Slide
Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
Jaberi, M.; Falk, T. H.
A Literature Survey on Potential Private User Information Leakage in Metaverse Applications Journal Article
In: Advanced Intelligent Systems, vol. 8, no. 1, 2026, ISSN: 26404567 (ISSN).
Abstract | Links | BibTeX | Tags: age, augmented reality, Brain, brain computer interface, Computer privacy, Data privacy, Electroencephalography, eye tracking, Gender, Haptic interfaces, Information leakage, Intelligent systems, Literature survey, metaverse, Metaverses, Neurophysiological signal, neurophysiological signals, Neurophysiology, Privacy, Private user information, Race, Signal analysis, User information, Virtual and augmented reality
@article{jaberiLiteratureSurveyPotential2026,
title = {A Literature Survey on Potential Private User Information Leakage in Metaverse Applications},
author = {M. Jaberi and T. H. Falk},
url = {https://www.scopus.com/pages/publications/105012929167?origin=resultslist},
doi = {10.1002/aisy.202500263},
issn = {26404567 (ISSN)},
year = {2026},
date = {2026-01-01},
journal = {Advanced Intelligent Systems},
volume = {8},
number = {1},
publisher = {John Wiley and Sons Inc},
abstract = {The Metaverse is revolutionizing various fields, including healthcare, education, social interaction, and the workplace. Commercial multisensory devices (e.g., smell diffusion and haptic technologies) are available, and virtual and augmented reality (VR/AR) headsets are increasingly integrated with brain–computer interfaces (BCI). These integrations enable adaptive, personalized virtual immersive experiences that are more engaging, interactive, and effective. As these applications become mainstream, concerns arise regarding the security and privacy of personal information. Recent studies demonstrate that users can be identified with high accuracy using the data monitored from sensors available in VR/AR headsets. This literature survey investigates the types of personal user information that can be inferred from BCI-instrumented headsets. In particular, it focuses on predicting age, gender, and ethnic/racial background from neurophysiological signals currently monitored by commercial devices. The survey highlights the predictive strength of electroencephalogram and electrocardiogram signal modalities, followed by eye tracking and iris scanning. It also considers future privacy risks posed by biometric and gesture-based monitoring using non-contact technologies such as computer vision and WiFi signal analysis. The survey concludes with recommendations for future research aimed at contributing to the development of robust frameworks that safeguard user privacy in the evolving Metaverse landscape. © 2025 The Author(s). Advanced Intelligent Systems published by Wiley-VCH GmbH.},
keywords = {age, augmented reality, Brain, brain computer interface, Computer privacy, Data privacy, Electroencephalography, eye tracking, Gender, Haptic interfaces, Information leakage, Intelligent systems, Literature survey, metaverse, Metaverses, Neurophysiological signal, neurophysiological signals, Neurophysiology, Privacy, Private user information, Race, Signal analysis, User information, Virtual and augmented reality},
pubstate = {published},
tppubtype = {article}
}
The Metaverse is revolutionizing various fields, including healthcare, education, social interaction, and the workplace. Commercial multisensory devices (e.g., smell diffusion and haptic technologies) are available, and virtual and augmented reality (VR/AR) headsets are increasingly integrated with brain–computer interfaces (BCI). These integrations enable adaptive, personalized virtual immersive experiences that are more engaging, interactive, and effective. As these applications become mainstream, concerns arise regarding the security and privacy of personal information. Recent studies demonstrate that users can be identified with high accuracy using the data monitored from sensors available in VR/AR headsets. This literature survey investigates the types of personal user information that can be inferred from BCI-instrumented headsets. In particular, it focuses on predicting age, gender, and ethnic/racial background from neurophysiological signals currently monitored by commercial devices. The survey highlights the predictive strength of electroencephalogram and electrocardiogram signal modalities, followed by eye tracking and iris scanning. It also considers future privacy risks posed by biometric and gesture-based monitoring using non-contact technologies such as computer vision and WiFi signal analysis. The survey concludes with recommendations for future research aimed at contributing to the development of robust frameworks that safeguard user privacy in the evolving Metaverse landscape. © 2025 The Author(s). Advanced Intelligent Systems published by Wiley-VCH GmbH.
2.
Dang, L. B.; Truong, V. Tuan; Le, L. B.; Falk, T. H.
EM-Auth: A Generalizable Eye-Movement Authentication Framework using Event Cameras Proceedings Article
In: IEEE Conf. Artif. Intell., CAI, pp. 2064–2069, Institute of Electrical and Electronics Engineers Inc., 2026, ISBN: 979-833156039-3 (ISBN), (Journal Abbreviation: IEEE Conf. Artif. Intell., CAI).
Abstract | Links | BibTeX | Tags: augmented reality, Authentication, Cameras, Convolutional neural networks, Data privacy, Eye movement patterns, Eye movements, eye tracking, Eye-tracking, Frame-based, High power consumption, Neuromorphic vision sensors, Power potential, Privacy concerns, Temporal resolution, Transfer learning, User authentication, Virtual and augmented reality, virtual reality
@inproceedings{dangEMAuthGeneralizableEyeMovement2026,
title = {EM-Auth: A Generalizable Eye-Movement Authentication Framework using Event Cameras},
author = {L. B. Dang and V. Tuan Truong and L. B. Le and T. H. Falk},
url = {https://www.scopus.com/pages/publications/105042114237?origin=resultslist},
doi = {10.1109/CAI68641.2026.11536355},
isbn = {979-833156039-3 (ISBN)},
year = {2026},
date = {2026-01-01},
booktitle = {IEEE Conf. Artif. Intell., CAI},
pages = {2064–2069},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {With the rapid emergence of virtual and augmented reality (VR/AR) head-mounted devices that closely interact with users' eyes, eye-tracking-based applications are becoming increasingly promising. Among them, eye movement patterns have emerged as a reliable biometric modality for user authentication. However, existing solutions based on conventional frame-based cameras face significant limitations, including low temporal resolution, high latency, high power consumption, and potential privacy concerns due to the detailed appearance captured around the eyes. To address these challenges, we propose EM-Auth, a novel framework for eye-tracking-based user authentication that leverages event cameras, a type of neuromorphic vision sensor providing asynchronous, high-temporal-resolution data, while preserving user privacy. Our method introduces a two-stage spatiotemporal feature extraction pipeline: first, a lightweight convolutional neural network (CNN) extracts spatial features from event streams; second, a transformer-based module models the temporal dependencies to generate robust eye representations. Extensive experiments show that our framework significantly outperforms existing state-of-the-art (SOTA) methods, achieving 0.008 and 0.015 equal error rates (EERs) on two representative datasets. Notably, EM-Auth demonstrates a strong generalization capability. In a zero-shot setting where the model is trained on a specific dataset and evaluated on previously unseen users, our approach achieves authentication accuracies of 98.4% and 95.9% on the EV-Eye and EBV-Eye datasets, respectively. Under cross-dataset evaluation, our framework achieves an authentication accuracy of nearly 85% without additional fine-tuning, and consistently improves performance through transfer learning. © 2026 IEEE.},
note = {Journal Abbreviation: IEEE Conf. Artif. Intell., CAI},
keywords = {augmented reality, Authentication, Cameras, Convolutional neural networks, Data privacy, Eye movement patterns, Eye movements, eye tracking, Eye-tracking, Frame-based, High power consumption, Neuromorphic vision sensors, Power potential, Privacy concerns, Temporal resolution, Transfer learning, User authentication, Virtual and augmented reality, virtual reality},
pubstate = {published},
tppubtype = {inproceedings}
}
With the rapid emergence of virtual and augmented reality (VR/AR) head-mounted devices that closely interact with users' eyes, eye-tracking-based applications are becoming increasingly promising. Among them, eye movement patterns have emerged as a reliable biometric modality for user authentication. However, existing solutions based on conventional frame-based cameras face significant limitations, including low temporal resolution, high latency, high power consumption, and potential privacy concerns due to the detailed appearance captured around the eyes. To address these challenges, we propose EM-Auth, a novel framework for eye-tracking-based user authentication that leverages event cameras, a type of neuromorphic vision sensor providing asynchronous, high-temporal-resolution data, while preserving user privacy. Our method introduces a two-stage spatiotemporal feature extraction pipeline: first, a lightweight convolutional neural network (CNN) extracts spatial features from event streams; second, a transformer-based module models the temporal dependencies to generate robust eye representations. Extensive experiments show that our framework significantly outperforms existing state-of-the-art (SOTA) methods, achieving 0.008 and 0.015 equal error rates (EERs) on two representative datasets. Notably, EM-Auth demonstrates a strong generalization capability. In a zero-shot setting where the model is trained on a specific dataset and evaluated on previously unseen users, our approach achieves authentication accuracies of 98.4% and 95.9% on the EV-Eye and EBV-Eye datasets, respectively. Under cross-dataset evaluation, our framework achieves an authentication accuracy of nearly 85% without additional fine-tuning, and consistently improves performance through transfer learning. © 2026 IEEE.
3.
Lapointe, J. -F.; Allili, M. S.; Hammouche, N.
Field Trials of an AI-AR-Based System for Remote Bridge Inspection by Drone Proceedings Article
In: D., Harris; W.-C., Li; H., Krömker (Ed.): Lect. Notes Comput. Sci., pp. 278–287, Springer Science and Business Media Deutschland GmbH, 2025, ISBN: 03029743 (ISSN); 978-303176823-1 (ISBN), (Journal Abbreviation: Lect. Notes Comput. Sci.).
Abstract | Links | BibTeX | Tags: Advanced systems, Air navigation, Artificial intelligence, artificial intelligence (AI), augmented reality, augmented reality (AR), Bridge inspection, Concrete bridges, Drone, Drones, Field trial, HIgh speed networks, High-speed Networks, Network links, Performance, Remote guidance, Transportation infrastructures, UAV
@inproceedings{lapointe_field_2025,
title = {Field Trials of an AI-AR-Based System for Remote Bridge Inspection by Drone},
author = {J. -F. Lapointe and M. S. Allili and N. Hammouche},
editor = {Harris D. and Li W.-C. and Krömker H.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85213387549&doi=10.1007%2f978-3-031-76824-8_20&partnerID=40&md5=565ae5dded9cfdf27632e79e702c7718},
doi = {10.1007/978-3-031-76824-8_20},
isbn = {03029743 (ISSN); 978-303176823-1 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Lect. Notes Comput. Sci.},
volume = {15381 LNCS},
pages = {278–287},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {Bridge inspections are important to ensure the safety of users of these critical transportation infrastructures and avoid tragedies that could be caused by the collapse of these infrastructures. This paper describes the results of field trials of an advanced system for remotely guided inspection of bridges by a drone, which relies on artificial intelligence and augmented reality to achieve it. Results indicate that a high speed network link is critical to achieve good performance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.},
note = {Journal Abbreviation: Lect. Notes Comput. Sci.},
keywords = {Advanced systems, Air navigation, Artificial intelligence, artificial intelligence (AI), augmented reality, augmented reality (AR), Bridge inspection, Concrete bridges, Drone, Drones, Field trial, HIgh speed networks, High-speed Networks, Network links, Performance, Remote guidance, Transportation infrastructures, UAV},
pubstate = {published},
tppubtype = {inproceedings}
}
Bridge inspections are important to ensure the safety of users of these critical transportation infrastructures and avoid tragedies that could be caused by the collapse of these infrastructures. This paper describes the results of field trials of an advanced system for remotely guided inspection of bridges by a drone, which relies on artificial intelligence and augmented reality to achieve it. Results indicate that a high speed network link is critical to achieve good performance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
4.
Lapointe, J. -F.; Allili, M. S.; Hammouche, N.
Field Trials of an AI-AR-Based System for Remote Bridge Inspection by Drone Proceedings Article
In: D., Harris; W.-C., Li; H., Krömker (Ed.): Lect. Notes Comput. Sci., pp. 278–287, Springer Science and Business Media Deutschland GmbH, 2025, ISBN: 03029743 (ISSN); 978-303176823-1 (ISBN), (Journal Abbreviation: Lect. Notes Comput. Sci.).
Abstract | Links | BibTeX | Tags: Advanced systems, Air navigation, Artificial intelligence, artificial intelligence (AI), augmented reality, augmented reality (AR), Bridge inspection, Concrete bridges, Drone, Drones, Field trial, HIgh speed networks, High-speed Networks, Network links, Performance, Remote guidance, Transportation infrastructures, UAV
@inproceedings{lapointeFieldTrialsAIARBased2025a,
title = {Field Trials of an AI-AR-Based System for Remote Bridge Inspection by Drone},
author = {J. -F. Lapointe and M. S. Allili and N. Hammouche},
editor = {Harris D. and Li W.-C. and Krömker H.},
url = {https://www.scopus.com/pages/publications/85213387549?origin=resultslist},
doi = {10.1007/978-3-031-76824-8_20},
isbn = {03029743 (ISSN); 978-303176823-1 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Lect. Notes Comput. Sci.},
volume = {15381 LNCS},
pages = {278–287},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {Bridge inspections are important to ensure the safety of users of these critical transportation infrastructures and avoid tragedies that could be caused by the collapse of these infrastructures. This paper describes the results of field trials of an advanced system for remotely guided inspection of bridges by a drone, which relies on artificial intelligence and augmented reality to achieve it. Results indicate that a high speed network link is critical to achieve good performance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.},
note = {Journal Abbreviation: Lect. Notes Comput. Sci.},
keywords = {Advanced systems, Air navigation, Artificial intelligence, artificial intelligence (AI), augmented reality, augmented reality (AR), Bridge inspection, Concrete bridges, Drone, Drones, Field trial, HIgh speed networks, High-speed Networks, Network links, Performance, Remote guidance, Transportation infrastructures, UAV},
pubstate = {published},
tppubtype = {inproceedings}
}
Bridge inspections are important to ensure the safety of users of these critical transportation infrastructures and avoid tragedies that could be caused by the collapse of these infrastructures. This paper describes the results of field trials of an advanced system for remotely guided inspection of bridges by a drone, which relies on artificial intelligence and augmented reality to achieve it. Results indicate that a high speed network link is critical to achieve good performance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
5.
Lapointe, J. -F.; Allili, M. S.; Hammouche, N.
Field Trials of an AI-AR-Based System for Remote Bridge Inspection by Drone Proceedings Article
In: D., Harris; W.-C., Li; H., Krömker (Ed.): Lect. Notes Comput. Sci., pp. 278–287, Springer Science and Business Media Deutschland GmbH, 2025, ISBN: 03029743 (ISSN); 978-303176823-1 (ISBN), (Journal Abbreviation: Lect. Notes Comput. Sci.).
Abstract | Links | BibTeX | Tags: Advanced systems, Air navigation, Artificial intelligence, artificial intelligence (AI), augmented reality, augmented reality (AR), Bridge inspection, Concrete bridges, Drone, Drones, Field trial, HIgh speed networks, High-speed Networks, Network links, Performance, Remote guidance, Transportation infrastructures, UAV
@inproceedings{lapointeFieldTrialsAIARBased2025,
title = {Field Trials of an AI-AR-Based System for Remote Bridge Inspection by Drone},
author = {J. -F. Lapointe and M. S. Allili and N. Hammouche},
editor = {Harris D. and Li W.-C. and Krömker H.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85213387549&doi=10.1007%2f978-3-031-76824-8_20&partnerID=40&md5=565ae5dded9cfdf27632e79e702c7718},
doi = {10.1007/978-3-031-76824-8_20},
isbn = {03029743 (ISSN); 978-303176823-1 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Lect. Notes Comput. Sci.},
volume = {15381 LNCS},
pages = {278–287},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {Bridge inspections are important to ensure the safety of users of these critical transportation infrastructures and avoid tragedies that could be caused by the collapse of these infrastructures. This paper describes the results of field trials of an advanced system for remotely guided inspection of bridges by a drone, which relies on artificial intelligence and augmented reality to achieve it. Results indicate that a high speed network link is critical to achieve good performance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.},
note = {Journal Abbreviation: Lect. Notes Comput. Sci.},
keywords = {Advanced systems, Air navigation, Artificial intelligence, artificial intelligence (AI), augmented reality, augmented reality (AR), Bridge inspection, Concrete bridges, Drone, Drones, Field trial, HIgh speed networks, High-speed Networks, Network links, Performance, Remote guidance, Transportation infrastructures, UAV},
pubstate = {published},
tppubtype = {inproceedings}
}
Bridge inspections are important to ensure the safety of users of these critical transportation infrastructures and avoid tragedies that could be caused by the collapse of these infrastructures. This paper describes the results of field trials of an advanced system for remotely guided inspection of bridges by a drone, which relies on artificial intelligence and augmented reality to achieve it. Results indicate that a high speed network link is critical to achieve good performance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
6.
Lapointe, J. -F.; Allili, M. S.; Belliveau, L.; Hebbache, L.; Amirkhani, D.; Sekkati, H.
AI-AR for Bridge Inspection by Drone Journal Article
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13318 LNCS, pp. 302–313, 2022, ISSN: 03029743, (ISBN: 9783031060144).
Abstract | Links | BibTeX | Tags: AR, augmented reality, Bridge inspection, Bridges, Deep learning, Drone, Drones, Human-in-the-loop, Inspection, Regular inspections, Remote guidance, RPAS, Transportation infrastructures, Visual inspection
@article{lapointe_ai-ar_2022,
title = {AI-AR for Bridge Inspection by Drone},
author = {J. -F. Lapointe and M. S. Allili and L. Belliveau and L. Hebbache and D. Amirkhani and H. Sekkati},
editor = {Fragomeni G. Chen J.Y.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131961739&doi=10.1007%2f978-3-031-06015-1_21&partnerID=40&md5=f57dfc1d9207b936684f18893eb5bfa7},
doi = {10.1007/978-3-031-06015-1_21},
issn = {03029743},
year = {2022},
date = {2022-01-01},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
volume = {13318 LNCS},
pages = {302–313},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {Good and regular inspections of transportation infrastructures such as bridges and overpasses are necessary to maintain the safety of the public who uses them and the integrity of the structures. Until recently, these inspections were done entirely manually by using mainly visual inspection to detect defects on the structure. In the last few years, inspection by drone is an emerging way of achieving inspection that allows more efficient access to the structure. This paper describes a human-in-the-loop system that combines AI and AR for bridge inspection by drone. © 2022, Springer Nature Switzerland AG.},
note = {ISBN: 9783031060144},
keywords = {AR, augmented reality, Bridge inspection, Bridges, Deep learning, Drone, Drones, Human-in-the-loop, Inspection, Regular inspections, Remote guidance, RPAS, Transportation infrastructures, Visual inspection},
pubstate = {published},
tppubtype = {article}
}
Good and regular inspections of transportation infrastructures such as bridges and overpasses are necessary to maintain the safety of the public who uses them and the integrity of the structures. Until recently, these inspections were done entirely manually by using mainly visual inspection to detect defects on the structure. In the last few years, inspection by drone is an emerging way of achieving inspection that allows more efficient access to the structure. This paper describes a human-in-the-loop system that combines AI and AR for bridge inspection by drone. © 2022, Springer Nature Switzerland AG.
7.
Ma, L.; Mor, S.; Anderson, P. L.; Baños, R. M.; Botella, C.; Bouchard, S.; Cárdenas-López, G.; Donker, T.; Fernández-Álvarez, J.; Lindner, P.; Mühlberger, A.; Powers, M. B.; Quero, S.; Rothbaum, B.; Wiederhold, B. K.; Carlbring, P.
Integrating virtual realities and psychotherapy: SWOT analysis on VR and MR based treatments of anxiety and stress-related disorders Journal Article
In: Cognitive Behaviour Therapy, vol. 50, no. 6, pp. 509–526, 2021, ISSN: 16506073, (Publisher: Routledge).
Abstract | Links | BibTeX | Tags: Anxiety, Anxiety disorder, Anxiety Disorders, augmented reality, health care survey, Health Care Surveys, human, Humans, mental stress, Psychological, psychology, Psychotherapists, psychotherapy, Stress, virtual reality
@article{ma_integrating_2021,
title = {Integrating virtual realities and psychotherapy: SWOT analysis on VR and MR based treatments of anxiety and stress-related disorders},
author = {L. Ma and S. Mor and P. L. Anderson and R. M. Baños and C. Botella and S. Bouchard and G. Cárdenas-López and T. Donker and J. Fernández-Álvarez and P. Lindner and A. Mühlberger and M. B. Powers and S. Quero and B. Rothbaum and B. K. Wiederhold and P. Carlbring},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111974867&doi=10.1080%2f16506073.2021.1939410&partnerID=40&md5=37846f3bc3b9b7e260efba2709cb3c7b},
doi = {10.1080/16506073.2021.1939410},
issn = {16506073},
year = {2021},
date = {2021-01-01},
journal = {Cognitive Behaviour Therapy},
volume = {50},
number = {6},
pages = {509–526},
publisher = {Routledge},
abstract = {The use of virtual reality (VR) and mixed reality (MR) technology in clinical psychology is growing. Efficacious VR-based treatments for a variety of disorders have been developed. However, the field of technology-assisted psychotherapy is constantly changing with the advancement in technology. Factors such as interdisciplinary collaboration, consumer familiarity and adoption of VR products, and progress in clinical science all need to be taken into consideration when integrating virtual technologies into psychotherapies. We aim to present an overview of current expert opinions on the use of virtual technologies in the treatment of anxiety and stress-related disorders. An anonymous survey was distributed to a select group of researchers and clinicians, using an analytic framework known as Strengths, Weaknesses, Opportunities, and Threats (SWOT). Overall, the respondents had an optimistic outlook regarding the current use as well as future development and implementation of technology-assisted interventions. VR and MR psychotherapies offer distinct advantages that can overcome shortcomings associated with traditional therapy. The respondents acknowledged and discussed current limitations of VR and MR psychotherapies. They recommended consolidation of existing knowledge and encouraged standardisation in both theory and practice. Continued research is needed to leverage the strengths of VR and MR to develop better treatments. Abbreviations: AR: Augmented Reality; MR: Mixed Reality; RCT: Randomised Controlled Trial; SWOT: Strengths, Weaknesses, Opportunities, and Threats; VR: Virtual Reality; VR-EBT: Virtual Reality Exposure-Based Therapy. © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.},
note = {Publisher: Routledge},
keywords = {Anxiety, Anxiety disorder, Anxiety Disorders, augmented reality, health care survey, Health Care Surveys, human, Humans, mental stress, Psychological, psychology, Psychotherapists, psychotherapy, Stress, virtual reality},
pubstate = {published},
tppubtype = {article}
}
The use of virtual reality (VR) and mixed reality (MR) technology in clinical psychology is growing. Efficacious VR-based treatments for a variety of disorders have been developed. However, the field of technology-assisted psychotherapy is constantly changing with the advancement in technology. Factors such as interdisciplinary collaboration, consumer familiarity and adoption of VR products, and progress in clinical science all need to be taken into consideration when integrating virtual technologies into psychotherapies. We aim to present an overview of current expert opinions on the use of virtual technologies in the treatment of anxiety and stress-related disorders. An anonymous survey was distributed to a select group of researchers and clinicians, using an analytic framework known as Strengths, Weaknesses, Opportunities, and Threats (SWOT). Overall, the respondents had an optimistic outlook regarding the current use as well as future development and implementation of technology-assisted interventions. VR and MR psychotherapies offer distinct advantages that can overcome shortcomings associated with traditional therapy. The respondents acknowledged and discussed current limitations of VR and MR psychotherapies. They recommended consolidation of existing knowledge and encouraged standardisation in both theory and practice. Continued research is needed to leverage the strengths of VR and MR to develop better treatments. Abbreviations: AR: Augmented Reality; MR: Mixed Reality; RCT: Randomised Controlled Trial; SWOT: Strengths, Weaknesses, Opportunities, and Threats; VR: Virtual Reality; VR-EBT: Virtual Reality Exposure-Based Therapy. © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
8.
Lapointe, J. -F.; Molyneaux, H.; Allili, M. S.
A Literature Review of AR-Based Remote Guidance Tasks with User Studies Journal Article
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12191 LNCS, pp. 111–120, 2020, ISSN: 03029743, (ISBN: 9783030496975).
Abstract | Links | BibTeX | Tags: Artificial intelligence, augmented reality, Efficiency, Future of works, Human computer interaction, Immersive environment, Literature reviews, Mixed reality, Remote collaboration, Remote guidance, Smartphones, systematic review, Technical requirement, Technical support
@article{lapointe_literature_2020,
title = {A Literature Review of AR-Based Remote Guidance Tasks with User Studies},
author = {J. -F. Lapointe and H. Molyneaux and M. S. Allili},
editor = {Fragomeni G. Chen J.Y.C.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089165019&doi=10.1007%2f978-3-030-49698-2_8&partnerID=40&md5=7af5345630a6dc4fc14e46a4ee1b1fdc},
doi = {10.1007/978-3-030-49698-2_8},
issn = {03029743},
year = {2020},
date = {2020-01-01},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
volume = {12191 LNCS},
pages = {111–120},
publisher = {Springer},
abstract = {The future of work is increasingly mobile and distributed across space and time. Institutions and individuals are phasing out desktops in favor of laptops, tablets and/or smart phones as much work (assessment, technical support, etc.) is done in the field and not at a desk. There will be a need for systems that support remote collaborations such as remote guidance. Augmented reality (AR) is praised for its ability to show the task at hand within an immersive environment, allowing for spatial clarity and greater efficiency, thereby showing great promise for collaborative and remote guidance tasks; however, there are no systematic reviews of AR based remote guidance systems. This paper reviews the literature describing AR-based remote guidance tasks and discusses the task settings, technical requirements and user groups within the literature, followed by a discussion of further areas of interest for the application of this technology combined with artificial intelligence (AI) algorithms to increase the efficiency of applied tasks. © 2020, NRC Canada.},
note = {ISBN: 9783030496975},
keywords = {Artificial intelligence, augmented reality, Efficiency, Future of works, Human computer interaction, Immersive environment, Literature reviews, Mixed reality, Remote collaboration, Remote guidance, Smartphones, systematic review, Technical requirement, Technical support},
pubstate = {published},
tppubtype = {article}
}
The future of work is increasingly mobile and distributed across space and time. Institutions and individuals are phasing out desktops in favor of laptops, tablets and/or smart phones as much work (assessment, technical support, etc.) is done in the field and not at a desk. There will be a need for systems that support remote collaborations such as remote guidance. Augmented reality (AR) is praised for its ability to show the task at hand within an immersive environment, allowing for spatial clarity and greater efficiency, thereby showing great promise for collaborative and remote guidance tasks; however, there are no systematic reviews of AR based remote guidance systems. This paper reviews the literature describing AR-based remote guidance tasks and discusses the task settings, technical requirements and user groups within the literature, followed by a discussion of further areas of interest for the application of this technology combined with artificial intelligence (AI) algorithms to increase the efficiency of applied tasks. © 2020, NRC Canada.
9.
Khazaal, Y.; Favrod, J.; Sort, A.; Borgeat, F.; Bouchard, S.
Editorial: Computers and games for mental health and well-being Journal Article
In: Frontiers in Psychiatry, vol. 9, no. APR, 2018, ISSN: 16640640 (ISSN), (Publisher: Frontiers Media S.A.).
Links | BibTeX | Tags: augmented reality, Cognitive behavior therapy, Cognitive remediation, computer assisted therapy, controlled clinical trial (topic), editorial, human, information processing, Internet treatment, mental disease, mental health care, mobile application, Patient Compliance, prophylaxis, schizophrenia, Serious games, Smartphone app, telehealth, video game, virtual reality, wellbeing
@article{khazaal_editorial_2018,
title = {Editorial: Computers and games for mental health and well-being},
author = {Y. Khazaal and J. Favrod and A. Sort and F. Borgeat and S. Bouchard},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045511603&doi=10.3389%2ffpsyt.2018.00141&partnerID=40&md5=51e50eac3fa902a4358d2bbf8562179c},
doi = {10.3389/fpsyt.2018.00141},
issn = {16640640 (ISSN)},
year = {2018},
date = {2018-01-01},
journal = {Frontiers in Psychiatry},
volume = {9},
number = {APR},
publisher = {Frontiers Media S.A.},
note = {Publisher: Frontiers Media S.A.},
keywords = {augmented reality, Cognitive behavior therapy, Cognitive remediation, computer assisted therapy, controlled clinical trial (topic), editorial, human, information processing, Internet treatment, mental disease, mental health care, mobile application, Patient Compliance, prophylaxis, schizophrenia, Serious games, Smartphone app, telehealth, video game, virtual reality, wellbeing},
pubstate = {published},
tppubtype = {article}
}
10.
Khazaal, Y.; Favrod, J.; Sort, A.; Borgeat, F.; Bouchard, S.
Editorial: Computers and games for mental health and well-being Journal Article
In: Frontiers in Psychiatry, vol. 9, no. APR, 2018, ISSN: 16640640 (ISSN).
Links | BibTeX | Tags: augmented reality, Cognitive behavior therapy, Cognitive remediation, computer assisted therapy, controlled clinical trial (topic), editorial, human, information processing, Internet treatment, mental disease, mental health care, mobile application, Patient Compliance, prophylaxis, schizophrenia, Serious games, Smartphone app, telehealth, video game, virtual reality, wellbeing
@article{khazaalEditorialComputersGames2018,
title = {Editorial: Computers and games for mental health and well-being},
author = {Y. Khazaal and J. Favrod and A. Sort and F. Borgeat and S. Bouchard},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045511603&doi=10.3389%2ffpsyt.2018.00141&partnerID=40&md5=51e50eac3fa902a4358d2bbf8562179c},
doi = {10.3389/fpsyt.2018.00141},
issn = {16640640 (ISSN)},
year = {2018},
date = {2018-01-01},
journal = {Frontiers in Psychiatry},
volume = {9},
number = {APR},
publisher = {Frontiers Media S.A.},
keywords = {augmented reality, Cognitive behavior therapy, Cognitive remediation, computer assisted therapy, controlled clinical trial (topic), editorial, human, information processing, Internet treatment, mental disease, mental health care, mobile application, Patient Compliance, prophylaxis, schizophrenia, Serious games, Smartphone app, telehealth, video game, virtual reality, wellbeing},
pubstate = {published},
tppubtype = {article}
}