This study aims to review the key findings of past studies that assessed the impact of virtual environments, such as nature and forests for stress therapy. Previous research has found that virtual reality (VR) experiences affect socio-affective behavior, indicating the potential of using VR for cognitive and psychological stress therapy. However, evidence for the impacts of virtual forest therapy as a stress-reduction technique is lacking, and the usefulness of these techniques has yet to be determined. This review was carried out following the preferred reporting items for meta-analyses and systematic reviews. It summarized the literature and provided evidence on virtual forest therapy (VFT) effectiveness in stress relief. We conducted a literature search considering VR-related studies published from 2013 until June 2021 for different databases, including Embase, Medline/PubMed, Hindawi, ScienceDirect, Scopus, Web of Science, Taylor & Francis, and the Cochrane Library, to see how effective VFT reduces stress levels and improves mental well-being. According to the set inclusion criteria, eighteen relevant papers detailing original research were eligible for inclusion. This overview suggests that VR provides benefits for assessing and reducing stress levels. While real natural environments effectively promote recovery from stress, virtual exposure to nature also positively affects stress. Thus, VR could be an effective technique for promoting relaxation, particularly during the COVID-19 pandemic, where stress levels rise globally. However, more in-depth studies are required to substantiate this potential field of VR relaxation.

The authors of this paper sought to investigate the impact of virtual forest therapy based on realistic versus dreamlike environments on reducing stress levels. Today, people are facing an increase in stress levels in everyday life, which may be due to personal life, work environment, or urban area expansion. Previous studies have reported that urban environments demand more attention and mental workload than natural environments. However, evidence for the effects of natural environments as virtual forest therapy on stress levels has not yet been fully explored. In this study, a total of 20 healthy participants completed a letter-detection test to increase their stress level and were then randomly assigned to two different virtual environments representing realistic and dreamlike graphics. The participants’ stress levels were assessed using two physiological methods that measured heart rate and skin conductance levels and one psychological method through the Profile of Mood States (POMS) questionnaire. These indicators were analyzed using a sample t-test and a one-way analysis of variance. The results showed that virtual forest environments could have positive stress-relieving effects. However, realistic graphics were more efficient in reducing stress. These findings contribute to growing forest therapy concepts and provide new directions for future forest therapy research.

Human detection is a special application of object recognition and is considered one of the greatest challenges in computer vision. It is the starting point of a number of applications, including public safety and security surveillance around the world. Human detection technologies have advanced significantly in recent years due to the rapid development of deep learning techniques. Despite recent advances, we still need to adopt the best network-design practices that enable compact sizes, deep designs, and fast training times while maintaining high accuracies. In this article, we propose ReSTiNet, a novel compressed convolutional neural network that addresses the issues of size, detection speed, and accuracy. Following SqueezeNet, ReSTiNet adopts the fire modules by examining the number of fire modules and their placement within the model to reduce the number of parameters and thus the model size. The residual connections within the fire modules in ReSTiNet are interpolated and finely constructed to improve feature propagation and ensure the largest possible information flow in the model, with the goal of further improving the proposed ReSTiNet in terms of detection speed and accuracy. The proposed algorithm downsizes the previously popular Tiny-YOLO model and improves the following features: (1) faster detection speed; (2) compact model size; (3) solving the overfitting problems; and (4) superior performance than other lightweight models such as MobileNet and SqueezeNet in terms of mAP. The proposed model was trained and tested using MS COCO and Pascal VOC datasets. The resulting ReSTiNet model is 10.7 MB in size (almost five times smaller than Tiny-YOLO), but it achieves an mAP of 63.74% on PASCAL VOC and 27.3% on MS COCO datasets using Tesla k80 GPU.

Numerous studies have reported the beneficial effects of natural environments on human health and wellbeing. Virtual games may offer a practical approach to experience the illusion of being in a natural setting for those with limited access to nature. This study presents an evaluation of a nature-based virtual environment application to modulate the participant’s affective and psychological state. We developed a game-based virtual therapy using the Unity 3D game engine by implementing forest therapy activities and designing the forest environment like a real-life forest. Eight healthy adults participated in this study and were observed remotely. The participants’ mood states before and after the game were evaluated using the Profile of Mood States (POMS). In addition, the satisfaction and usability of the game-based virtual forest were assessed using the Game-User Experience Satisfaction Scale and System Usability Scale, respectively. The results revealed that participants experienced significantly improved moods (p < 0.05) and decreased stress levels (p < 0.05) after playing the game. Moreover, the results indicated multiple positive correlations between the game experience and immersion subscales, revealing that audio and visual aesthetics offered an environment for users to feel more immersed. The study suggests using virtual forest games to promote positive mood and mental health.

The signifier is regarded as a crucial part of interface design since it ensures that the user can manage the device appropriately and understand the interaction that is taking place. Useful signifiers keep users’ attention on learning, but poorly designed signifiers can disrupt learning by slowing progress and making it harder to use the interface. The problem is that prior research identified the qualities of signifiers, but their attributes in terms of being visually apparent in broad interaction areas were not well recognized. Implementing the signifier without sufficient visual features such as a picture, figure or gesture may interfere with the user’s ability to navigate the surface, particularly when dealing with domains that demand “leisure exploration,” such as those in culture and heritage, and notably the museum application. As technology has evolved and expanded, adopting a multi-touch tabletop as a medium of viewing should be advantageous in conserving cultural heritage. As technology advances and improves, employing a multi-touch tabletop as a public viewing medium should be advantageous in maintaining cultural heritage. Some visual elements should be incorporated into the signifier to produce a conspicuous presentation and make it easier for users to identify. In this study, a preliminary study, a card sorting survey, and a high-fidelity experiment were used to investigate users’ experience, perspective, and interpretation of the visual signifier of the museum interface for large displays. This work offered a set of integrated visual signifiers on a big multi-touch display that makes a substantial contribution to supporting navigation and interaction on a large display, therefore aiding comprehension of the exhibited information visualization.