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Prior work has shown that frame rate significantly influences user behavior in fast-response tasks in 2D and 3D contexts. However, its impact on a steering task, which involves navigating an object along a path from the start to the end, remains relatively unexplored, especially in the context of virtual reality (VR). This task is considered a typical non-fast-response activity, as it does not demand rapid reactions within a limited time frame. Our work aims to understand and model users' steering behavior and predict movement time with different task complexities and frame rates in VR environments. We first conducted a user study to collect user behavior in a steering task with four factors: frame rate, path length, width, and radius of curvature. Based on the results, we then quantified the effects of frame rate and built two predictive models. Our models exhibited the best fit ([Formula: see text]) and over 17% improvement in prediction accuracy for movement time compared to existing models. Our models' robustness was further validated by applying them to predict steering performance with different VR tasks and frame rates. The two models keep the best predictability for both movement time and speed.
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Objective: Following the initial measures taken to manage the repercussions of the COVID-19 pandemic, mental health conditions have become a critical concern. Mental health has become a foremost priority not only for health care providers but also for many other organizations, such as educational institutions, companies, and government agencies. A significant proportion of the Australian population having experienced mental disorders highlights the need for effective interventions. Those with pre-existing mental health issues experienced particularly pronounced effects. Among these challenges, advancements in technology offer new possibilities for mental health support. Videogames have shown effectiveness in mitigating symptoms of depression. Previous research has shown that game interface preferences correlate with players' emotional responses. This study aims to use MoodJumper, a game we designed, developed, and evaluated to examine the choice of game preferences in individuals with depressive symptoms. Materials and Methods: A pilot study was carried out after obtaining the Human Ethics committee's approval (n = 20). The participants were asked to fill out a Patient Health Questionnaire-9 (PHQ-9) questionnaire. They then played with the MoodJumper game for 20-30 minutes. Upon completing the game session, they were asked to fill out a questionnaire regarding their experience. Results: The results indicate a nonsignificant correlation between music preference, the direction of movement, and depressive symptoms meaning no significant relationship was found between depressive symptoms and chosen settings. However, a significant negative correlation was found between decision-making ability regarding game preferences and Patient Health Questionnaire-9 scores showing the difficulty of choosing preferred settings when having depressive symptoms. Conclusion: This contribution paves the way for designing and evaluating more impactful game experiences for individuals with mental health challenges.
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COVID-19 , Dépression , Jeux vidéo , Humains , Projets pilotes , Jeux vidéo/psychologie , Jeux vidéo/statistiques et données numériques , Dépression/psychologie , Mâle , Femelle , Adulte , COVID-19/psychologie , Australie , Enquêtes et questionnaires , SARS-CoV-2 , Adulte d'âge moyenRÉSUMÉ
VR exergames offer an engaging solution to combat sedentary behavior and promote physical activity. However, challenges emerge when playing these games in shared spaces, particularly due to the presence of bystanders. VR's passthrough functionality enables players to maintain awareness of their surrounding environment while immersed in VR gaming, rendering it a promising solution to improve users' awareness of the environment. This study investigates the passthrough's impact on player performance and experiences in shared spaces, involving an experiment with 24 participants that examines Space (Office vs. Corridor) and Passthrough Function (With vs. Without). Results reveal that Passthrough enhances game performance and environmental awareness while reducing immersion. Players prefer an open area to an enclosed room, whether with or without Passthrough, finding it more socially acceptable. Additionally, Passthrough appears to encourage participation among players with higher self-consciousness, potentially alleviating their concerns about being observed by bystanders. Our findings provide valuable insights for designing VR experiences in shared spaces, underscoring the potential of VR's passthrough to enhance user experiences and promote VR adoption in these environments.
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Pratique des jeux vidéo d'exercices physiques , Réalité de synthèse , Humains , Interface utilisateur , Infographie , Exercice physiqueRÉSUMÉ
Users' perceived image quality of virtual reality head-mounted displays (VR HMDs) is determined by multiple factors, including the HMD's structure, optical system, display and render resolution, and users' visual acuity (VA). Existing metrics such as pixels per degree (PPD) have limitations that prevent accurate comparison of different VR HMDs. One of the main limitations is that not all VR HMD manufacturers released the official PPD or details of their HMDs' optical systems. Without these details, developers and users cannot know the precise PPD or calculate it for a given HMD. The other issue is that the visual clarity varies with the VR environment. Our work has identified a gap in having a feasible metric that can measure the visual clarity of VR HMDs. To address this gap, we present an end-to-end and user-centric visual clarity metric, omnidirectional virtual visual acuity (OVVA), for VR HMDs. OVVA extends the physical visual acuity chart into a virtual format to measure the virtual visual acuity of an HMD's central focal area and its degradation in its noncentral area. OVVA provides a new perspective to measure visual clarity and can serve as an intuitive and accurate reference for VR applications sensitive to visual accuracy. Our results show that OVVA is a simple yet effective metric for comparing VR HMDs and environments.
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Lunettes intelligentes , Réalité de synthèse , Infographie , Acuité visuelleRÉSUMÉ
Alphanumeric and special characters are essential during text entry. Text entry in virtual reality (VR) is usually performed on a virtual Qwerty keyboard to minimize the need to learn new layouts. As such, entering capitals, symbols, and numbers in VR is often a direct migration from a physical/touchscreen Qwerty keyboard-that is, using the mode-switching keys to switch between different types of characters and symbols. However, there are inherent differences between a keyboard in VR and a physical/touchscreen keyboard, and as such, a direct adaptation of mode-switching via switch keys may not be suitable for VR. The high flexibility afforded by VR opens up more possibilities for entering alphanumeric and special characters using the Qwerty layout. In this work, we designed two controller-based raycasting text entry methods for alphanumeric and special characters input (Layer-ButtonSwitch and Key-ButtonSwitch) and compared them with two other methods (Standard Qwerty Keyboard and Layer-PointSwitch) that were derived from physical and soft Qwerty keyboards. We explored the performance and user preference of these four methods via two user studies (one short-term and one prolonged use), where participants were instructed to input text containing alphanumeric and special characters. Our results show that Layer-ButtonSwitch led to the highest statistically significant performance, followed by Key-ButtonSwitch and Standard Qwerty Keyboard, while Layer-PointSwitch had the slowest speed. With continuous practice, participants' performance using Key-ButtonSwitch reached that of Layer-ButtonSwitch. Further, the results show that the key-level layout used in Key-ButtonSwitch led users to parallel mode switching and character input operations because this layout showed all characters on one layer. We distill three recommendations from the results that can help guide the design of text entry techniques for alphanumeric and special characters in VR.
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We propose three novel spatial data selection techniques for particle data in VR visualization environments. They are designed to be target- and context-aware and be suitable for a wide range of data features and complex scenarios. Each technique is designed to be adjusted to particular selection intents: the selection of consecutive dense regions, the selection of filament-like structures, and the selection of clusters-with all of them facilitating post-selection threshold adjustment. These techniques allow users to precisely select those regions of space for further exploration-with simple and approximate 3D pointing, brushing, or drawing input-using flexible point- or path-based input and without being limited by 3D occlusions, non-homogeneous feature density, or complex data shapes. These new techniques are evaluated in a controlled experiment and compared with the Baseline method, a region-based 3D painting selection. Our results indicate that our techniques are effective in handling a wide range of scenarios and allow users to select data based on their comprehension of crucial features. Furthermore, we analyze the attributes, requirements, and strategies of our spatial selection methods and compare them with existing state-of-the-art selection methods to handle diverse data features and situations. Based on this analysis we provide guidelines for choosing the most suitable 3D spatial selection techniques based on the interaction environment, the given data characteristics, or the need for interactive post-selection threshold adjustment.
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BACKGROUND: Depression and anxiety are common and debilitating mental disorders with severe negative repercussions at both individual and societal levels. Although virtual reality (VR) has emerged as a safe and effective tool for the treatment of anxiety disorders, studies of the therapeutic application of VR to treat depression are more limited. OBJECTIVE: The purpose of this study was to test whether a novel type of individualized VR (iVR) can be used to improve self-compassion and decrease depressive symptoms and to evaluate the usability and acceptability of this approach, as rated by participants. The iVR system was designed and developed based on the feedback obtained from a previous study, with improved appearance and feel of the avatar and enhanced graphical quality. METHODS: A total of 36 young adult participants were recruited from a university community social media site. Participants were aware that the study was investigating a treatment for depression but were not recruited based on depression diagnosis. Participants were asked to complete 2 iVR sessions, spaced 2 weeks apart. At baseline and upon completion of each iVR session, participants were asked to complete validated measures of self-compassion and depression. Upon completion of both iVR sessions, additional measures were administered to assess participants' perceptions about the perceived usability and system acceptability of the iVR approach. RESULTS: Self-compassion was assessed at the beginning of session 1 (preintervention baseline) and at the end of session 1 (postintervention assessment). Owing to COVID-19 constraints, 36% (13/36) of the participants were unable to complete the follow-up iVR session. Self-compassion was assessed again for the remaining 64% (23/36) of the participants at the end of session 2 (postintervention assessment). Within-group analyses revealed that self-compassion was significantly increased at the end of both session 1 (P=.01) and session 2 (P=.03) relative to baseline. There was also a nonsignificant trend for depressive symptoms to be low at the end of session 2 relative to baseline. Both quantitative and qualitative participant data supported the iVR approach as being acceptable and usable. CONCLUSIONS: Although these data must be treated as preliminary owing to the small sample size and potential selection bias, the data provide encouraging initial evidence that iVR might be a useful tool to enhance self-compassion and reduce depressive symptoms, highlighting the need for randomized controlled trials in the future.
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Despite the widespread interest in leveraging non-player characters (NPCs) to enhance gameplay experiences, there is a gap in understanding of how NPC spectators (i.e., those virtual characters in the scene that watch users' actions) affect players. For instance, the impact of NPC spectators' presence and feedback on players' performance and experience has not been studied, especially in virtual reality (VR) exergames. This paper aims to fill this gap and reports two user studies that assess their effect on such games. Study 1 explored the impact of having NPC spectators present and their feedback available in a gesture-based VR exergame and found having NPC spectators and their feedback could improve players' game performance, experience, and exertion. Based on Study 1's results, we further explored two characteristics of the spectators-their group size (small/large) and their feedback (with/without). The results show that (1) a large spectator number is more helpful since it improves the overall game experience (higher competence, flow, immersion), increases AvgHR% (the average heart rate percentage divided by the maximum heart rate), and enhances performance (improved players' combo performance and increased gesture success rate for particular gesture); (2) spectator feedback is instrumental in improving players' performance (higher gesture success rates, more combos performed successfully, more monster's combos prevented), enhancing game experience (positive affect, competence, flow, and immersion), and reducing negative game experience, increasing exertion (AvgHR% and burned more calories). Based on the results, we derived two main design recommendations for VR exergames that could pave the way for improving gameplay performance and game experience, especially among young adults.
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BACKGROUND: Urinary pan-cancer system is a general term for tumors of the urinary system including renal cell carcinoma (RCC), prostate cancer (PRAD), and bladder cancer (BLCA). Their location, physiological functions, and metabolism are closely related, making the occurrence and outcome of these tumors highly similar. Cuproptosis is a new type of cell death that is different from apoptosis and plays an essential role in tumors. Therefore, it is necessary to study the molecular mechanism of cuproptosis-related lncRNAs to urinary system pan-cancer for the prognosis, clinical diagnosis, and treatment of urinary tumors. METHOD: In our study, we identified 35 co-expression cuproptosis-related lncRNAs (CRLs) from the urinary pan-cancer system. 28 CRLs were identified as prognostic-related CRLs by univariate Cox regression analysis. Then 12 CRLs were obtained using lasso regression and multivariate cox analysis to construct a prognostic model. We divided patients into high- and low-risk groups based on the median risk scores. Next, Kaplan-Meier analysis, principal component analysis (PCA), functional rich annotations, and nomogram were used to compare the differences between the high- and low-risk groups. Finally, the prediction of tumor immune dysfunction and rejection, gene mutation, and drug sensitivity were discussed. CONCLUSION: Finally, the candidate molecules of the urinary system pan-cancer were identified. This CRLs risk model may be promising for clinical prediction of prognosis and immunotherapy response in urinary system pan-cancer patients.
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Tumeurs du rein , ARN long non codant , Mâle , Humains , ARN long non codant/génétique , Pronostic , Immunothérapie , Nomogrammes , ApoptoseRÉSUMÉ
The presence of an audience and its feedback could affect people's performance and experience during an event, especially related to sports such as tennis or boxing. Similarly, in videogames, players' gameplay could be affected if there is an audience and its feedback in response to players' performance in the environment. The inclusion of an audience with non-player characters (NPC) is common in videogames in general. However, there is a limited exploration of the use of an NPC audience in virtual reality (VR) exergames, especially focusing on elderly players. To fill this gap, this work examines the effect of an NPC audience and its associated feedback (with/without) on elderly users of VR exergames. In a user study, we used 120 NPC in a virtual audience. Results showed that the presence of the NPC audience with responsive feedback led to higher performance (with a higher success rate of performing gesture actions, more successful combinations of actions (or combos for short) performed, and more opponent's combos prevented) and better gameplay experience (with higher levels of competence, autonomy, relatedness, immersion, and intuitive controls) of elderly players. Our results can help frame the design and engineering of VR exergames that are targeted at elderly users to help them have an enhanced gameplay experience and improve their health.
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In real scenes, due to the problems of low light and unsuitable views, the images often exhibit a variety of degradations, such as low contrast, color distortion, and noise. These degradations affect not only visual effects but also computer vision tasks. This paper focuses on the combination of traditional algorithms and machine learning algorithms in the field of image enhancement. The traditional methods, including their principles and improvements, are introduced from three categories: gray level transformation, histogram equalization, and Retinex methods. Machine learning based algorithms are not only divided into end-to-end learning and unpaired learning, but also concluded to decomposition-based learning and fusion based learning based on the applied image processing strategies. Finally, the involved methods are comprehensively compared by multiple image quality assessment methods, including mean square error, natural image quality evaluator, structural similarity, peak signal to noise ratio, etc.
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The refresh rate of virtual reality (VR) head-mounted displays (HMDs) has been growing rapidly in recent years because of the demand to provide higher frame rate content as it is often linked with a better experience. Today's HMDs come with different refresh rates ranging from 20Hz to 180Hz, which determines the actual maximum frame rate perceived by users' naked eyes. VR users and content developers often face a choice because having high frame rate content and the hardware that supports it comes with higher costs and other trade-offs (such as heavier and bulkier HMDs). Both VR users and developers can choose a suitable frame rate if they are aware of the benefits of different frame rates in user experience, performance, and simulator sickness (SS). To our knowledge, limited research on frame rate in VR HMDs is available. In this paper, we aim to fill this gap and report a study with two VR application scenarios that compared four of the most common and highest frame rates currently available (60, 90, 120, and 180 frames per second (fps)) to explore their effect on users' experience, performance, and SS symptoms. Our results show that 120fps is an important threshold for VR. After 120fps, users tend to feel lower SS symptoms without a significant negative effect on their experience. Higher frame rates (e.g., 120 and 180fps) can ensure better user performance than lower rates. Interestingly, we also found that at 60fps and when users are faced with fast-moving objects, they tend to adopt a strategy to compensate for the lack of visual details by predicting or filling the gaps to try to meet the performance needs. At higher fps, users do not need to follow this compensatory strategy to meet the fast response performance requirements.
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Virtual reality (VR) has emerged as a powerful tool for rehabilitation. Many effective VR applications have been developed to support motor rehabilitation of people affected by motor issues. Movement reproduction, which transfers users' movements from the physical world to the virtual environment, is commonly used in VR rehabilitation applications. Three major components are required for movement reproduction in VR: (1) movement input, (2) movement representation, and (3) movement modulation. Until now, movement reproduction in virtual rehabilitation has not yet been systematically studied. This article aims to provide a state-of-the-art review on this subject by focusing on existing literature on immersive motor rehabilitation using VR. In this review, we provided in-depth discussions on the rehabilitation goals and outcomes, technology issues behind virtual rehabilitation, and user experience regarding movement reproduction. Similarly, we present good practices and highlight challenges and opportunities that can form constructive suggestions for the design and development of fit-for-purpose VR rehabilitation applications and can help frame future research directions for this emerging area that combines VR and health.
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Téléréadaptation , Réalité de synthèse , Humains , Infographie , Mouvement , Interface utilisateurRÉSUMÉ
Education is one area that was significantly affected by the COVID-19 pandemic with much of the education being transferred online. Many subjects that require hands-on experimental experience suffer when taught online. Education is also one area that many believe can benefit from the advances in virtual reality (VR) technology, particularly for remote, online learning. Furthermore, because the technology shows overall good results with hands-on experiential learning education, one possible way to overcome online education barriers is with the use of VR applications. Given that VR has yet to make significant inroads in education, it is essential to understand what factors will influence this technology's adoption and acceptance. In this work, we explore factors influencing the adoption of VR for hands-on practical learning around the world based on the Unified Theory of Acceptance and Use of Technology and three additional constructs. We also performed a cross-cultural analysis to examine the model fit for developed and developing countries and regions. Moreover, through open-ended questions, we gauge the overall feeling people in these countries have regarding VR for practical learning and how it compares with regular online learning.
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This study provides a comprehensive review about the use of videogames and virtual reality (VR) for the assessment of anxiety and depression. This review aimed to answer the research question of the viability of games and VR for the assessment of anxiety and depression. An extensive literature search spanning across several databases published since the year 2000 returned a total of 4566 records. Based on the eligibility criteria, the screening process resulted in the selection of 10 articles for the final review. Equal number of studies utilized games (n = 5) and VR. Three studies made use of machine learning techniques. Only two were found to be clinical studies. An interesting finding was that the studies that focused on anxiety disorders relied mostly on VR, whereas those focused on depression disorders relied mostly on the use of videogames for the assessment. Majority of studies reported encouraging findings that support the use of games or VR for the assessment of anxiety and depression. This study identified potential digital biomarkers or correlates of anxiety and depression that may guide researchers in the design process. It is necessary to highlight that researchers should consider consultation with trained mental health experts, while designing such assessments to ensure safety and privacy. However, due to limited number of articles as well as lack of clinical studies, more clinical evidence is required to strongly support this notion of using videogames or VR as assessment tools for anxiety and depression.
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In recent years, Virtual Reality (VR) Head-Mounted Displays (HMD) have been used to provide an immersive, first-person view in real-time for the remote-control of Unmanned Ground Vehicles (UGV). One critical issue is that it is challenging to perceive the distance of obstacles surrounding the vehicle from 2D views in the HMD, which deteriorates the control of UGV. Conventional distance indicators used in HMD take up screen space which leads clutter on the display and can further reduce situation awareness of the physical environment. To address the issue, in this paper we propose off-screen in-device feedback using vibro-tactile and/or light-visual cues to provide real-time distance information for the remote control of UGV. Results from a study show a significantly better performance with either feedback type, reduced workload and improved usability in a driving task that requires continuous perception of the distance between the UGV and its environmental objects or obstacles. Our findings show a solid case for in-device vibro-tactile and/or light-visual feedback to support remote operation of UGVs that highly relies on distance perception of objects.
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Conduite automobile , Réalité de synthèse , Perception de la distance , Rétroaction , Humains , Interface utilisateurRÉSUMÉ
Large interactive displays can provide suitable workspaces for learners to conduct collaborative learning tasks with visual information in co-located settings. In this research, we explored the use of these displays to support collaborative engagement and exploratory tasks with visual representations. Our investigation looked at the effect of four factors (number of virtual workspaces within the display, number of displays, position arrangement of the collaborators, and collaborative modes of interaction) on learners' knowledge acquisition, engagement level, and task performance. To this end, a user study was conducted with 72 participants divided into 6 groups using an interactive tool developed to support the collaborative exploration of 3D visual structures. The results of this study showed that learners with one shared workspace and one single display can achieve better user performance and engagement levels. In addition, the back-to-back position with learners sharing their view and control of the workspaces was the most favorable. It also led to improved learning outcomes and engagement levels during the collaboration process.
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Stage interdisciplinaire , Humains , ApprentissageRÉSUMÉ
BACKGROUND: In recent years, there has been an increase in the number of students with depression, anxiety, and perceived stress. A solution that has been increasingly used for improving health and well-being is exergaming. The effects and acceptability of exergames have been studied widely but mostly with older adults. The feasibility and usability of exergames among university students, especially those of immersive virtual reality (iVR) exergames, remain unexplored. OBJECTIVE: This study aimed to explore the feasibility of a 6-week iVR exergame-based intervention in reducing anxiety, depression, and perceived stress among university students and to examine the usability and acceptability of such games. METHODS: A total of 31 university students were recruited to participate in a 6-week study in which they needed to play a boxing-style iVR exergame called FitXR (FitXR Limited) twice per week (30 minutes per session). Their anxiety (Beck Anxiety Inventory), depression (Beck Depression Inventory-II), and perceived stress (Perceived Stress Scale) levels were measured before and after intervention. RESULTS: A total of 15 participants completed the 6-week study. Our results suggested that participants' mean depression scores decreased significantly from 8.33 (SD 5.98) to 5.40 (SD 5.14) after the intervention (P=.01). In addition, most participants (14/15, 93%) believed that the iVR exergame has good usability. Furthermore, most participants (14/15, 93%) were satisfied with the iVR gameplay experience and would play the iVR exergame again in the future. Of the 15 participants, 11 (73%) would recommend the iVR exergame to their friends. CONCLUSIONS: The results gained from this study show that the iVR exergame has good usability, is highly acceptable, and has the potential to reduce depression levels among university students.
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BACKGROUND: Mental health conditions pose a major challenge to health care providers and society at large. The World Health Organization predicts that by 2030, mental health conditions will be the leading cause of disease burden worldwide. The current need for mental health care is overwhelming. In New Zealand, 1 in 6 adults has been diagnosed with common mental disorders, such as depression and anxiety disorders, according to a national survey. Cognitive behavioral therapy (CBT) has been shown to effectively help patients overcome a wide variety of mental health conditions. Virtual reality exposure therapy (VRET) might be one of the most exciting technologies emerging in the clinical setting for the treatment of anxiety and depression. OBJECTIVE: This study aims to investigate the virtual reality (VR) technologies currently being used to help support the treatment of depression and anxiety. We also aim to investigate whether and how CBT is included as part of VRET and look at the VR technologies and interventions that have been used in recent studies on depression and anxiety. METHODS: We performed a scoping review. To identify significant studies, we decided to use already aggregated sources from the Google Scholar database. Overall, the goal of our search strategy was to limit the number of initial results related to VR in mental health to only a relevant minimum. RESULTS: Using our defined keywords, Google Scholar identified >17,300 articles. After applying all the inclusion and exclusion criteria, we identified a total of 369 articles for further processing. After manual evaluation, 34 articles were shortlisted; of the 34 articles, 9 (26%) reported the use of CBT with VR. All of the articles were published between 2017 and 2021. Out of the 9 studies, CBT was conducted within a VR environment in 5 (56%) studies, whereas in the remaining 4 (44%) studies, CBT was used as an addition to VRET. All 9 studies reported the use of CBT either in vivo or in a virtual environment to be effective in supporting the treatment of anxiety or depression. CONCLUSIONS: Most studies demonstrated the use of VR to be effective for supporting the treatment of anxiety or depression in a range of settings and recommended its potential as a tool for use in a clinical environment. Even though standalone headsets are much easier to work with and more suitable for home use, the shift from tethered VR headsets to standalone headsets in the mental health environment was not observed. All studies that looked at the use of CBT either in vivo or in a virtual environment found it to be effective in supporting the treatment of anxiety or depression.
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Research from psychology has suggested that body movement may directly activate emotional experiences. Movement-based emotion regulation is the most readily available but often underutilized strategy for emotion regulation. This research aims to investigate the emotional effects of movement-based interaction and its sensory feedback mechanisms. To this end, we developed a smart clothing prototype, E-motionWear, which reacts to four movements (elbow flexion/extension, shoulder flexion/extension, open and closed arms, neck flexion/extension), fabric-based detection sensors, and three-movement feedback mechanisms (audio, visual and vibrotactile). An experiment was conducted using a combined qualitative and quantitative approach to collect participants' objective and subjective emotional feelings. Results indicate that there was no interaction effect between movement and feedback mechanism on the final emotional results. Participants preferred vibrotactile and audio feedback rather than visual feedback when performing these four kinds of upper body movements. Shoulder flexion/extension and open-closed arm movements were more effective for improving positive emotion than elbow flexion/extension movements. Participants thought that the E-motionWear prototype were comfortable to wear and brought them new emotional experiences. From these results, a set of guidelines were derived that can help frame the design and use of smart clothing to support users' emotional regulation.