Use Of Assistive Robots Research Articles

Disability 4.0: bioethical considerations on the use of embodied artificial intelligence.

Robotics and artificial intelligence have marked the beginning of a new era in the care and integration of people with disabilities, helping to promote their independence, autonomy and social participation. In this area, bioethical reflection assumes a key role at anthropological, ethical, legal and socio-political levels. However, there is currently a substantial diversity of opinions and ethical arguments, as well as a lack of consensus on the use of assistive robots, while the focus remains predominantly on the usability of products. The article presents a bioethical analysis that highlights the risk arising from using embodied artificial intelligence according to a functionalist model. Failure to recognize disability as the result of a complex interplay between health, personal and situational factors could result in potential damage to the intrinsic dignity of the person and human relations with healthcare workers. Furthermore, the danger of discrimination in accessing these new technologies is highlighted, emphasizing the need for an ethical approach that considers the social and moral implications of implementing embodied AI in the field of rehabilitation.

User-oriented needs assessment of the potential use of assistive robots in direct nursing care: A mixed methods study

User-oriented needs assessment of the potential use of assistive robots in direct nursing care: A mixed methods study Abstract. Background: So far, hardly any robots have been used in nursing that take over patient-related activities and thereby reduce the physical strain on the caregivers. Using user-centered design approaches, the interdisciplinary project "PfleKoRo" was therefore developing a robotic assistance system that can be used in the direct care of bedridden patients requiring intensive or very intensive care. Aim: The aim of this study was to identify nursing activities with the greatest support potential for an assistant robot for the direct care of bedridden patients. Method: Focus groups (n = 3) with nursing professionals (n = 14) from acute and long-term care were conducted first in an explorative mixed method design and then evaluated by means of content analysis. A selection of nursing activities was then prioritized by the participants of the focus groups (n = 10) with regard to their potential for support from an assistant robot in a standardized survey. Results: The highest priority was given to turning and holding patients in a lateral position as well as holding their legs in order to perform nursing tasks. Further support was needed, among other things, for repositioning the patient to the head of the bed and for tasks such as the transfer of patients. Conclusion: Turning patients and holding them in a lateral position as well as holding the leg are seen as target activities with the greatest support potential for "PfleKoRo", presenting the starting point for further development.

Estimation of knee joint movement using single-channel sEMG signals with a feature-guided convolutional neural network

Estimating human motion intention, such as intent joint torque and movement, plays a crucial role in assistive robotics for ensuring efficient and safe human-robot interaction. For coupled human-robot systems, surface electromyography (sEMG) signal has been proven as an effective means for estimating human's intended movements. Usually, joint movement estimation uses sEMG signals measured from multiple muscles and needs many sEMG sensors placed on the human body, which may cause discomfort or result in mechanical/signal interference from wearable robots/environment during long-term routine use. Although the muscle synergy principle implies that it is possible to estimate human motion using sEMG signals from even one signal muscle, few studies investigated the feasibility of continuous motion estimation based on single-channel sEMG. In this study, a feature-guided convolutional neural network (FG-CNN) has been proposed to estimate human knee joint movement using single-channel sEMG. In the proposed FG-CNN, several handcrafted features have been fused into a CNN model to guide CNN feature extraction, and both handcrafted and CNN-extracted features were applied to a regression model, i.e., random forest regression, to estimate knee joint movements. Experiments with 8 healthy subjects were carried out, and sEMG signals measured from 6 muscles, i.e., vastus lateralis, vastus medialis, biceps femoris, semitendinosus, lateral or medial gastrocnemius (LG or MG), were separately evaluated for knee joint estimation using the proposed method. The experimental results demonstrated that the proposed FG-CNN method with single-channel sEMG signals from LG or MG can effectively estimate human knee joint movements. The average correlation coefficient between the measured and the estimated knee joint movements is 0.858 ± 0.085 for LG and 0.856 ± 0.057 for MG. Meanwhile, comparative studies showed that the combined handcrafted-CNN features outperform either the handcrafted features or the CNN features; the performance of the proposed signal-channel sEMG-based FG-CNN method is comparable to those of the traditional multi-channel sEMG-based methods. The outcomes of this study enable the possibility of developing a single-channel sEMG-based human-robot interface for knee joint movement estimation, which can facilitate the routine use of assistive robots.

Assistive Healthcare Robotics – Challenges in Nursing Service Innovation: Critical Review

Healthcare robots assist older people and caregivers. Many scientists and researchers have been looking at the use of robotic technology to help not only elderly people but also their care providers. Through a review of the literature and an in-depth study of published papers, we include a timely overview of care robotics. In this study, we review what we know about the use of assistive robots in the elderly care context, their benefits and potential challenges. These humanoid resources offer a range of physical, cognitive, and social tasks in the aim of improving health outcomes. Service Science calls for understanding complex service systems, our Sociotechnical system (STS) lens applied to the use of robotics in the nursing function aims at learning the underlying trajectories of socio-technical dynamics within the nursing service system and the complexity introduced by their humanoid counterpart. This presents a significant contribution to Service Science. In essence, the research introduces the STS lens to understand the interaction between human and machine in the nursing ecosystem, while proposing learnings on a better design in practice. We focus on the current and potential future challenges of healthcare robotics as well as how such technology can help healthy aging, healthcare staff, especially nurses, and our healthcare system as a whole. We conclude that, despite the potential advantages, the adoption of care robots is still shy. Using the lens of the sociotechnical perspective and concepts of service innovation roadmaps, we pave the way for identifying factors of adoption that may influence the proliferation of care robots.

Use and usability of software verification methods to detect behaviour interference when teaching an assistive home companion robot: A proof-of-concept study

Abstract When studying the use of assistive robots in home environments, and especially how such robots can be personalised to meet the needs of the resident, key concerns are issues related to behaviour verification, behaviour interference and safety. Here, personalisation refers to the teaching of new robot behaviours by both technical and non-technical end users. In this article, we consider the issue of behaviour interference caused by situations where newly taught robot behaviours may affect or be affected by existing behaviours and thus, those behaviours will not or might not ever be executed. We focus in particular on how such situations can be detected and presented to the user. We describe the human–robot behaviour teaching system that we developed as well as the formal behaviour checking methods used. The online use of behaviour checking is demonstrated, based on static analysis of behaviours during the operation of the robot, and evaluated in a user study. We conducted a proof-of-concept human–robot interaction study with an autonomous, multi-purpose robot operating within a smart home environment. Twenty participants individually taught the robot behaviours according to instructions they were given, some of which caused interference with other behaviours. A mechanism for detecting behaviour interference provided feedback to participants and suggestions on how to resolve those conflicts. We assessed the participants’ views on detected interference as reported by the behaviour teaching system. Results indicate that interference warnings given to participants during teaching provoked an understanding of the issue. We did not find a significant influence of participants’ technical background. These results highlight a promising path towards verification and validation of assistive home companion robots that allow end-user personalisation.

Role of Assistive Robots in the Care of Older People: Survey Study Among Medical and Nursing Students.

BackgroundPopulations are aging at an alarming rate in many countries around the world. There has been not only a decrease in the number of births and an increase in the percentage of older people, but also an increase in the number of people living alone. There is growing demand for specialist medical care and daily care with the number of people who can act as caregivers reducing. The use of assistive robots can, at least partially, solve these problems.ObjectiveThe purpose of this study was to examine the opinions of future health care professionals (medical and nursing students) regarding the use of assistive robots in the care of older people.MethodsThe study was conducted with a group of 178 students from Poznan University of Medical Sciences, Poznań, Poland (110 nursing students and 68 medical students), using the Users’ Needs, Requirements, and Abilities Questionnaire.ResultsThe participants of this study believed that assistive robots should, first of all, remind older people to take medication regularly, ensure their safety, monitor their health status and environment, provide cognitive training, and encourage them to maintain physical activity. In the students’ opinion, the robot should not be an older person’s companion but only act as an assistant. Nursing students had significantly higher scores than medical students in several statements concerning everyday use of robots, including reminding about meals (P=.03), monitoring the environment (P=.001), providing advice about a healthy diet (P=.04), monitoring the intake of food and fluids (P=.02), and automatic “switch on” function (P=.02). Nursing students were more focused on the social functions of robots, including encouraging contact with friends (P=.003) and reducing the sense of loneliness and improving mood (P=.008). Medical students were more aware of privacy issues in the statement concerning the possibility of switching off the robot in specific situations (P=.01).ConclusionsOur study revealed a generally positive attitude of future doctors and nurses toward assistive robots, which can have an impact on their acceptance by older adults. In the future, medical professionals could help their patients to choose the right robots (and necessary functions) that are best suited to their needs. However, this would require expanding the curriculum to include the issues of gerontechnology.

Could Robots Help Older People with Age-Related Nutritional Problems? Opinions of Potential Users.

Background: The rapid development of new technologies has recently raised interest in the use of assistive robots in the care of older people. The success or failure of robots’ implementation is mediated by their acceptance by users. The aim of the study was to answer the question of how both older people and caregivers perceive the possibility of using an assistive robot for nutritional support. Methods: Opinions of 252 respondents (126 older—aged 65 and above; 126 younger ones—aged below 65) from five European countries were collected using the Users’ Needs, Requirements, and Abilities Questionnaire. Results: The majority of participants positively assessed the possibility of using a robot to improve the diet of older people by giving advice on healthy eating or monitoring the amount of food consumed by the owner. An age-related difference was observed, as older people less frequently accepted the reminding of meal times or drinking liquids than younger participants. Four key categories related to the robot’s role in the diet of older people were identified: matching the needs, robot’s characteristics, ethical issues and technical/financial issues. Conclusions: Our preliminary research has shown a positive approach to robots in the context of their nutrition-related aspects. An indication has been made of the need to include older people and other stakeholders in the process of designing these functionalities and modeling human–robot interactions based on communication theories.

Technology Acceptance and User-Centred Design of Assistive Exoskeletons for Older Adults: A Commentary

Assistive robots are emerging as technologies that enable older adults to perform activities of daily living with autonomy. Exoskeletons are a subset of assistive robots that can support mobility. Perceptions and acceptance of these technologies require understanding in a user-centred design context to ensure optimum experience and adoption by as broad a spectrum of older adults as possible. The adoption and use of assistive robots for activities of daily living (ADL) by older adults is poorly understood. Older adult acceptance of technology is affected by numerous factors, such as perceptions and stigma associated with dependency and ageing. Assistive technology (AT) models provide theoretical frameworks that inform decision-making in relation to assistive devices for people with disabilities. However, technology acceptance models (TAMs) are theoretical explanations of factors that influence why users adopt some technologies and not others. Recent models have emerged specifically describing technology acceptance by older adults. In the context of exoskeleton design, these models could influence design approaches. This article will discuss a selection of TAMs, displaying a chronology that highlights their evolution, and two prioritised TAMs—Almere and the senior technology acceptance model (STAM)—that merit consideration when attempting to understand acceptance and use of assistive robots by older adults.

RAPP: A Robotic-Oriented Ecosystem for Delivering Smart User Empowering Applications for Older People

It is a general truth that increase of age is associated with a level of mental and physical decline but unfortunately the former are often accompanied by social exclusion leading to marginalization and eventually further acceleration of the aging process. A new approach in alleviating the social exclusion of older people involves the use of assistive robots. As robots rapidly invade everyday life, the need of new software paradigms in order to address the user's unique needs becomes critical. In this paper we present a novel architectural design, the RAPP [a software platform to deliver smart, user empowering robotic applications (RApps)] framework that attempts to address this issue. The proposed framework has been designed in a cloud-based approach, integrating robotic devices and their respective applications. We aim to facilitate seamless development of RApps compatible with a wide range of supported robots and available to the public through a unified online store.

“Teach Me–Show Me”—End-User Personalization of a Smart Home and Companion Robot

Care issues and costs associated with an increasing elderly population are becoming a major concern for many countries. The use of assistive robots in “smart-home” environments has been suggested as a possible partial solution to these concerns. A challenge is the personalization of the robot to meet the changing needs of the elderly person over time. One approach is to allow the elderly person, or their carers or relatives, to make the robot learn activities in the smart home and teach it to carry out behaviors in response to these activities. The overriding premise being that such teaching is both intuitive and “nontechnical.” To evaluate these issues, a commercially available autonomous robot has been deployed in a fully sensorized but otherwise ordinary suburban house. We describe the design approach to the teaching, learning, robot, and smart home systems as an integrated unit and present results from an evaluation of the teaching component with 20 participants and a preliminary evaluation of the learning component with three participants in a human–robot interaction experiment. Participants reported findings using a system usability scale and ad-hoc Likert questionnaires. Results indicated that participants thought that this approach to robot personalization was easy to use, useful, and that they would be capable of using it in real-life situations both for themselves and for others.

The Design of an Expressive Humanlike Socially Assistive Robot

It is anticipated that the use of assistive robots will be one of the most important service applications of robotic systems of the future. In this paper, the development of a unique noncontact socially assistive robot consisting of a humanlike demeanor is presented for utilization in hospital wards and nursing∕veteran homes to study its role and impact on the well-being of patients, addressing patient’s needs and its overall effect on the quality of patient care. The robot will be an embodied entity that will participate in hands-off noncontact social interaction with a patient during the convalescence, rehabilitation, or end-of-life care stage. The robot has been designed as a platform to incorporate the three design parameters of embodiment, emotion, and nonverbal communication to encourage natural human-robot interactions. Herein, we present the overall mechanical design of the socially assistive robot focusing mainly on the development of the actuation system of the face, head, and upper body. In particular, we propose the development of a unique muscle actuation mechanism for the robotic face to allow for the display of rich facial expressions during social assistive interaction scenarios. The novelty of the actuation system is in its use of the dependency of facial muscle activity to minimize the number of individual actuators required to control the robotic face.

Assistive Robots in Health Care Settings

Excellence in patient care is achieved through the very latest in technological advancements such as assistive robots. The purpose of this article is to review the literature on the use of assistive robots in various health care settings. The article includes a discussion of the strengths and limitations for noninteractive and interactive robots in health care and a summary of the implications for practice.