A Systematic Review of Human and Robot Personality in Health Care Human-Robot Interaction

An Exploratory Study of the Potential of Online Counseling for University Students by a Human-Operated Avatar Counselor

Recently, the use of digital technologies, such as avatars and virtual reality, has been increasingly explored to address university students' mental health issues. However, there is limited research on the advantages and disadvantages of counselors using avatars in online video counseling. Herein, 25 university students were enrolled in a pilot online counseling session with a human counselor-controlled avatar, and asked about their emotional experiences and impressions of the avatar and to provide qualitative feedback on their communication experience. Positive emotions during the session were associated with impressions of the avatar's intelligence and likeability. The anthropomorphism, animacy, likeability, and intelligent impressions of the avatar were interrelated, indicating that the avatar's smile and the counselor's expertise in empathy and approval may have contributed to these impressions. However, no associations were observed between participant experiences and their prior communication with avatars, or between participant experiences and their gender or the perceived gender of the avatar. Accordingly, recommendations for future practice and research are provided. Accumulating practical and empirical findings on the effectiveness of human-operated avatar counselors is crucial for addressing university students' mental health issues.

Human-Robot Interaction Using Learning from Demonstrations and a Wearable Glove with Multiple Sensors

Human-robot interaction is of the utmost importance as it enables seamless collaboration and communication between humans and robots, leading to enhanced productivity and efficiency. It involves gathering data from humans, transmitting the data to a robot for execution, and providing feedback to the human. To perform complex tasks, such as robotic grasping and manipulation, which require both human intelligence and robotic capabilities, effective interaction modes are required. To address this issue, we use a wearable glove to collect relevant data from a human demonstrator for improved human-robot interaction. Accelerometer, pressure, and flexi sensors were embedded in the wearable glove to measure motion and force information for handling objects of different sizes, materials, and conditions. A machine learning algorithm is proposed to recognize grasp orientation and position, based on the multi-sensor fusion method.

Robots in travel clinics: building on tourism's use of technology and robots for infection control during a pandemic

The arrival of COVID-19 impacted every aspect of life around the world. The virus, whose spread was facilitated overwhelmingly by people's close contact at home and by travelling, devastated the tourism, hospitality, and transportation industry. Economic survival depended largely on demonstrating to authorities and potential travellers the strict adherence to infection control measures. Fortunately, long before the pandemic, the industry had already employed digital technology, artificial intelligence, and service robots, not to keep the world safe, but to either bridge staff shortages or save costs, reduce waiting times, streamline administration, complete unattractive, tedious, or physical tasks, or use technology as marketing gimmicks. With COVID-19, offering social distancing and touchless service was an easy step by extending quickly what was already there. The question arose: could travellers' acceptance of technology and robots for infection control be useful in travel medicine? COVID-19 fostered the rapid and increased acceptance of touchless technology relating to all things travel. The public's expectations regarding hygiene, health and safety, and risk of infection have changed and may stay with us long after the pandemic is 'the new normal', or a new one approaches. This insight, combined with the current experience with robots in health and medicine, is useful in exploring how robots could assist travel medicine practice. However, several aspects need to be considered in terms of type of robot, tasks required, and the public's positive or negative attitudes towards robots to avoid known pitfalls. To meet the crucial infection control measures of social distancing and touch avoidance, the use of robots in travel medicine may not only be readily accepted but expected, and implications for management, practice, and research need to be considered.

Ethics 4.0: Ethical Dilemmas in Healthcare Mediated by Social Robots

This study examined people's moral judgments and trait perception toward a healthcare agent's response to a patient who refuses to take medication. A sample of 524 participants was randomly assigned to one of eight vignettes in which the type of healthcare agent (human vs. robot), the use of a health message framing (emphasizing health-losses for not taking vs. health-gains in taking the medication), and the ethical decision (respect the autonomy vs. beneficence/nonmaleficence) were manipulated to investigate their effects on moral judgments (acceptance and responsibility) and traits perception (warmth, competence, trustworthiness). The results indicated that moral acceptance was higher when the agents respected the patient's autonomy than when the agents prioritized beneficence/nonmaleficence. Moral responsibility and perceived warmth were higher for the human agent than for the robot, and the agent who respected the patient's autonomy was perceived as warmer, but less competent and trustworthy than the agent who decided for the patient's beneficence/nonmaleficence. Agents who prioritized beneficence/nonmaleficence and framed the health gains were also perceived as more trustworthy. Our findings contribute to the understanding of moral judgments in the healthcare domain mediated by both healthcare humans and artificial agents.

AppraisalCloudPCT: A Computational Model of Emotions for Socially Interactive Robots for Autistic Rehabilitation

Computational models of emotions can not only improve the effectiveness and efficiency of human-robot interaction but also coordinate a robot to adapt to its environment better. When designing computational models of emotions for socially interactive robots, especially for robots for people with special needs such as autistic children, one should take into account the social and communicative characteristics of such groups of people. This article presents a novel computational model of emotions called AppraisalCloudPCT that is suitable for socially interactive robots that can be adopted in autistic rehabilitation which, to the best of our knowledge, is the first computational model of emotions built for robots that can satisfy the needs of a special group of people such as autistic children. To begin with, some fundamental and notable computational models of emotions (e.g., OCC, Scherer's appraisal theory, PAD) that have deep and profound influence on building some significant models (e.g., PRESENCE, iGrace, xEmotion) for socially interactive robots are revisited. Then, a comparative assessment between our AppraisalCloudPCT and other five significant models for socially interactive robots is conducted. Great efforts have been made in building our proposed model to meet all of the six criteria for comparison, by adopting the appraisal theories on emotions, perceptual control theory on emotions, a component model view of appraisal models, and cloud robotics. Details of how to implement our model in a socially interactive robot we developed for autistic rehabilitation are also elaborated in this article. Future studies should examine how our model performs in different robots and also in more interactive scenarios.

Design and Development of a Scale for Evaluating the Acceptance of Social Robotics for Older People: The Robot Era Inventory

Introduction

Nowadays, several robots have been developed to provide not only companionship to older adults, but also to cooperate with them during health and lifestyle activities. Despite the undeniable wealth of socially assistive robots (SARs), there is an increasing need to customize the tools used for measuring their acceptance in real-life applications.

Methods

Within the Robot-Era project, a scale was developed to understand the degree of acceptance of the robotic platform. A preliminary test with 21 participants was performed to assess the statistical validity of the Robot-Era Inventory (REI) scales.

Results

Based on the criteria observed in the literature, 41 items were developed and grouped in different scales (perceived robot personality, human–robot interaction, perceived benefit, ease of use, and perceived usefulness). The reliability of the Robot-Era Inventory scale was analyzed with Cronbach's alpha, with a mean value of 0.79 (range = 0.61–0.91). Furthermore, the preliminary validity of this scale has been tested by using the correlation analysis with a gold standard, the Unified Theory of Acceptance and Use of Technology (UTAUT) model.

Discussion

The Robot-Era Inventory represents a useful tool that can be easily personalized and included in the assessment of any SARs that cooperate with older people in real environment applications.