Patients with cancer (PwC) have a hard time getting prompt treatment in acute care settings, and feel unseen, unheard, and neglected. This is due to systemic problems: worldwide, Emergency Department (ED) healthcare workers (HCWs) are overworked and EDs are understaffed. Robots will not fix these problems; however, prior work suggests if well-designed and contextualized, they may support cancer care. Based on longstanding collaborations with PwC and ED HCWs, in this paper we report on an exploration of the design space of social robots for acute cancer care. Using a care ethics lens, we found robots can be uniquely positioned to amplify compassion within deeply human care relationships through their social presence, while performing routine tasks, such as patient monitoring. However, participants suggested the human experiences of pain and distress may remain elusive for robots to engage with meaningfully. Our work reveals HCWs and PwC saw robots as means to expand relational care in the ED, and explores how future HRI research may meaningfully support these care relationships.

When designing socially assistive robots, HRI researchers often focus on robot personality as a means of increasing a person’s engagement, enjoyment, and trust. In this work, we argue that using only trait-based personality models is often limited in its ability to capture the nuance that matches end users’ desires, experiences, and cultural backgrounds. To address this gap, we introduce the concept of a robot character , a holistic framing of robot personality that extends the trait-based approach to include external factors, such as shared interests between the user and robot, as sociocultural and environmental factors. We introduced and validated the Robot Role Character Creation (R2C2) tool, an accessible scaffolding tool to co-design robot characters with end users in order to support more nuanced and personalized robots. R2C2 highlights the voices of end users and enables them to easily ideate and communicate their unique robot characters, particularly for populations often underrepresented in robot design. Through a cross-cultural study (the U.S. and Mexico), we validated the R2C2 tool in eliciting rich design insights for robot characters from people with mild cognitive impairment (MCI) and dementia (PwD). We report our findings, enabled by the R2C2 tool, on the role participants envisioned for their desired robot characters, the multidimensionality and adaptability of these robot characters, and how participants’ socio-cultural backgrounds influenced their characters. Our findings demonstrate that R2C2 can facilitate the creation of nuanced and personalized robot characters that resonate with user experiences, needs, and preferences. We analyze how participants envisioned the roles, multidimensionality, and cultural influences shaping their ideal robot characters, highlighting R2C2’s ability to capture these diverse perspectives. This work will serve as a basis for HRI designers to create more effective robot interactions, enhance acceptance and trust, and promote engagement with robot characters while centering the wisdom and personhood of people with cognitive impairments.

Many robot-delivered health interventions aim to support people longitudinally at home to complement or replace in-clinic treatments. However, there is little guidance on how robots can support collaborative goal setting (CGS). CGS is the process in which a person works with a clinician to set and modify their goals for care; it can improve treatment adherence and efficacy. However, for home-deployed robots, clinicians will have limited availability to help set and modify goals over time, which necessitates that robots support CGS on their own. In this work, we explore how robots can facilitate CGS in the context of our robot CARMEN (Cognitively Assistive Robot for Motivation and Neurorehabilitation), which delivers neurorehabilitation to people with mild cognitive impairment (PwMCI). We co-designed robot behaviors for supporting CGS with clinical neuropsychologists and PwMCI, and prototyped them on CARMEN. We present feedback on how PwMCI envision these behaviors supporting goal progress and motivation during an intervention. We report insights on how to support this process with home-deployed robots and propose a framework to support HRI researchers interested in exploring this both in the context of cognitively assistive robots and beyond. This work supports designing and implementing CGS on robots, which will ultimately extend the efficacy of robot-delivered health interventions.

Much research in healthcare robotics explores extending rehabilitative interventions to the home. However, for adults, little guidance exists on how to translate human-delivered, clinic-based interventions into robot-delivered, home-based ones to support longitudinal interaction. This is particularly problematic for neurorehabilitation, where adults with cognitive impairments require unique styles of interaction to avoid frustration or overstimulation. In this paper, we address this gap by exploring the design of robot-delivered neurorehabilitation interventions for people with mild cognitive impairment (PwMCI). Through a multi-year collaboration with clinical neuropsychologists and PwMCI, we developed robot prototypes which deliver cognitive training at home. We used these prototypes as design probes to understand how participants envision long-term deployment of the intervention, and how it can be contextualized to the lives of PwMCI. We report our findings and specify design patterns and considerations for translating neurorehabilitation interventions to robots. This work will serve as a basis for future endeavors to translate cognitive training and other clinical interventions onto a robot, support longitudinal engagement with home-deployed robots, and ultimately extend the accessibility of longitudinal health interventions for people with cognitive impairments.

The Emergency Department (ED) is a stressful, safety-critical environment, which is often overcrowded, noisy, chaotic, and understaffed. The built environment plays a key role in patient outcomes, experiences, and the mental health of healthcare workers (HCWs). However, once a space is built, it is difficult to change it; so the modularity and adaptability of new technologies such as robots could potentially help stakeholders mitigate some of these challenges; yet, there is a lack of research in this area, particularly in the ED. In this paper, we address this gap by engaging HCWs in a research-through-design process, utilizing design fiction, to envision a future resilient ED. Here, robots scurry along the ceiling, provide help at the bedside, and smart furniture and walls provide spaces for privacy and calm. We co-created design prototypes of future intelligent systems that can modify the built environment to support resilience, which we then used to co-create a Design Catalog with HCWs, which contains a collection of future technology prototypes contextualized within the ED. We found that HCWs envisioned many ways for intelligent systems to help them reimagine the built environment, including ways to enhance HCW-patient communication, improve patient experience, support both HCW and patient safety, and use reconfigurable spaces to support privacy. We hope our work inspires further exploration into using new technologies to reimagine and reconfigure the built environment to support resilient hospitals.