Evaluation of a Companion Robot for Individuals With Dementia: Quantitative Findings of the MARIO Project in an Irish Residential Care Setting.

The current study focuses on the short-term effect of MARIO, a social robot, on quality of life, depression, and perceived social support in persons with dementia (PWD) and evaluates their acceptability of MARIO. Ten PWD in one nursing home took part in a 4-week pilot study, where each participant had up to 12 sessions with MARIO. Sessions comprised engagement in music, news, reminiscence, games, and calendar applications. Standardized questionnaires were administered before and after the 4-week period. Participants had a sustained interest in MARIO during their interactions and an acceptance of MARIO's appearance, sound, and applications. Consequently, participants spent more time socially engaged. No statistically significant differences were found in quality of life, depression, and perceived social support. PWD can engage with a social robot in a real-world nursing home. Future research should incorporate a larger sample and longer intervention period. [Journal of Gerontological Nursing, 45(7), 36-45.].

MARIO Project: Validation and Evidence of Service Robots for Older People with Dementia.

BACKGROUND: In the EU funded MARIO project, specific technological tools are adopted for the people living with dementia (PLWD). In the final stage of the project, a validation of the MARIO companion robot was performed from August to October 2017. OBJECTIVE: The aims of the present study are: 1) to illustrate the key results and evidence obtained in the final evaluation phase of the project across the three different pilot sites; 2) to assess the engagement dimensions of the PLWD who interacted with the MARIO robot; and 3) to assess the acceptability and efficacy of the MARIO companion robot on clinical, cognitive, neuropsychiatric, affective and social aspects, resilience, quality of life in PLWD, and burden level of the caregivers. METHODS: 38 people (M = 14; F = 24) with Alzheimer's disease were screened for eligibility and all were included. The following tests were administered Pre and Post interactions with MARIO: Observational Measurement of Engagement (OME), Mini-Mental State Examination (MMSE), Clock Drawing Test (CDT), Frontal Assessment Battery (FAB), Neuropsychiatric Inventory (NPI), Cornell Scale for Depression in Dementia (CSDD), Multidimensional Scale of Perceived Social Support (MSPSS), 14-item Resilience Scale (RS-14), Quality of Life in Alzheimer's Disease (QOL-AD), Caregiver Burden Inventory (CBI), Tinetti Balance Assessment (TBA), and Comprehensive Geriatric Assessment (CGA) was carried out. RESULTS: In Post-MARIO interactions, significant improvements were observed in RS-14 (p = 0.020).Considering the age of the people, PLWD with 68-76 years perceived that they had major social support (MSPSS Total: p = 0.016) and friends to support them (MSPSS Fri: p = 0.014). Indeed, the younger people (55-67 years) were less depressed (CSDD: p = 0.033), and more resilient (RS-14: p = 0.003). The people aged 77-85 years perceived they had major family support (MSPSS Fam: p = 0.018). The participants were gender and education matched without any statistically significant difference. CONCLUSION: MARIO may be a useful tool in mitigating depression and loneliness, while enhancing social connectedness, resilience, and overall quality of life for people with dementia.

Interacting with Dementia: The MARIO Approach.

MARIO is a companion robot that aims to help people with dementia (PWD) to battle isolation and loneliness by enabling them to stay socially active by providing a number of applications focused on hobbies (music, movies, etc), staying engaged with communities (reading headlines, reading local twitter feeds etc.) and staying connected with family and friends (telephoning them, reading their news from twitter, etc.). This paper presents the results from the initial trials of MARIO interacting with PWD involving a limited set of applications. It confirms some of the challenges hypothesized at the outset of the study and provides guidelines for future development work.

Investigating the Effect of Social Robot Embodiment.

The experiment described in this paper is an early assessment to identify if the embodiment of a verbal and visual user interaction system in a robot is more effective in people with dementia than when using the same system in a simple laptop. This study provides input for the robot's design.

A cloud-based simulation architecture for pandemic influenza simulation.

High-fidelity simulations of pandemic outbreaks are resource consuming. Cluster-based solutions have been suggested for executing such complex computations. We present a cloud-based simulation architecture that utilizes computing resources both locally available and dynamically rented online. The approach uses the Condor framework for job distribution and management of the Amazon Elastic Computing Cloud (EC2) as well as local resources. The architecture has a web-based user interface that allows users to monitor and control simulation execution. In a benchmark test, the best cost-adjusted performance was recorded for the EC2 H-CPU Medium instance, while a field trial showed that the job configuration had significant influence on the execution time and that the network capacity of the master node could become a bottleneck. We conclude that it is possible to develop a scalable simulation environment that uses cloud-based solutions, while providing an easy-to-use graphical user interface.