Syadiah Nor Wan Shamsuddin

VREAD: A Virtual Simulation to Investigate Cognitive Function in the Elderly

Recent studies have shown that people with mild cognitive impairment (MCI) may convert to Alzheimers disease (AD) over time although not all MCI cases progress to dementia. The diagnosis of MCI is important 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. VREAD is a quick, easy and friendly tool that was developed with an aim to investigate cognitive functioning in a group of healthy elderly and those with MCI. It focuses on the task of following a route, since Topographical Disorientation (TD) is common in AD. The results shows that this novel simulation was able to predict with about 90% overall accuracy using weighting function proposed to discriminate between MCI and healthy elderly.

Using a virtual environment to assess cognition in the elderly

Abstract Early 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 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 (MCI). 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 MCI.

Development and usability evaluation of virtual environment for early diagnosis of dementia

Virtual Technology (VT) plays a vital role in many areas. It is a promising tool in healthcare and offers opportunities and solutions for early detection of dementia. Dementia is associated with loss of brain function from the process of ageing. This serious illness needs early diagnosis if medical treatment and healthcare services are to be deployed in time. We developed a new prototype called Virtual Reality for Early Detection of Dementia (VReDD), and have applied psychology theories in an attempt to make an early diagnosis of dementia. In this paper, we will focus on the usability of user satisfaction for young participants to see the complexity and effectiveness of the prototype as a first step prior to the implementation the experiment with elderly, those with a mild cognitive impairment and Alzheimer patients. These preliminary findings show that the prototype is reliable and suitable to be used with elderly people.

Teachers’ Feedback on the Development of Virtual Speaking Buddy (VirSbud) Application

This study aims at identifying the ideal characteristics of a virtual speaking buddy (VirSbud), as perceived by the teachers, so that the current VirSbud application can be further developed to meet the users’ expectation. Employing a qualitative approach, an in-depth group interviews was conducted with five English language teachers teaching in Standard Three (nine-year-old pupils). Prior to the interview, the teachers used the application as a teaching aid for eight weeks. The interview reveals the ideal characteristics of an application for virtual speaking buddy. The teachers expected a more sophisticated application which enables online participation, two different interfaces accessible by learners and teachers, looping in the prompts given to the learners, and the use of voice recognition which enables automatic response to the learners. The findings point towards the need of semi-formal learning, instead of formal and informal learning, in developing learners’ speaking skills with the teachers being virtually present at a distance.

Towards Early Diagnosis of Dementia Using a Virtual Environment

Dementia is one of the biggest fears in the process of ageing and the most common cause is Alzheimer’s Disease(AD). Topographic disorientation is an early manifestation of AD and threatens activities of their daily lives. Finding solutions are essential in the early diagnosis of dementia if medical treatment and healthcare services to be deployed in time. Recent studies have shown that people with mild cognitive impairment (MCI) may convert to Alzheimer’s disease (AD) over time although not all MCI cases progress to dementia. The diagnosis of MCI is important 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. This work presents a virtual environment which can be utilized as a quick, easy and friendly tool for early diagnosis of dementia. This tool was developed with an aim to investigate cognitive functioning in a group of healthy elderly and those with MCI. It focuses on the task of following a route, since Topographical Disorientation (TD) is common in AD. The results shows that this novel simulation was able to predict with about 90% overall accuracy using weighting function proposed to discriminate between MCI and healthy elderly.