Assessment of Perceived Attractiveness, Usability, and Societal Impact of a Multimodal Robotic Assistant for Aging Patients With Memory Impairments

Staff's Attitudes towards the Use of Mobile Telepresence Robots in Long-Term Care Homes in Canada

This cross-sectional study investigated staff's attitudes towards the use of mobile telepresence robots in long-term care (LTC) homes in western Canada. We drew on a Health Technology Assessment Core Model 3.0 to design a survey examining attitudes towards nine domains of mobile telepresence robots. Staff, including nurses, care staff, and managers, from two LTC homes were invited to participate. Statistical analysis of survey data from 181 participants revealed that overall, participants showed positive attitudes towards features and characteristics, self-efficacy on technology use, organizational aspects, clinical effectiveness, and residents and social aspects; neutral attitudes towards residents' ability to use technology, and costs; and negative attitudes towards safety and privacy. Participants who disclosed their demographic backgrounds tended to exhibit more positive attitudes than participants who did not. Content analysis of textual data identified specific concerns and benefits of using the robots. We discuss options for implementing mobile telepresence robots in LTC.

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.

Enhancing neurocognitive health, abilities, networks, & community engagement for older adults with cognitive impairments through technology: a scoping review introducing the ENHANCE Center

PURPOSE

Age associated cognitive impairments (CIs) result in difficulties with a wide range of daily activities. As the older adult population increases, so does the importance of understanding and supporting the needs and disabilities of those with CIs. The Enhancing Neurocognitive Health, Abilities, Networks, and Community Engagement (ENHANCE) Centre was established with a focus on developing assistive technology to support the socialisation, transportation, and prospective memory needs of older adults with CIs. The extent to which relevant literature in these domains existed was unknown.

MATERIALS AND METHODS

A scoping review identified existing research meeting the following criteria: participants aged 50+ years classified as having a CI due to mild cognitive impairment (MCI), traumatic brain injury (TBI), or stroke; and a focus on technology-based support for socialisation, transportation, and/or prospective memory activities.

RESULTS

Qualitative and quantitative data are reported from relevant studies. In addition to few studies available, it was common for studies to include 20 or fewer participants. Most assessed technology interactions at one time and few studies examined longitudinal use and benefit. While each paper examined one aspect of user-centred design, no technologies were reported that underwent all stages of the user-centred design process, from needs assessment to iterative design and usability testing, to efficacy trial.

CONCLUSIONS

Gaps highlight notable directions for future research and the important role ENHANCE can play in addressing the needs and disabilities of older adults with CIs. IMPLICATIONS FOR REHABILITATIONAlthough older adults with common cognitive impairments often experience challenges in the domains of socialisation, transportation, and/or prospective memory, few studies exist that examine assistive technology solutions in these domains.Additional research with more robust designs and larger sample sizes is needed to discover and assess assistive technology solutions for the needs and disabilities of older adults with mild cognitive impairment (MCI), traumatic brain injury (TBI), and post-stroke cognitive impairment (PSCI).The ENHANCE Centre will employ a systematic process of needs assessments, user testing, and efficacy tests to develop novel technology solutions to support the needs of older adults with common cognitive impairment.

The most used questionnaires for evaluating the usability of robots and smart wearables: A scoping review

Background

As the field of robotics and smart wearables continues to advance rapidly, the evaluation of their usability becomes paramount. Researchers may encounter difficulty in finding a suitable questionnaire for evaluating the usability of robotics and smart wearables. Therefore, the aim of this study is to identify the most commonly utilized questionnaires for assessing the usability of robots and smart wearables.

Methods

A comprehensive search of databases, including PubMed, Web of Science, and Scopus, was conducted for this scoping review. Two authors performed the selection of articles and data extraction using a 10-field data extraction form. In cases of disagreements, a third author was consulted to reach a consensus. The inclusions were English-language original research articles that utilized validated questionnaires to assess the usability of healthcare robots and smart wearables. The exclusions comprised review articles, non-English publications, studies not focused on usability, those assessing clinical outcomes, articles lacking questionnaire details, and those using non-validated or researcher-made questionnaires. Descriptive statistics methods (frequency and percentage), were employed to analyze the data.

Results

A total of 314 articles were obtained, and after eliminating irrelevant and duplicate articles, a final selection of 50 articles was included in this review. A total of 17 questionnaires were identified to evaluate the usability of robots and smart wearables, with 10 questionnaires specifically for wearables and 7 questionnaires for robots. The System Usability Scale (50%) and Post-Study System Usability Questionnaire (19.44%) were the predominant questionnaires utilized to assess the usability of smart wearables. Moreover, the most commonly used questionnaires for evaluating the usability of robots were the System Usability Scale (56.66%), User Experience Questionnaire (16.66%), and Quebec User Evaluation of Satisfaction with Assistive Technology (10%).

Conclusion

Commonly employed questionnaires serve as valuable tools in assessing the usability of robots and smart wearables, aiding in the refinement and optimization of these technologies for enhanced user experiences. By incorporating user feedback and insights, designers can strive towards creating more intuitive and effective robotic and wearable solutions.

Assistive robotic systems in nursing care: a scoping review

BACKGROUND

The use of assistive robotic systems in care is intended to relieve nursing staff. Differentiated and literature-based findings on current application possibilities, technological developments and empirical findings are necessary to enable a goal-oriented and participatory development of assistive robotic systems of care. The aim of this review was to identify assistive robotic systems and their areas of application in nursing settings. Furthermore, an overview of existing social and nursing science findings from the research field of assistive robotic systems will be described.

METHODS

A systematic literature search was performed based on the JBI scoping review methodology. During the period from May to August 2020, the databases MEDLINE via PubMed, CINAHL, Cochrane Library, Web of Science, and IEEE Xplore Digital Library were searched. In order to reflect current developments and evidence in the present literature work, a supplementary search with these same requirements was conducted in January 2022.

RESULTS

The 47 included publications are divided into 15 studies, 23 technical articles and nine opinion-based articles (text-opinion). A total of 39 different assistive robotic systems were identified. There were 55% in the testing phase and 29% of the systems in the development phase. Assistive robotic systems can be divided into six fields of application: Information and patient data processing, assistance with activities of daily living, fetch and bring activities, telepresence and communication, monitoring, safety and navigation, and complex assistance systems. The description of the study findings is divided into "integration of technology and impact on practice" and "attitude and acceptance of elderly people towards assistive robotic systems".

CONCLUSION

The results of the research show that the use of assistive robotic systems in care mainly take place in the context of development and testing phases. In addition to usability and acceptance issues, implementation factors must be integrated into theory-driven research projects.

User Profiling to Enhance Clinical Assessment and Human-Robot Interaction: A Feasibility Study

Socially Assistive Robots (SARs) are designed to support us in our daily life as a companion, and assistance but also to support the caregivers' work. SARs should show personalized and human-like behavior to improve their acceptance and, consequently, their use. Additionally, they should be trustworthy by caregivers and professionals to be used as support for their work (e.g. objective assessment, decision support tools). In this context the aim of the paper is dual. Firstly, this paper aims to present and discuss the robot behavioral model based on sensing, perception, decision support, and interaction modules. The novel idea behind the proposed model is to extract and use the same multimodal features set for two purposes: (i) to profile the user, so to be used by the caregiver as a decision support tool for the assessment and monitoring of the patient; (ii) to fine-tune the human-robot interaction if they can be correlated to the social cues. Secondly, this paper aims to test in a real environment the proposed model using a SAR robot, namely ASTRO. Particularly, it measures the body posture, the gait cycle, and the handgrip strength during the walking support task. Those collected data were analyzed to assess the clinical profile and to fine-tune the physical interaction. Ten older people (65.2 ± 15.6 years) were enrolled for this study and were asked to walk with ASTRO at their normal speed for 10 m. The obtained results underline a good estimation (p < 0.05) of gait parameters, handgrip strength, and angular excursion of the torso with respect to most used instruments. Additionally, the sensory outputs were combined in the perceptual model to profile the user using non-classical and unsupervised techniques for dimensionality reduction namely T-distributed Stochastic Neighbor Embedding (t-SNE) and non-classic multidimensional scaling (nMDS). Indeed, these methods can group the participants according to their residual walking abilities.

Study protocol for the implementation and evaluation of a digital-robotic-based intervention for nurses and patients in a hospital: a quantitative and qualitative triangulation based on the Medical Research Council (MRC) framework for developing and evaluating complex interventions

BACKGROUND

Nurses spend part of their working time on non-nursing tasks. Unnecessary walking distances and the assumption of service activities and other non-care-related tasks take up a lot of space, which reduces the time for direct patient care and demonstrably increases the dissatisfaction of the persons involved. The REsPonSe project aims to relieve nursing staff by using a smartphone app for communication in combination with an autonomous service robot to reduce walking distances and service activities. The technical systems are tested on a nuclear medicine ward and are intended to reduce the radiation exposure of the staff. The aim of this study is to test and evaluate the use and intervention of the technical systems, the acceptance of the users and the change in the utilisation of the nursing service. In addition to findings on usability and manageability, effects on nursing practice, as well as facilitating and inhibiting contextual factors for implementation, will be identified.

METHODS

The Medical Research Council (MRC) Framework for Developing and Evaluating for Complex Interventions was chosen as the theoretical basis. The data collection in the Feasibility and Evaluation phase is a triangulation of quantitative and qualitative methods. Standardised observations are planned to collect data on non-care activities and walking distances, and a survey of utilisation by use of a questionnaire based on the NASA TLX. Qualitative individual interviews with patients and group discussions with nursing staff will be conducted. Statements on the subjective experiences, as well as the evaluation of the use of the digital-robotic system in the clinical setting, will be collected. The descriptive evaluation of the usage and retrieval data will provide information on duration, time, requests, and reduced contact times, as well as error and fault messages.

DISCUSSION

The evaluation study will make it possible to represent a variety of perspectives from different interest groups. The results should contribute to the definition of implementation and evaluation criteria and facilitate the integration of digital-robotic assistance systems in nursing acute inpatient settings.

TRIAL REGISTRATION

The trial was registered with the German Clinical Trials Register (DRKS) on 16.02.2022: DRKS00028127.

Learning-based control approaches for service robots on cloth manipulation and dressing assistance: a comprehensive review

Background

Service robots are defined as reprogrammable, sensor-based mechatronic devices that perform useful services in an autonomous or semi-autonomous way to human activities in an everyday environment. As the number of elderly people grows, service robots, which can operate complex tasks like dressing tasks for disabled people, are being demanded increasingly. Consequently, there is a growing interest in studying dressing tasks, such as putting on a t-shirt, a hat, or shoes. Service robots or robot manipulators have been developed to accomplish these tasks using several control approaches. The robots used in this kind of application are usually bimanual manipulator (i.e. Baxter robot) or single manipulators (i.e. Ur5 robot). These arms are usually used for recognizing clothes and then folding them or putting an item on the arm or on the head of a person.

Methods

This work provides a comprehensive review of the most relevant attempts/works of robotic dressing assistance with a focus on the control methodology used for dressing tasks. Three main areas of control methods for dressing tasks are proposed: Supervised Learning (SL), Learning from Demonstration (LfD), and Reinforcement Learning (RL). There are also other methods that cannot be classified into these three areas and hence they have been placed in the other methods section. This research was conducted within three databases: Scopus, Web of Science, and Google Scholar. Accurate exclusion criteria were applied to screen the 2594 articles found (at the end 39 articles were selected). For each work, an evaluation of the model is made.

Conclusion

Current research in cloth manipulation and dressing assistance focuses on learning-based robot control approach. Inferring the cloth state is integral to learning the manipulation and current research uses principles of Computer Vision to address the issue. This makes the larger problem of control robot based on learning data-intensive; therefore, a pressing need for standardized datasets representing different cloth shapes, types, materials, and human demonstrations (for LfD) exists. Simultaneously, efficient simulation capabilities, which closely model the deformation of clothes, are required to bridge the reality gap between the real-world and virtual environments for deploying the RL trial and error paradigm. Such powerful simulators are also vital to collect valuable data to train SL and LfD algorithms that will help reduce human workload.

Does the Personality of Consumers Influence the Assessment of the Experience of Interaction with Social Robots?

In recent years, in response to the effects of Covid-19, there has been an increase in the use of social robots in service organisations, as well as in the number of interactions between consumers and robots. However, it is not clear how consumers are valuing these experiences or what the main drivers that shape them are. Furthermore, it is an open research question whether these experiences undergone by consumers can be affected by their own personality. This study attempts to shed some light on these questions and, to do so, an experiment is proposed in which a sample of 378 participants evaluate a simulated front-office service experience delivered by a social robot. The authors investigate the underlying process that explains the experience and find that cognitive-functional factors, emphasising efficiency, have practically the same relevance as emotional factors, emphasising stimulation. In addition, this research identifies the personality traits of the participants and explores their moderating role in the evaluation of the experience. The results reveal that each personality trait, estimated between high and low poles, generates different responses in the evaluation of the experience.

Boundary work in value co-creation practices: the mediating role of cognitive assistants

Purpose

How to improve healthcare for the ageing population is attracting academia attention. Emerging technologies (i.e. robots and intelligent agents) look relevant. This paper aims to analyze the role of cognitive assistants as boundary objects in value co-creation practices. We include the perceptions of the main actors – patients, (in)formal caregivers, healthcare professionals – for a fuller network perspective to understand the potential overlap between boundary work and value co-creation practices.

Design/methodology/approach

We adopted a grounded approach to gain a contextual understanding design to effectively interpret context and meanings related to human–robot interactions. The study context concerns 21 health solutions that had embedded the Watson cognitive platform and its adoption by the youngest cohort (50–64-year-olds) of the ageing population.

Findings

The cognitive assistant acts as a boundary object by bridging actors, resources and activities. It enacts the boundary work of actors (both ageing and professional, caregivers, families) consisting of four main actions (automated dialoguing, augmented sharing, connected learning and multilayered trusting) that elicit two ageing value co-creation practices: empowering ageing actors in medical care and engaging ageing actors in a healthy lifestyle.

Originality/value

We frame the role of cognitive assistants as boundary objects enabling the boundary work of ageing actors for value co-creation. A cognitive assistant is an “object of activity” that mediates in actors' boundary work by offering novel resource interfaces and widening resource access and resourceness. The boundary work of ageing actors lies in a smarter resource integration that yields broader applications for augmented agency.

User Experience in Social Robots

Social robots are increasingly penetrating our daily lives. They are used in various domains, such as healthcare, education, business, industry, and culture. However, introducing this technology for use in conventional environments is not trivial. For users to accept social robots, a positive user experience is vital, and it should be considered as a critical part of the robots' development process. This may potentially lead to excessive use of social robots and strengthen their diffusion in society. The goal of this study is to summarize the extant literature that is focused on user experience in social robots, and to identify the challenges and benefits of UX evaluation in social robots. To achieve this goal, the authors carried out a systematic literature review that relies on PRISMA guidelines. Our findings revealed that the most common methods to evaluate UX in social robots are questionnaires and interviews. UX evaluations were found out to be beneficial in providing early feedback and consequently in handling errors at an early stage. However, despite the importance of UX in social robots, robot developers often neglect to set UX goals due to lack of knowledge or lack of time. This study emphasizes the need for robot developers to acquire the required theoretical and practical knowledge on how to perform a successful UX evaluation.

Social Telepresence Robots: A Narrative Review of Experiments Involving Older Adults before and during the COVID-19 Pandemic

Social isolation is a common phenomenon among the elderly. Retirement, widowhood, and increased prevalence of chronic diseases in this age group lead to a decline in social relationships, which in turn has adverse consequences on health and well-being. The coronavirus COVID-19 crisis worsened this situation, raising interest for mobile telepresence robots (MTR) that would help create, maintain, and strengthen social relationships. MTR are tools equipped with a camera, monitor, microphone, and speaker, with a body on wheels that allows for remote-controlled and sometimes autonomous movement aiming to provide easy access to assistance and networking services. We conducted a narrative review of literature describing experimental studies of MTR involving elderly people over the last 20 years, including during the COVID-19 period. The aim of this review was to examine whether MTR use was beneficial for reducing loneliness and social isolation among older adults at home and in health and care institutions and to examine the current benefits and barriers to their use and implementation. We screened 1754 references and included 24 research papers focusing on the usability, acceptability, and effectiveness of MTR. News reports on MTR use during the COVID-19 period were also examined. A qualitative, multidimensional analysis methodology inspired by a health technology assessment model was used to identify facilitating and limiting factors and investigate if and how MTR could reduce social isolation in elderly people. Reviewed studies provide encouraging evidence that MTR have potential in this regard, as experiments report positive feedback on MTR design and core functionalities. However, our analysis also points to specific technical, ergonomic, and ethical challenges that remain to be solved, highlighting the need for further multidimensional research on the design and impact of MTR interventions for older adults and building on new insights gained during the COVID-19 pandemic.

Robotic assistance for people with dementia: a viable option for the future?

INTRODUCTION

Demographic changes in society and fewer personnel working in healthcare services have resulted in an increase in the speed of development of safe, reliable robotic assistance technologies for patients with neurological diseases. This paper aims to advocate for the frailty of patients in light of the economic need for robotic assistance, discuss potential hazards, and outline related factors that influence positive outcomes.

AREAS COVERED

This article reviews the state of the art and perspectives regarding the use of robotics in older adults with dementia. We focus on current trends in the development of robotic technologies for these patients and discuss the potential hazards associated with the implementation of such cutting-edge technology in daily practice.

EXPERT OPINION

We envisage a gradual increase in the usage of robot-based devices for the management and support of patients with cognitive deficits. In particular, the introduction of artificial intelligence will enhance the functionality of these technologies, but also increase potential hazards resulting from human-robot interactions. The development of such technology must consider whether neurological syndromes are static or progressive. Progressive syndromes pose the biggest challenge since the functionality of robotic devices must adapt to patients changing cognitive and motor performance profiles.

Assistive robots to improve the independent living of older persons: results from a needs study

BACKGROUND

More than 70% of elderly people age 80 and older are experiencing problems in personal mobility. Assistive robotics can represent a concrete support providing also a support for caregivers, clinicians and nurses by reducing their burden.

METHODS

A total of 20 older people and 34 caregivers (formal and informal) were interviewed in Italy and the Netherlands to investigate and prioritize their needs concerning the personal mobility domains and their attitudes towards assistive robots. The data were analysed from a user point of view by means of thematic content analysis by underlying recurrent topics.

RESULTS

The results revealed four categories of needs from the perspective of the older individuals: instrumental needs, rehabilitation needs, personal safety and indoor activities of daily life. Additionally, the results underline how personal mobility issues influence different aspects of daily life. Complementarily, three categories of caregiver needs were also distinguished: instrumental needs, rehabilitation monitoring needs and checkup needs. The highest percentage of participants showed a positive expectation towards assistive robotics.

CONCLUSIONS

The results were clustered according to the robot abilities (i.e., motion, interaction, manipulation, decision support and perception abilities) as a list of functional and technical requirements that should be developed to address all the needs related to the personal mobility. Robotic developer teams that work in this context could take advantage of this research. Additionally, this work can be used as a basis for clinicians and nurses working in geriatric units to understand how the robots can support and enhance their work. Implications for rehabilitation The incidence of personal mobility limitations affects 35% of adults age 70 and older and 72% of people over 80 years of age. Assistive robots can support elderly people during daily tasks: they could promote their personal mobility acting as a supporting tool. The results of the needs analysis revealed four categories of needs from the perspective of the older individuals: instrumental needs, rehabilitation needs, personal safety, and indoor activities of daily life. Three categories of caregiver needs were also distinguished: instrumental needs, rehabilitation monitoring needs, and check-up needs.

A Survey of Behavioral Models for Social Robots

The cooperation between humans and robots is becoming increasingly important in our society. Consequently, there is a growing interest in the development of models that can enhance and enrich the interaction between humans and robots. A key challenge in the Human-Robot Interaction (HRI) field is to provide robots with cognitive and affective capabilities, by developing architectures that let them establish empathetic relationships with users. Over the last several years, multiple models were proposed to face this open-challenge. This work provides a survey of the most relevant attempts/works. In details, it offers an overview of the architectures present in literature focusing on three specific aspects of HRI: the development of adaptive behavioral models, the design of cognitive architectures, and the ability to establish empathy with the user. The research was conducted within two databases: Scopus and Web of Science. Accurate exclusion criteria were applied to screen the 4916 articles found. At the end, 56 articles were selected. For each work, an evaluation of the model is made. Pros and cons of each work are detailed by analyzing the aspects that can be improved to establish an enjoyable interaction between robots and users.