An ageing population and the need of providing adequate care have led to developing robots to relieve healthcare workers and to assist individuals in their own homes. However, the successful integration of robots in such settings relies on more than just ensuring physical safety associated with physical risks (e.g., collisions): it also requires the user’s perceived safety – the users perceiving the robot as not doing any harm. This paper explores the potential influence of a robot gripper’s visual and tactile properties, such as materials and texture, on the users’ perceived safety and comfort of human-robot interaction. An initial survey was distributed to 53 participants, exploring five (n=5) robot gripper designs focusing on the robots’ gripper shape. One design shape was thereafter selected to be constructed as a cover to be placed over the parallel grippers of the TIAGo robot, by using 1) wood filament and 2) plastic. The covers were then tested in an experimental setting with 11 participants. The covers were attached to the TIAGo mobile manipulator robot and participants interacted with both of the designed gripper covers within a controlled laboratory environment. A questionnaire was distributed to all 11 experiment participants, at different stages of the interactions. The findings indicate that the material of the gripper influenced participants’ sense of comfort, familiarity, and perceived capabilities of the robot. The study suggests that perceived safety in human-robot interaction (HRI) is shaped not only by physical factors but also by how materials are personally and contextually interpreted. To better support safe and comfortable interactions, further research is needed to understand how material choices shape users’ perceived safety.

Studies foresee a dramatic increase in the elderly population of Western Europe over the next decades, putting pressure on healthcare systems. Healthcare robots are developed to facilitate independent living for elderly people. This article aims to provide a qualitative analysis of recent projects in healthcare robotics (2008–2024) and proposes new research directions for healthcare robots for older adults. We provide an overview of current research and a roadmap for upcoming research. Our study began with a literature search using four databases. Searches were performed for articles from research projects containing the words “elderly care,” “assisted aging,” “health monitoring,” or “elderly health.” Additional exclusion criteria were used to focus on elderly healthcare and utilization of commercial robotic systems. Resulting from this endeavor, 20 recent research projects are described and categorized in this article. Then, these projects were analyzed using thematic analysis. Our findings are summarized in common themes: Most projects have a strong bias towards care robots’ functionalities; robots are often seen as outsiders in care settings; there is an emphasis on robots as commercial products; and there is some limited attention to the design and ethical aspects of care robots, but very little attention to their legal aspects. The article concludes with key points representing a roadmap for future research addressing robotics for the elderly.

Striking a balance between utility and privacy holds significant importance in systems that rely on sensor utilization, such as robots. This balance is even more vital in care robots, given the sensitivity of personal data and the necessity for privacy-preserving monitoring to ensure user comfort. This paper presents a comprehensive investigation into the utility-privacy trade-off concerning different vision-based sensors. Specifically, RGB cameras, color and mono-color thermal cameras, and depth sensors are compared, considering technical aspects and users’ perception of privacy. The technical analysis addresses human pose tracking, human presence detection, human vital sign monitoring, and human facial and emotion recognition. The quantitative examination of sensors in real-life scenarios highlights the mono-color thermal camera’s effectiveness for user monitoring. Particularly, this sensor excels in challenging human presence detection scenarios compared to RGB cameras. Furthermore, interview and survey studies, encompassing two different age groups were carried out to compare how sensors are perceived in terms of user privacy. The quantitative and qualitative assessments of users’ feedback in these studies reveal that apart from depth sensors, thermal mono-color, and thermal color sensors are perceived as better at preserving user privacy compared to RGB cameras. The analysis includes the influence of participant age on privacy perception, indicating non-significant effects. Considering both the technical assessment and user preferences, the mono-color thermal camera emerges as the optimal choice for human monitoring purposes.

Successfully implementing robots to support senior adults requires their acceptance. Leveraging nonverbal communication could enhance the ease and intuitiveness of accepting robot assistance. However, it is essential to see how different age groups understand nonverbal communication cues to understand the dynamics between different user groups and assistive robots. Our research specifically delves into the intuitive understanding of handshaking gestures across multiple interactions, focusing on seniors (between 70 and 97) and young (21 and 26) adults. Through a combination of observations and open-ended surveys, we conducted a video observation and thematic analysis. Interestingly, our findings indicate no significant differences between the two age groups, except for reactions and interaction time variables. Furthermore, we report on possible motivations behind the initial reactions in the two age groups, familiarity, and ways to improve the overall Human-Robot Interaction experience potentially.

Robots have the potential to provide everyday life care and support for senior adults, but acceptance is essential for successful implementation in the domestic environment. Nonverbal social behavior can enhance this acceptance, and behavioral cues should be easy and intuitive to understand. However, which factors contribute to senior adults’ intuitive understanding of social cues, such as handshakes? Our research aims to address this question using video observations and semi-structured interviews. Based on a thematic analysis and video observations, our findings indicate that some participants intuitively understood how to shake hands. Most did not shake hands due to not understanding the robot’s behavior or fear. Other identified themes included: contributing features for intuitive handshakes, design improvements, and experiences with the robot’s end effector. Lastly, we found no significant effect between the initial response of the participants to the handshake and either the reaction time or the handshake duration. By designing the gripper and the robot itself in a more familiar, less fear-eliciting way, senior adults might understand the gesture of shaking hands more intuitively.

We used the story dialog method (SDM) to gather the viewpoints of health professionals about the use of social robots in the home and healthcare services with vulnerable users. SDM consists of participants bringing stories that they discuss together. The aim of the study was to address universal design and accessibility issues with robots in specific use situations. We used three social robots in four stories: TIAGo, Romibo and robot pets. We used the SDM method in two workshops with eight participants. The participants uncovered issues regarding ethics, responsibility, use of data, infrastructure, design, and user concerns based on provided stories and their own experiences. These issues provide important aspects that researchers and roboticists should consider when using robots with vulnerable users and ensuring that a robot is usable by as many people as possible.