Sofia Segkouli

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. VSMs 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.

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  = 247.41 s/ sd = 89.006) and MCI (μ= 454.52 s/ 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.

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 residents 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.

Designing a gamified social platform for people living with dementia and their live-in family caregivers

In the current paper, a social gamified platform for people living with dementia and their live-in family caregivers, integrating a broader diagnostic approach and interactive interventions is presented. The CAREGIVERSPRO-MMD (C-MMD) platform constitutes a support tool for the patient and the informal caregiver - also referred to as the dyad - that strengthens self-care, and builds community capacity and engagement at the point of care. The platform is implemented to improve social collaboration, adherence to treatment guidelines through gamification, recognition of progress indicators and measures to guide management of patients with dementia, and strategies and tools to improve treatment interventions and medication adherence. Moreover, particular attention was provided on guidelines, considerations and user requirements for the design of a User-Centered Design (UCD) platform. The design of the platform has been based on a deep understanding of users, tasks and contexts in order to improve platform usability, and provide adaptive and intuitive User Interfaces with high accessibility. In this paper, the architecture and services of the C-MMD platform are presented, and specifically the gamification aspects.

Parkinson’s Disease Patients Classification Based on a Motion Tracking Methodology

This study demonstrates how a computer based methodology for tracking motor abilities of Parkinson’s disease can be utilized for patient classification and assessment of the Parkinson’s disease severity. The Line Test methodology evaluates the impaired voluntary movement and generates a set of features that describe the motion. A total cohort of 6 control subjects and 37 Parkinson’s disease subjects were recruited and assessed for the test. During the test, a vertical line appears on the screen and the device evaluates patient’s performance by producing features that correlate the motion to the last medication dosage, the line-test position, the line-test reaction time and the line-test total error. A common cohort of 24 Parkinson’s disease subjects (patients that carried out the Line Test more than once) was formed to track the features alterations between repetitions in time. Results evaluation was performed in both cohorts based on information visualization methodology, optimized for the multi-objective dataset. The line-test position and the time from the last medication dosage features were proved to present the major relation to patients’ group formation. Additionally, line-test reaction time and the line-test total error features proved significant between patients’ performance in the common cohort. Study limitations are correlated to the size of the cohort and the time frame of the study. In general, the current practice supports further investigation into using Line Test methodology for addressing Parkinson’s disease severity.

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

ABSTRACT 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.

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.

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.