Immersive participatory design of assistive robots to support older adults.

Assistive robots have the potential to support independence, enhance safety, and lower healthcare costs for older adults, as well as alleviate the demands of their care partners. However, ensuring that these robots will effectively and reliably address end-user needs in the long term requires user-specific design factors to be considered during the robot development process. To identify these design factors, we embedded Stretch, a mobile manipulator created by Hello Robot Inc., in the home of an older adult with motor impairments and his care partner for four weeks to support them with everyday activities. An occupational therapist and a robotics engineer lived with them during this period, employing an immersive participatory design approach to co-design and customise the robot with them. We highlight the benefits of this immersive participatory design experience and provide insights into robot design that can be applied broadly to other assistive technologies.

Comfort and Attitudes Towards Robots Among Young, Middle-Aged, and Older Adults: A Cross-Sectional Study.

PURPOSE: To explore the social impact of, comfort with, and negative attitudes towards robots among young, middle-aged, and older adults in the United States. DESIGN: Descriptive, cross-sectional. Conducted in 2014-2015 in an urban area of the western United States using a purposive sample of adults 18 years of age or older. METHODS: Respondents completed a survey that included the Negative Attitudes Toward Robots Scale (NARS) and two questions taken or modified from the European Commission's Autonomous System 2015 Report. Analyses were conducted to compare perceptions and demographic factors by age groups (young adults:18-44, middle-aged adults: 45-64, and older adults: >65 years old). FINDINGS: Sample included 499 individuals (n = 322 age 18-44 years, n = 50 age 45-64 years, and n = 102 age 65-98 years). There were no significant differences between age groups for 9 of the 11 items regarding social impact of robots and comfort with robots. There were no significant differences by age groups for 9 of the 14 items in the NARS. Among those items with statistically significant differences, the mean scores indicate similar sentiments for each group. CONCLUSIONS: Older, middle-aged, and younger adults had similar attitudes regarding the social impact of and comfort with robots; they also had similar negative attitudes towards robots. Findings dispel current perceptions that older adults are not as receptive to robots as other adults. This has implications for nurses who integrate supportive robots in their practice. CLINICAL RELEVANCE: Nurses working in clinical and community roles can use these findings when developing and implementing robotic solutions. Understanding attitudes towards robots can support how, where, and with whom robots can be used in nursing practice.

Visual Categorization with Random Projection.

Humans learn categories of complex objects quickly and from a few examples. Random projection has been suggested as a means to learn and categorize efficiently. We investigate how random projection affects categorization by humans and by very simple neural networks on the same stimuli and categorization tasks, and how this relates to the robustness of categories. We find that (1) drastic reduction in stimulus complexity via random projection does not degrade performance in categorization tasks by either humans or simple neural networks, (2) human accuracy and neural network accuracy are remarkably correlated, even at the level of individual stimuli, and (3) the performance of both is strongly indicated by a natural notion of category robustness.

Connecting the Dots of Social Robot Design From Interviews With Robot Creators.

Despite promises about the near-term potential of social robots to share our daily lives, they remain unable to form autonomous, lasting, and engaging relationships with humans. Many companies are deploying social robots into the consumer and commercial market; however, both the companies and their products are relatively short lived for many reasons. For example, current social robots succeed in interacting with humans only within controlled environments, such as research labs, and for short time periods since longer interactions tend to provoke user disengagement. We interviewed 13 roboticists from robot manufacturing companies and research labs to delve deeper into the design process for social robots and unearth the many challenges robot creators face. Our research questions were: 1) What are the different design processes for creating social robots? 2) How are users involved in the design of social robots? 3) How are teams of robot creators constituted? Our qualitative investigation showed that varied design practices are applied when creating social robots but no consensus exists about an optimal or standard one. Results revealed that users have different degrees of involvement in the robot creation process, from no involvement to being a central part of robot development. Results also uncovered the need for multidisciplinary and international teams to work together to create robots. Drawing upon these insights, we identified implications for the field of Human-Robot Interaction that can shape the creation of best practices for social robot design.

Exploring Teens as Robot Operators, Users and Witnesses in the Wild.

As social robots continue to show promise as assistive technologies, the exploration of appropriate and impactful robot behaviors is key to their eventual success. Teens are a unique population given their vulnerability to stress leading to both mental and physical illness. Much of teen stress stems from school, making the school environment an ideal location for a stress reducing technology. The goal of this mixed-methods study was to understand teens' operation of, and responsiveness to, a robot only capable of movement compared to a robot only capable of speech. Stemming from a human-centered approach, we introduce a Participatory Wizard of Oz (PWoz) interaction method that engaged teens as operators, users, and witnesses in a uniquely transparent interaction. In this paper, we illustrate the use of the PWoz interaction method as well as how it helps identify engaging robot interactions. Using this technique, we present results from a study with 62 teens that includes details of the complexity of teen stress and a significant reduction in negative attitudes toward robots after interactions. We analyzed the teens' interactions with both the verbal and non-verbal robots and identified strong themes of (1) authenticity, (2) empathy, (3) emotional engagement, and (4) imperfection creates connection. Finally, we reflect on the benefits and limitations of the PWoz method and our study to identify next steps toward the design and development of our social robot.

Acceptance and perceived usefulness of robots to assist with activities of daily living and healthcare tasks.

As the number of older adults living with chronic conditions continues to rise, they will require assistance with activities of daily living (ADL) and healthcare tasks to continue living independently in their homes. One proposed solution to assist with the care needs of an aging population and a shrinking healthcare workforce is robotic technology. Using a cross-sectional survey design, we purposively sampled adults (≥18 years old) to assess generational acceptance and perceived usefulness of robots to assist with ADLs, healthcare tasks, and evaluate acceptance of robotic healthcare assistance across different settings. A total of 499 adults (age range [years] 18-98, Mean = 38.7, SD = 22.7) responded to the survey. Significant differences were found among young, middle-aged, and older adults on perceived usefulness of robots for cleaning, escorting them around town, acting as companionship, delivering meals, assessing sadness and calling for help, providing medical advice, taking vital sign assessments, and assisting with personal care (p < 0.05). The majority of younger adults reported that they would like a robot to provide healthcare assistance in the hospital, compared to middle-aged and older adults (p < 0.001). Results of this study can guide the design of robots to assist adults of all ages with useful tasks.