Auditory and Spatial Assessment in Inattentive Children Using Smart Devices and Gesture Interaction

We present an interactive game for assessing auditory and spatial memory. We compared the performance of children with and without inattention using the game and using a variety of classical tools for assessment of auditory and spatial memory. The children with inattention showed statistically worse performance in the game. There were no statistically significant differences between the two groups for the satisfaction and interaction outcomes. Therefore, our game could be a good tool for distinguishing performances of children with and without inattention

Evaluating new interaction paradigms in SEN teaching: defining the experiment

New devices have made their way into everyday life in recent years, opening the doors to new ways of interacting with computers, providing different, and potentially better, solutions to some problems. But this raises the question of if there is any way of measuring whether or not these new devices are suitable. This paper presents a strategy for evaluating the suitability of new interaction devices in the context of teaching children with special educational need

Detection of visitors in elderly care using a low-resolution visual sensor network

Loneliness is a common condition associated with aging and comes with extreme health consequences including decline in physical and mental health, increased mortality and poor living conditions. Detecting and assisting lonely persons is therefore important-especially in the home environment. The current studies analyse the Activities of Daily Living (ADL) usually with the focus on persons living alone, e.g., to detect health deterioration. However, this type of data analysis relies on the assumption of a single person being analysed, and the ADL data analysis becomes less reliable without assessing socialization in seniors for health state assessment and intervention. In this paper, we propose a network of cheap low-resolution visual sensors for the detection of visitors. The visitor analysis starts by visual feature extraction based on foreground/background detection and morphological operations to track the motion patterns in each visual sensor. Then, we utilize the features of the visual sensors to build a Hidden Markov Model (HMM) for the actual detection. Finally, a rule-based classifier is used to compute the number and the duration of visits. We evaluate our framework on a real-life dataset of ten months. The results show a promising visit detection performance when compared to ground truth

Designing for Ballet Classes: Identifying and Mitigating Communication Challenges Between Dancers and Teachers

Dancer-teacher communication in a ballet class can be challenging: ballet is one of the most complex forms of movements, and learning happens through multi-faceted interactions with studio tools (mirror, barre, and floor) and the teacher. We conducted an interview-based qualitative study with seven ballet teachers and six dancers followed by an open-coded analysis to explore the communication challenges that arise while teaching and learning in the ballet studio. We identified key communication issues, including adapting to multi-level dancer expertise, transmitting and realigning development goals, providing personalized corrections and feedback, maintaining the state of flow, and communicating how to properly use tools in the environment. We discuss design implications for crafting technological interventions aimed at mitigating these communication challenges

GESTURE RECOGNITION FOR PENCAK SILAT TAPAK SUCI REAL-TIME ANIMATION

The main target in this research is a design of a virtual martial arts training system in real-time and as a tool in learning martial arts independently using genetic algorithm methods and dynamic time warping. In this paper, it is still in the initial stages, which is focused on taking data sets of martial arts warriors using 3D animation and the Kinect sensor cameras, there are 2 warriors x 8 moves x 596 cases/gesture = 9,536 cases. Gesture Recognition Studies are usually distinguished: body gesture and hand and arm gesture, head and face gesture, and, all three can be studied simultaneously in martial arts pencak silat, using martial arts stance detection with scoring methods. Silat movement data is recorded in the form of oni files using the OpenNI ™ (OFW) framework and BVH (Bio Vision Hierarchical) files as well as plug-in support software on Mocap devices. Responsiveness is a measure of time responding to interruptions, and is critical because the system must be able to meet the demand

Effect of sensory-based technologies on atypical sensory responses of children with Autism Spectrum Disorder: A systematic review

© 2021 ACM, Inc. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1145/3485768.3485782.Atypical sensory responses are one of the most common issues observed in Autism Spectrum Disorder (ASD), affecting the development of a child's capability for social interaction, independent living and learning. In the past two decades, there has been a growing number of studies of technology-based interventions for atypical sensory responses of individuals with ASD. However, their effects and limitations have not been fully examined. This systematic review investigates the effects of sensory-based technologies (SBTs) on atypical sensory responses of children with ASD. Publications that report on the use of a SBT as an intervention tool were retrieved from four academic databases: “PubMed”, “IEEE Xplore”, “ACM Digital Library” and “Web of Science”. The search finally yielded 18 articles. The results indicated an emerging trend of studies investigating the effects of SBTs on atypical sensory responses over the past decade. Challenges and limitations were found in studies, mainly because the literatures adopted different methods and indicators, small sample sizes, and varying experimental designs. Findings were that the use of SBTs could effectively improve auditory and visual recognition, and some other behavioural outcomes such as attention in children with ASD. Future development of SBTs could further integrate more advanced techniques, such as machine learning, in order to widen the scope of SBTs usage to help more ASD children

A Survey of Smart Classroom Literature

Recently, there has been a substantial amount of research on smart classrooms, encompassing a number of areas, including Information and Communication Technology, Machine Learning, Sensor Networks, Cloud Computing, and Hardware. Smart classroom research has been quickly implemented to enhance education systems, resulting in higher engagement and empowerment of students, educators, and administrators. Despite decades of using emerging technology to improve teaching practices, critics often point out that methods miss adequate theoretical and technical foundations. As a result, there have been a number of conflicting reviews on different perspectives of smart classrooms. For a realistic smart classroom approach, a piecemeal implementation is insufficient. This survey contributes to the current literature by presenting a comprehensive analysis of various disciplines using a standard terminology and taxonomy. This multi-field study reveals new research possibilities and problems that must be tackled in order to integrate interdisciplinary works in a synergic manner. Our analysis shows that smart classroom is a rapidly developing research area that complements a number of emerging technologies. Moreover, this paper also describes the co-occurrence network of technological keywords using VOSviewer for an in-depth analysis

Evaluation of CNN-based Single-Image Depth Estimation Methods

While an increasing interest in deep models for single-image depth estimation methods can be observed, established schemes for their evaluation are still limited. We propose a set of novel quality criteria, allowing for a more detailed analysis by focusing on specific characteristics of depth maps. In particular, we address the preservation of edges and planar regions, depth consistency, and absolute distance accuracy. In order to employ these metrics to evaluate and compare state-of-the-art single-image depth estimation approaches, we provide a new high-quality RGB-D dataset. We used a DSLR camera together with a laser scanner to acquire high-resolution images and highly accurate depth maps. Experimental results show the validity of our proposed evaluation protocol

Learning in hybrid spaces as a technology-enhanced outdoor learning: Key terms

One of the ideas for improving urban green spaces is adding to them a virtual dimension, or - in other words - equipping them with some kind of technological infrastructure. Such spaces, combining a nature with technology, are named in many terms, e.g. outdoor cyber-mediated spaces, technologically enhanced urban green spaces, blended digital/urban green spaces or - what is the most precise - hybrid spaces. Hybrid space is quite innovative solution, because traditionally the natural environment and digital domains are seen as distinctly different. In addition, researchers agree that hybrid spaces offer an attractive learning context. Although little is known about learning in hybrid spaces. This paper defines learning in hybrid spaces as a technology-enhanced outdoor learning and discusses contextual key terms as technology-enhanced learning and outdoor learning, and also technological requirements for technology-enhanced outdoor learning, selected technologies of technology-enhanced outdoor learning such as personal digital assistant, e-library, quick response codes, Kinect-laptop-integrated system, geographic positioning system, digital textbooks, cloud computing; and finally design guidelines for technology-enhanced outdoor learning. This can be useful for anyone interested in educational use of hybrid spaces