AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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Here you can find the complete list of our publications.
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You can use the tag cloud to select only the papers dealing with specific research topics.
You can expand the Abstract, Links and BibTex record for each paper.
2024
Sheehy, L.; Bouchard, S.; Kakkar, A.; Hakim, R. El; Lhoest, J.; Frank, A.
Development and Initial Testing of an Artificial Intelligence-Based Virtual Reality Companion for People Living with Dementia in Long-Term Care Journal Article
In: Journal of Clinical Medicine, vol. 13, no. 18, 2024, ISSN: 20770383 (ISSN).
Abstract | Links | BibTeX | Tags: aged, Article, Artificial intelligence, cognitive decline, cognitive impairment, compassion, conversation, Dementia, Elderly, female, human, large language models, long term care, long-term care, major clinical study, male, program acceptability, program feasibility, reaction time, reminiscence, speech discrimination, very elderly, Virtual Reality
@article{sheehy_development_2024,
title = {Development and Initial Testing of an Artificial Intelligence-Based Virtual Reality Companion for People Living with Dementia in Long-Term Care},
author = {L. Sheehy and S. Bouchard and A. Kakkar and R. El Hakim and J. Lhoest and A. Frank},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205071099&doi=10.3390%2fjcm13185574&partnerID=40&md5=844732ff858a0d5feb0a95a54093ad4d},
doi = {10.3390/jcm13185574},
issn = {20770383 (ISSN)},
year = {2024},
date = {2024-01-01},
journal = {Journal of Clinical Medicine},
volume = {13},
number = {18},
abstract = {Background/Objectives: Feelings of loneliness are common in people living with dementia (PLWD) in long-term care (LTC). The goals of this study were to describe the development of a novel virtual companion for PLWD living in LTC and assess its feasibility and acceptability. Methods: The computer-generated virtual companion, presented using a head-mounted virtual reality display, was developed in two stages. In Stage 1, the virtual companion asked questions designed to encourage conversation and reminiscence. In Stage 2, more powerful artificial intelligence tools allowed the virtual companion to engage users in nuanced discussions on any topic. PLWD in LTC tested the application at each stage to assess feasibility and acceptability. Results: Ten PLWD living in LTC participated in Stage 1 (4 men and 6 women; average 82 years old) and Stage 2 (2 men and 8 women; average 87 years old). Session lengths ranged from 0:00 to 5:30 min in Stage 1 and 0:00 to 53:50 min in Stage 2. Speech recognition issues and a limited repertoire of questions limited acceptance in Stage 1. Enhanced conversational ability in Stage 2 led to intimate and meaningful conversations with many participants. Many users found the head-mounted display heavy. There were no complaints of simulator sickness. The virtual companion was best suited to PLWD who could engage in reciprocal conversation. After Stage 2, response latency was identified as an opportunity for improvement in future versions. Conclusions: Virtual reality and artificial intelligence can be used to create a virtual companion that is acceptable and enjoyable to some PLWD living in LTC. Ongoing innovations in hardware and software will allow future iterations to provide more natural conversational interaction and an enhanced social experience. © 2024 by the authors.},
keywords = {aged, Article, Artificial intelligence, cognitive decline, cognitive impairment, compassion, conversation, Dementia, Elderly, female, human, large language models, long term care, long-term care, major clinical study, male, program acceptability, program feasibility, reaction time, reminiscence, speech discrimination, very elderly, Virtual Reality},
pubstate = {published},
tppubtype = {article}
}
Background/Objectives: Feelings of loneliness are common in people living with dementia (PLWD) in long-term care (LTC). The goals of this study were to describe the development of a novel virtual companion for PLWD living in LTC and assess its feasibility and acceptability. Methods: The computer-generated virtual companion, presented using a head-mounted virtual reality display, was developed in two stages. In Stage 1, the virtual companion asked questions designed to encourage conversation and reminiscence. In Stage 2, more powerful artificial intelligence tools allowed the virtual companion to engage users in nuanced discussions on any topic. PLWD in LTC tested the application at each stage to assess feasibility and acceptability. Results: Ten PLWD living in LTC participated in Stage 1 (4 men and 6 women; average 82 years old) and Stage 2 (2 men and 8 women; average 87 years old). Session lengths ranged from 0:00 to 5:30 min in Stage 1 and 0:00 to 53:50 min in Stage 2. Speech recognition issues and a limited repertoire of questions limited acceptance in Stage 1. Enhanced conversational ability in Stage 2 led to intimate and meaningful conversations with many participants. Many users found the head-mounted display heavy. There were no complaints of simulator sickness. The virtual companion was best suited to PLWD who could engage in reciprocal conversation. After Stage 2, response latency was identified as an opportunity for improvement in future versions. Conclusions: Virtual reality and artificial intelligence can be used to create a virtual companion that is acceptable and enjoyable to some PLWD living in LTC. Ongoing innovations in hardware and software will allow future iterations to provide more natural conversational interaction and an enhanced social experience. © 2024 by the authors.
Hubal, R.
Rethinking some Virtual Human Applications Journal Article
In: Annual Review of CyberTherapy and Telemedicine, vol. 22, pp. 28–33, 2024, ISSN: 15548716 (ISSN).
Abstract | Links | BibTeX | Tags: Article, Artificial intelligence, character and application fidelity, ChatGPT, Consequential conversations, conversation, Engagement, human, Large language model, Learning, responsibility, responsive virtual humans, social competence, telehealth, Virtual Reality
@article{hubal_rethinking_2024,
title = {Rethinking some Virtual Human Applications},
author = {R. Hubal},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215435480&partnerID=40&md5=4526a7d54606ef0f1cc6234099eb4aae},
issn = {15548716 (ISSN)},
year = {2024},
date = {2024-01-01},
journal = {Annual Review of CyberTherapy and Telemedicine},
volume = {22},
pages = {28–33},
abstract = {Increasingly realistic virtual environments incorporating virtual characters have been used to train or assess actual behavior, such as of people at risk, and identify reasons to remediate or intervene. Technology has improved so rapidly that today’s capabilities to create situations to focus training and intervention outshine past efforts. To name just a few current examples, tools like Unreal’s MetaHuman Creator for creating characters, Midjourney for creating environments, OpenAI’s ChatGPT for scripting, and GIFT for tutoring have enormous potential, as these tools promise to reduce simulation costs and increase realism. This paper, in contrast, discusses some movement in the other direction: Recent efforts suggest that increased realism may not always have resulting cost-benefit for training and assessment. Lessons learned and recommendations are presented to guide future developers. © 2024, Interactive Media Institute. All rights reserved.},
keywords = {Article, Artificial intelligence, character and application fidelity, ChatGPT, Consequential conversations, conversation, Engagement, human, Large language model, Learning, responsibility, responsive virtual humans, social competence, telehealth, Virtual Reality},
pubstate = {published},
tppubtype = {article}
}
Increasingly realistic virtual environments incorporating virtual characters have been used to train or assess actual behavior, such as of people at risk, and identify reasons to remediate or intervene. Technology has improved so rapidly that today’s capabilities to create situations to focus training and intervention outshine past efforts. To name just a few current examples, tools like Unreal’s MetaHuman Creator for creating characters, Midjourney for creating environments, OpenAI’s ChatGPT for scripting, and GIFT for tutoring have enormous potential, as these tools promise to reduce simulation costs and increase realism. This paper, in contrast, discusses some movement in the other direction: Recent efforts suggest that increased realism may not always have resulting cost-benefit for training and assessment. Lessons learned and recommendations are presented to guide future developers. © 2024, Interactive Media Institute. All rights reserved.