Jenay M. Beer

Mobile remote presence systems for older adults: acceptance, benefits, and concerns

While much of human-robot interaction research focuses upon people interacting with autonomous robots, there is also much to be gained from exploring human interpersonal interaction through robots. The current study focuses on mobile remote presence (MRP) systems as used by a population who could potentially benefit from more social connectivity and communication with remote people - older adults. Communication technologies are important for ensuring safety, independence, and social support for older adults, thereby potentially improving their quality of life and maintaining their independence [24]. However, before such technologies would be accepted and used by older adults, it is critical to understand their perceptions of the benefits, concerns, and adoption criteria for MRP systems. As such, we conducted a needs assessment with twelve volunteer participants (ages 63-88), who were given first-hand experience with both meeting a visitor via the MRP system and driving the MRP system to visit that person. The older adult participants identified benefits such as being able to see and be seen via the MRP system, reducing travel costs and hassles, and reducing social isolation. Among the concerns identified were etiquette of using the MRP, personal privacy, and overuse of the system. Some new use-cases were identified that have not yet been explored in prior work, for example, going to museums, attending live performances, and visiting friends who are hospitalized. The older adults in the current study preferred to operate the MRP themselves, rather than to be visited by others operating the MRP system. More findings are discussed in terms of their implications for design.

Assisted driving of a mobile remote presence system: System design and controlled user evaluation

As mobile remote presence (MRP) systems become more pervasive in everyday environments such as office spaces, it is important for operators to navigate through remote locations without running into obstacles. Human-populated environments frequently change (e.g., doors open and close, furniture is moved around) and mobile remote presence systems must be able to adapt to such changes and to avoid running into obstacles. As such, we implemented an assisted teleoperation feature for a MRP system and evaluated its effectiveness with a controlled user study, focusing on both the system-oriented dimensions (e.g., autonomous assistance vs. no assistance) and human-oriented dimensions (e.g., gaming experience, locus of control, and spatial cognitive abilities) (N=24). In a systems-only analysis, we found that the assisted teleoperation helped people avoid obstacles. However, assisted teleoperation also increased time to complete an obstacle course. When human-oriented dimensions were evaluated, gaming experience and locus of control affected speed of completing the course. Implications for future research and design are discussed.

Toward a framework for levels of robot autonomy in human-robot interaction

Autonomy is a critical construct related to human-robot interaction (HRI) and varies widely across robot platforms. Levels of robot autonomy (LORA), ranging from teleoperation to fully autonomous systems, influence the way in which humans and robots interact with one another. Thus, there is a need to understand HRI by identifying variables that influence---and are influenced by---robot autonomy. Our overarching goal is to develop a framework for LORA in HRI. To reach this goal, our framework draws links between HRI and human-automation interaction, a field with a long history of studying and understanding human-related variables. The construct of autonomy is reviewed and redefined within the context of HRI. Additionally, this framework proposes a process for determining a robots autonomy level by categorizing autonomy along a 10-point taxonomy. The framework is intended to be treated as a guideline for determining autonomy, categorizing the LORA along a qualitative taxonomy and considering HRI variables (e.g., acceptance, situation awareness, reliability) that may be influenced by the LORA.

Older Adults’ Preferences for and Acceptance of Robot Assistance for Everyday Living Tasks

Many older adults value their independence and prefer to age in place. Robots can be designed to assist older people with performing everyday living tasks and maintaining their independence at home. Yet, there is a scarcity of knowledge regarding older adults’ attitudes toward robots and their preferences for robot assistance. Twenty-one older adults (M = 80.25 years old, SD = 7.19) completed questionnaires and participated in structured group interviews investigating their openness to and preferences for assistance from a mobile manipulator robot. Although the older adults were generally open to robot assistance for performing home-based tasks, they were selective in their views. Older adults preferred robot assistance over human assistance for many instrumental (e.g., housekeeping, laundry, medication reminders) and enhanced activities of daily living (e.g., new learning, hobbies). However, older adults were less open to robot assistance for some activities of daily living (e.g., shaving, hair care). Results from this study provide insight into older adults’ attitudes toward robot assistance with home-based everyday living tasks.

Understanding Challenges in the Front Lines of Home Health Care: A Human-Systems Approach

A human-systems perspective is a fruitful approach to understanding home health care because it emphasizes major individual components of the system - persons, equipment/technology, tasks, and environments - as well as the interaction between these components. The goal of this research was to apply a human-system perspective to consider the capabilities and limitations of the persons, in relation to the demands of the tasks and equipment/technology in home health care. Identification of challenges and mismatches between the person(s) capabilities and the demands of providing care provide guidance for human factors interventions. A qualitative study was conducted with 8 home health Certified Nursing Assistants and 8 home health Registered Nurses interviewed about challenges they encounter in their jobs. A systematic categorization of the challenges the care providers reported was conducted and human factors recommendations were proposed in response, to improve home health. The challenges inform a human-systems model of home health care.

Challenges for Home Health Care Providers: A Needs Assessment

ABSTRACT Home health care is the delivery of predominantly medically related services to patients in a home setting rather than in a medical facility. It provides substantial benefits over traditional, hospital-based health care, such as supporting older adults’ independence and quality of life, as well as being more cost-effective. This aspect of the health care industry could be enhanced through increased technological supports. When providing health care in a home setting, formal caregivers, such as certified nursing assistants (CNAs), registered nurses (RNs), physical therapists (PTs), and occupational therapists (OTs), are faced with many challenges that impede their ability to perform their jobs. Technological interventions have the potential to alleviate many of these challenges. However, to achieve this potential, new technologies must be created to meet the needs of home health care providers. To date, these providers’ specific and most critical needs are not thoroughly understood. This understanding can be gained by conducting a detailed needs assessment that captures the common challenges and difficulties that home health care providers encounter. We conducted a needs assessment comprising three phases: (a) an extensive literature review of research regarding the needs of home health providers, both hospital and home-based (CNAs, RNs, PTs, and OTs); (b) subject matter expert interviews with experienced individuals from home health care; and (c) structured interviews with CNAs. We identified several significant sources of frustration and difficulty faced by CNAs including medical device usage, patient education, family involvement, provider isolation, and barriers to communication. This analysis provides an understanding of the challenges confronting home health care providers that can provide guidance for interventions. Future home health care technology can be developed to specifically target these workers’ most urgent needs and allow them to perform their jobs with greater ease. Moreover, RNs, PTs, and OTs can benefit from understanding some of the challenges faced by their teammates in the home health care process.

Emotion Recognition of Virtual Agents Facial Expressions: The Effects of Age and Emotion Intensity

People make determinations about the social characteristics of an agent (e.g., robot or virtual agent) by interpreting social cues displayed by the agent, such as facial expressions. Although a considerable amount of research has been conducted investigating age-related differences in emotion recognition of human faces (e.g., Sullivan, & Ruffman, 2004), the effect of age on emotion identification of virtual agent facial expressions has been largely unexplored. Age-related differences in emotion recognition of facial expressions are an important factor to consider in the design of agents that may assist older adults in a recreational or healthcare setting. The purpose of the current research was to investigate whether age-related differences in facial emotion recognition can extend to emotion-expressive virtual agents. Younger and older adults performed a recognition task with a virtual agent expressing six basic emotions. Larger age-related differences were expected for virtual agents displaying negative emotions, such as anger, sadness, and fear. In fact, the results indicated that older adults showed a decrease in emotion recognition accuracy for a virtual agents emotions of anger, fear, and happiness.

Socially assistive robots for the aging population: are we trapped in stereotypes?

Robots caring for the older population in care facilities and at home is an ongoing theme in HRI research. Research projects on this topic exist all over the globe in the USA, Europe, and Asia. All of these projects have the overall ambitious goal to increase the well-being of older adults and to enable them to stay at home as long as possible. In this workshop we want to reflect whether the HRI community is trapped in stereotypes when it comes to socially assistive robots for older adults? Therefore we want to gather and compare findings from user needs analysis, user evaluation studies, as well as interaction scenarios and functionalities of existing care robots. Are our results suggesting similar scenarios? Do older end users in all countries have similar needs and desires when it comes to assistive robots? What are the challenges and opportunities for future assistive robots (maybe for those we develop for ourselves when we belong to the older population...) also on an ethical and legal level? In this workshop we want to escape the stereotype trap what socially assistive robots should do. Can socially assistive robots solve the aging population problem on a societal and individual level? Are older people in general technology opponents? Will robotic helpers be accepted in the home as long as they pretend to be social actors? Categories and Subject Descriptors J4 [Computer Applications]: Social and Behavioral Sciences – Sociology; Psychology General Terms Design, Experimentation, Human Factors, Theory.

Applied Experimental Psychology: A Capstone Course for Undergraduate Psychology Degree Programs

Learning-by-doing and a transgenerational educational format are incorporated into a semesterlong undergraduate capstone course. The goal of the course is to provide students with an understanding of the fundamentals of applied experimental psychology (e.g., applications of methods), and using that understanding in the context of design. Students participate in seminarstyle class meetings and a weekly laboratory meeting. Every class meeting is devoted to discussing a reading assignment related to the fundamentals of aging, as well as a breadth of applied experimental psychology domains. The students are encouraged to engage in collaborative discussion to critique the main points of the reading. In the laboratory, each student learns about and applies human factors methods. The students work in teams and develop a project in which they apply their fundamental knowledge of experimental psychology to the domain of successful aging. Each team develops or redesigns a technology, device, or environment to aid older adults to live independently, maintain their health, and/or improve their well-being. Transgenerational education is promoted through the students’ interaction with a panel of elders, who participate in user testing and feedback. The students and older adults alike reported that the course is beneficial. Students learned about the fundamentals of applying experimental psychology and aging, whereas older adults increased their awareness of technology development and how technology can impact successful aging.

Recognizing Emotion in Virtual Agent, Synthetic Human, and Human Facial Expressions:

A growing interest in the HCI community is the design and development of embodied agents in virtual environments. For virtual environments where social interaction is needed, an agents facial expression may communicate emotive state to users both young and old. However, younger and older adults differ in how they label human facial expressions (Ruffman et al., 2008). Such possible age-related differences in labeling virtual agent expressions may impact the users social experience in a virtual environment. The purpose of the current research was to investigate age-related differences in emotion recognition of several on-screen characters of varying degrees of human-likeness. Participants performed a recognition task with three characters demonstrating four basic emotions or neutral. The results indicated age-related differences for all character types. Older adults commonly mislabeled the human and synthetic human emotions of anger, fear, sadness, and neutral. For the virtual agent face, older adults commonly mislabeled the emotions of anger, fear, happiness, and neutral.