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.

As technological advancements increase exponentially, mobile phones become smarter with machine learning and artificial intelligence algorithms. These advancements have allowed mobile phone users to perform most of their daily routine tasks on mobile phones; tasks performed in daily routines are called repetitive tasks and are performed manually by the users themselves. However, machine learning and artificial intelligence have enabled those tasks to be performed automatically, known as task automation. The users can perform task automation, e.g., through creating automation rules or an intelligent agent, e.g., conversational agents, virtual personal assistants, etc. Several techniques to achieve task automation have been proposed, but this review shows that task automation by programming by demonstration has had massive developmental growth because of its user-centered approach. Apple Siri, Google Assistant, MS Cortana, and Amazon Alexa are the most known task automation agents. However, these agents are not widely adopted because of their usability issues. In this study, two research questions are evaluated through the available literature to expand the research on intelligent task automation agents: (1) What is the state-of-the-art in task automation agents? (2) What are the existing methods and techniques for developing usability heuristics, specifically for intelligent agents? Research shows groundbreaking developments have been made in mobile phone task automation recently. However, it must still be conducted per usability principles to achieve maximum usability and user satisfaction. The second research question further justifies developing a set of domain-specific usability heuristics for mobile task automation intelligent agents.

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.

Cancer is a leading cause of death worldwide. Lung cancer is a type of cancer that is considered as one of the most leading causes of death globally. In Malaysia, it is the 3rd common cancer type and the 2nd type of cancer among men. In this paper, machine learning techniques have been utilized to develop a computer-aided diagnosis system for lung cancer. The system consists of feature extraction phase, feature selection phase and classification phase. For feature extraction/selection, different wavelets functions have been applied in order to find the one that produced the highest accuracy. Clustering-K-nearest-neighbor algorithm has been developed/utilized for classification. Japanese Society of Radiological Technology's standard dataset of lung cancer has been used to test the system. The data set has 154 nodule regions (abnormal) and 92 non-nodule regions (normal). Accuracy levels of over 96% for classification have been achieved which demonstrate the merits of the proposed approach.

Virtual reality (VR) is highly recommended for stroke rehabilitation as it was found to aid in recovery and could motivate users. While there are various VR rehabilitation studies, the impact of virtual environments on rehabilitation is less studied. This study investigates the added value of an enriched virtual environment on motivation and engagement in stroke rehabilitation. A validity study was conducted on healthy participants (N=25) in two environments, enriched VR and non-enriched VR. Our hypotheses were: 1) Enriched virtual environment with multisensory feedback, gamification, and adaptive function adds value to motivation and engagement of user with applications by increasing interest/enjoyment, perceived choice, value/usefulness, relatedness of application. 2) Motivated and engaged users spent more time or scored more points in the application. The key findings of this study are that intrinsic motivation is higher in the enriched VR environment (EVE) compared to the non-enriched VR (NEVE). There are significant differences in motivation between these two environments. Besides, results have shown that more participants are engaged in enriched VR, thus spending more time and scoring higher, Spearman’s ρ = 0.809.