Slide
Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
Santana, S. T. O. D.; Silva, J. C. Da; Hatano, Y.; Guerrero-Mendez, C. D.; Souza, M. L. De; Igasaki, T.; Bastos-Filho, T.; Dantas, A. F. O. De Azevedo; Falk, T. H.; Delisle-Rodriguez, D.
Cognitive Training Using a Brain-Computer Interface for θ/β Ratio Self-Regulation - Preliminary Results with Long Covid-19 Survivors Article d'actes
Dans: IEEE Int. Conf. Hum.-Mach. Syst., ICHMS, p. 646–650, Institute of Electrical and Electronics Engineers Inc., 2026, ISBN: 979-833154511-6 (ISBN), (Journal Abbreviation: IEEE Int. Conf. Hum.-Mach. Syst., ICHMS).
Résumé | Liens | BibTeX | Étiquettes: 'current, Behavioral research, Brain, brain computer interface, Brain mapping, cognitive impairment, Cognitive skill, Cognitive systems, Cognitive training, Computer games, COVID-19, Electroencephalography, Electrophysiology, Executive Function, Interfaces (computer), Memory functions, Neurotechnology, Personnel training, Self regulation, Sustained attention, working memory
@inproceedings{santanaCognitiveTrainingUsing2026,
title = {Cognitive Training Using a Brain-Computer Interface for θ/β Ratio Self-Regulation - Preliminary Results with Long Covid-19 Survivors},
author = {S. T. O. D. Santana and J. C. Da Silva and Y. Hatano and C. D. Guerrero-Mendez and M. L. De Souza and T. Igasaki and T. Bastos-Filho and A. F. O. De Azevedo Dantas and T. H. Falk and D. Delisle-Rodriguez},
url = {https://www.scopus.com/pages/publications/105045602964?origin=resultslist},
doi = {10.1109/ICHMS69701.2026.11602366},
isbn = {979-833154511-6 (ISBN)},
year = {2026},
date = {2026-01-01},
booktitle = {IEEE Int. Conf. Hum.-Mach. Syst., ICHMS},
pages = {646–650},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Long COVID-19 can generate cognitive impairments, affecting a person's attention, working memory, and executive functions. Previous studies have suggested that therapies based on neurotechnologies can be used to recover cognitive skills. This current research presents an electroencephalography brain-computer interface based serious game for sustained attention training. The system classifies attention levels while the user controls the speed of a virtual car by self-regulating the θ/β power band ratio across multiple brain locations. Pilot experiments were conducted with two COVID-19 adult survivors who experienced cognitive decline due to long COVID19 symptoms. Participants underwent 10 sessions across consecutive working days (2 sessions × week). Both participants enhanced brain wave oscillations in both frontal and central regions, reducing theta activity and simultaneously increasing beta oscillations) after the training, achieving therefore healthy brain behavior during a cognitive attention task. Furthermore, both individuals improved cognitive skills, such as attention, working memory, and executive functions. These preliminary findings are promising and motivate the further development of multichannel neurofeedback systems for cognitive training for long COVID-19 survivors. © 2026 IEEE.},
note = {Journal Abbreviation: IEEE Int. Conf. Hum.-Mach. Syst., ICHMS},
keywords = {'current, Behavioral research, Brain, brain computer interface, Brain mapping, cognitive impairment, Cognitive skill, Cognitive systems, Cognitive training, Computer games, COVID-19, Electroencephalography, Electrophysiology, Executive Function, Interfaces (computer), Memory functions, Neurotechnology, Personnel training, Self regulation, Sustained attention, working memory},
pubstate = {published},
tppubtype = {inproceedings}
}
Long COVID-19 can generate cognitive impairments, affecting a person's attention, working memory, and executive functions. Previous studies have suggested that therapies based on neurotechnologies can be used to recover cognitive skills. This current research presents an electroencephalography brain-computer interface based serious game for sustained attention training. The system classifies attention levels while the user controls the speed of a virtual car by self-regulating the θ/β power band ratio across multiple brain locations. Pilot experiments were conducted with two COVID-19 adult survivors who experienced cognitive decline due to long COVID19 symptoms. Participants underwent 10 sessions across consecutive working days (2 sessions × week). Both participants enhanced brain wave oscillations in both frontal and central regions, reducing theta activity and simultaneously increasing beta oscillations) after the training, achieving therefore healthy brain behavior during a cognitive attention task. Furthermore, both individuals improved cognitive skills, such as attention, working memory, and executive functions. These preliminary findings are promising and motivate the further development of multichannel neurofeedback systems for cognitive training for long COVID-19 survivors. © 2026 IEEE.
2.
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 Article de journal
Dans: Journal of Clinical Medicine, vol. 13, no 18, 2024, ISSN: 20770383 (ISSN), (Publisher: Multidisciplinary Digital Publishing Institute (MDPI)).
Résumé | Liens | BibTeX | Étiquettes: 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},
publisher = {Multidisciplinary Digital Publishing Institute (MDPI)},
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.},
note = {Publisher: Multidisciplinary Digital Publishing Institute (MDPI)},
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.
3.
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 Article de journal
Dans: Journal of Clinical Medicine, vol. 13, no 18, 2024, ISSN: 20770383 (ISSN).
Résumé | Liens | BibTeX | Étiquettes: 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{sheehyDevelopmentInitialTesting2024,
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},
publisher = {Multidisciplinary Digital Publishing Institute (MDPI)},
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.