Classification of Daily Activities for the Elderly Using Wearable Sensors

Monitoring of activities of daily living (ADL) using wearable sensors can provide an objective indication of the activity levels or restrictions experienced by patients or elderly. The current study presented a two-sensor ADL classification method designed and tested specifically with elderly subjects. Ten healthy elderly were involved in a laboratory testing with 6 types of daily activities. Two inertial measurement units were attached to the thigh and the trunk of each subject. The results indicated an overall rate of misdetection being 2.8%. The findings of the current study can be used as the first step towards a more comprehensive activity monitoring technology specifically designed for the aging population

A Study Exploring Different Modalities to Integrate Learning Objectives in Games

This research aims to provide further insight on how to design effective educational games by exploring whether the integration of educational content through game mechanics, text, or a combination of both text and game mechanics is more effective in teaching the learning outcomes in games. The results of the study show that all three methods led to information assimilation. The study showed that the participants did not necessarily learn better through a combination of text and game mechanics as compared with those who were exposed to learning objectives integrated into the game only through text or game mechanics. Some learning objectives were better learned when they were integrated through text while others through game mechanics

Conceptual Model of Game Aesthetics for Perceived Learning in Narrative Games

Narrative games may offer reasoning on players’ behaviour or make-believe on players’ personation as a pursuit to achieve specific goals. One of the goals is probably the intention to instil learning, which subconsciously provide information on the content of the game. However, there is lack of studies on the contribution of game aesthetics towards player’s perceived learning. By means of expert review, this article reports on conceptual model of game aesthetics towards perceived learning and the degree of importance of each attributes in perceived learning.  Findings reveal that all experts agreed on the contribution of game aesthetics towards perceived learning. In additon, expert recommends three other factors that may contribute to learning: player’s motivation, learning content, and gameplay. Future work will continue to design and develop the game prototype and to investigate the relationship between game aesthetics and perceived learning

Visualization of Tomato Growth Based on Dry Matter Flow

The visualization of tomato growth can be used in 3D computer games and virtual gardens. Based on the growth theory involving the respiration theory, the photosynthesis, and dry matter partition, a visual system is developed. The tomato growth visual simulation system is light-and-temperature-dependent and shows plausible visual effects in consideration of the continuous growth, texture map, gravity influence, and collision detection. In addition, the virtual tomato plant information, such as the plant height, leaf area index, fruit weight, and dry matter, can be updated and output in real time

Edu-Interact:An Authoring Tool for Interactive Digital Storytelling based Games

In this research, we present an authoring environment, Edu-Interact, that supports the creation of adaptive interactive digital storytelling based games. Edu-Interact allows to design a story that seamlessly evaluates the student knowledge, performs the subsequent adaptation of the digital storytelling, and provides a summative assessment. The authoring environment allows also to assign weights to different concepts the student could accumulate through the interaction with the storytelling. This can provide a score that could be used as a means of gamifying the interactive digital storytelling or provide teachers or other stakeholders with feedback on the student performance

The effect of interactive digital storytelling gamification on microbiology classroom interactions

In this research, we study the use of interactive digital storytelling in teaching microbiology. More specifically, we carried out an exploratory study assessing the effect of using the gamification of an interactive digital storytelling on classroom dynamics and students’ interaction. The results show that the presence of gamification led to an increase in classroom discussions and in students’ engagement with the learning objectives taught by the interactive digital storytelling

New Trends in Using Augmented Reality Apps for Smart City Contexts

The idea of virtuality is not new, as research on visualization and simulation dates back to the early use of ink and paper sketches for alternative design comparisons. As technology has advanced so the way of visualizing simulations as well, but the progress is slow due to difficulties in creating workable simulations models and effectively providing them to the users. Augmented Reality and Virtual Reality, the evolving technologies that have been haunting the tech industry, receiving excessive attention from the media and colossal growing are redefining the way we interact, communicate and work together. From consumer application to manufacturers these technologies are used in different sectors providing huge benefits through several applications. In this work, we demonstrate the potentials of Augmented Reality techniques in a Smart City (Smart Campus) context. A multiplatform mobile app featuring Augmented Reality capabilities connected to GIS services are developed to evaluate different features such as performance, usability, effectiveness and satisfaction of the Augmented Reality technology in the context of a Smart Campus

Feature Analysis to Human Activity Recognition

Human activity recognition (HAR) is one of those research areas whose importance and popularity have notably increased in recent years. HAR can be seen as a general machine learning problem which requires feature extraction and feature selection. In previous articles different features were extracted from time, frequency and wavelet domains for HAR but it is not clear that, how to determine the best feature combination which maximizes the performance of a machine learning algorithm. The aim of this paper is to present the most relevant feature extraction methods in HAR and to compare them with widely-used filter and wrapper feature selection algorithms. This work is an extended version of [1]a where we tested the efficiency of filter and wrapper feature selection algorithms in combination with artificial neural networks. In this paper the efficiency of selected features has been investigated on more machine learning algorithms (feed-forward artificial neural network, k-nearest neighbor and decision tree) where an independent database was the data source. The result demonstrates that machine learning in combination with feature selection can overcome other classification approaches