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15th International Workshop on Human-Friendly Robotics, HFR 2022 ; 26:105-119, 2023.
Article in English | Scopus | ID: covidwho-2269019

ABSTRACT

Robots' visual qualities (VQs) impact people's perception of their characteristics and affect users' behaviors and attitudes toward the robot. Recent years point toward a growing need for Socially Assistive Robots (SARs) in various contexts and functions, interacting with various users. Since SAR types have functional differences, the user experience must vary by the context of use, functionality, user characteristics, and environmental conditions. Still, SAR manufacturers often design and deploy the same robotic embodiment for diverse contexts. We argue that the visual design of SARs requires a more scientific approach considering their multiple evolving roles in future society. In this work, we define four contextual layers: the domain in which the SAR exists, the physical environment, its intended users, and the robot's role. Via an online questionnaire, we collected potential users' expectations regarding the desired characteristics and visual qualities of four different SARs: a service robot for an assisted living/retirement residence facility, a medical assistant robot for a hospital environment, a COVID-19 officer robot, and a personal assistant robot for domestic use. Results indicated that users' expectations differ regarding the robot's desired characteristics and the anticipated visual qualities for each context and use case. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

2.
14th International Conference on Social Robotics, ICSR 2022 ; 13818 LNAI:217-227, 2022.
Article in English | Scopus | ID: covidwho-2257940

ABSTRACT

In this paper, we present the development of a novel autonomous social robot deep learning architecture capable of real-time COVID-19 screening during human-robot interactions. The architecture allows for autonomous preliminary multi-modal COVID-19 detection of cough and breathing symptoms using a VGG16 deep learning framework. We train and validate our VGG16 network using existing COVID datasets. We then perform real-time non-contact preliminary COVID-19 screening experiments with the Pepper robot. The results for our deep learning architecture demonstrate: 1) an average computation time of 4.57 s for detection, and 2) an accuracy of 84.4% with respect to self-reported COVID symptoms. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

3.
4th IEEE Global Conference on Life Sciences and Technologies, LifeTech 2022 ; : 246-247, 2022.
Article in English | Scopus | ID: covidwho-1840260

ABSTRACT

As the percentage of the older adults population increases worldwide, both the risk of social isolation of the older adults and the shortage of nursing care personnel have become major issues. To address these issues, we have developed a recreational program, the scenario-type robot-assisted recreation, to promote communication among the older adults in aged care facilities. While the burden of the facility staff increases due to the COVID-19 pandemic, we improved the robot operation interface, developed a system to support the operation of this activity by the facility staff from a remote location, and developed a system to realize communication with remote family members, in order to smoothly operate this recreational activity by the facility staff by themselves. © 2022 IEEE.

4.
Sensors (Basel) ; 21(24)2021 Dec 16.
Article in English | MEDLINE | ID: covidwho-1580511

ABSTRACT

This work introduces a new socially assistive robot termed MARIA T21 (meaning "Mobile Autonomous Robot for Interaction with Autistics", with the addition of the acronym T21, meaning "Trisomy 21", which is used to designate individuals with Down syndrome). This new robot is used in psychomotor therapies for children with Down syndrome (contributing to improve their proprioception, postural balance, and gait) as well as in psychosocial and cognitive therapies for children with autism spectrum disorder. The robot uses, as a novelty, an embedded mini-video projector able to project Serious Games on the floor or tables to make already-established therapies funnier to these children, thus creating a motivating and facilitating effect for both children and therapists. The Serious Games were developed in Python through the library Pygame, considering theoretical bases of behavioral psychology for these children, which are integrated into the robot through the robot operating system (ROS). Encouraging results from the child-robot interaction are shown, according to outcomes obtained from the application of the Goal Attainment Scale. Regarding the Serious Games, they were considered suitable based on both the "Guidelines for Game Design of Serious Games for Children" and the "Evaluation of the Psychological Bases" used during the games' development. Thus, this pilot study seeks to demonstrate that the use of a robot as a therapeutic tool together with the concept of Serious Games is an innovative and promising tool to help health professionals in conducting therapies with children with autistic spectrum disorder and Down syndrome. Due to health issues imposed by the COVID-19 pandemic, the sample of children was limited to eight children (one child with typical development, one with Trisomy 21, both female, and six children with ASD, one girl and five boys), from 4 to 9 years of age. For the non-typically developing children, the inclusion criterion was the existence of a conclusive diagnosis and fulfillment of at least 1 year of therapy. The protocol was carried out in an infant psychotherapy room with three video cameras, supervised by a group of researchers and a therapist. The experiments were separated into four steps: The first stage was composed of a robot introduction followed by an approximation between robot and child to establish eye contact and assess proxemics and interaction between child/robot. In the second stage, the robot projected Serious Games on the floor, and emitted verbal commands, seeking to evaluate the child's susceptibility to perform the proposed tasks. In the third stage, the games were performed for a certain time, with the robot sending messages of positive reinforcement to encourage the child to accomplish the game. Finally, in the fourth stage, the robot finished the games and said goodbye to the child, using messages aiming to build a closer relationship with the child.


Subject(s)
Autism Spectrum Disorder , COVID-19 , Down Syndrome , Robotics , Autism Spectrum Disorder/therapy , Down Syndrome/therapy , Female , Humans , Male , Pandemics , Pilot Projects , SARS-CoV-2
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