Cracking the walnut: Using a computer game to impact cognition,emotion, and behavior of highly aggressive fifth grade students

Three fifth grade highly aggressive students participated in a study examining effects of an aggression intervention game. Using single-subject multiple baseline research design, the effect of the game was measured across three domains: attribution of peer intent (cognitive), emotional response (affective) and behavior response (behavioral). The results indicate that, while there were observable individual differences, the game had an immediate impact on attribution of peer behavior across all participants, had a less predictable impact on reported behavioral reactions, and had no discernable impact on reported emotional response. Theoretical and practical implications of the study are discussed.     

A hardware-independent virtual reality development system

Simulating virtual reality (VR) hardware allows programs to be written in a desktop environment without constant use of limited VR resources. Rather than shifting constantly between VR and workstation environments, developers at the Electronic Visualization Laboratory (EVL) wanted to be able to test VR applications on the normal workstation console. We therefore created a software simulator for VR development. It simulates various VR system features with an interface that runs on an ordinary workstation. The simulator is implemented as part of the CAVE library, the programming library originally written to support the CAVE hardware. It can, however, be used to develop applications for several VR systems, including ImmersaDesks and head-coupled displays. The library itself has been designed so that use of the simulator or any supported hardware is entirely transparent to application code     

Reverse‐Engineering Visualizations: Recovering Visual Encodings from Chart Images

We investigate how to automatically recover visual encodings from a chart image, primarily using inferred text elements. We contribute an end‐to‐end pipeline which takes a bitmap image as input and returns a visual encoding specification as output. We present a text analysis pipeline which detects text elements in a chart, classifies their role (e.g., chart title, x‐axis label, y‐axis title, etc.), and recovers the text content using optical character recognition. We also train a Convolutional Neural Network for mark type classification. Using the identified text elements and graphical mark type, we can then infer the encoding specification of an input chart image. We evaluate our techniques on three chart corpora: a set of automatically labeled charts generated using Vega, charts from the Quartz news website, and charts extracted from academic papers. We demonstrate accurate automatic inference of text elements, mark types, and chart specifications across a variety of input chart types.     

Multi-class classification of construction hazards via cognitive states assessment using wearable EEG

Improving workers’ safety and health is one of the most critical issues in the construction industry. Research attempts have been made to better identify construction hazards on a jobsite by analyzing workers’ physical responses (e.g., stride and balance) or physiological responses (e.g., brain waves and heart rate) collected from the wearable devices. Among them, electroencephalogram (EEG) holds unique potential since it reveals abnormal patterns immediately when a hazard is perceived and recognized. Unfortunately, the unproven capacity of EEG signals for multi-hazard classification is a primary barrier towards ubiquitous hazard identification in real-time on jobsites. This study correlates EEG signal patterns with construction hazard types and develops an EEG classifier based on the experiments conducted in an immersive virtual reality (VR) environment. Hazards of different types (e.g., fall and slip/trip) were simulated in a VR environment. EEG signals were collected from subjects who wore both wearable EEG and VR devices during the experimentation. Two types of EEG features (time-domain/frequency-domain features and cognitive features) were extracted for training and testing. A total of eighteen advanced machine learning algorithms were used to develop the EEG classifier. The initial results showed that the LightGBM classifier achieved 70.1% accuracy based on the cognitive feature set for the 7-class classification. To improve the performance, the input data was relabeled, and three strategies were designed and tested. As a result, the combined approach (two-step ensemble classification) achieved 82.3% accuracy. As such, this study not only demonstrates the feasibility of coupling wearable EEG, VR, and machine learning to differentiate jobsite hazards but also provides strategies to improve multi-class classification performance. The research results support ubiquitous hazard identification and thereby contribute to the safety of the construction workplace.     

Intelligent virtual environments for virtual reality art

The development of virtual reality (VR) art installations is faced with considerable difficulties, especially when one wishes to explore complex notions related to user interaction. We describe the development of a VR platform, which supports the development of such installations, from an art+science perspective. The system is based on a CAVE™-like immersive display using a game engine to support visualisation and interaction, which has been adapted for stereoscopic visualisation and real-time tracking. In addition, some architectural elements of game engines, such as their reliance on event-based systems have been used to support the principled definition of alternative laws of Physics. We illustrate this research through the development of a fully implemented artistic brief that explores the notion of causality in a virtual environment. After describing the hardware architecture supporting immersive visualisation we show how causality can be redefined using artificial intelligence technologies inspired from action representation in planning and how this symbolic definition of behaviour can support new forms of user experience in VR.     

Physical ergonomics of virtual environment use

This paper describes an investigation of the types of problems that may be experienced by Virtual Reality (VR) users. Initial concerns have been voiced about various issues concerning the design of VR equipment, particularly the physical ergonomics of head-mounted displays (HMDs) and hand-held input devices, and the problems associated with display resolution and lags. This study investigated a number of VR users' perceptions of the types of physical ergonomics issues that they were aware of when participating in a number of different virtual environments (VEs), using different VR systems. Several different methods were employed, including questionnaires, body mapping, user observation and interviews. Issues highlighted as either causing participants discomfort or interfering with their experience of the VE were: discomfort from static posture requirements, general discomfort from wearing the HMD, difficulty becoming accustomed to 3D hand held input devices, dissatisfaction with deficits in the visual display and fear of getting 'tangled' in connecting cables. The implications of these findings for developers, implementers and users of VR are discussed.     

A hierarchically structured and constraint-based data model for intuitive and precise solid modeling in a virtual reality environment

This article proposes a hierarchically structured and constraint-based data model for intuitive and precise solid modeling in a virtual reality (VR) environment. The data model integrates a high level constraint-based model for intuitive and precise manipulation, a middle level solid model for complete and precise representation and a low-level polygon mesh model for real-time interactions and visualization in a VR environment. The solid model is based on a hybrid B-rep/CSG data structure. Constraints are embedded in the solid model and are organized at hierarchical levels as feature constraints among internal feature elements, part constraints among internal features and assembly constraints between individual parts. In addition to providing a complete and precise model representation and the support for real-time visualization, the proposed data model permits intuitive and precise interaction through constraint-based manipulations for solid modeling in a VR environment. This is a critical issue for product design in a VR environment due to the limited resolutions of today's VR input and output devices.     

VR-Rides: An object-oriented application framework for immersive virtual reality exergames

Exercise can improve health and well-being. With this in mind, immersive virtual reality (VR) games are being developed to promote physical activity, and are generally evaluated through user studies. However, building such applications is time consuming and expensive. This paper introduces VR-Rides, an object-oriented application framework focused on the development of experiment-oriented VR exergames. Following the modular programming pattern, this framework facilitates the integration of different hardware (such as VR devices, sensors, and physical activity devices) within immersive VR experiences that overlay game narratives on Google Street View panoramas. Combining software engineering and interaction patterns, modules of VR-Rides can be easily added and managed in the Unity game engine. We evaluate the code efficiency and development effort across our VR exergames developed using VR-Rides. The reliability, maintainability, and usability of our framework are also demonstrated via code metrics analysis and user studies. The results show that investing in a systematic approach to reusing code and design can be a worthwhile effort for researchers beyond software engineering.     

Acceptability of a custom-designed game,CityQuest, aimed at improving balance confidence and spatial cognition in fall-prone and healthy older adults

Virtual reality or video games show great potential as low-cost and effective interventions for improving balance and cognitive function in older adults. This research describes the design and acceptability of a serious game (CityQuest) aimed at improving balance confidence, spatial navigation, and perceptual function in older adults with the use of a virtual environment and a balance board. Community-dwelling healthy (N?=?28) and fall-prone (N?=?28) older adults were pseudo-randomly assigned to train with CityQuest or one of two control games developed to evaluate the specific effects of the CityQuest game. Following completion of 10 training sessions, participants completed questionnaires measuring their acceptability of the game as a falls-related intervention, game experience, and subjective cognitive or balance confidence changes associated with the game. The results revealed high acceptance scores of the game and positive game experiences for all three game conditions. Older adults prone to falls reported a greater reduction in fear of falling and greater improvement in vigilance following training, compared to healthy older adults. These findings suggest that a serious game based on VR technology that trains both motor and cognitive processes is perceived to be beneficial and acceptable to healthy and fall-prone older adults.     

计算机测量控制系统的自诊断方法

通过对计算机的过程输入、输出通道电路分析，提出了扩大量程自诊断法和相关自诊法。该方法在不需要增加任何硬件检测接口电路的基础上，即能实现对过程输入、输出通道及传感器和执行器的自诊断。实践证明该方法经济、可靠、简单、易行，可以广泛应用于计算机测量控制系统和智能仪表等。     

Immersive Multiplayer Games With Tangible and Physical Interaction

In this paper, we present a new immersive multiplayer game system developed for two different environments, namely, virtual reality (VR) and augmented reality (AR). To evaluate our system, we developed three game applications-a first-person-shooter game (for VR and AR environments, respectively) and a sword game (for the AR environment). Our immersive system provides an intuitive way for users to interact with the VR or AR world by physically moving around the real world and aiming freely with tangible objects. This encourages physical interaction between players as they compete or collaborate with other players. Evaluation of our system consists of users' subjective opinions and their objective performances. Our design principles and evaluation results can be applied to similar immersive game applications based on AR/VR.     

Game engine virtual reality with CaveUT

CaveUT, an open source freeware project, uses game technology to make projection-based virtual reality affordable and accessible. The CaveUT works well for low-cost displays and supports real-time spatial tracking and stereographic imaging. Computer games with the most advanced simulation and graphics usually employ a game engine, a commercially available software package that handles basic functions. Based on the Unreal Tournament the CaveUT game engine gives developers a high-performance, low-cost VR alternative. VR applications developed with CaveUT inherit all the Unreal Engine's capabilities along with Unreal Tournament's authoring support, open source code, content library, and large user community.     

A system for head-neck rehabilitation exercises based on serious gaming and virtual reality

Acute and chronic neck pain are common medical conditions, and the treatment typically includes physical therapy involving daily exercises. Insufficient motivation of people afflicted with neck pain to adhere to the prescribed exercise regimen may delay their recovery. Accordingly, in this work, we propose a system that motivates the users to perform neck exercises by engaging them in a serious exergame within virtual reality (VR) environment. The system measures the users’ neck movements via a few static and dynamic kinematic tests and a novel VR serious game, tailored to the neck range of motion of each individual user. The game is designed to make the users perform rehabilitative neck movements according to the prescribed exercise regimen while playing. The analysis of acquired data from VR hardware provides insight into flexibility of the neck during head movements and overall neck kinematics, which is valuable for assessment of pain-related stiffness, as well as for progress monitoring. In a user study performed with the proposed system and the Oculus Rift DK2 VR headset, we show that the users find exercising more interesting and engaging when using the proposed system, and that introducing visually rich VR environments makes the users more motivated to continue exercising.     

基于AVR单片机的智能跑步机控制器设计

介绍了基于AVR单片机ATmega128的智能电动跑步机控制器的软、硬件设计。系统采用上、下位机的结构,上位机提供虚拟场景漫游和人机界面的显示,下位机以单片机为核心控制器,通过多路开关量输入/输出、编码器信号输入、矩阵式键盘输入、与上位机的串行通信等对电动跑步机进行实时控制。在操作上采用触摸屏与薄膜按键结合的方式,通过串行通信实现上下位机的协调,在实际应用中运行稳定,达到设计要求。     

基于VR技术的电力系统异常情况巡检系统设计

为有效提高电力异常情况巡检系统的数据读取效率和系统稳定性,提出了基于VR技术的电力系统异常情况巡检系统。在硬件部分,设计服务器端口模块和数据通信接口模块,实现对电力系统异常情况的检验、采集和传输;在软件部分,制定异常数据巡检流程,输入VR全景巡视信息,通过系统分析实现对异常情况的读取。仿真测试结果显示,相比于其它巡检系统,所提系统对异常数据的读取效率大大提高,巡检过程受外界干扰较小、输出结果有效性更强、系统运行过程稳定性较高。     

An integrated emotional and physiological assessment for VR-based active shooter incident experiments

Unfortunately, active shooter incidents are on the rise in the United States. With the recent technological advancements, virtual reality (VR) experiments could serve as an effective method to prepare civilians and law enforcement personnel for such scenarios. However, for VR experiments to be effective for active shooter training and research, such experiments must be able to evoke emotional and physiological responses as live active shooter drills and events do. The objective of this study is thus to test the effectiveness of an active shooter VR experiment on emotional and physiological responses. Additionally, we consider different locomotion techniques (i.e., walk-in-place and controller) and explore their impact on users’ sense of presence. The results suggest that the VR active shooter experiment in this study can induce emotional arousal and increase heart rate of the participants immersed in the virtual environment. Furthermore, compared to the controller, the walk-in-place technique resulted in a higher emotional arousal in terms of negative emotions and a stronger sense of presence. The study presents a foundation for future active shooter experiments as it supports the ecological validity using VR for active shooter incident related work for the purposes of training or research.     

Body Movement Reduces Pain Intensity in Virtual Reality–Based Analgesia

In this study we investigated the relationship between body movement during virtual reality (VR) analgesia and the experience of pain. Thermal (cold) stimulation was used to inflict pain. Two measures of pain were used—pain tolerance and pain intensity. Participants were wearing head mounted displays (Oculus Rift DK2) and were playing a game created by authors of the study.

Forty-six students of Wroclaw University participated in a within-subject design experiment. Each subject participated in a non-VR control condition and in two experimental conditions. Participants navigated the VR game using a computer mouse, but the mouse sensitivity (and therefore amount of physical movement necessary to navigate) was different in each experimental condition. We also measured feeling of presence in VR, game behavior, and attitudes toward the game.

The amount of body movement while steering the game was related to a decrease in pain intensity, but not in pain tolerance. This was an opposite result to our previously published experiment where we found an effect on pain tolerance but not on sensitivity. There was no significant correlation between presence and any of the pain measures.     

基于VR的虚拟现实模型优化研究

分析了影响模型输出的3种原因：硬件、图形处理卡和模型表面构成。以＂绘制流水线＂理论为基础,分析了VR系统结构的设计方法,重点研究了绘制流水线上应用程序阶段、几何阶段、光栅化阶段产生瓶颈的原因以解决瓶颈的优化方法,讨论了加快模型输出的方法。     

System Integration for Cognitive Model of a Robot Partner

This paper introduces the integrated system of a smart-device-based cognitive robot partner called iPhonoid-C. Interaction with a robot partner requires many elements, including verbal communication, nonverbal communication, and embodiment as well. A robot partner should be able to understand human sentences, as well as nonverbal information such as human gestures. In the proposed system, the robot has an emotional model connecting the input information from the human with the robot’s behavior. Since emotions are involved in human natural communication, and emotion has a significant impact on humans’ actions, it is important to develop an emotional model for the robot partner to enhance human robot interaction. In our proposed system, human sentences and gestures influence the robot’s emotional state, and then the robot will perform gestural and facial expressions and generate sentences according to its emotional state. The proposed cognitive method is validated using a real robot partner.