Virtual, Augmented, and Mixed Reality in Healthcare

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    Empathy Games for Depression Using Virtual Reality: A Literature Review and A Study Design
    ( 2021-01-05) Li, Yi (Joy) ; Luo, Hao ; Zhang, Chi
    Raising public awareness and accessing information about depression can help the patients receive social support and timely treatment. Studies have shown that serious games benefit education and healthcare. The interactive and immersive environment embedded in serious games can help people learn and apply the concepts. In this paper, we reviewed prior research in designing empathy games for depression using virtual reality (VR). We proposed a study design for a VR game to reflect the feelings and struggling the patients with depression experience through interactive and immersive game scenes. The game intends to cultivate caregivers’ empathy and compassion for the patients by enhancing their understanding of depression. By raising social awareness of depression through the immersive game, we hope that this study will encourage discussion and further research in the field.
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    Depression Detection Using Virtual Reality: A Literature Review
    ( 2021-01-05) Zhang, Chi ; Luo, Hao ; Li, Yi (Joy)
    Depression is a mood disorder that can cause mental suffering, functional impairment, physical abuse or automutilation. Early detection will help depressed people to seek professional advice and treatment earlier and recover sooner. Emerging technologies such as virtual reality (VR) have been used to assist in interventions because of their advantages in providing more flexible solutions to implement therapeutic methods. However, the applications of using VR as a diagnostic tool for mental disorders have not been thoroughly investigated. In this study, prior studies that used VR for detecting depression were reviewed and summarized. Also reviewed were other emerging technologies for depression detection. By summarizing the effort on this topic and proposing an integrated framework, we hope that the presented work will reduce the barriers to implement emerging technologies in supporting traditional depression diagnostic methods, with a further expectation to provide inspiration and guidance for future studies.
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