Older Adults' Medication Management in the Home: How can Robots Help?

Humanoid robots for assisting people with physical disabilities in activities of daily living: A scoping review

The aim of this scoping review was to gather, summarize, and map the knowledge of peoples' experiences on humanoid robots, capable of assisting people with activities of daily living. The review was guided by the framework of Joanna Briggs Institute and PRISMA-ScR. We found 44 papers describing nine robots that could assist with a variety of tasks listed in the International Classification of Functioning, Disability, and Health. The mixed population experienced little or no anxiety toward the robots, and most accepted the robots' ability to monitor for safety reasons. Some participants disliked the robots' large size and slow movements. Most of the participants found the robots easy to use. They wanted improvements in the robots' functionality and the ability to personalize services. Several of the participants found the services interesting and useful, but not for themselves. The experiences of humanoid robotic assistance showed an insufficient level of technical readiness for assisting in physical assistance, a lack of personalization and readiness for use in home settings. The practical relevance of these findings lies in guiding future research and development toward a more individualized approach focusing on user needs and experiences to enhance the efficacy and integration of humanoid robots in health-care.

How Should Your Assistive Robot Look Like? A Scoping Review on Embodiment for Assistive Robots

Assistive robots have the potential to support older people and people with disabilities in various tasks so that they can live more independently. One of the research challenges is the appearance of assistive robots so that they are accepted by prospective users and encourage interaction. This scoping review aims to identify studies that report preferences in order to derive indicators for the embodiment of a robot with assistance functions. A systematic literature research was conducted in the three electronic databases IEEE Xplore, ACM Digital Library and PubMed Central (PMC). Included papers date back not further than 2015 and report empirical studies about the preferred appearance of service robots. The search resulted in 1,760 papers. 29 were included, of which 20 papers reported quantitative studies, three described a qualitative and six a mixed-methods design. Out of these papers, seven categories of robot appearances and design components could be extracted. Most papers focused on humanoid or humanlike robots and components like facial features or gender aspects. Others relied on design that reflects the robot’s function or simulated emotions through light applications. Only eight studies focused on older adults, and no study on people with disabilities. The appearance of a humanoid robot is often described as favorable, but the definition of ‘humanoid’ varies widely within all analyzed studies and an explizit allocation of features is not possible. For their practical work, robot designers can extract various aspects from the papers; however, for generalization more research is necessary.

Double-Bind of Recruitment of Older Adults Into Studies of Successful Aging via Assistive Information and Communication Technologies: Mapping Review

BACKGROUND

Two fields of research and development targeting the needs of the aging population of the world are flourishing, successful aging and assistive information and communication technologies (A-ICTs). The risks of ageist stereotypes emerging from how we communicate in both discourses are long known. This raises questions about whether using specific age criteria in the context of "aging deficits" can bias participation in, or compliance with, the research process by older adults who try to avoid age-related stigma.

OBJECTIVE

This study aimed to examine subject recruitment, study designs (based on age >65 years criteria), as well as discourses in research objectives and conclusions in health research on affordances of A-ICTs for older adults.

METHODS

A systematic mapping approach was used to characterize rationales, methods, stated objectives, and expected outcomes of studies indexed in PubMed and retrieved through the search logic (["Older Adults" OR Seniors OR Elderly] AND [ICT OR gerontechnology OR "Assistive Technology")] AND ("Healthy Aging" OR "Successful Aging" OR "healthy ageing" OR "successful ageing"). Inclusion criteria were as follows: the study should have recruited older participants (aged >65 years), been qualitative or quantitative research, and involved the introduction of at least one A-ICT for health-related improvements. Exclusion criteria were as follows: reviews, viewpoints, surveys, or studies that used information and communication technology for data collection instead of lifestyle interventions. Content, thematic, and discourse analyses were used to map the study characteristics and synthesize results with respect to the research question.

RESULTS

Of 180 studies that passed the search logic, 31 (17.2%) satisfied the inclusion criteria (6 randomized controlled trials, 4 purely quantitative studies, 9 focus groups, 2 observational studies, and 10 mixed methods studies). In all but one case, recruitment was pragmatic and nonrandom. Thematic analysis of rationales revealed a high likelihood of emphasis on the burdens of aging, such as rising costs of care (12/31, 39%) and age-related deficits (14/31, 45%). The objectives of the research fell under 4 categories: promotion of physical activity, acceptance and feasibility of robots and remote health monitoring systems, risk detection, and the future of A-ICTs in health care for older adults. Qualitative studies were more attentive to the nonageist research guidelines. Heterogeneity in the study results (both qualitative and quantitative) was not related to age but to individual agency, acceptance, and adherence. A combination of research strategies (participatory, longitudinal, playful, flexible, and need-based designs) proved successful in characterizing variations in study outcomes. Studies that documented recruitment dynamics revealed that fear of stigma was a factor that biased participants' engagement.

CONCLUSIONS

This review indicates that age is not an informative criterion for recruitment and retention of participants. Charting the dynamics of adoption of, and interaction with, A-ICTs is critical for advancing research and technology development.

Acceptance of Remote Assistive Robots with and without Human-in-the-Loop for Healthcare Applications

Assistive social robots aim to facilitate outpatient-care including required safety critical measures. Accepting a robot to perform such measures, e.g., operate in close physical interaction for medical examinations, requires human trust towards the robot. Human-in-the-loop (HIL) applications where the robot is teleoperated by a human expert can help the person to accept even risky tasks performed by a robot. Therefore, the assistive humanoid GARMI was designed to enable HIL applications with varying autonomy. In this study, we use GARMI to understand which tasks in the framework of care may be accepted depending on human socio-demographics and user beliefs as well as the level of robot autonomy. Firstly, we seek to understand the general acceptance of GARMI using the Almere questionnaire. Secondly, we ask adults to rate their willingness to use several functionalities of GARMI. Lastly, we investigate the effect of the introduction method of GARMI on user acceptance. We assemble all relevant factors on acceptance to provide direction in the user-centered design process of assistive robots. The results of 166 participants show that alongside others, trust towards the robot and utilitarian variables such as perceived usefulness are the most influencing factors on the acceptance of GARMI and should be considered for the design of robotic semi-autonomous outpatient-services.

A deep learning-based medication behavior monitoring system

The internet of things (IoT) and deep learning are emerging technologies in diverse research fields, including the provision of IT services in medical domains. In the COVID-19 era, intelligent medication behavior monitoring systems for stable patient monitoring are further required, because many patients cannot easily visit hospitals. Several previous studies made use of wearable devices to detect medication behaviors of patients. However, the wearable devices cause inconvenience while equipping the devices. In addition, they suffer from inconsistency problems due to errors of measured values. We devise a medication behavior monitoring system that uses the IoT and deep learning to avoid sensing errors and improve user experiences by effectively detecting various activities of patients. Based on the real-time operation of our proposed IoT device, the proposed solution processes captured images of patents via OpenPose to check medication situations. The proposed system identifies medication status on time by using a human activity recognition scheme and provides various notifications to patients' mobile devices. To support reliable communication between our system and doctors, we employ MQTT protocol with periodic data transmissions. Thus, the measured information of patient's medication status is transmitted to the doctors so that they can periodically perform remote treatments. Experimental results show that all medication behaviors are accurately detected and notified to the doctor efficiently, improving the accuracy of monitoring the patient's medication behavior.

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.

Commanding Home Robots

Developing robots that are useful to older adults is more than simply creating robots that complete household tasks. Careful consideration of the users’ capabilities, robot autonomy, and task is needed. Perceived usefulness, according to the Technology Acceptance Model (TAM), is described as a person’s perception of how well the technology’s capability matches his or her own needs. The purpose of this qualitative study was to investigate the construct of perceived usefulness within the context of robot assistance and user capability. Two user groups participated: mobile older adults (N = 12; used no ambulation aid) and older adults with mobility loss (N=12; used walker or wheelchair). Participants took part in a think aloud task. We asked participants to discuss their robot control preferences for household tasks (e.g., clean, find and fetch). Older adults with mobility loss tended to prefer to command/control the robot themselves (low robot autonomy); however, mobile older adults’ preferences were split between commanding/controlling the robot themselves (low robot autonomy) or the robot commands/controls itself (high robot autonomy). Reasons for their preferences were task specific and related to barriers/facilitators of robot acceptance, such as trust, reliability, and user need. Findings provide practical guidance to choosing robot autonomy level, broadly defined, for different groups of older adults.

Supporting Active and Healthy Aging with Advanced Robotics Integrated in Smart Environment

The technological advances in the robotic and ICT fields represent an effective solution to address specific societal problems to support ageing and independent life. One of the key factors for these technologies is the integration of service robotics for optimising social services and improving quality of life of the elderly population. This chapter aims to underline the barriers of the state of the art, furthermore the authors present their concrete experiences to overcome these barriers gained at the RoboTown Living Lab of Scuola Superiore Sant'Anna within past and current projects. They analyse and discuss the results in order to give recommendations based on their experiences. Furthermore, this work highlights the trend of development from stand-alone solutions to cloud computing architecture, describing the future research directions.

Why Some Humanoid Faces Are Perceived More Positively Than Others: Effects of Human-Likeness and Task

Ample research in social psychology has highlighted the importance of the human face in human-human interactions. However, there is a less clear understanding of how a humanoid robot's face is perceived by humans. One of the primary goals of this study was to investigate how initial perceptions of robots are influenced by the extent of human-likeness of the robot's face, particularly when the robot is intended to provide assistance with tasks in the home that are traditionally carried out by humans. Moreover, although robots have the potential to help both younger and older adults, there is limited knowledge of whether the two age groups' perceptions differ. In this study, younger (N = 32) and older adults (N = 32) imagined interacting with a robot in four different task contexts and rated robot faces of varying levels of human-likeness. Participants were also interviewed to assess their reasons for particular preferences. This multi-method approach identified patterns of perceptions across different appearances as well as reasons that influence the formation of such perceptions. Overall, the results indicated that people's perceptions of robot faces vary as a function of robot human-likeness. People tended to over-generalize their understanding of humans to build expectations about a human-looking robot's behavior and capabilities. Additionally, preferences for humanoid robots depended on the task although younger and older adults differed in their preferences for certain humanoid appearances. The results of this study have implications both for advancing theoretical understanding of robot perceptions and for creating and applying guidelines for the design of robots.