A Semantic Memory Bank Assisted by an Embodied Conversational Agents for Mobile Devices

Francisco Seron; Angel Zaldivar; Alfonso Blesa; Jose Martin-Albo; Juan Magallon

doi:doi:10.11648/j.eas.20210601.11

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A Semantic Memory Bank Assisted by an Embodied Conversational Agents for Mobile Devices

Francisco Seron, Angel Zaldivar, Alfonso Blesa, Jose Martin-Albo, Juan Magallon

Published in Engineering and Applied Sciences (Volume 6, Issue 1)

Received: 1 February 2021 Accepted: 8 February 2021 Published: 23 February 2021

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Abstract

Alzheimer’s disease is a type of dementia that causes memory loss and interferes with intellectual abilities seriously. It has no current cure and therapeutic efficiency of current medication is limited. However, there is evidence that non-pharmacological treatments could be useful to stimulate cognitive abilities. In the last few year, several studies have focused on describing and under- standing how Virtual Coaches (VC) could be key drivers for health promotion in home care settings. The use of VC gains an augmented attention in the considerations of medical innovations. In this paper, we propose an approach that exploits semantic technologies and Embodied Conversational Agents to help patients training cognitive abilities using mobile devices. In this work, semantic technologies are used to provide knowledge about the memory of a specific person, who exploits the structured data stored in a linked data repository and take advantage of the flexibility provided by ontologies to define search domains and expand the agent’s capabilities. Our Memory Bank Embodied Conversational Agent (MBECA) is used to interact with the patient and ease the interaction with new devices. The framework is oriented to Alzheimer’s patients, caregivers, and therapists.

Published in	Engineering and Applied Sciences (Volume 6, Issue 1)
DOI	10.11648/j.eas.20210601.11
Page(s)	1-17
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Semantic Embodied Conversational Agents, Semantic Knowledge, Alzheimer’s Disease, Mobile Computing, Virtual Coaching (VC)

References

[1]	S. Llanque, L. Savage, N. Rosenburg, and M. Caserta, “Concept Analysis: Alzheimer’s Caregiver Stress,” Nurs. Forum, vol. 51, no. 1, pp. 21–31, Jan. 2016.
[2]	M. S. Mittelman, D. L. Roth, O. J. Clay, and W. E. Haley, “Preserving health of alzheimer caregivers: Impact of a spouse caregiver intervention,” Am. J. Geriatr. Psychiatry, vol. 15, no. 9, pp. 780–789, 2007.
[3]	L. Tárraga et al., “A randomised pilot study to assess the efficacy of an interactive, multimedia tool of cognitive stimulation in Alzheimer’s disease,” J. Neurol. Neurosurg. Psychiatry, vol. 77, no. 10, pp. 1116–1121, Oct. 2006.
[4]	M. Takeda, T. Tanaka, M. Okochi, and H. Kazui, “Non-pharmacological intervention to dementia patients,” Psychiatry Clin. Neurosci., vol. 66, pp. 1–7, 2012.
[5]	S. Douglas, I. James, and C. Ballard, “Non-pharmacological interventions in dementia,” Advances in Psychiatric Treatment, vol. 10, no. 3. pp. 171–179, May-2004.
[6]	A. Lampit, H. Hallock, and M. Valenzuela, “Computerized Cognitive Training in Cognitively Healthy Older Adults: A Systematic Review and Meta-Analysis of Effect Modifiers,” PLoS Med., vol. 11, no. 11, p. e1001756, Nov. 2014.
[7]	European Innovation Partnership, “Personalised coaching for wellbeing and care of people as they age,” European Commission. [Online]. Available: https://ec.europa.eu/eip/ageing/funding/horizon-2020/personalised-coaching-wellbeing-and-care-people-they-age-sc1-pm-15-2017_en. [Accessed: 03-Apr-2020].
[8]	T. Bickmore, A. Gruber, and R. Picard, “Establishing the computer-patient working alliance in automated health behavior change interventions,” Patient Educ. Couns., vol. 59, no. 1, pp. 21–30, Oct. 2005.
[9]	S. Provoost, H. M. Lau, J. Ruwaard, and H. Riper, “Embodied conversational agents in clinical psychology: A scoping review,” Journal of Medical Internet Research, vol. 19, no. 5. Journal of Medical Internet Research, p. e151, 01-May-2017.
[10]	A. N. Vaidyam, H. Wisniewski, J. D. Halamka, M. S. Kashavan, and J. B. Torous, “Chatbots and Conversational Agents in Mental Health: A Review of the Psychiatric Landscape,” Canadian Journal of Psychiatry, vol. 64, no. 7. SAGE Publications Inc., pp. 456–464, 01-Jul-2019.
[11]	N. Novielli, I. Mazzotta, B. De Carolis, and S. Pizzutilo, “Analysing user’s reactions in advice-giving dialogues with a socially intelligent ECA,” Cogn. Process., vol. 13, no. SUPPL. 2, pp. 487–97, Oct. 2012.
[12]	E. Hudlicka, “Virtual training and coaching of health behavior: Example from mindfulness meditation training,” Patient Educ. Couns., vol. 92, no. 2, pp. 160–166, Aug. 2013.
[13]	C. J. Stevens et al., “Mimicry and expressiveness of an ECA in human-agent interaction: familiarity breeds content!,” Comput. Cogn. Sci., vol. 2, no. 1, p. 1, Dec. 2016.
[14]	J. A. García-Casal, A. Loizeau, E. Csipke, M. Franco-Martín, M. V. Perea-Bartolomé, and M. Orrell, “Computer-based cognitive interventions for people living with dementia: a systematic literature review and meta-analysis,” Aging and Mental Health, vol. 21, no. 5. Routledge, pp. 454–467, 04-May-2017.
[15]	M. Turunen et al., “Computer-based cognitive training for older adults: Determinants of adherence,” PLoS One, vol. 14, no. 7, 2019.
[16]	R. Jacobsen, J.-H., Stelzer, J., Fritz, T. H., Chételat, G., La Joie, R., & Turner, “Why Musical Memory Can Be Preserved in advanced Alzeheimer’s disease,” Brain Sci., no. July, pp. 2438–2450, 2015.
[17]	K. Fleming, S. H. Kim, M. Doo, G. Maguire, and S. G. Potkin, “Memory for emotional stimuli in patients with Alzheimer’s disease.,” Am. J. Alzheimers. Dis. Other Demen., vol. 18, no. 6, pp. 340–2, Nov. 2003.
[18]	S. B. Hamann, E. S. Monarch, and F. C. Goldstein, “Memory enhancement for emotional stimuli is impaired in early Alzheimer’s disease,” Neuropsychology, vol. 14, no. 1, pp. 82–92, 2000.
[19]	G. Tur and R. De Mori, Spoken language understanding : systems for extracting semantic information from speech. Wiley, 2011.
[20]	J. R. Bellegarda, “Spoken Language Understanding for Natural Interaction: The Siri Experience,” in Natural Interaction with Robots, Knowbots and Smartphones, Springer New York, 2014, pp. 3–14.
[21]	F. Serón and C. Bobed, “VOX System: A Semantic Embodied Conversational Agent exploiting Linked Data,” Multimed. Tools Appl., vol. 75, pp. 381–404, 2016.
[22]	P. Cimiano and S. Kopp, “Accessing the Web of Data through embodied virtual characters,” Semant. Web, vol. 1, no. 1–2, pp. 83–88, 2010.
[23]	U. Waltinger, A. Breuing, and I. Wachsmuth, “Interfacing Virtual Agents with Collaborative Knowledge: Open Domain Question Answering Using Wikipedia-Based Topic Models,” in Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence - Volume Volume Three, 2011, pp. 1896–1902.
[24]	G. W. I. Lcock and G. W. I. Lcock, “WikiTalk: A Spoken Wikipedia-based Open-Domain Knowledge Access System.”
[25]	A. Breuing, “Improving human-agent conversations by accessing contextual knowledge from Wikipedia,” in Proceedings - 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 2010, 2010, pp. 428–431.
[26]	T. R. Gruber, “A translation approach to portable ontology specifications,” Knowl. Acquis., vol. 5, no. 2, pp. 199–220, Jun. 1993.
[27]	T. R. Gruber, “Toward principles for the design of ontologies used for knowledge sharing,” Int. J. Hum. - Comput. Stud., vol. 43, no. 5–6, pp. 907–928, 1995.
[28]	J. Cassell, “Human Representation and Intelligence in Face-to-Face Conversation,” pp. 67–84, 2001.
[29]	L. Mignonneau and C. Sommerer, “Designing emotional, metaphoric, natural and intuitive interfaces for interactive art, edutainment and mobile communications,” Comput. Graph., vol. 29, no. 6, pp. 837–851, Dec. 2005.
[30]	J. Ortiz, A.; Aizpurua, I.; Posada, “Some techniques for avatar support of digital sto- rytelling systems,” in Technologies for Interactive Digital Storytelling and Entertainment, 2003.
[31]	A. García and C. Lamsfus, “AN eLEARNING PLATFORM TO SUPPORT VOCATIONAL TRAINING CENTERS ON DIGITAL SECURITY TRAINING WITH VIRTUAL TUTORS AND GRAPHICAL SPATIAL METAPHORES,” Technology, pp. 1–2.
[32]	A. C. Graesser, P. Chipman, B. C. Haynes, and A. Olney, “Auto tutor: An intelligent tutoring system with mixed-initiative dialogue,” IEEE Trans. Educ., vol. 48, no. 4, pp. 612–618, Nov. 2005.
[33]	J. C. Lester, J. C. Lester, S. G. Towns, and P. J. FitzGerald, “Achieving affective impact: Visual emotive communication in lifelike pedagogical agents,” Int. J. Artif. Intell. Educ., vol. 10, pp. 278--291, 1999.
[34]	T. Rieger, “Avatar Gestures,” J. WSCG, vol. Vol. 1, pp. 379–386, 2003.
[35]	S. C. Marsella, W. L. Johnson, and C. LaBore, “Interactive pedagogical drama,” in Proceedings of the International Conference on Autonomous Agents, 2000, pp. 301–308.
[36]	D. C. Berry, L. T. Butler, and F. De Rosis, “Evaluating a realistic agent in an advice-giving task,” Int. J. Hum. Comput. Stud., vol. 63, no. 3, pp. 304–327, 2005.
[37]	X. Yuan and Y. S. Chee, “Design and evaluation of Elva: an embodied tour guide in an interactive virtual art gallery,” Comput. Animat. Virtual Worlds, vol. 16, no. 2, pp. 109–119, 2005.
[38]	E. Isaac, A; Summers, “SKOS Simple Knowledge Organization System Primer,” W3C Working Group Note, 2009. [Online]. Available: https://www.w3.org/TR/skos-primer/. [Accessed: 19-Jan-2020].
[39]	Amazon, “AWS Elastic compute cloud (EC2) de capacidad modificable en la nube,” Amazon Web Services, Inc., 2015. [Online]. Available: //aws.amazon.com/es/ec2/. [Accessed: 19-Jan-2020].
[40]	M. Jovanovik, D. Trajanov, and M. Kostovski, “Open Data Portal based on Semantic Web Technologies LDA: Linked Data Authorization View project HOBBIT: Holistic Benchmarking of Big Linked Data View project Open Data Portal based on Semantic Web Technologies,” 2012.
[41]	S. S. Naveen Malviya, Nishchol Mishra, N. Malviya, N. Mishra, and S. Sahu, “Developing University Ontology using protégé OWL Tool: Process and Reasoning,” Int. J. Sci. Eng. Res. Vol. 2, Issue 9, vol. 2, no. 9, pp. 1–8, 2011.
[42]	C. Bobed, G. Esteban, and E. Mena, “Enabling keyword search on linked data repositories: An ontology-based approach,” Int. J. Knowledge-Based Intell. Eng. Syst., vol. 17, no. 1, pp. 67–77, 2013.
[43]	A. Quint and P. Liu, “Scalable vector graphics,” IEEE Multimed., vol. 10, no. 3, pp. 99–102, Jul. 2003.
[44]	J.- Ferraiolo, “Scalable Vector Graphics (SVG) 1.0 Specification,” W3C Working Group Note, 2001. [Online]. Available: https://www.w3.org/TR/2001/REC-SVG-20010904/. [Accessed: 19-Jan-2020].
[45]	M. Pilgrim, HTML5: Up and Running, 1st ed. O’Reilly Media, Inc., 2010.
[46]	G. Anthes, “HTML5 Leads a Web Revolution,” Commun. ACM, vol. 55, no. 7, pp. 16–17, Jul. 2012.
[47]	L. Stevens, R. Owen, L. Stevens, and R. Owen, “The Truth About SVG: The Flash Challenger That Was, Wasn’t, and Now…,” in The Truth About HTML5, Apress, 2014, pp. 135–151.
[48]	K. Man\ˇena, V.; S\ˇpilka, R.; Rybensk\´a, “A comparison of free and open source technologies suitable for future authoring tools in education,” in Future Communication Technology and Engineering: Proceedings of the 2014 International Conference on Future Communication Technology and Engineering (FCTE 2014) - CRC Press Book, pp. 83–86.
[49]	Gates, N. J., Rutjes, A. W., Di Nisio, M., Karim, S., Chong, L. Y., March, E., Martínez, G., Vernooij, R. W., 2019. Computerised cognitive training for maintaining cognitive function in cognitively healthy people in late life. The Cochrane database of systematic reviews 3, CD012277. URL: http://www.ncbi.nlm.nih.gov/pubmed/30864187http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC6414816, doi:10.1002/14651858.CD012277.pub2.
[50]	McBride, B., 2001. Jena: Implementing the rdf model and syntax specification, in: Proceedings of the Second International Conference on Semantic Web - Volume 40, CEUR-WS.org, Aachen, DEU. p. 23–28.

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APA Style

Francisco Seron, Angel Zaldivar, Alfonso Blesa, Jose Martin-Albo, Juan Magallon. (2021). A Semantic Memory Bank Assisted by an Embodied Conversational Agents for Mobile Devices. Engineering and Applied Sciences, 6(1), 1-17. https://doi.org/10.11648/j.eas.20210601.11

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ACS Style

Francisco Seron; Angel Zaldivar; Alfonso Blesa; Jose Martin-Albo; Juan Magallon. A Semantic Memory Bank Assisted by an Embodied Conversational Agents for Mobile Devices. Eng. Appl. Sci. 2021, 6(1), 1-17. doi: 10.11648/j.eas.20210601.11

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AMA Style

Francisco Seron, Angel Zaldivar, Alfonso Blesa, Jose Martin-Albo, Juan Magallon. A Semantic Memory Bank Assisted by an Embodied Conversational Agents for Mobile Devices. Eng Appl Sci. 2021;6(1):1-17. doi: 10.11648/j.eas.20210601.11

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@article{10.11648/j.eas.20210601.11,
  author = {Francisco Seron and Angel Zaldivar and Alfonso Blesa and Jose Martin-Albo and Juan Magallon},
  title = {A Semantic Memory Bank Assisted by an Embodied Conversational Agents for Mobile Devices},
  journal = {Engineering and Applied Sciences},
  volume = {6},
  number = {1},
  pages = {1-17},
  doi = {10.11648/j.eas.20210601.11},
  url = {https://doi.org/10.11648/j.eas.20210601.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.eas.20210601.11},
  abstract = {Alzheimer’s disease is a type of dementia that causes memory loss and interferes with intellectual abilities seriously. It has no current cure and therapeutic efficiency of current medication is limited. However, there is evidence that non-pharmacological treatments could be useful to stimulate cognitive abilities. In the last few year, several studies have focused on describing and under- standing how Virtual Coaches (VC) could be key drivers for health promotion in home care settings. The use of VC gains an augmented attention in the considerations of medical innovations. In this paper, we propose an approach that exploits semantic technologies and Embodied Conversational Agents to help patients training cognitive abilities using mobile devices. In this work, semantic technologies are used to provide knowledge about the memory of a specific person, who exploits the structured data stored in a linked data repository and take advantage of the flexibility provided by ontologies to define search domains and expand the agent’s capabilities. Our Memory Bank Embodied Conversational Agent (MBECA) is used to interact with the patient and ease the interaction with new devices. The framework is oriented to Alzheimer’s patients, caregivers, and therapists.},
 year = {2021}
}

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TY  - JOUR
T1  - A Semantic Memory Bank Assisted by an Embodied Conversational Agents for Mobile Devices
AU  - Francisco Seron
AU  - Angel Zaldivar
AU  - Alfonso Blesa
AU  - Jose Martin-Albo
AU  - Juan Magallon
Y1  - 2021/02/23
PY  - 2021
N1  - https://doi.org/10.11648/j.eas.20210601.11
DO  - 10.11648/j.eas.20210601.11
T2  - Engineering and Applied Sciences
JF  - Engineering and Applied Sciences
JO  - Engineering and Applied Sciences
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PB  - Science Publishing Group
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UR  - https://doi.org/10.11648/j.eas.20210601.11
AB  - Alzheimer’s disease is a type of dementia that causes memory loss and interferes with intellectual abilities seriously. It has no current cure and therapeutic efficiency of current medication is limited. However, there is evidence that non-pharmacological treatments could be useful to stimulate cognitive abilities. In the last few year, several studies have focused on describing and under- standing how Virtual Coaches (VC) could be key drivers for health promotion in home care settings. The use of VC gains an augmented attention in the considerations of medical innovations. In this paper, we propose an approach that exploits semantic technologies and Embodied Conversational Agents to help patients training cognitive abilities using mobile devices. In this work, semantic technologies are used to provide knowledge about the memory of a specific person, who exploits the structured data stored in a linked data repository and take advantage of the flexibility provided by ontologies to define search domains and expand the agent’s capabilities. Our Memory Bank Embodied Conversational Agent (MBECA) is used to interact with the patient and ease the interaction with new devices. The framework is oriented to Alzheimer’s patients, caregivers, and therapists.
VL  - 6
IS  - 1
ER  -

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Author Information

Francisco Seron

Department of Informatics, University of Zaragoza, Zaragoza, Spain
Angel Zaldivar

Department of Informatics, University of Zaragoza, Zaragoza, Spain
Alfonso Blesa

Department of Electronics, University of Zaragoza, Teruel, Spain
Jose Martin-Albo

Department of Psychology and Sociology, University of Zaragoza, Teruel, Spain
Juan Magallon

Department of Informatics, University of Zaragoza, Zaragoza, Spain

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APA Style

Francisco Seron, Angel Zaldivar, Alfonso Blesa, Jose Martin-Albo, Juan Magallon. (2021). A Semantic Memory Bank Assisted by an Embodied Conversational Agents for Mobile Devices. Engineering and Applied Sciences, 6(1), 1-17. https://doi.org/10.11648/j.eas.20210601.11

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ACS Style

Francisco Seron; Angel Zaldivar; Alfonso Blesa; Jose Martin-Albo; Juan Magallon. A Semantic Memory Bank Assisted by an Embodied Conversational Agents for Mobile Devices. Eng. Appl. Sci. 2021, 6(1), 1-17. doi: 10.11648/j.eas.20210601.11

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AMA Style

Francisco Seron, Angel Zaldivar, Alfonso Blesa, Jose Martin-Albo, Juan Magallon. A Semantic Memory Bank Assisted by an Embodied Conversational Agents for Mobile Devices. Eng Appl Sci. 2021;6(1):1-17. doi: 10.11648/j.eas.20210601.11

Copy | Download

@article{10.11648/j.eas.20210601.11,
  author = {Francisco Seron and Angel Zaldivar and Alfonso Blesa and Jose Martin-Albo and Juan Magallon},
  title = {A Semantic Memory Bank Assisted by an Embodied Conversational Agents for Mobile Devices},
  journal = {Engineering and Applied Sciences},
  volume = {6},
  number = {1},
  pages = {1-17},
  doi = {10.11648/j.eas.20210601.11},
  url = {https://doi.org/10.11648/j.eas.20210601.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.eas.20210601.11},
  abstract = {Alzheimer’s disease is a type of dementia that causes memory loss and interferes with intellectual abilities seriously. It has no current cure and therapeutic efficiency of current medication is limited. However, there is evidence that non-pharmacological treatments could be useful to stimulate cognitive abilities. In the last few year, several studies have focused on describing and under- standing how Virtual Coaches (VC) could be key drivers for health promotion in home care settings. The use of VC gains an augmented attention in the considerations of medical innovations. In this paper, we propose an approach that exploits semantic technologies and Embodied Conversational Agents to help patients training cognitive abilities using mobile devices. In this work, semantic technologies are used to provide knowledge about the memory of a specific person, who exploits the structured data stored in a linked data repository and take advantage of the flexibility provided by ontologies to define search domains and expand the agent’s capabilities. Our Memory Bank Embodied Conversational Agent (MBECA) is used to interact with the patient and ease the interaction with new devices. The framework is oriented to Alzheimer’s patients, caregivers, and therapists.},
 year = {2021}
}

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TY  - JOUR
T1  - A Semantic Memory Bank Assisted by an Embodied Conversational Agents for Mobile Devices
AU  - Francisco Seron
AU  - Angel Zaldivar
AU  - Alfonso Blesa
AU  - Jose Martin-Albo
AU  - Juan Magallon
Y1  - 2021/02/23
PY  - 2021
N1  - https://doi.org/10.11648/j.eas.20210601.11
DO  - 10.11648/j.eas.20210601.11
T2  - Engineering and Applied Sciences
JF  - Engineering and Applied Sciences
JO  - Engineering and Applied Sciences
SP  - 1
EP  - 17
PB  - Science Publishing Group
SN  - 2575-1468
UR  - https://doi.org/10.11648/j.eas.20210601.11
AB  - Alzheimer’s disease is a type of dementia that causes memory loss and interferes with intellectual abilities seriously. It has no current cure and therapeutic efficiency of current medication is limited. However, there is evidence that non-pharmacological treatments could be useful to stimulate cognitive abilities. In the last few year, several studies have focused on describing and under- standing how Virtual Coaches (VC) could be key drivers for health promotion in home care settings. The use of VC gains an augmented attention in the considerations of medical innovations. In this paper, we propose an approach that exploits semantic technologies and Embodied Conversational Agents to help patients training cognitive abilities using mobile devices. In this work, semantic technologies are used to provide knowledge about the memory of a specific person, who exploits the structured data stored in a linked data repository and take advantage of the flexibility provided by ontologies to define search domains and expand the agent’s capabilities. Our Memory Bank Embodied Conversational Agent (MBECA) is used to interact with the patient and ease the interaction with new devices. The framework is oriented to Alzheimer’s patients, caregivers, and therapists.
VL  - 6
IS  - 1
ER  -

Copy | Download