A dynamic interface adaptation approach for accessible immersive environments

Current trends in context-Aware computing have altered the static nature of interfaces and equipped them with the ability to adapt to the physical or social context. This paper investigates new paradigms towards cognitive context-Awareness which relies on adaptation and personalization factors of more explicit interfaces oriented by individuals' cognitive processes. The main objective is to propose a smooth transition from existing interface design practices to advanced adaptation techniques concerning interfaces' design, based on cognitive abilities' inclination. To prove this, a group of young users, elderly and MCI positives, were asked to perform series of common tasks in a Metaverse interface design. A prediction model was developed to categorize users based on the way they interact with the interface. The outcomes of the interaction pattern analysis serve as the criterion based on which the proposed novel interaction-Aware interface can adapt users' abilities to maximize accessibility and comfort

Study of EEG power fluctuations enhanced by linguistic stimulus for cognitive decline screening

Relative Electroencephalography (EEG) power can reflect cognitive decline and play a critical diagnostic role for dementia onset. The current paper investigates power changes in EEG channels on elderly people having Mild Cognitive Impairment (MCI) during a linguistic test. The main objective was to identify patterns in EEG power changes during a linguistically enriched cognitive assessment test which involved working memory abilities, selective attention and perception. Groups of MCI, demented and healthy controls were recruited to take part in an experiment. It was found that MCI and demented patients showed significantly different patterns in delta and theta frequency bands during the linguistic tasks. Results are valuable in the study of the way brain processes linguistic information in people with cognitive impairment and in screening assessment procedures. © Springer International Publishing Switzerland 2016

Design of novel screening environments for Mild Cognitive Impairment: Giving priority to elicited speech and language abilities

Recent cognitive decline screening batteries have highlighted the importance of language deficits related to semantic knowledge breakdown to reveal the incipient dementia. This paper proposes the introduction of novel enriched linguistic tests and examines the hypothesis that language can be a sensitive cognitive measure for Mild Cognitive Impairment (MCI). A group of MCI and healthy elderly were administered a set of proposed linguistic tests. Performance measures were made on both groups to indicate that concrete verbal production deficits such as impaired verb fluency can distinguish the MCI from normal aging. In addition, it was found that even in cases where the MCI subjects preserved scores, language tests took significantly more time compared to healthy controls. These findings indicate that language could be a sensitive cognitive marker in preclinical stages of MCI. © 2015 ICST

Media enhanced educational and training interventions for people at risk of Alzheimer's disease

Changes in cognition observed in Mild Cognitive Impairment (MCI) syndrome can be noticed by individuals and their families and in most cases this is the reason for asking for medical advice. Later on, computerized cognitive skills training and screening services are offered to sense those conditions and to numerically express the changes in cognition over time. This paper describes a web-platform designed to offer skills-training interventions to people at risk of developing Alzheimer's disease (AD). The content development was based mainly on verbal fluency and other combinatorial mental abilities judgment. One hundred fifteen (115) people, aged 55 to 78 years old (M=65.57, SD=5.89) were recruited in a proof-of-concept study (92 MCI/ 22 healthy controls). The results indicated that the systematic use of language in computerized interventions could provide an additional diagnostic and skills-training value for the management of the MCI patients. © 2018 P.Ziti and Co. All rights reserved

Novel Virtual User Models of Mild Cognitive Impairment for Simulating Dementia

Virtual user modeling research has attempted to address critical issues of human-computer interaction (HCI) such as usability and utility through a large number of analytic, usability-oriented approaches as cognitive models in order to provide users with experiences fitting to their specific needs. However, there is demand for more specific modules embodied in cognitive architecture that will detect abnormal cognitive decline across new synthetic task environments. Also, accessibility evaluation of graphical user interfaces (GUIs) requires considerable effort for enhancing ICT products accessibility for older adults. The main aim of this study is to develop and test virtual user models (VUM) simulating mild cognitive impairment (MCI) through novel specific modules, embodied at cognitive models and defined by estimations of cognitive parameters. Well-established MCI detection tests assessed users' cognition, elaborated their ability to perform multitasks, and monitored the performance of infotainment related tasks to provide more accurate simulation results on existing conceptual frameworks and enhanced predictive validity in interfaces' design supported by increased tasks' complexity to capture a more detailed profile of users' capabilities and limitations. The final outcome is a more robust cognitive prediction model, accurately fitted to human data to be used for more reliable interfaces' evaluation through simulation on the basis of virtual models of MCI users

Synthetic ground truth data generation for automatic trajectory-based ADL detection

In-house automatic activity detection is highly important toward the automatic evaluation of the resident's cognitive state. However, current activity detection systems suffer from the demand for on-site acquisition of large amounts of ground truth data for training purposes, which poses a major obstacle to their real-world applicability. In this paper, focusing on resident location trajectory-based activity recognition through limited amount of low-cost cameras, we introduce a novel scheme for automatic ground truth data generation, via simulation of resident trajectories based on formal descriptions of activities. Additionally, we present an activity detection scheme capable of learning activity patterns from such synthetic ground truth data. Experimental results show that our methodology achieves activity detection performance that is comparable to state-of-art methods, while suppressing the need for any actual ground truth recordings, thus boosting the real-world applicability of practical activity detection systems. © 2014 IEEE

A tool to monitor and support physical exercise interventions for MCI and AD patients

This paper presents a tool to monitor and support the execution of common physical exercise interventions targeting people with Mild Cognitive Impairment (MCI), Alzheimer's Disease (AD) and elderly in general. Our tool aims (a) to stimulate and guide patients within physical exercise programs, (b) to monitor patient capacity to perform exercises suggested by clinicians and provide objective feedback and (c) to enable early diagnosis of significant changes in the physical capacity of users over time. Our tool incorporates a virtual 3D trainer, demonstrating prescribed exercises; currently, arms lifting, arms stretching, torso bending and torso twisting are supported. Utilizing a low-cost depth camera and markerless skeletal joint estimation, our tool monitors movement during exercise execution, evaluating patient performance with a set of metrics introduced herein. Through preliminary experimental analysis, our metrics were found of significant potential to discriminate among good and bad executions of the currently supported exercises. Copyright © 2014 ICST

A computerized test for the assessment of mild cognitive impairment subtypes in sentence processing

This study examines thesentence processing ability of mild cognitive impairment (MCI) subtypes. In addition to standard MCI neuropsychological tests, an experimental approach was applied to assess language. 133 people (93 MCI/40 controls) participated in novel computerized sentence processing tasks. Results presented statistically significant differences between MCI/controls andMCI subtypes (ANOVA):(a) duration F(2,92) = 19.259,p <.001) in sentence construction; (b) correct answers (F(2, 89) = 8.560,p <.001) and duration (F2,89) = 15.525,p <.001)in text comprehension; (c) correct answers (F(2, 92) = 8.975,p <.001) andduration (F(2, 92) = 4.360,p =.016) in metaphoric sentences comprehension; (d) correct answers (F(2, 92) = 12.836,p <.001) andduration (F(2, 92) = 10.974,p <.001) in verb form generation. Subtle changes in MCIsubtypes could affect sentence processing and provide useful information for cognitive decline risk estimation and screening purposes. © 2017 Informa UK Limited, trading as Taylor & Francis Group

A Preliminary Study on the Feasibility of Using a Virtual Reality Cognitive Training Application for Remote Detection of Mild Cognitive Impairment

Background: It has been demonstrated that virtual reality (VR) applications can be used for the detection of mild cognitive impairment (MCI). Objective: The aim of this study is to provide a preliminary investigation on whether a VR cognitive training application can be used to detect MCI in persons using the application at home without the help of an examiner. Methods: Two groups, one of healthy older adults (n=6) and one of MCI patients (n=6) were recruited from Thessaloniki day centers for cognitive disorders and provided with a tablet PC with custom software enabling the self-administration of the Virtual Super Market (VSM) cognitive training exercise. The average performance (from 20 administrations of the exercise) of the two groups was compared and was also correlated with performance in established neuropsychological tests. Results: Average performance in terms of duration to complete the given exercise differed significantly between healthy(μ =247.41s/ sd=89.006) and MCI (μ=454.52s/ sd=177.604) groups, yielding a correct classification rate of 91.8 with a sensitivity and specificity of 94 and 89 respectively for MCI detection. Average performance also correlated significantly with performance in Functional Cognitive Assessment Scale (FUCAS), Test of Everyday Attention (TEA), and Rey Osterrieth Complex Figure test (ROCFT). Discussion: The VR application exhibited very high accuracy in detecting MCI while all participants were able to operate the tablet and application on their own. Diagnostic accuracy was improved compared to a previous study using data from only one administration of the exercise. The results of the present study suggest that remote MCI detection through VR applications can be feasible. © 2017 - IOS Press and the authors. All rights reserved

Can a Virtual Reality Cognitive Training Application Fulfill a Dual Role? Using the Virtual Supermarket Cognitive Training Application as a Screening Tool for Mild Cognitive Impairment

Background: Recent research advocates the potential of virtual reality (VR) applications in assessing cognitive functions highlighting the possibility of using a VR application for mild cognitive impairment (MCI) screening. Objective: The aim of this study is to investigate whether a VR cognitive training application, the virtual supermarket (VSM), can be used as a screening tool for MCI. Methods: Two groups, one of healthy older adults (n=21) and one of MCI patients (n=34), were recruited from day centers for cognitive disorders and administered the VSM and a neuropsychological test battery. The performance of the two groups in the VSM was compared and correlated with performance in established neuropsychological tests. At the same time, the effectiveness of a combination of traditional neuropsychological tests and the VSM was examined. Results: VSM displayed a correct classification rate (CCR) of 87.30% when differentiating between MCI patients and healthy older adults, while it was unable to differentiate between MCI subtypes. At the same time, the VSM correlates with various established neuropsychological tests. A limited number of tests were able to improve the CCR of the VSM when combined with the VSM for screening purposes. Discussion: VSM appears to be a valid method of screening for MCI in an older adult population though it cannot be used for MCI subtype assessment. VSM's concurrent validity is supported by the large number of correlations between the VSM and established tests. It is considered a robust test on its own as the inclusion of other tests failed to improve its CCR significantly