Young Adults Searching for Health-Related Information on the Internet

This study aimed to examine the use of internet as a source of health-related information (HRI), as well as the change in attitudes following the online search for HRI. The current study sample included 88 participants, randomly divided into two experimental groups. One was given the name of an unfamiliar disease and told to search for information about it using various search engines, and the second was given a text about the disease from a credible scientific source. The study findings show a large percentage of participants used the internet as a source of HRI. Likewise, no differences were found in the extent to which the internet was used as a source of HRI when demographic were compared. Those who searched for the HRI on the internet had more negative opinions and believed symptoms of the disease were worse than the average opinion among those who obtained the information about the disease from a credible scientific source. Internet clearly influences the participants' beliefs, regardless of demographic differences.

User experience of human-robot long-term interactions

Since interactions with social robots are novel and exciting for many people, one particular concern in this specific area of human-robot interaction (HRI) is the extent to which human users will experience the interactions positively over time, when the robot's novelty is particularly salient. In the current paper, we investigated users' experience in long-term HRIs;how users perceive the ongoing interactions and the robot's ability to sustain it over time. Therefore, here we examine the effect of the repeated measures (10 testing sessions) and the discussion theme (Covid-19 related vs general) on the way participants experienced the interaction quality with a social robot and perceived the robot's communication competency over time. We found that despite individual differences between the participants, over time participants found the interactions with Pepper to be of higher quality and that Pepper's communication skills got better. Nevertheless, our results also stressed that the discussion theme has no meaningful nor significant effect on the way people perceive Pepper and the interaction. © 2022 ACM.

Remote HRI: a Methodology for Maintaining COVID-19 Physical Distancing and Human Interaction Requirements in HRI Studies.

Observing how humans and robots interact is an integral part of understanding how they can effectively coexist. This ability to undertake these observations was taken for granted before the COVID-19 pandemic restricted the possibilities of performing HRI study-based interactions. We explore the problem of how HRI research can occur in a setting where physical separation is the most reliable way of preventing disease transmission. We present the results of an exploratory experiment that suggests Remote-HRI (R-HRI) studies may be a viable alternative to traditional face-to-face HRI studies. An R-HRI study minimizes or eliminates in-person interaction between the experimenter and the participant and implements a new protocol for interacting with the robot to minimize physical contact. Our results showed that participants interacting with the robot remotely experienced a higher cognitive workload, which may be due to minor cultural and technical factors. Importantly, however, we also found that whether participants interacted with the robot in-person (but socially distanced) or remotely over a network, their experience, perception of, and attitude towards the robot were unaffected.

Care Workers Making Use of Robots: Results of a Three-Month Study on Human-Robot Interaction within a Care Home

Research on social robots in care has often focused on either the care recipients or the technology itself, neglecting the care workers who, in and through their collaborative and coordinative practices, will need to work with the robots. To better understand these interactions with a social robot (Pepper), we undertook a 3 month long-term study within a care home to gain empirical insights into the way the robot was used. We observed how care workers learned to use the device, applied it to their daily work life, and encountered obstacles. Our findings show that the care workers used the robot regularly (1:07 hours/day) mostly in one-to-one interactions with residents. While the robot had a limited effect on reducing the workload of care workers, it had other positive effects, demonstrating the potential to enhance the quality of care. © 2022 Owner/Author.

Human-Robot Interaction in Bengali language for Healthcare Automation integrated with Speaker Recognition and Artificial Conversational Entity

The research study presents an architecture of HumanRobot Interaction (HRI) based Artificial Conversational Entity integrated with speaker recognition ability to avail modern healthcare services. Due to the Covid-19 pandemic, the situation has become troublesome for health workers and patients to visit hospitals because of the high risk of virus dissemination. To minimize the mass congestion, our developed architecture would be an appropriate, cost-effective solution that automates the reception system by enabling AI-based HRI and providing fast and advanced healthcare services in the context of Bangladesh. The architecture consists of two significant subsections: Speaker Recognition and Artificial Conversational Entities having Automatic Speech Recognition in Bengali, Interactive Agent, and Text-to-Speech-synthesis. We used MFCC features as the linguistic parameters and the GMM statistical model to adapt each speaker's voice and estimation and maximization algorithm to identify the speaker's identity. The developed speaker recognition module performed significantly with 94.38% average accuracy in noisy environments and 96.27% average accuracy in studio quality environments and achieved a word error rate (WER) of 42.15% from RNN based Deep Speech 2 model for Bangla Automatic Speech Recognition (ASR). Besides, Artificial Conversational Entity performs with an average accuracy of 98.58% in a small-scale real-time environment. © 2021 IEEE.

Zenbo on Zoom: Evaluating the Human-Robot Interaction User Experience in a Video Conferencing Session

The COVID-19 pandemic has restricted the ability of HRI researchers to undertake face-to-face HRI user studies while obeying existing social and physical distancing mandates. In this pilot study we evaluated the quality of the user experience reported by undergraduate CS/IT students after they had two online interactions with a social robot using the Zoom video conferencing system. Our results showed that there was nothing inherently detrimental to performing HRI user studies online. Indeed, based on these preliminary results, researchers who are conducting HRI user studies online can have more confidence that the online interaction modality does not negatively affect their results. © 2022 IEEE.

War and Peace: Ethical Challenges and Risks in Military Robotics

The United States Department of Defense (DoD) designs, constructs, and deploys social and autonomous robots and robotic weapons systems. Military robots are designed to follow the rules and conduct of the professions or roles they emulate, and it is expected that ethical principles are applied and aligned with such roles. The application of these principles appear paramount during the COVID-19 global pandemic, wherein substitute technologies are crucial in carrying out duties as humans are more restrained due to safety restrictions. This article seeks to examine the ethical implications of the utilization of military robots. The research assesses ethical challenges faced by the United States DoD regarding the use of social and autonomous robots in the military. The authors provide a summary of the current status of these lethal autonomous and social military robots, ethical and moral issues related to their design and deployment, a discussion of policies, and the call for an international discourse on appropriate governance of such systems.

Perceived Usefulness of a Social Robot Augmented Telehealth Platform by Therapists in the United States.

With the shortage of rehabilitation clinicians in rural areas and the ongoing COVID-19 pandemic, remote rehabilitation (telerehab) fills an important gap in access to rehabilitation, especially for the treatment of adults and children experiencing upper arm disability due to stroke and cerebral palsy. We propose the use of a socially assistive robot with arms, a torso, and a face to play games with and guide patients, coupled with a telepresence platform, to maintain the patient-clinician interaction, and a computer vision system, to aid in automated objective assessments, as a tool for achieving more effective telerehab. In this paper, we outline the design of such a system, Lil'Flo, and present a uniquely large perceived usefulness evaluation of the Lil'Flo platform with 351 practicing therapists in the United States. We analyzed responses to the question of general interest and 5 questions on Lil'Flo's perceived usefulness. Therapists believe that Lil'Flo would significantly improve communication, motivation, and compliance during telerehab interactions when compared to traditional telepresence. 27% of therapists reported that they were interested in using Lil'Flo. Therapists interested in using Lil'Flo perceived it as having significantly higher usefulness across all measured dimensions than those who were not interested in using it.