Abstract
Social and assistive robots have been widely discussed in the context of psychological interventions. These studies have confirmed that facial and body expressions increase perceived safety during human-robot interaction. In this paper, we present the design of a social assistive humanoid robot with articulated robotic arms intended to deliver telepsychological interventions. The design of the robot is presented, including the description of its features for interactive communication. The robot’s design and basic nonverbal communication were evaluated through an online behavioral experiment designed to examine the perceived valence and meaning of its gestures and the overall appraisal of its appearance. We found that the design of the telepresence robot was positively assessed by a sample (N = 34) of STEM-related participants according to Godspeed metrics. Moreover, we observed that the robot was able to perform gestures that were correctly identified and discerned in terms of their valence.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Stasse , O., Flayols, T.: An overview of humanoid robots technologies. In: Venture, G., Laumond, J.-P., Watier, B. (eds.) Biomechanics of Anthropomorphic Systems, vol. 124, pp. 281–310. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-93870-713
Rabbitt, S.M., Kazdin, A.E., Scassellati, B.: Integrating socially assistive robotics into mental healthcare interventions: applications and recommendations for expanded use. Clin. Psychol. Rev. 35, 35–46 (2015). https://doi.org/10.1016/j.cpr.2014.07.001
Feil-Seifer, D., Mataric, M.J.: Socially assistive robotics. In: 9th International Conference on Rehabilitation Robotics, ICORR 2005, Chicago, IL, USA, pp. 465–468 (2005). https://doi.org/10.1109/ICORR.2005.1501143
. Lane, G.W., et al.: Effectiveness of a social robot, ‘Paro’, in a VA long-term care setting. Psychol. Serv. 13(3), 292–299 (2016). https://doi.org/10.1037/ser0000080
) Lopez-Caudana, E., Eduardo Baltazar Reyes, G., Ponce Cruz, P.: Socially assistive robotics: state-of-the-art scenarios in Mexico. In: Grau, A., Wang, Z. (eds.) Industrial Robotics - New Paradigms, IntechOpen (2020). https://doi.org/10.5772/intechopen.91446
Fong, T., Nourbakhsh, I., Dautenhahn, K.: A survey of socially interactive robots. Rob. Auton. Syst. 42(3–4), 143–166 (2003). https://doi.org/10.1016/S0921-8890(02)00372-X
Alves-Oliveira, P., Orr, A., Björling, E.A., Cakmak, M.: Connecting the dots of social robot design from interviews with robot creators. Front. Robot. AI 9, 720799 (2022). https://doi.org/10.3389/frobt.2022.720799
Costescu, C.A., Vanderborght, B., David, D.O.: The effects of robot-enhanced psychotherapy: a meta-analysis. Rev. Gener. Psychol. 18(2), 127–136 (2014). https://doi.org/10.1037/gpr0000007
Rasouli, S., Gupta, G., Nilsen, E., Dautenhahn, K.: Potential applications of social robots in robot-assisted interventions for social anxiety. Int. J. Soc. Rob. (2022). https://doi.org/10.1007/s12369-021-00851-0.
Yuan, F., Klavon, E., Liu, Z., Lopez, R.P., Zhao, X.: A systematic review of robotic rehabilitation for cognitive training. Front. Robot. AI 8, 605715 (2021). https://doi.org/10.3389/frobt.2021.605715
Shen, Z., Elibol, A., Chong, N.Y.: Understanding nonverbal communication cues of human personality traits in human-robot interaction. IEEE/CAA J. Autom. Sinica 7(6), 1465–1477 (2020). https://doi.org/10.1109/JAS.2020.1003201
Zabala, U., Rodriguez, I., Martínez-Otzeta, J.M., Lazkano, E.: Expressing robot personality through talking body language. Appl. Sci. 11(10), 4639 (2021). https://doi.org/10.3390/app11104639
Bartneck, C., Belpaeme, T., Eyssel, F., Kanda, T., Keijsers, M., Sabanovic, S.: Human-robot interaction: an introduction, p. 264 (2020). https://doi.org/10.1017/9781108676649
Blut, M., Wang, C., Wünderlich, N.V., Brock, C.: Understanding anthropomorphism in service provision: a meta-analysis of physical robots, chatbots, and other AI. J. Acad. Mark. Sci. 49(4), 632–658 (2021). https://doi.org/10.1007/s11747-020-00762-y
Zabala, U., Rodriguez, I., Martínez-Otzeta, J.M., Lazkano, E.: Modeling and evaluating beat gestures for social robots. Multimedia Tools Appl. 81(3), 3421–3438 (2022). https://doi.org/10.1007/s11042-021-11289-x
Riek, L.D., Paul, P.C., Robinson, P.: When my robot smiles at me: enabling human-robot rapport via real-time head gesture mimicry. J. Multimodal User Interfaces 3(1–2), 99–108 (2010). https://doi.org/10.1007/s12193-009-0028-2
Heinonen, K.: Positive and negative valence influencing consumer engagement. J. Serv. Theory Pract. 28(2), 147–169 (2018). https://doi.org/10.1108/JSTP-02-2016-0020
Xu, J., Broekens, J., Hindriks, K., Neerincx, M.A.: Mood contagion of robot body language in human robot interaction. Auton. Agents Multi-Agent Syst. 29(6), 1216–1248 (2015). https://doi.org/10.1007/s10458-015-9307-3
Castillo, J.C., Alonso-Martín, F., Cáceres-Domínguez, D., Malfaz, M., Salichs, M.A.: The influence of speed and position in dynamic gesture recognition for human-robot interaction. J. Sensors 2019, 1–12 (2019). https://doi.org/10.1155/2019/7060491
. Story, M., Webb, P., Fletcher, S.R., Tang, G., Jaksic, C., Carberry, J.: Do speed and proximity affect human-robot collaboration with an industrial robot arm?. Int. J. Soc. Rob. (2022). https://doi.org/10.1007/s12369-021-00853-y.
Isabet, B., Pino, M., Lewis, M., Benveniste, S., Rigaud, A.-S.: Social telepresence robots: a narrative review of experiments involving older adults before and during the COVID-19 pandemic. Int. J. Environ. Res. Public Health 18(7), Art. no. 7 (2021). https://doi.org/10.3390/ijerph18073597
Pu, L., Moyle, W., Jones, C., Todorovic, M.: The effectiveness of social robots for older adults: a systematic review and meta-analysis of randomized controlled studies. Gerontologist 59(1), e37–e51 (2019). https://doi.org/10.1093/geront/gny046
Marchetti, A., Di Dio, C., Manzi, F., Massaro, D.: Robotics in clinical and developmental psychology. Compre. Clin. Psychol., 121–140 (2022). https://doi.org/10.1016/B978-0-12-818697-8.00005-4
Nomura, T., Kanda, T., Suzuki, T., Yamada, S.: Do people with social anxiety feel anxious about interacting with a robot? AI Soc. 35(2), 381–390 (2019). https://doi.org/10.1007/s00146-019-00889-9
Hempel, S., et al.: Evidence map of mindfulness. VA-ESP Project #05-226 (2014)
Jeong, S. et al.: A social robot to mitigate stress, anxiety, and pain in hospital pediatric care. In: Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction Extended Abstracts, Portland Oregon USA, pp. 103–104 (2015). https://doi.org/10.1145/2701973.2702028
Aly, A., Tapus, A.: A model for synthesizing a combined verbal and nonverbal behavior based on personality traits in human-robot interaction. In: 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI), Tokyo, Japan, pp. 325–332 (2013). https://doi.org/10.1109/HRI.2013.6483606
Bartneck, C., Croft, E., Kulic, D., Zoghbi, S.: Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots. Int. J. Soc. Rob. 1, 71–81 (2009). https://doi.org/10.1007/s12369-008-0001-3
Peirce, J., et al.: PsychoPy2: experiments in behavior made easy. Behav. Res. Methods 51(1), 195–203 (2019). https://doi.org/10.3758/s13428-018-01193-y
Vallat, P.: Statistics in python. J. Open Source Softw. 3(31), 1026 (2018). https://doi.org/10.21105/joss.01026.
Waskom, M.L.: Seaborn: statistical data visualization. J. Open Source Softw. 6(60) (2021). https://doi.org/10.21105/joss.03021
Paredes Venero, R., Davila, A.: Experimental research methodology and statistics insights. In: Jost, C., et al. (eds.) Human-Robot Interaction: Evaluation Methods and Their Standardization, pp. 333–353. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-42307-013
Weiss, A., Bartneck, C.: Meta analysis of the usage of the Godspeed Questionnaire Series. In: 2015 24th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), Kobe, Japan, pp. 381–388 (2015). https://doi.org/10.1109/ROMAN.2015.7333568
Acknowledgment
The authors wish to thank the National Fund for Scientific, Technological Development and Technological Innovation (FONDECYT) through its national program PROCIENCIA (160-2020-FONDECYT) and the Pontificia Universidad Católica del Perú (PUCP) through its funding program CAP (PI0516 - ID 627) for providing the means and resources for this research and development.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Arce, D. et al. (2022). Design and Preliminary Validation of Social Assistive Humanoid Robot with Gesture Expression Features for Mental Health Treatment of Isolated Patients in Hospitals. In: Cavallo, F., et al. Social Robotics. ICSR 2022. Lecture Notes in Computer Science(), vol 13818. Springer, Cham. https://doi.org/10.1007/978-3-031-24670-8_46
Download citation
DOI: https://doi.org/10.1007/978-3-031-24670-8_46
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-24669-2
Online ISBN: 978-3-031-24670-8
eBook Packages: Computer ScienceComputer Science (R0)