Designing Robots with the Context in Mind- One Design Does Not Fit All

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.

Deep Learning-Based Multi-modal COVID-19 Screening by Socially Assistive Robots Using Cough and Breathing Symptoms

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.

Developing a VR Socially Assistive Robot Simulator Employing Game Development Tools

Long-term care facilities (LTCFs) face challenges due to the personalized care required by people with developmental disabilities. The COVID-19 pandemic exacerbated the issues associated with limited staff who are overworked. Such a scenario also disrupted the research and development of socially assistive robots (SARs) as access to care facilities and the elderly was restricted. The restriction sparked creative thinking and innovation aimed at addressing the challenges introduced by the pandemic. Such is the case for developing Aether™, a SAR designed to monitor falls and engage in playful activities with users. This paper presents the use of game technologies to develop a Virtual reality digital twin simulator for overcoming the lack of access to LTCFs and the elderly by creating synthetic data that simulates the robot's behavior, interactions with the environment, and virtual avatars, before its deployment. Our approach additionally allows overcoming the limitation with traditional datasets for training machine learning where depicted people and actions are not representative of the elderly population. Our preliminary results indicate that combining DTs and VR expedites robot development. We tested and compared the robot navigation, person detection, and inspection behavior while observing COVID-19 restrictions. © 2022 IEEE.

Socially Assistive Robots Assisting Older Adults in an Internet and Smart Healthcare Era: A Literature Review

This study aims to investigate the effects of socially assistive robots (SARs) on emotional health and social interaction in older adults through a literature review and metaanalysis. From inception to August 2022, we used keywords (involving combinations of AND and OR Boolean operators) to search the Cochrane Library, MEDLINE, CINAHL, EMBASE, IEEE Digital Library, PsycINFO, PubMed, Web of Science, Scopus, and Chinese Electronic Periodical Service for randomized and controlled trials. RevMan 5.4.1 software was used for the meta-analysis, and the Cochrane Collaboration's bias assessment was used to evaluate the quality of the articles. The meta-analysis comprised a complete of four studies. SARs provides older adults with the happiness of positive emotional health and improve their social interaction through conversation and companionship. Socially assistive robots can enhance positive emotions in older adults. They also alleviate the healthcare workers' strain during the COVID-19 pandemic. For more precise conclusions, more careful designs, and standardized programs to accumulate different results are required. © 2022 IEEE.

The role of a socially assistive robot in enabling older adults with mild cognitive impairment to cope with the measures of the COVID-19 lockdown: A qualitative study.

BACKGROUND: During the COVID-19 pandemic, mandatory containment measures led to lockdowns and severely diminished social interaction, with older adults being one vulnerable group. Socially assistive robots (SARs) could prove to be an effective intervention. OBJECTIVES: To explore the experiences of older adults with mild cognitive impairment (MCI) with a SAR during the first lockdown in Belgium. METHODS: Inductive thematic analysis was used. After a two-week interaction period with robot James®, semi-structured interviews were conducted. RESULTS: Four people were interviewed (median: 86 years; range: 70-90 years; 2 men, 2 women). Four themes were identified. The first theme described the robot as a companion, alleviating feelings of loneliness and social isolation. The second theme explored the robot in light of meaningful activity. The third theme detailed the technical aspects of the robot and the fourth theme described notable barriers and areas of improvement. CONCLUSION: The study demonstrated the potential of SARs during the first lockdown period in Belgium. The robot proved to be promising in terms of alleviating feelings of loneliness and social isolation. It was found to be both motivating and facilitating in terms of meaningful activity. SIGNIFICANCE: The study provided valuable insights for the care of lonely and occupationally deprived older adults.

My Precious Friend: Human-Robot Interactions in Home Care for Socially Isolated Older Adults.

OBJECTIVES: Using a friendship framework, we explored interactions between a multi-functional companion robot and older adults residing in a low-resource community in South Korea. METHODS: We conducted in-depth interviews with 12 older adults who kept a doll-shaped companion robot called Hyodol for 18 months on average. We applied the Framework Analysis Method to explore three types of friendship (i.e., friendships of utility, pleasure, and the good) that participants cultivated with the robot. RESULTS: The most common aspect of utility companionship reported by all participants was Hyodol's role as their health coach who reminded them to take medication and to exercise. Participants also found pleasure in playing with Hyodol and reported reduced feelings of loneliness. In the absence of other social supports, all participants also regarded Hyodol as a surrogate family member or human-friend, and interacted with Hyodol as such. CONCLUSIONS: Findings illustrated high acceptability of Hyodol among these socially isolated older adults especially during the global COVID-19 pandemic, suggesting that a humanoid like Hyodol could be complementary to homecare services for solo-living older adults. CLINICAL IMPLICATIONS: Well-designed robot interventions, as complements to existing aging service and clinical interventions, have a potential to improve health behaviors among socially isolated older adults.

Therapists' Opinions on Telehealth, Robotics, and Socially Assistive Robot-Augmented Telepresence Systems for Rehabilitation

Shortages in therapists, along with the COVID-19 pandemic, have created a gap in care for people with cerebral palsy, stroke, and many other conditions requiring rehabilitation. Socially assistive robots and telehealth are two tools which could help fill this gap and may be able to work together, in socially assistive robot-Augmented telerehabilitation, to create meaningful telerehab encounters. We present results from a survey completed between Jun 31, 2020, and Dec 31, 2020, asking 379 therapists in the United States for their opinions on features which may be useful for a telerehabilitation platform and for their general feelings towards robots. We explore their answers and reduce the response space by identifying six factors underlying the answers. We show that therapists want high quality video, control over robots, and more regulations. We also find that they are positive about the features which could be used in socially assistive robot-Augmented telerehabilitation. © 2022 IEEE.

The role of culturally competent robots in major health disasters

Prompted by the 2020 COVID-19 pandemic, this chapter draws evidence from research studies regarding the huge changes in the practices and methods for providing nursing, medical, and spiritual care in massively prohibitive working environments. Examples of AI and robotic devices used during the pandemic will be covered in the spirit of constructive reflection and contemplation. The reported unpreparedness for an effective, efficient, and humane response to such major health disasters and hazards will be discussed, and suggestions for the future will be given. The training needs reported by health and social care workers will be analyzed in the light of the technological challenges they are required to cope with. © 2022 Elsevier Inc. All rights reserved.

A Meta-Analysis on Remote HRI and In-Person HRI: What Is a Socially Assistive Robot to Do?

Recently, due to the COVID-19 pandemic and the related social distancing measures, in-person activities have been significantly reduced to limit the spread of the virus, especially in healthcare settings. This has led to loneliness and social isolation for our most vulnerable populations. Socially assistive robots can play a crucial role in minimizing these negative affects. Namely, socially assistive robots can provide assistance with activities of daily living, and through cognitive and physical stimulation. The ongoing pandemic has also accelerated the exploration of remote presence ranging from workplaces to home and healthcare environments. Human-robot interaction (HRI) researchers have also explored the use of remote HRI to provide cognitive assistance in healthcare settings. Existing in-person and remote comparison studies have investigated the feasibility of these types of HRI on individual scenarios and tasks. However, no consensus on the specific differences between in-person HRI and remote HRI has been determined. Furthermore, to date, the exact outcomes for in-person HRI versus remote HRI both with a physical socially assistive robot have not been extensively compared and their influence on physical embodiment in remote conditions has not been addressed. In this paper, we investigate and compare in-person HRI versus remote HRI for robots that assist people with activities of daily living and cognitive interventions. We present the first comprehensive investigation and meta-analysis of these two types of robotic presence to determine how they influence HRI outcomes and impact user tasks. In particular, we address research questions regarding experience, perceptions and attitudes, and the efficacy of both humanoid and non-humanoid socially assistive robots with different populations and interaction modes. The use of remote HRI to provide assistance with daily activities and interventions is a promising emerging field for healthcare applications.

Developing a VR Simulator for Robotics Navigation and Human Robot Interactions employing Digital Twins

Providing care to seniors and adults with Developmental Disabilities (DD) has seen increased use and development of assistive technologies including service robots. Such robots ease the challenges associated with care, companionship, medication intake, and fall prevention, among others. Research and development in this field rely on in-person data collection to ensure proper robot navigation, interactions, and service. However, the current COVID-19 pandemic has caused the implementation of physical distancing and access restrictions to long-term care facilities, thus making data collection very difficult. This traditional method poses numerous challenges as videos may not be representative of the population in terms of how people move, interact with the environment, or fall. In this paper, we present the development of a VR simulator for robotics navigation and fall detection with digital twins as a solution to test the virtual robot without having access to the real physical location, or real people. The development process required the development of virtual sensors that are able to create LIDAR data for the virtual robot to navigate and detect obstacles. Preliminary testing has allowed us to obtain promising results for the virtual simulator to train a service robot to navigate and detect falls. Our results include virtual maps, robot navigation, and fall detection.

Adapting 'sunshine,' a socially assistive chat robot for older adults with cognitive impairment: A pilot study

This reprinted chapter originally appeared in Journal of Gerontological Social Work, 2020, 63[6-7], 520-528. (The following of the original article appeared in record 2020-51139-001.) The COVID-19 pandemic challenges us to think outside of the box to respond to this unprecedented global crisis. In this letter, we propose a pilot study to use a socially assistive robot to help meet social needs for older adults with cognitive impairment residing in long-term care facilities. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Development of remote support system for robotassisted recreation for older adults

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.