Search

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. This research is supported by Yayasan Universiti Teknologi PETRONAS through YUTP Fundamental Research Grant No. 015LC0-246.

This study investigates subjects’ behavior in visual audio conflict conditions in stressful and stressless environments. To increase subjects’ stress and anxiety in subjects we placed subjects in a chaotic city and to decrease subjects’ stress we benefit from a green virtual environment. On the other hand to study the effect of sound on physiological data we designed confilict condition in which in the City environment participants heared the sound of Forest and in the Forest nvironment they heared the sound of City. To evaluate our findings we benefit from the heart rate of the participants which is directly related to subjects’ emotions and participants can not involve their opinion to change this feature autonomously. French government funding managed by the National Research Agency under the Investments for the Future program (PIA) grant ANR-21-ESRE-0030 (CONTINUUM).

Human detection is an important task in computer vision. It is one of the most important tasks in global security and safety monitoring. In recent days, Deep Learning has improved human detection technology. Despite modern techniques, there are very few optimal techniques to construct networks with a small size, deep architecture, and fast training time while maintaining accuracy. ReSTiNet is a novel small convolutional neural network that overcomes the problems of network size, detection speed, and accuracy. The developed ReSTiNet contains fire modules by evaluating their number and position in the network to minimize the model parameters and network size. To improve the detection speed and accuracy of ReSTiNet, the residual block within the fire modules is carefully designed to increase the feature propagation and maximize the information flow in the network. The developed approach compresses the well-known Tiny-YOLO architecture while improving the following features

It is estimated that by 2050, the world’s population will increase to 10 billion people and water scarcity is going to be a major problem due to an increase number of populations with limited water resources. One of the ways to tackle this problem is by having a precision irrigation which is by estimating the crops water need in which it can improve water utilization. This research is very suitable to be implemented for paddy since paddy consumed a lot of water compared to other types of crops. In order to be able to do it, ANN and Evapotranspiration Rate equation will be used to develop a prediction model to estimate water lost. The prediction model in theory will analyze the historical data and compared it with current data collected in the field and predict water needs based on the output concluded. IoT will act as monitoring and controlling platform for irrigation by automating the irrigation which in result, better water utilization. Prediction model and IoT combination proved that better water utilization can be achieved. The targeted result will be to achieve better water utilization using prediction model and IoT.

Accessibility and usability are two important concepts for universal design but have been given less emphasis by most developers especially when developing web interfaces. Among the affected users are the elderly people who are facing difficulties interacting with the computer devices as the interface could not fully support the changes in their sensorial, motor and cognitive abilities. The objective of this study is to elicit elderly readers’ opinions on the interface of eText in order to support their reading. It discovers elderly people preferences on the background and font color on the interface for reading. The study is motivated by reported work claiming that these two interface elements could support the elders in reading. Through an interview, a suitable contrast color of background and text was determined. The findings were used to design an e-text interface and tested with elderly people. The study findings could help designers to better design e-text interface for elderly readers.

Stress-related disorders are increasing because of work load, forces in teamwork, surroundings pressures and health related conditions. Thus, to avoid people living under heavy stress and develop more severe stress-related disorders, different internet and applications of stress management interventions are offered. Mobile applications with self-assessed health, burnout-scores and well-being are commonly used as outcome measures. Few studies have used sickleave to compare effects of stress interventions. A new approach is to use nature and garden in a multimodal stress management context. This study aimed to explore the effects of immersive and non-immersive games application by using nature theme virtual stress therapy in reducing stress level. Two weeks’ of experiments had involved 18 participants. Nine (9) of them were invited to join the first experiment which focused on immersive virtual reality (VR) experience. Their Blood Volume Pulse with Heart Rate (BVP+HR) and Skin Conductance (SC) were recorded using BioGraph Infiniti Biofeedback System that comes with three (3) sensors attached to the fingers. The second experiment were joined by another nine (9) participants. This experiment was testing on non-immersive desktop control experience. The same protocol measurements were taken which are BVP+HR and SC. Participants were given the experience to feel and get carried into the virtual nature as a therapy so that they will reduce stress. The result of this study points to whether immersive or non-immersive VR display using nature theme virtual therapy would reduce individuals stress level. After conducted series of experiments, results showed that both immersive and non-immersive VR display reduced stress level. However, participants were satisfied of using the immersive version as it provided a 360 degree of viewing, immersed experiences and feeling engaged. Thus, this showed and proved that applications developed with nature theme affect successfully reduce stress level no matter it is put in immersive or non-immersive display.

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. This research is supported by the Institute of Health Analytics (IHA), Universiti Teknologi PETRONAS.

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. Yayasan Universiti Teknologi PETRONAS through YUTP Fundamental Research Grant No. 015LC0-001

International audience; Stroke is a condition that happens when the brain is cut off from blood supply. Patients are at risk of disabilities. To help patient recover, gain mobility, and independence, rehabilitation starts as soon as possible. Unfortunately for some patients, they are forced to undergo long-term rehabilitation period. Since the activities during therapy are repetitive, many patient losses their motivation to continue therapy thus unable to recover. Virtual reality has been found to increase motivation for stroke rehabilitation. Its key elements, especially sensory feedback and interactivity have been found to increase motivation and engagement especially when applied to gamification. However, practitioners in related field have raised concern on the relevancy of some VR elements used for rehabilitation. Inappropriate elements may not be effective for the program; thus, requires further investigation. This paper explores various elements that could encourage motivation, bring better engagement, and enhance task performance of stroke patients via VR-based rehabilitation. A literature survey was conducted. The findings signal for the importance of sensory feedback and interactivity when used in VR environment for stroke patients in their rehabilitation programme.

Imputing missing data plays a pivotal role in minimizing the biases of knowledge in computational data. The principal purpose of this paper is to establish a better approach to dealing with missing data. Clinical data often contain erroneous data, which cause major drawbacks for analysis. In this paper, we present a new dynamic approach for managing missing data in biomedical databases in order to improve overall modeling accuracy. We propose a reinforcement Bayesian regression model. Furthermore; we compare the Bayesian Regression and the random forest dynamically under a reinforcement approach to minimize the ambiguity of knowledge. Our result indicates that the imputation method of random forest scores better than the Bayesian regression in several cases. At best the reinforcement Bayesian regression scores over 85% under range condition of 5% missing data. The reinforcement Bayesian regression performs over 70% accuracy for imputing missing medical data in overall condition. However; the proposed reinforcement Bayesian regression models imputed missing data on over 70% cases are exactly identical to the missing value, which is remarkably making the advantage of the study. This approach significantly improves the accuracy of imputing missing data for clinical research.