Healthcare robotics

Riek, Laurel D.

doi:10.1145/3127874

Cited by 221 publications

(140 citation statements)

References 24 publications

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“…Yet as the number of older people continues to grow, many homecare organisations face challenges in recruiting staff, and there is considerable concern about how quality care can be maintained. Care robots are frequently proposed as a solution to the problem [3][4][5]. Care robots are portrayed as a technological revolution in the sense that they allow for innovative applications in healthcare [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Technological Frames and Care Robots in Eldercare

Frennert

Aminoff

Östlund

2020

Int J of Soc Robotics

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Care robots are often portrayed as an exciting new technology for improving care practices. Whether these robots will be accepted and integrated into care work or not, is likely to be affected by the assumptions, expectations and understandings held by potential end users, such as frontline staff and the people that are cared for. This paper describes how the conceptual framework of technological frames was used to identify the nature of care robots, care robots in use and care robot strategy as shared group level assumptions, expectations and understandings of care robots among care staff and potential care receivers. Focus groups were conducted with 94 participants. These groups consisted of line managers, frontline care staff, older people and students training to become carers. The technological frame of the nature of care robots revealed two complementary components: care robots as a threat to the quality of care, and care robots as substitute for humans and human care, held together by imaginaries of care robots. The technological frame of care robots in use revealed aspects of prospective end-users' uncertainty of their ability to handle care robots, and their own perceived lack of competence and knowledge about care robots. In addition, the following potential criteria for successful use of care robots were identified: adequate training, incentives for usage (needs and motives), usability, accessibility and finances. The technological frame of care robot strategy was revealed as believed cost savings and staff reduction. The novelty of the results, and their relevance for science and practice, is derived from the theoretical framework which indicates that adoption of care robots will be dependent on how well societies succeed in collectively shaping congruent technological frames among different stakeholders and aligning technological development accordingly.

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Section: Introductionmentioning

confidence: 99%

Technological Frames and Care Robots in Eldercare

Frennert

Aminoff

Östlund

2020

Int J of Soc Robotics

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“…Most of these applications have shown promising results, where people feel encouraged and motivated to work along with robots in healthcare and rehabilitation environments [2,7]. However, most of these studies have been carried out in laboratory conditions with healthy patients or during short time interventions [8], which do not allow to have a complete perspective of the interaction between humans and robots, and it is often neglected several factors, such as novelty effect [9] and the adaptation of the technology [10]. In fact, only a few number of studies have explored long-term interactions with social robotic agents [11,12], where results report a considerable reduction in people's interest and motivation compared to the first interaction [8,13,14].…”

Section: Introductionmentioning

confidence: 99%

Expectation vs. Reality: Attitudes Towards a Socially Assistive Robot in Cardiac Rehabilitation

et al. 2019

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Currently, Social Assistive Robotics (SAR) is widely explored in different areas and scenarios. In cardiac rehabilitation, SAR has been recently implemented as a tool to improve the quality of the procedures and support patients to boost their performance. As cardiac rehabilitation comprises numerous sessions, such systems must guarantee to be effective in the long term. Therefore, to achieve this goal, it is important to understand how users, namely patients and clinicians who mostly know the needs and the therapy environment, perceive this technology. In this context, this paper presents the assessment of the attitudes towards a social robot in order to evaluate the expectation of potential new users, and perception of users who interacted with the social robot during a period of 18 weeks performing cardiac rehabilitation. A total of 43 participants (28 patients and 15 clinicians) were included in the study, and acceptance and perception factors were evaluated through a modified UTAUT questionnaire model and open discussion sessions. Results show that 75% of patients have positive thoughts regarding the usefulness, utility, safety, and trust perceived of a social robot, and 80% of clinicians consider that the robot is a useful tool for cardiac rehabilitation. Similarly, a more positive perception was noticed after the users interacted with the robot. Furthermore, this perception study allows the enhancement of the social model of interaction in the future, aiming to provide a more natural interaction trough personalized features, increasing social abilities and engagement of the users during the therapy.

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“…sum jjW j jj 2 (1) where N the number of samples, L the number of layers, W j the weights of lth layer, and L x i ; y i ð Þ the negative conditional log-likelihood of training data.…”

Section: Cnn-svr Modelmentioning

confidence: 99%

“…In recent years, many assisted systems for health care have been clinical interventions [1]. As a new therapy mode in ASD rehabilitation, assisted system is applied to autism children's coordination and interaction abilities training for communicating with neurotypical people naturally [2].…”

Section: Introductionmentioning

confidence: 99%

Assisted therapeutic system based on reinforcement learning for children with autism

Xie

et al. 2019

Computer Assisted Surgery

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2019)Assisted therapeutic system based on reinforcement learning for children with autism, Computer Assisted Surgery, 24:sup2, 94-104, ABSTRACT Assisted therapy is increasingly used in autism spectrum disorders (ASD) for improving social interaction and communication skills in recent years. A lot of studies have proven that the form of interactive games for therapy has a good effect on children with autism. Thus, our study provided an assisted therapeutic system based on Reinforcement Learning (RL) for children with ASD, which has five interactive subgames. As is well known, it is necessary to establish and maintain compelling interactions in therapeutic process. Therefore, we aim to adjust the interactive content according to the emotions of children with autism. However, due to the atypical and unusually differences in children with autism, most systems are based on off-line training of small samples of individuals and online recognition, so the existing assisted systems are limited in their ability to automatically update system parameters of new mappings. The integration of RL and Convolutional Neural Network (CNN)-Support Vector Regression (SVR) was used to deal with the updating online of prediction model's weights. The normalized emotion labels were evaluated by the therapists. Eleven children with autism as subjects were invited in this experiment and captured facial video images. The experiment lasted for five weeks of intermittent assisted therapy, and the results were evaluated for the system and the therapy effect. Finally, we achieved a general reduction in the root mean square error of the model prediction results and labels. Although there is no significant difference in Social Responsiveness Scale (SRS) scores before and after assisted therapy (p value ¼ 0.60), in individual subjects (Sub. 1, Sub. 2 and Sub.3), the SRS total score is significantly reduced (Average drop of 19 points). These results demonstrate the effectiveness of prediction model based on RL and show the feasibility of assisted therapeutic system in children with autism.

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Healthcare robotics

Abstract: Healthcare robotics can provide health and wellness support to billions of people.

Cited by 221 publications

References 24 publications

Technological Frames and Care Robots in Eldercare

Technological Frames and Care Robots in Eldercare

Expectation vs. Reality: Attitudes Towards a Socially Assistive Robot in Cardiac Rehabilitation

Assisted therapeutic system based on reinforcement learning for children with autism

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