The CaMeLi Framework—A Multimodal Virtual Companion for Older Adults
Abstract
Artificial Social Companions are a promising solution for the increasing challenges in elderly care. This chapter describes the CaMeLi autonomous conversational agent system which simulates human-like affective behaviour and acts as a companion for older adults living alone at home. The agent employs synthetic speech, gaze, facial expressions, and gestures to support multimodal natural interaction with its users and assists them in a number of daily life scenarios.We present the agent’s overall architecture, with a focus on the perception, decision making and synthesis components which give rise to the agent’s intelligent affective behavior. The agent was evaluated in an exploratory study where it was introduced in 20 homes of older adults (aged 65+) in three European countries (Switzerland, the Netherlands, Portugal) for a total duration of 12 weeks. We present the results of the evaluation study with regards to acceptance, perceived usability, and usefulness of the agent, and discuss future opportunities for fellow researchers who are striving to bring virtual agents out of the laboratories into successful real world applications.
Notes
Acknowledgements
This work was supported by the European research projects CaMeLi (Grant No. 010000-2012-16), Miraculous Life (Grant No. 616421), Vizier (Grant No. AAL-2015-2-145), GrowMeUp (Grant No. 643647) and GEO-SAFE (Grant No. 691161). We express our gratitude to all the study participants and to all the project partners, including SIEMENS AG and Noldus IT who led the design of CaMeLi’s GUI and the end-users VIVA and Zuyderland who performed tremendous work in supporting the user studies and trials.
References
- 1.Aldoma, A., Tombari, F., Di Stefano, L., Vincze, M.: A Global Hypotheses Verification Method for 3D Object Recognition, In: ECCV, pp. 511–524 (2012)Google Scholar
- 2.Austin, J.T., Vancouver, J.B.: Goal constructs in psychology: structure, process, and content. Psychol. Bull. 120(3), 338–375 (1996)Google Scholar
- 3.Ben Moussa, M., Magnenat-Thalmann, N.: Toward socially responsible agents: integrating attachment and learning in emotional decision-making. Comput. Animat. Virtual Worlds. vol. 24, no. 34, pp. 327–334 (2013)Google Scholar
- 4.Bickmore, T.W., Caruso, L., Clough-Gorr, K., Heeren, T.: Its just like you talk to a friend relational agents for older adults. Interact. Comput. 17(6), 711–735 (2005)Google Scholar
- 5.Bickmore, T.W., Gruber, A., Picard, R.W.: Establishing the computer-patient working alliance in automated health behavior change interventions. Patient Educ. Couns. 59(1), 2130 (2005)Google Scholar
- 6.Bickmore, T.W., Silliman, R.A., Nelson, K., Cheng, M., Winter, M., Henault, L., Paasche-Orlow, M.K.: A randomized controlled trial of an automated exercise coach for older adults. J. Am. Geriatr. Soc. 61(10), 1676–1683 (2013)Google Scholar
- 7.Bickmore, T.W.: Relational agents: effecting change through human-computer relationships. Massachusetts Institute of Technology (2003)Google Scholar
- 8.Bickmore, T.W., Schulman, D., Sidner, C.L.: A reusable framework for health counseling dialogue systems based on a behavioral medicine ontology. J. Biomed. Inform. 44(2), 183197 (2011)CrossRefGoogle Scholar
- 9.Brooke, J.: SUS —a quick and dirty usability scale. Usability Eval. Ind. 189(194), 47 (1996)Google Scholar
- 10.Cassell, J., Bickmore, T., Campbell, L., Vilhjlmsson, H., Yan, H.: Human conversation as a system framework: designing embodied conversational agents. 29–63 (2001)Google Scholar
- 11.Cassell, J.: More than just another pretty face: embodied conversational interface agents. Commun. 43, 70–78. ACM (2000)Google Scholar
- 12.Colby, B.N., Ortony, A., Clore, G.L., Collins, A.: The Cognitive Structure of Emotions. Contemp. Sociol. 18(6), 957 (1989)Google Scholar
- 13.Dantas, C., Jegundo, A.L., Quintas, J., Martins, A.I., Queirós, A., Rocha, N.P.: European portuguese validation of usefulness, satisfaction and ease of use questionnaire (USE). In: World Conference on Information Systems and Technologies, pp. 561–570 (2017)Google Scholar
- 14.de Rosis, F., Novielli, N., Carofiglio, V., Cavalluzzi, A., De Carolis, B.: User modeling and adaptation in health promotion dialogs with an animated character. J. Biomed. Inform. 39(5), 51431 (2006)CrossRefGoogle Scholar
- 15.Ekman, P., Keltner, D.: Universal facial expressions of emotion. Calif. Ment. Heal. Res. Dig. 8(4), 151–158 (1970)Google Scholar
- 16.Fagel, S., Ben-Moussa, M., Cereghetti, D.: How avatars in care context should show affect. In: Pervasive Health 2016 Workshop on Affective Interaction with Virtual Assistants within the Healthcare Context (2016)Google Scholar
- 17.Group, T.W.: Development of the world health organization WHOQOL-BREF quality of life assessment. The WHOQOL Group. Psychol. Med. 28(3), 551–558 (1998)Google Scholar
- 18.Hanke, S., Tsiourti, C., Sili, M., Christodoulou, E.: Embodied ambient intelligent systems. in ambient intelligence and smart environments: recent advances in ambient assisted living, bridging assistive technologies, e-health and personalized health care, vol. 20, pp. 65–85. IOS Press (2015)Google Scholar
- 19.Kasap, Z., Magnenat-Thalmann, N.: Building long-term relationships with virtual and robotic characters: the role of remembering. Vis. Comput. 28(1), 87–97 (2012)Google Scholar
- 20.Kelley, J.F.: An iterative design methodology for user-friendly natural language office information applications. ACM Trans. Inf. Syst. 2(1), 26–41 (1984)Google Scholar
- 21.Khoshhal, K., Aliakbarpour, H., Quintas, J., Drews, P., Dias, J.: Probabilistic LMA-based classification of human behaviour understanding using power spectrum technique. In: 2010 13th International Conference of Information Fusion, pp. 17 (2010)Google Scholar
- 22.Klein, J., Moon, Y., Picard, R.W.: This computer responds to user frustration—theory, design, results and implications. In: Proceedings of CHI 99 Extended Abstracts on Human Factors in Computing Systems, pp. 242 (1999)Google Scholar
- 23.Kramer, M., Yaghoubzadeh, R., Kopp, S., Pitsch, K.: A conversational virtual human as autonomous assistant for elderly and cognitively impaired users?. Social acceptability and design considerations. Lect. Notes Inf. (2013)Google Scholar
- 24.Lim, M.Y.: Memory models for intelligent social companions. Human-Computer Interaction: The Agency Perspective, pp. 241–262. Springer (2012)Google Scholar
- 25.Lisetti, C., Yasavur, U., de Leon, C., Amini, R., Rishe, N., Visserv, U.: Building an on-demand avatar-based health intervention for behavior change. In: Proceedings of Twenty-Fifth International Florida Intelligence Research Soceity Conference, no. Mi, pp. 175–180 (2012)Google Scholar
- 26.Nijholt, A.: Disappearing computers, social actors and embodied agents. In: Proceedings of the International Conference on Cyberworlds, pp. 128–134 (2003)Google Scholar
- 27.Ortiz, A., Carretero, P., Oyarzun, D., Yanguas, J.J., Buiza, C., Gonzalez, M.F., Etxeberria, I.: Elderly users in ambient intelligence : does an avatar improve the interaction? Intelligence 4397, 99–114 (2002)Google Scholar
- 28.Quintas, J., Paulo, M., Jorge, D.: Information model and architecture specification for context awareness interaction decision support in cyber-physical human-machine systems. IEEE Trans. Hum. Mach. Syst. 47(3), 323–331 (2016)Google Scholar
- 29.Rusu, R.B., Cousins, S.: 3D is here: point cloud library. In: IEEE International Conference on Robotics and Automation, pp. 1–4 (2011)Google Scholar
- 30.Sakai, Y., Nonaka, Y., Yasuda, K., Nakano, Y.I.: Listener agent for elderly people with dementia. In: 2012 7th ACM/IEEE International Conference on Human-Robot Interaction (HRI), pp. 199–200 (2012)Google Scholar
- 31.Thiebaux, M., Marsella, S., Marshall, A.N., Kallmann, M.: SmartBody: behavior realization for embodied conversational agents. In: Proceedings of the 7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS ’08), pp. 151–158 (2008)Google Scholar
- 32.Traum, D., Larsson, S.: The information state approach to dialogue management. Current and New Directions in Discourse and Dialogue, pp. 325–353 (2003)Google Scholar
- 33.Tsiourti, C., Ben Moussa, M., Joly, E., Wings, C., Wac, K.: Virtual assistive companions for older adults: qualitative field study and design implications. In: 8th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) (2014)Google Scholar
- 34.Tsiourti, C., Ben-Moussa, M., Quintas, J., Loke, B., Jochem, I., Lopes, J.A., Konstantas, D.: A virtual assistive companion for older adults: design and evaluation of a real-world application. In: Proceedings of SAI Intelligent Systems Conference 2016, London, UK (2016)Google Scholar
- 35.Van Kuilenburg, H., Wiering, M., Den Uyl, M.: A model based method for automatic facial expression recognition. In: Proceeding of Machine Learning: ECML 2005, pp. 194–205. Springer (2005)Google Scholar
- 36.Vardoulakis, L.P., Ring, L., Barry, B., Sidner, C.L., Bickmore, T.: Designing relational agents as long term social companions for older adults. In: Proceedings of the 12th International Conference on Intelligent Virtual Agents, vol. 7502, pp. 289–302 (2012)Google Scholar
- 37.Verberne, F.M.F., Ham, J., Ponnada, A., Midden, C.J.H.: Trusting digital chameleons: the effect of mimicry by a virtual social agent on user trust. In: Berkovsky, S., Freyne, J. (eds.) Persuasive Technology, vol. 7822, pp. 234–245, Springer, Berlin, Heidelberg (2013)Google Scholar
- 38.Woelfel, M., McDonough, J.: Distant Speech Recognition. Wiley (2009)Google Scholar
- 39.Yaghoubzadeh, R., Kramer, M., Pitsch, K., Kopp, S.: Virtual Agents as daily assistants for elderly or cognitively impaired people. In: Proceedings 13th International Conference of Intelligence Virtual Agents, vol. 8108, pp. 91 (2013)Google Scholar