Development of a novel virtual environment for assessing cognitive function. Design, Development and Evaluation of a Novel Virtual Environment to Investigate Cognitive Function and Discriminate between Mild Cognitive Impairment and Healthy Elderly.

Alzheimer's disease (AD) is neurodegenerative disorder that causes memory loss and cognitive dysfunction. It affects one in five people over the age of 80 and is distressing for both sufferers and their families. A transitional stage between normal ageing and dementia including AD is termed a mild cognitive impairment (MCI). Recent studies have shown that people with MCI may convert to AD over time although not all MCI cases progress to AD. Much research is now focussing on early detection of AD and diagnosing an MCI that will progress to AD to allow prompt treatment and disease management before the neurons degenerate to a stage beyond repair. Hence, the ability to obtain a method of identifying MCI is of great importance. Virtual reality plays an important role in healthcare and offers opportunities for detection of MCI. There are various studies that have focused on detection of early AD using virtual environments, although results remain limited. One significant drawback of these studies has been their limited capacity to incorporate levels of difficulty to challenge users' capability. Furthermore, at best, these studies have only been able to discriminate between early AD and healthy elderly with about 80% of overall accuracy. As a result, a novel virtual simulation called Virtual Reality for Early Detection of Alzheimer's Disease (VREAD) was developed. VREAD is a quick, easy and friendly tool that aims to investigate cognitive functioning in a group of healthy elderly participants and those with MCI. It focuses on the task of following a route, since Topographical Disorientation (TD) is common in AD. An investigation was set up with two cohorts: non-elderly and elderly participants. The findings with regard to the non-elderly are important as they represent a first step towards implementation with elderly people. The results with elderly participants indicate that this simulation based assessment could provide a method for the detection of MCI since significant correlations between the virtual simulation and existing neuropsychological tests were found. In addition, the results proved that VREAD is comparable with well-known neuropsychological tests, such as Cambridge Neuropsychological Automated Test Battery, Paired Associate Learning (CANTAB PAL) and Graded Naming Test (GNT). Furthermore, analysis through the use of machine learning techniques with regard to the prediction of MCI also obtained encouraging results. This novel simulation was able to predict with about 90% overall accuracy using weighting function proposed to discriminate between MCI and healthy elderly.Ministry of Higher Education, Malaysia and University Sultan Zainal Abidin, Malaysia (UNisZa

Shape-Based Single Object Classification Using Ensemble Method Classifiers

Nowadays, more and more images are available. Annotation and retrieval of the images pose classification problems, where each class is defined as the group of database images labelled with a common semantic label. Various systems have been proposed for content-based retrieval, as well as for image classification and indexing. In this paper, a hierarchical classification framework has been proposed for bridging the semantic gap effectively and achieving multi-category image classification. A well-known pre-processing and post-processing method was used and applied to three problems; image segmentation, object identification and image classification. The method was applied to classify single object images from Amazon and Google datasets. The classification was tested for four different classifiers; BayesNetwork (BN), Random Forest (RF), Bagging and Vote. The estimated classification accuracies ranged from 20% to 99% (using 10-fold cross validation). The Bagging classifier presents the best performance, followed by the Random Forest classifier

Heuristic Evaluation Of i-Dyslex Tool for Dyslexia Screening

Early detection for dyslexia is crucial in order for children to receive early as well as proper treatment. There are various studies that have focused on early detection of dyslexia, however the results remain limited. Therefore, an easy and user-friendly dyslexia screening tool called i-Dyslex was developed. In order to make sure the tool is free from design and interface problems, heuristic evaluation has been carried out. This paper discusses the heuristic evaluation of i-Dyslex tool for dyslexia screening among expert evaluators. This study adopted ten Usability Heuristics to be included in the questionnaire. Overall result derived from the evaluation is above average mean score, which are neutral (3.00) in one domain. Several comments and feedback from the experts. Both the experts’ evaluation and the feedback were essentials for further improvement of the i-Dyslex tool to ensure meets the user requirement and expectation

Energy efficient CF-OFDM scheme with single IFFT modulator for broadband wireless devices

In many low-cost mobile device applications, the drawback of high crest factor (CF) may outweigh all the potential benefits of broadband communication systems. Orthogonal frequency division multiplexing (OFDM) is considered to be one of the important multicarrier standards in broadband communication systems. However, high CF is the major problem of OFDM, which may have a deleterious effect on battery lifetime on broadband wireless devices. Therefore, applying a low-complexity high-efficiency technique in recent communications standard will significantly reduce the complexity of those systems and bring down the cost of the system. In this paper, a novel scrambling CF reduction scheme to reduce the CF in OFDM systems is proposed. In this scheme, two re-ordering methods are proposed. Then, a new optimization scheme is introduced in which only a single two-phase sequence need to be applied. Unlike the conventional-partial transmit sequence (C-PTS) scheme which needs Q-IFFT modulators, the proposed scheme requires only a single IFFT modulator. This feature significantly reduces processing time and less computation that leads to reduced complexity. Simulation results demonstrate that the proposed scheme can effectively reduce the complexity compared with the conventional and latest CF reduction scheme and yields good CF performance

Using a virtual environment to assess cognition in the elderly

YesEarly diagnosis of Alzheimer’s disease (AD) is essential if treatments are to be administered at an earlier point in time before neurons degenerate to a stage beyond repair. In order for early detection to occur tools used to detect the disorder must be sensitive to the earliest of cognitive impairments. Virtual reality (VR) technology offers opportunities to provide products which attempt to mimic daily life situations, as much as is possible, within the computational environment. This may be useful for the detection of cognitive difficulties. We develop a virtual simulation designed to assess visuospatial memory in order to investigate cognitive function in a group of healthy elderly participants and those with a mild cognitive impairment. Participants were required to guide themselves along a virtual path to reach a virtual destination which they were required to remember. The preliminary results indicate that this virtual simulation has the potential to be used for detection of early AD since significant correlations of scores on the virtual environment with existing neuropsychological tests were found. Furthermore, the test discriminated between healthy elderly participants and those with a mild cognitive impairment (MCI)

Developing Speaking Skills Using Virtual Speaking Buddy

This interdisciplinary study integrates ICT in education through the innovation of an interactive audio-based application as a tool to enhance English language speaking skills among less proficient students. Drawing on the sociocultural perspective of learning, the application named ‘V-Buddy’ has been developed and tested with a group of participants which consists of five primary school students and an English language teacher. The teacher was briefed of her role as a facilitator before the students were exposed to V-Buddy for eight weeks. Adopting one group pre-test and post-test experimental design as its methodology, the teacher was asked to evaluate the students' level of confidence to speak prior to and after their engagement with the V-Buddy. The teacher was also interviewed to obtain her feedback on V-Buddy whilst the students were asked to complete the Personal Report of Confidence (PRC). The analysis reveals that all the students developed higher confidence level after their engagement with V-Buddy and the teacher perceived it positively which suggests its potential to be used as a tool in developing speaking skills among less proficient students

VirSbud: Key Characteristics, Applications, and its Future

Learning a second language is not an easy task. Learners need to have enough support in terms of learning materials in order to be successful in mastering the language. One of the common problems faced by the second language learners is the difficulty to find the learning materials to develop their speaking skills. This is in contrast to the materials for the development of other language skills, such as reading and writing which are easily accessible from bookstores and resource centers. This paper introduces an innovative application named Virtual Speaking Buddy (VirSbud) which is specially designed to help second language learners develop their speaking skills. It is hoped that this application will be a useful resource to improve the standard of speaking skills among English language learners

Developing Speaking Skills Using Virtual Speaking Buddy

This interdisciplinary study integrates ICT in education through the innovation of an interactive audio-based application as a tool to enhance English language speaking skills among less proficient students. Drawing on the sociocultural perspective of learning, the application named ‘V-Buddy’ has been developed and tested with a group of participants which consists of five primary school students and an English language teacher. The teacher was briefed of her role as a facilitator before the students were exposed to V-Buddy for eight weeks. Adopting one group pre-test and post-test experimental design as its methodology, the teacher was asked to evaluate the students' level of confidence to speak prior to and after their engagement with the V-Buddy. The teacher was also interviewed to obtain her feedback on V-Buddy whilst the students were asked to complete the Personal Report of Confidence (PRC). The analysis reveals that all the students developed higher confidence level after their engagement with V-Buddy and the teacher perceived it positively which suggests its potential to be used as a tool in developing speaking skills among less proficient students

VirSbud: Key Characteristics, Applications, and its Future

Learning a second language is not an easy task. Learners need to have enough support in terms of learning materials in order to be successful in mastering the language. One of the common problems faced by the second language learners is the difficulty to find the learning materials to develop their speaking skills. This is in contrast to the materials for the development of other language skills, such as reading and writing which are easily accessible from bookstores and resource centers. This paper introduces an innovative application named Virtual Speaking Buddy (VirSbud) which is specially designed to help second language learners develop their speaking skills. It is hoped that this application will be a useful resource to improve the standard of speaking skills among English language learners