Assessment of personal care and medical robots from older adults' perspective

Acceptance of social assistant robots for the older adults living in the community in China

BACKGROUND

Social assistant robots (SARs) are an important part of providing high quality health and social care for older people, and are an effective measure to promote the development of smart aging. Therefore, it is important to understand the factors that influence the acceptance of assistive robots by older adults.

PURPOSE

To investigate the acceptance of SARs for older adults living in the community and explore its influencing factors.

METHODS

207 elderly was invited to answer a questionnaire after watching a SAR video and discussing it. Participants' characteristics, physical health status, general self-efficacy, personality trait and acceptance toward SARs were recorded and analyzed using multiple linear regression analysis.

RESULTS

showed that the degree of acceptance among older adults living in the community was moderate(2.55±0.86), and the acceptance rate was 51.0%. Whether to use mobile devices(smartphones, computers, robots), the experience of using mobile service devices, perceived usefulness, perceived enjoyment, perceived ease of use and attitude were the main affecting factors (P<0.05).

CONCLUSIONS

The elderly Chinese in the community have a low acceptance of SARs. The higher the perceived usefulness, perceived enjoyment and perceived ease of use, the more positive attitude to using. The elderly who has the experience of using mobile service devices have a higher acceptance of SARs.

Application of Artificial Intelligence in Geriatric Care: Bibliometric Analysis

BACKGROUND

Artificial intelligence (AI) can improve the health and well-being of older adults and has the potential to assist and improve nursing care. In recent years, research in this area has been increasing. Therefore, it is necessary to understand the status of development and main research hotspots and identify the main contributors and their relationships in the application of AI in geriatric care via bibliometric analysis.

OBJECTIVE

Using bibliometric analysis, this study aims to examine the current research hotspots and collaborative networks in the application of AI in geriatric care over the past 23 years.

METHODS

The Web of Science Core Collection database was used as a source. All publications from inception to August 2022 were downloaded. The external characteristics of the publications were summarized through HistCite and the Web of Science. Keywords and collaborative networks were analyzed using VOSviewers and Citespace.

RESULTS

We obtained a total of 230 publications. The works originated in 499 institutions in 39 countries, were published in 124 journals, and were written by 1216 authors. Publications increased sharply from 2014 to 2022, accounting for 90.87% (209/230) of all publications. The United States and the International Journal of Social Robotics had the highest number of publications on this topic. The 1216 authors were divided into 5 main clusters. Among the 230 publications, 4 clusters were modeled, including Alzheimer disease, aged care, acceptance, and the surveillance and treatment of diseases. Machine learning, deep learning, and rehabilitation had also become recent research hotspots.

CONCLUSIONS

Research on the application of AI in geriatric care has developed rapidly. The development of research and cooperation among countries/regions and institutions are limited. In the future, strengthening the cooperation and communication between different countries/regions and institutions may further drive this field's development. This study provides researchers with the information necessary to understand the current state, collaborative networks, and main research hotspots of the field. In addition, our results suggest a series of recommendations for future research.

Exploring home health-care robots adoption in Malaysia: extending the UTAUT model

Purpose

This study aims to examine the possible factors affecting Malaysians’ intention to adopt new technology such as home health-care robots (HHRs) based on the extended unified theory of acceptance and use of technology (UTAUT) model. The variable price, awareness and alternative attractiveness were added since HHRs is a new technology in Malaysia.

Design/methodology/approach

This study collected the self-administered questionnaire from 316 respondents who are currently taking care of elderly or disabled people at home. The UTAUT variables, price and awareness were the predictors, and the intention to adopt HHRs was the independent variable, with alternative attractiveness as the moderator. The partial least squares structural equation modeling was used for analysis of the measurement model and the structural model of this study.

Findings

The results show that performance expectancy, social influence, facilitating conditions, price and awareness significantly and positively affect Malaysians’ intention to adopt HHRs. Alternative attractiveness moderates the relationship between price and intention to adopt HHRs.

Research limitations/implications

The findings provide insights to marketers, managers and policymakers in identifying the right strategies to promote HHRs and thus, solving the problem of scarcity in caretakers for elderly and disabled people.

Originality/value

This study adds value to the current literature by integrating price and awareness constructs with the UTAUT model. This study also examines the moderating effect of alternative attractiveness on the intention to adopt HHRs, which is still limited but significant for developing nations.

Factors Influencing Intention to Technological Use in Older Adults. The TAM Model Aplication

The use of digital technology by older adults has improved in recent years in response to the need for their functional adaptation to an increasingly technological social context. Understanding this type of technological adaptation has recently become an important field of inquiry in both social and gerontological studies. Working within this framework, the aim of this study is to identify the main determinants that influence the intention of older people to use digital technology in their daily lives, using the Technological Acceptance Model. A study was carried out with the participation of 1155 people over 65 years of age in Spain. Confirmatory Factor Analysis and structural equation models (SEM) were performed. The results show that the TAM is a useful model to explain the intention of older adults to use Digital Technology, showing a high predictive power, highlighting Perceived Usefulness and Perceived Ease of Use as the main predictor variables.

Convolution-Based Encoding of Depth Images for Transfer Learning in RGB-D Scene Classification

Classification of indoor environments is a challenging problem. The availability of low-cost depth sensors has opened up a new research area of using depth information in addition to color image (RGB) data for scene understanding. Transfer learning of deep convolutional networks with pairs of RGB and depth (RGB-D) images has to deal with integrating these two modalities. Single-channel depth images are often converted to three-channel images by extracting horizontal disparity, height above ground, and the angle of the pixel’s local surface normal (HHA) to apply transfer learning using networks trained on the Places365 dataset. The high computational cost of HHA encoding can be a major disadvantage for the real-time prediction of scenes, although this may be less important during the training phase. We propose a new, computationally efficient encoding method that can be integrated with any convolutional neural network. We show that our encoding approach performs equally well or better in a multimodal transfer learning setup for scene classification. Our encoding is implemented in a customized and pretrained VGG16 Net. We address the class imbalance problem seen in the image dataset using a method based on the synthetic minority oversampling technique (SMOTE) at the feature level. With appropriate image augmentation and fine-tuning, our network achieves scene classification accuracy comparable to that of other state-of-the-art architectures.

Robots in Healthcare? What Patients Say

In this paper, we analyse patients’ perspectives on the introduction of artificial intelligence (AI) and robotic systems in healthcare. Based on citizens’ experiences when hospitalised for COVID-19, we explore how the opinions and concerns regarding healthcare automation could not be disassociated from a context of high pressure on the health system and lack of resources, and a political discourse on AI and robotics; a situation intensified by the pandemic. Thus, through the analysis of a set of interviews, a series of issues are identified that revolve around the following: the empirical effects of imagined robots, the vivid experience of citizens with the care crisis, the discomfort of the ineffective, the virtualised care assemblages, the human-based face-to-face relationships, and the automatisation of healthcare tasks. In light of these results, we show the variability in patients’ perspectives on AI and robotic systems and explain it by distinguishing two interpretive repertoires that account for different views and opinions: a well-being repertoire and a responsibility repertoire. Both interpretative repertoires are relevant in order to grasp the complexity of citizens’ approaches to automatisation of healthcare. Attending to both allows us to move beyond the dominant (political) discourse of technology markets as the only way to respond to healthcare challenges. Thus, we can analyse and integrate patients’ perspectives to develop AI and robotic systems in healthcare to serve citizens’ needs and collective well-being.

Development and usability evaluation of a bedside robot system for inpatients

BACKGROUND

Many inpatients become anxious or frightened about scheduled treatment processes, and medical staff do not have sufficient time to provide emotional support. The recent advancement of information and communications technology (ICT) and the use of artificial intelligence (AI), including robots, in the health care field is being put to the test.

OBJECTIVE

This study aimed to develop a bedside robot system to deliver information and provide emotional support to inpatients and to evaluate the usability and perceptions of the developed robot.

METHODS

The first stage was accomplished by deriving essential functions from the results of user demand surveys on robots and by implementing a prototype by mapping each essential function to the robot's hardware and software. For the second stage, the robot was assessed for usability and perceptions in a simulation center, a hospital-like environment, by 10 nurses, 10 inpatients, and family caregivers. Usability and perception were evaluated using the think-aloud method, a survey, and individual interviews.

RESULTS

Based on the usability evaluation, the perceived usefulness, ease of use, and satisfaction were 5.28 ± 1.27 points, 5.42 ± 1.55 points, and 5.27 ± 1.46 points out of 7, respectively. It was found that overall, the robot was positively perceived by participants. As a result of the qualitative data analysis, the participants perceived the robot as an object that had the positive effect of providing emotional support through communication.

CONCLUSIONS

The bedside robot in this study, which incorporated human-robot interaction (HRI) technology, is an alternative suited to the new normal era that will contribute to ensuring that patients have more self-directed hospital stays as well as emotional support through information delivery and communication.

Older adults' experiences with and perceptions of the use of socially assistive robots in aged care: A systematic review of quantitative evidence

BACKGROUND

Socially assistive robots (SARs) are created to meet challenges of the global increase of older adults. SARs are autonomous embodied technologies, equipped with auditory and visual faculties, enabling them to interact with users while performing assistive roles. Despite studies focusing on older adults' experiences with and perceptions of SARs, it remains unclear what these encompass.

OBJECTIVE

To gain insight into common aspects of older adults' experiences with and perceptions of SAR use in aged care, the relevant quantitative research literature was reviewed and synthesized.

METHODS

Six electronic databases were searched using detailed search strings. Applying pre-specified inclusion and exclusion criteria resulted in 23 articles to be included. Full texts were analyzed thematically, and graphs were developed to facilitate comparisons.

RESULTS

Six main themes related to older adults' experiences with and perceptions of SAR use were identified: (1) general attitudes toward SARs, (2) feelings about SARs, (3) perceived usefulness and perceived ease of use of SARs, (4) intention to use SARs, (5) tasks of SARs, (6) SARs' appearances. Ethical issues linked to SARs were barely described in the studies.

CONCLUSION

Older adults are relatively open-minded about SARs, generally feeling comfortable with at least some aspects of them, and intend to use SARs in the future, especially for physical assistive functions. Thus, SARs may meet some of older ones' needs. Although the quantitative evidence contributes to gaining insight in older adults' experiences with and perceptions of SARs, social contextualization is necessary to understand their full meaning.

Learning-Enabled Robotic Assistive Support: Understanding Older Adult Opinions and Comparing Them to Younger Adult Opinions

Background

As older adults age, they may require assistance completing activities of daily living (ADLs). Robotic assistance can offset healthcare costs and allow older adults to preserve their autonomy. Younger adults are often involved in the design and purchase of these robotic technologies, and must take into account the needs and expectations of the target population (i.e., older adults) to create a robot that the end-user will adopt.

Research Aim/Questions

This study evaluated the opinions of both younger and older adults regarding the design and performance of the Robot Activity Support (RAS) system. It is important to understand points of agreement and divergence between these populations' perspectives so that effective robotic aids are created for older adults.

Methods

Fifty-two younger and older adults completed three scripted tasks with the RAS robot in a smart home environment. Each participant made task errors to cue the robot to offer help via three prompt modalities (guide to the object, video of forgotten step, and video of the full task). After interacting with the robot, participants completed questionnaires to evaluate their opinions of and satisfaction with the robot.

Results

There were no differences between younger and older adults' perceptions of the robot across a variety of factors (e.g., likability, cognitive demand), with both age groups expressing generally neutral opinions. Both groups rated the Full Video prompt as least helpful, effective, and liked. Participants recommended the robot's response accuracy, movement speed, alerting style and system flexibility be improved. Younger adults overestimated how much older adults would want a robot like this.

Conclusions

This study underscores the importance of testing technology with the end-user, as older adults were less interested in having a similar robot in their home than younger counterparts expected. Future studies will show if older adults' opinions can be improved after making the recommended changes.

Ethical perceptions towards real-world use of companion robots with older people and people with dementia: survey opinions among younger adults

BACKGROUND

Use of companion robots may reduce older people's depression, loneliness and agitation. This benefit has to be contrasted against possible ethical concerns raised by philosophers in the field around issues such as deceit, infantilisation, reduced human contact and accountability. Research directly assessing prevalence of such concerns among relevant stakeholders, however, remains limited, even though their views clearly have relevance in the debate. For example, any discrepancies between ethicists and stakeholders might in itself be a relevant ethical consideration while concerns perceived by stakeholders might identify immediate barriers to successful implementation.

METHODS

We surveyed 67 younger adults after they had live interactions with companion robot pets while attending an exhibition on intimacy, including the context of intimacy for older people. We asked about their perceptions of ethical issues. Participants generally had older family members, some with dementia.

RESULTS

Most participants (40/67, 60%) reported having no ethical concerns towards companion robot use when surveyed with an open question. Twenty (30%) had some concern, the most common being reduced human contact (10%), followed by deception (6%). However, when choosing from a list, the issue perceived as most concerning was equality of access to devices based on socioeconomic factors (m = 4.72 on a scale 1-7), exceeding more commonly hypothesized issues such as infantilising (m = 3.45), and deception (m = 3.44). The lowest-scoring issues were potential for injury or harm (m = 2.38) and privacy concerns (m = 2.17). Over half (39/67 (58%)) would have bought a device for an older relative. Cost was a common reason for choosing not to purchase a device.

CONCLUSIONS

Although a relatively small study, we demonstrated discrepancies between ethical concerns raised in the philosophical literature and those likely to make the decision to buy a companion robot. Such discrepancies, between philosophers and 'end-users' in care of older people, and in methods of ascertainment, are worthy of further empirical research and discussion. Our participants were more concerned about economic issues and equality of access, an important consideration for those involved with care of older people. On the other hand the concerns proposed by ethicists seem unlikely to be a barrier to use of companion robots.

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.

Cyber-physical Support of Daily Activities

This article introduces RAS, a cyber-physical system that supports individuals with memory limitations to perform daily activities in their own homes. RAS represents a partnership between a smart home, a robot, and software agents. When smart home residents perform activities, RAS senses their movement in the space and identifies the current activity. RAS tracks activity steps to detect omission errors. When an error is detected, the RAS robot finds and approaches the human with an offer of assistance. Assistance consists of playing a video recording of the entire activity, showing the omitted activity step, or guiding the resident to the object that is required for the current step. We evaluated RAS performance for 54 participants performing three scripted activities in a smart home testbed and for 2 participants using the system over multiple days in their own homes. In the testbed experiment, activity errors were detected with a sensitivity of 0.955 and specificity of 0.992. RAS assistance was performed successfully with a rate of 0.600. In the in-home experiments, activity errors were detected with a combined sensitivity of 0.905 and a combined specificity of 0.988. RAS assistance was performed successfully for the in-home experiments with a rate of 0.830.

Ethics and Occupational Health in the Contemporary World of Work

The last two decades have seen increasing attention to professional ethics in the field of occupational health in industrialized and developing countries, partly reflecting the changing world of work, demographic shifts and new technologies. These changes have led to the revisiting of traditional ethical principles and the emergence of ethical issues related to occupational health. This article looks at the problems raised by these ethical concerns and proposes some solutions. We revised the existing literature on the ethical conflict in occupational health in order to identifying drivers and barriers for correct professional ethics. The ethical choices are not only based on balanced risk and benefit assessment for various stakeholders, but there are a number of deontological aspects as well that go beyond the mere benefit domains. There is still no systematic approach for analysing the true extent of these issues and their solutions.

The Application of Medical Artificial Intelligence Technology in Rural Areas of Developing Countries

Background: Artificial intelligence (AI) is a rapidly developing computer technology that has begun to be widely used in the medical field to improve the professional level and efficiency of clinical work, in addition to avoiding medical errors. In developing countries, the inequality between urban and rural health services is a serious problem, of which the shortage of qualified healthcare providers is the major cause of the unavailability and low quality of healthcare in rural areas. Some studies have shown that the application of computer-assisted or AI medical techniques could improve healthcare outcomes in rural areas of developing countries. Therefore, the development of suitable medical AI technology for rural areas is worth discussing and probing. Methods: This article reviews and discusses the literature concerning the prospects of medical AI technology, the inequity of healthcare, and the application of computer-assisted or AI medical techniques in rural areas of developing countries. Results: Medical AI technology not only could improve physicians' efficiency and quality of medical services, but other health workers could also be trained to use this technique to compensate for the lack of physicians, thereby improving the availability of healthcare access and medical service quality. This article proposes a multilevel medical AI service network, including a frontline medical AI system (basic level), regional medical AI support centers (middle levels), and a national medical AI development center (top level). Conclusion: The promotion of medical AI technology in rural areas of developing countries might be one means of alleviating the inequality between urban and rural health services. The establishment of a multilevel medical AI service network system may be a solution.