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DC Field | Value | Language |
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dc.date.accessioned | 2024-04-09T10:14:21Z | - |
dc.date.available | 2024-04-09T10:14:21Z | - |
dc.date.issued | 2023 | - |
dc.identifier.citation | Bugeja, A. (2023). Personalised pain conditioning through affective computing and virtual reality (Master's dissertation). | en_GB |
dc.identifier.uri | https://www.um.edu.mt/library/oar/handle/123456789/120591 | - |
dc.description | M.Sc.(Melit.) | en_GB |
dc.description.abstract | Managing pain poses a significant challenge for many individuals, impacting their overall quality of life. While Virtual Reality (VR) distraction therapy has shown promise in alleviating pain perception, its real-world effectiveness requires further exploration. This research delves into the potential of VR technology and conditioning stimuli to deliver personalised distraction therapy in practical settings, addressing the need for effective pain management interventions. The study consisted of two phases. Initially, participants engaged in a VR experience while wearing a smartwatch that collected physiological data, specifically heart rate. This data was used to train a machine-learning model that estimated participants' distraction levels through affective computing. The model adjusted the VR experience, aiming to maintain participants in a "flow" state while simultaneously triggering vibrations on the wearable device. The second phase assessed the vibrational stimuli's effectiveness as a conditioned stimulus to enhance distraction and mitigate pain. Participants self-reported their pain levels before and after wearing the smartwatch in various scenarios. The study revealed significant findings concerning the reduction of pain, demonstrating a decrease of 41% in overall pain ratings. These results provide valuable insights into the varied responses to pain interventions across different conditions. In conclusion, this research addresses the general pain management problem by investigating the effectiveness of combining VR distraction therapy and conditioning techniques. The primary findings underscore that this integrated approach reduces pain perception in real-world scenarios. These insights have implications for enhancing pain management interventions, improving the well-being and quality of life for individuals struggling with pain. | en_GB |
dc.language.iso | en | en_GB |
dc.rights | info:eu-repo/semantics/restrictedAccess | en_GB |
dc.subject | Pain -- Treatment | en_GB |
dc.subject | Virtual reality | en_GB |
dc.subject | Distraction (Psychology) | en_GB |
dc.title | Personalised pain conditioning through affective computing and virtual reality | en_GB |
dc.type | masterThesis | en_GB |
dc.rights.holder | The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. | en_GB |
dc.publisher.institution | University of Malta | en_GB |
dc.publisher.department | Faculty of Information and Communication Technology. Department of Artificial Intelligence | en_GB |
dc.description.reviewed | N/A | en_GB |
dc.contributor.creator | Bugeja, Andrea (2023) | - |
Appears in Collections: | Dissertations - FacICT - 2023 Dissertations - FacICTAI - 2023 |
Files in This Item:
File | Description | Size | Format | |
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2419ICTICS520000010543_1.PDF Restricted Access | 4.59 MB | Adobe PDF | View/Open Request a copy |
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