From ‘hands up’ to ‘hands on’: harnessing the kinaesthetic potential of educational gaming

Traditional approaches to distance learning and the student learning journey have focused on closing the gap between the experience of off-campus students and their on-campus peers. While many initiatives have sought to embed a sense of community, create virtual learning environments and even build collaborative spaces for team-based assessment and presentations, they are limited by technological innovation in terms of the types of learning styles they support and develop. Mainstream gaming development – such as with the Xbox Kinect and Nintendo Wii – have a strong element of kinaesthetic learning from early attempts to simulate impact, recoil, velocity and other environmental factors to the more sophisticated movement-based games which create a sense of almost total immersion and allow untethered (in a technical sense) interaction with the games’ objects, characters and other players. Likewise, gamification of learning has become a critical focus for the engagement of learners and its commercialisation, especially through products such as the Wii Fit. As this technology matures, there are strong opportunities for universities to utilise gaming consoles to embed levels of kinaesthetic learning into the student experience – a learning style which has been largely neglected in the distance education sector. This paper will explore the potential impact of these technologies, to broadly imagine the possibilities for future innovation in higher education

A decision forest based feature selection framework for action recognition from RGB-Depth cameras

In this paper, we present an action recognition framework leveraging data mining capabilities of random decision forests trained on kinematic features. We describe human motion via a rich collection of kinematic feature time-series computed from the skeletal representation of the body in motion. We discriminatively optimize a random decision forest model over this collection to identify the most effective subset of features, localized both in time and space. Later, we train a support vector machine classifier on the selected features. This approach improves upon the baseline performance obtained using the whole feature set with a significantly less number of features (one tenth of the original). On MSRC-12 dataset (12 classes), our method achieves 94% accuracy. On the WorkoutSU-10 dataset, collected by our group (10 physical exercise classes), the accuracy is 98%. The approach can also be used to provide insights on the spatiotemporal dynamics of human actions

Designing wheelchair-based movement games

People using wheelchairs have access to fewer sports and other physically stimulating leisure activities than nondisabled persons, and often lead sedentary lifestyles that negatively influence their health. While motion- based video games have demonstrated great potential of encouraging physical activity among nondisabled players, the accessibility of motion-based games is limited for persons with mobility disabilities, thus also limiting access to the potential health benefits of playing these games. In our work, we address this issue through the design of wheelchair-accessible motion-based game controls. We present KINECTWheels, a toolkit designed to integrate wheelchair movements into motion-based games. Building on the toolkit, we developed Cupcake Heaven, a wheelchair-based video game designed for older adults using wheelchairs, and we created Wheelchair Revolution, a motion-based dance game that is accessible to both persons using wheelchairs and nondisabled players. Evaluation results show that KINECTWheels can be applied to make motion-based games wheelchair-accessible, and that wheelchair-based games engage broad audiences in physically stimulating play. Through the application of the wheelchair as an enabling technology in games, our work has the potential of encouraging players of all ages to develop a positive relationship with their wheelchair

Exploring heritage through time and space : Supporting community reflection on the highland clearances

On the two hundredth anniversary of the Kildonan clearances, when people were forcibly removed from their homes, the Timespan Heritage centre has created a program of community centred work aimed at challenging pre conceptions and encouraging reflection on this important historical process. This paper explores the innovative ways in which virtual world technology has facilitated community engagement, enhanced visualisation and encouraged reflection as part of this program. An installation where users navigate through a reconstruction of pre clearance Caen township is controlled through natural gestures and presented on a 300 inch six megapixel screen. This environment allows users to experience the past in new ways. The platform has value as an effective way for an educator, artist or hobbyist to create large scale virtual environments using off the shelf hardware and open source software. The result is an exhibit that also serves as a platform for experimentation into innovative ways of community co-creation and co-curation.Postprin

Deep Affordance-grounded Sensorimotor Object Recognition

It is well-established by cognitive neuroscience that human perception of objects constitutes a complex process, where object appearance information is combined with evidence about the so-called object "affordances", namely the types of actions that humans typically perform when interacting with them. This fact has recently motivated the "sensorimotor" approach to the challenging task of automatic object recognition, where both information sources are fused to improve robustness. In this work, the aforementioned paradigm is adopted, surpassing current limitations of sensorimotor object recognition research. Specifically, the deep learning paradigm is introduced to the problem for the first time, developing a number of novel neuro-biologically and neuro-physiologically inspired architectures that utilize state-of-the-art neural networks for fusing the available information sources in multiple ways. The proposed methods are evaluated using a large RGB-D corpus, which is specifically collected for the task of sensorimotor object recognition and is made publicly available. Experimental results demonstrate the utility of affordance information to object recognition, achieving an up to 29% relative error reduction by its inclusion.Comment: 9 pages, 7 figures, dataset link included, accepted to CVPR 201

Comparative Analysis of The Effects Of Virtual Reality Active Video Game And Controller-Free Active Video Game Play On Physiological Response, Perceived Exertion, And Hedonic Experience

Over 60% of US adults are overweight or obese. Sedentary lifestyles are considered major contributors to the high rates and increasing prevalence of obesity. Physical activity is a critical component in shifting from sedentary lifestyles. Studies indicate that less than half of U.S. adults meet the CDC/ACSM physical activity recommendations. Interactive video games can increase PA, but no study has yet assessed physiologic effort, hedonics, and perceived exertion for playing immersive virtual reality (VR) and controller-free screen-based active video games (AVGs), compared to treadmill walking and resting. We ran 25 subjects (9 female, 16 male) in 10-minute sessions of five conditions. Head Mounted Display VR: Oculus (Fruit Ninja and Boxing), Screen-based AVG: Kinect (Fruit Ninja and Boxing), and Treadmill walking at 3 mph. One, six-condition (Rest, Treadmill 3.0, Kinect Boxing, Kinect Fruit Ninja, Oculus Boxing, Oculus Fruit Ninja) repeated-measures ANOVA was used to examine differences in HRmean. Three, five-condition (Treadmill 3.0, Kinect Boxing, Kinect Fruit Ninja, Oculus Boxing, Oculus Fruit Ninja) repeated-measures ANOVA were used to examine differences in HRpeak, ratings of perceived exertion (RPE) and Hedonics (Liking). Post hoc analyses using pairwise comparisons were used to further assess significant main effects of the condition. A Pearson\u27s product-moment correlation was run to assess the relationship between activity condition HRmean and RPE VR Boxing elicited the greatest physiological effort, producing vigorous-intensity PA. There was no significant difference in average heart rate for the Treadmill, Kinect Fruit Ninja, Kinect Boxing, and VR Fruit Ninja. Thus, the Kinect and VR sport and casual games are comparable to treadmill walking PA levels and qualify as moderate-intensity activity. The VR Fruit Ninja, VR Boxing, Kinect Fruit Ninja were the most enjoyed activities. Despite having the highest Heart rate and the highest self-reported Rating of Perceived Exertion (RPE), VR Boxing was significantly more enjoyable than Treadmill Walking. There was no statistically significant correlation between Activity Condition HRmean and RPE. Both casual and sports VR and AVG activities are enjoyable activities for adults, stimulating moderate-to-vigorous activity through a traditionally sedentary medium. This research extends previous works in active video gaming effects on physiological cost, perceived exertion and hedonics and fills the gap relating virtual reality active video games. The significance of the research outcomes is that this analysis provides a scientifically validated approach to support the establishment of physical activity level goals and guidelines in the development of active video games as a response and/or remedy to address the sedentary lifestyles that are contributing to American and global obesity

Custom-designed motion-based games for older adults: a review of literature in human-computer interaction

Many older adults, particularly persons living in senior residences and care homes, lead sedentary lifestyles, which reduces their life expectancy. Motion-based video games encourage physical activity and might be an opportunity for these adults to remain active and engaged; however, research efforts in the field have frequently focused on younger audiences and little is known about the requirements and benefits of motion-based games for elderly players. In this paper, we present an overview of motion-based video games and other interactive technologies for older adults. First, we summarize existing approaches towards the definition of motion-based video games – often referred to as exergames – and suggest a categorization of motion-based applications into active video games, exergames, and augmented sports. Second, we use this scheme to classify case studies addressing design efforts particularly directed towards older adults. Third, we analyze these case studies with a focus on potential target audiences, benefits, challenges in their deployment, and future design opportunities to investigate whether motion-based video games can be applied to encourage physical activity among older adults. In this context, special attention is paid to evaluation routines and their implications regarding the deployment of such games in the daily lives of older adults. The results show that many case studies examine isolated aspects of motion-based game design for older adults, and despite the broad range of issues in motion-based interaction for older adults covered by the sum of all research projects, there appears to be a disconnect between laboratory-based research and the deployment of motion-based video games in the daily lives of senior citizens. Our literature review suggests that despite research results suggesting various benefits of motion-based play for older adults, most work in the field of game design for senior citizens has focused on the implementation of accessible user interfaces, and that little is known about the long-term deployment of video games for this audience, which is a crucial step if these games are to be implemented in activity programs of senior residences, care homes, or in therapy