D. J. Feil-Seifer, C. J.Winstein, Socially assistive robotics for post-stroke rehabilitation, Journal of NeuroEngineering and Rehabilitation, 2007, 4 (5), https://doi.org/10.1186/1743-0003-4-5CrossrefGoogle Scholar

  • [8] A. Tapus, C. Tapus, M. J. Mataric, The use of socially assistive robots in the design of intelligent cognitive therapies for people with dementia, IEEE International Conference on Rehabilitation Robotics (ICORR), Kyoto International Conference Center, 2009, 924-929, DOI: 10.1109/ICORR.2009.5209501.Google Scholar

  • [9] T. Nomura, M. Sasa, Investigation of differences on impressions of and behaviors toward real and virtual robots between elder people and university students, 2009 IEEE International Conference on Rehabilitation Robotics (ICORR), Kyoto International Conference Center, 2009, 934-939, DOI: 10.1109/ICORR.2009.5209626CrossrefGoogle Scholar

  • [10] N. Ezer, A. D. Fisk, W. A. Rogers, More than a servant: self-reported willingness of younger and older adults to having a robot perform interactive and critical tasks in the home, In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 2009, 53(2), 136-140, DOI: 10.1177/154193120905300206Google Scholar

  • [11] A. J. Mitchell, A meta-analysis of the accuracy of the mini-mental state examination in the detection of dementia and mild cognitive impairment, Journal of Psychiatric Research, 2009, 43(4), 411-431CrossrefWeb of ScienceGoogle Scholar

  • [12] L. D. Riek, Wizard of Oz studies in HRI: a systemic review and new reporting guidelines, Journal of Human-Robot Interaction, 2012, 1(1), 119-136Google Scholar

  • [13] C. Bartneck, D. Kulić, E. Croft, S. Zoghbi, Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots, International Journal of Humanoid Robots, 2009, 1, 71-81, DOI: 10.1007/s12369-008-0001-3CrossrefGoogle Scholar

  • [14] M. Lohse, Bridging the gap between users’ expectations and system evaluations, 20th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN 2011), Atlanta, GA, 2011, 485-490, DOI: 10.1109/ROMAN.2011.6005252CrossrefGoogle Scholar

  • [15] C. Comito, M. Caniot, E. Largue, P. Coignard, C. Fattal, Psychological and symbolic determinants relating to the first meeting with a humanoid robot, Annals of Physical and Rehabilitation Medicine, 2016, 59s, e87-e89Google Scholar

  • [16] K. L. Koay, D. S. Syrdal, M. L.Walters, K. Dautenhahn, Livingwith robots: investigating the habituation effect in participants’ preferences during a longitudinal human-robot interaction study, 16th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN 2007), Jeju, 2007, 564-569, DOI:10.1109/ROMAN.2007.4415149CrossrefGoogle Scholar

  • [17] I. Leite, C. Martinho, A. Paiva, Social robots for long-term interaction: a survey, International Journal of Humanoid Robotics, 2013, 5(2), 291-308, https://DOI.org/10.1007/s12369-013-0178-yCrossrefGoogle Scholar

  • [18] V. Chidambaram, Y.-H. Chiang, B. Mutlu, Designing persuasive robots: howrobots might persuade people using vocal and nonverbal cues, In: HRI ’12 Proceedings of the 7th annual ACM/IEEE International Conference on Human-Robot Interaction, 2012, 293-300, DOI: 10.1145/2157689.2157798CrossrefGoogle Scholar

  • [19] J. Han, N. Campbell, K. Jokinen, G. Wilcock, Investigating the use of non-verbal cues in human-robot interaction with a Nao robot, 2012 IEEE 3rd International Conference on Cognitive Infocommunications (CogInfoCom), Kosice, Slovakia, 2012, 679-683, DOI: 10.1109/CogInfoCom.2012.6421937CrossrefGoogle Scholar

  • [20] A. Aly, A. Tapus, A model for synthesizing a combined verbal and nonverbal behavior based on personality traits in humanrobot interaction, 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI), Tokyo, Japan, 2013, 325-332, DOI: 10.1109/hri.2013.6483606Google Scholar

  • [21] M. Salem, F. Eyssel, K. Rohlfing, S. Kopp, F. Joublin, To Err is human (-like): effects of robot gesture on perceived anthropomorphism and likability, International Journal of Social Robotics, 2013, 5(3), 313-323, DOI: 10.1007/s12369-0130196-9CrossrefGoogle Scholar

  • [22] S. O. Adalgeirsson, C. Breazeal, MeBot: a robotic platform for socially embodied telepresence, 2010 5th ACM/IEEE International Conference on Human-Robot Interaction (HRI), Osaka, Japan, 2010, 15-22, DOI: 10.1109/hri.2010.5453272CrossrefGoogle Scholar

  • [23] H. Z. H Mamode, P. Bremner, A. G. Pipe, B. Carse, Cooperative tabletop working for humans and humanoid robots: Group interaction with an avatar, 2013 IEEE International Conference on Robotics and Automation, Karlsruhe, Germany, 2013, 184-190, DOI: 10.1109/ICRA.2013.6630574CrossrefGoogle Scholar

  • [24] J. A.Mann, B. A.MacDonald, I.-Han Kuo, X. Li, E. Broadbent, People respond better to robots than computer tablets delivering healthcare instructions, Computers in Human Behavior, 2015, 43, 112-117Web of ScienceGoogle Scholar

  • [25] K. M Lee, Y. Jung, J. Kim, S. R. Kim, Are physically embodied social agents better than disembodied social agents?: The effects of physical embodiment, tactile interaction, and people’s loneliness in human-robot interaction, International Journal of Human-Computer Studies, 2006, 64(10), 962-973Google Scholar

  • [26] A. Gentsch, A. Panagiotopoulou, A. Fotopoulou, Active interpersonal touch gives rise to the social softness illusion, Current Biology, 2015, 21, 25(18), 2392-2397Web of ScienceGoogle Scholar

  • [27] R. Mead, M. J. Mataric, Robots have needs too: how and why people adapt their proxemic behavior to improve robot social signal understanding, Journal of Human Robot Interaction, 2016, 5(2), 48-68Google Scholar

  • [28] P. Kellmeyer, O. Mueller, R. Feingold-Polak, S. Levy-Tzedek, Social robots in rehabilitation: A question of trust, Science Robotics, (in press)Google Scholar

  • [29] D. Eizicovits, Y. Edan, I. Tabak, S. Levy-Tzedek, Robotic gaming prototype for upper limb exercise: Effects of age and embodiment on user preferences and movement, Restorative Neurology and Neuroscience, 2018, 36(2), 261-274, DOI:10.3233/RNN-170802Web of ScienceCrossrefGoogle Scholar

  • [30] S. Kashi, S. Levy-Tzedek, Smooth leader or sharp follower? Playing the mirror game with a robot, Restorative Neurology and Neuroscience, 2018, 36(2), 147-159, DOI 10.3233/RNN-170756.CrossrefGoogle Scholar

About the article

Received: 2017-12-29

Accepted: 2018-06-12

Published Online: 2018-08-22


Citation Information: Paladyn, Journal of Behavioral Robotics, Volume 9, Issue 1, Pages 183–192, ISSN (Online) 2081-4836, DOI: https://doi.org/10.1515/pjbr-2018-0013.

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© 2018 Ronit Feingold-Polak, et al., published by De Gruyter. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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