Expectations and Perceptions of Healthcare Professionals for Robot Deployment in Hospital Environments During the COVID-19 Pandemic

Advances in the Application of AI Robots in Critical Care: Scoping Review

BACKGROUND

In recent epochs, the field of critical medicine has experienced significant advancements due to the integration of artificial intelligence (AI). Specifically, AI robots have evolved from theoretical concepts to being actively implemented in clinical trials and applications. The intensive care unit (ICU), known for its reliance on a vast amount of medical information, presents a promising avenue for the deployment of robotic AI, anticipated to bring substantial improvements to patient care.

OBJECTIVE

This review aims to comprehensively summarize the current state of AI robots in the field of critical care by searching for previous studies, developments, and applications of AI robots related to ICU wards. In addition, it seeks to address the ethical challenges arising from their use, including concerns related to safety, patient privacy, responsibility delineation, and cost-benefit analysis.

METHODS

Following the scoping review framework proposed by Arksey and O'Malley and the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we conducted a scoping review to delineate the breadth of research in this field of AI robots in ICU and reported the findings. The literature search was carried out on May 1, 2023, across 3 databases: PubMed, Embase, and the IEEE Xplore Digital Library. Eligible publications were initially screened based on their titles and abstracts. Publications that passed the preliminary screening underwent a comprehensive review. Various research characteristics were extracted, summarized, and analyzed from the final publications.

RESULTS

Of the 5908 publications screened, 77 (1.3%) underwent a full review. These studies collectively spanned 21 ICU robotics projects, encompassing their system development and testing, clinical trials, and approval processes. Upon an expert-reviewed classification framework, these were categorized into 5 main types: therapeutic assistance robots, nursing assistance robots, rehabilitation assistance robots, telepresence robots, and logistics and disinfection robots. Most of these are already widely deployed and commercialized in ICUs, although a select few remain under testing. All robotic systems and tools are engineered to deliver more personalized, convenient, and intelligent medical services to patients in the ICU, concurrently aiming to reduce the substantial workload on ICU medical staff and promote therapeutic and care procedures. This review further explored the prevailing challenges, particularly focusing on ethical and safety concerns, proposing viable solutions or methodologies, and illustrating the prospective capabilities and potential of AI-driven robotic technologies in the ICU environment. Ultimately, we foresee a pivotal role for robots in a future scenario of a fully automated continuum from admission to discharge within the ICU.

CONCLUSIONS

This review highlights the potential of AI robots to transform ICU care by improving patient treatment, support, and rehabilitation processes. However, it also recognizes the ethical complexities and operational challenges that come with their implementation, offering possible solutions for future development and optimization.

Feasibility analysis of inactivating influenza A(H1N1) virus using UVC robot in classroom environment

Background

Starting from 2009, H1N1 has been one of the respiratory diseases that afflict the global population. Concurrently, due to the influence of COVID-19, it has become widely accepted that preventing the virus's spread necessitates personal protection measures and disinfection in public spaces.

Experiments

This study conducted two experiments. In the classroom experiment, six UVC dose test points were calibrated to test whether the UVC dose at each testing point met the standards for inactivating IAVs and the time required to meet the standards. In the simulated classroom experiment, seven square slides made of IAVs were placed. After 10 min of robot movement, irradiated sterile square slides were made into suspension and injected into chicken embryos. Cultivate chicken embryos and conduct IAVs testing.

Results

Classroom experiment has shown that 5 testing points can meet the standards for inactivating IAVs(3 mJ/cm2), with a required time of 80 min, 40 min, 15 min, 5 min and 10 min. The UVC dose for testing points that do not meet the standards in 80 min is only 0.5 mJ/cm2. The simulation classroom experiment outcomes revealed that 99.99 % of IAVs were deactivated. Furthermore, this study established both a desktop control group and a chair arm control group, both of which yielded identical results, indicating an inactivation logarithm of IAVs≥4log.

Conclusion

The study presented that IAVs on the surface of an object can be effectively and rapidly deactivated at an irradiation density of 1.8 mW/cm2. Meanwhile, the study provides evidence of the feasibility of using the GXU robot to inactivate IAVs in a classroom environment.

Personalized robots for long-term telerehabilitation after stroke: a perspective on technological readiness and clinical translation

Stroke rehabilitation, which demands consistent, intensive, and adaptable intervention in the long term, faced significant challenges due to the COVID-19 pandemic. During this time, telerehabilitation emerged as a noteworthy complement to traditional rehabilitation services, offering the convenience of at-home care delivery and overcoming geographical and resource limitations. Self-help rehabilitation robots deliver repetitive and intensive physical assistance, thereby alleviating the labor burden. However, robots have rarely demonstrated long-term readiness for poststroke telerehabilitation services. The transition from research trials to general clinical services presents several challenges that may undermine the rehabilitative gains observed in these studies. This perspective discusses the technological readiness of personal use robots in the context of telerehabilitation and identifies the potential challenges for their clinical translation. The goal is to leverage technology to seamlessly integrate it into standard clinical workflows, ultimately enhancing the outcomes of stroke rehabilitation.

The Translation of Mobile-Exoneuromusculoskeleton-Assisted Wrist-Hand Poststroke Telerehabilitation from Laboratory to Clinical Service

Rehabilitation robots are helpful in poststroke telerehabilitation; however, their feasibility and rehabilitation effectiveness in clinical settings have not been sufficiently investigated. A non-randomized controlled trial was conducted to investigate the feasibility of translating a telerehabilitation program assisted by a mobile wrist/hand exoneuromusculoskeleton (WH-ENMS) into routine clinical services and to compare the rehabilitative effects achieved in the hospital-service-based group (n = 12, clinic group) with the laboratory-research-based group (n = 12, lab group). Both groups showed significant improvements (p ≤ 0.05) in clinical assessments of behavioral motor functions and in muscular coordination and kinematic evaluations after the training and at the 3-month follow-up, with the lab group demonstrating better motor gains than the clinic group (p ≤ 0.05). The results indicated that the WH-ENMS-assisted tele-program was feasible and effective for upper limb rehabilitation when integrated into routine practice, and the quality of patient-operator interactions physically and remotely affected the rehabilitative outcomes.

On the importance of patient acceptance for medical robotic imaging

PURPOSE

Mutual acceptance is required for any human-to-human interaction. Therefore, one would assume that this also holds for robot-patient interactions. However, the medical robotic imaging field lacks research in the area of acceptance. This work, therefore, aims at analyzing the influence of robot-patient interactions on acceptance in an exemplary medical robotic imaging system.

METHODS

We designed an interactive human-robot scenario, including auditive and gestural cues, and compared this pipeline to a non-interactive scenario. Both scenarios were evaluated through a questionnaire to measure acceptance. Heart rate monitoring was also used to measure stress. The impact of the interaction was quantified in the use case of robotic ultrasound scanning of the neck.

RESULTS

We conducted the first user study on patient acceptance of robotic ultrasound. Results show that verbal interactions impacts trust more than gestural ones. Furthermore, through interaction, the robot is perceived to be friendlier. The heart rate data indicates that robot-patient interaction could reduce stress.

CONCLUSIONS

Robot-patient interactions are crucial for improving acceptance in medical robotic imaging systems. While verbal interaction is most important, the preferred interaction type and content are participant dependent. Heart rate values indicate that such interactions can also reduce stress. Overall, this initial work showed that interactions improve patient acceptance in medical robotic imaging, and other medical robot-patient systems can benefit from the design proposals to enhance acceptance in interactive scenarios.

Care Robotics: An Assessment of Professional Perception in the Face of the COVID-19 Pandemic

The COVID-19 crisis accelerated the adoption of technologies. Technological advancement is also expected in robotics applied to any sector, including in healthcare. The aim is to assess the professional perception of care robotics facing COVID-19. This study aimed to (1) select a tool for assessing different aspects of healthcare, (2) analyse the professional perception about the development, usefulness and helpfulness of technologies and robotics in the field of healthcare and (3) evaluate the correlation between the perceived helpfulness of care robotics and the selected tool. We implement five validated clinical tests which integrate 80 items about a person and their clinical situation. From the sample of 46 professionals, 95.65% affirmed that technology was moderately to completely useful for professional performance in the context of the pandemic, lowering to 67.39% when asked only about robotics; 93.48% stated that the inclusion of robotics in at least one health area affected by COVID-19 would have helped them. Finally, the variables extracted from clinical tests corresponded to the most relevant health areas as identified by the professionals. This research shows the potential of care robotics oriented towards healthcare from a care paradigm.

COVID-19 and public support for autonomous technologies—Did the pandemic catalyze a world of robots?

By introducing a novel risk to human interaction, COVID-19 may have galvanized interest in uses of artificial intelligence (AI). But was the pandemic a large enough catalyst to change public attitudes about the costs and benefits of autonomous systems whose operations increasingly rely on AI? To answer this question, we use a preregistered research design that exploits variation across the 2018 and 2020 waves of the CCES/CES, a nationally representative survey of adults in the United States. We compare support for autonomous cars, autonomous surgeries, weapons, and cyber defense pre- and post-the beginning of the COVID-19 pandemic. We find that, despite the incentives created by COVID-19, the pandemic did not increase support for most of these technologies, except in the case of autonomous surgery among those who know someone who died of COVID-19. The results hold even when controlling for a variety of relevant political and demographic factors. The pandemic did little to push potential autonomous vehicle users to support adoption. Further, American concerns about autonomous weapons, including cyber defense, remain sticky and perhaps exacerbated over the last two years. These findings suggest that the relationship between the COVID-19 pandemic and the adoption of many of these systems is far more nuanced and complex than headlines may suggest.

The adoption of socially assistive robots for long-term care: During COVID-19 and in a post-pandemic society

The rapid spread of COVID-19 has prompted a surge in the adoption of technology, highlighting a number of potential applications for Socially Assistive Robots (SARs). Our entire healthcare system has been under unprecedented strain, and going forward, we must consider how robotic technology could help improve the quality of care and day-to-day functionality of our care facilities. Herein, we present our human-robot interaction study in a local long-term care centre during the pandemic and the lessons learned from deploying a SAR to screen staff members. We investigate staff acceptance and the influence of demographics on perceptions of the SAR. Results show that overall, staff were positive about the screening robot, and that autonomous screening with a social robot is a potential application in long-term care homes. We further detail the challenges and future opportunities to develop SARs, including recommendations to successfully implement and adopt these robots in a post-pandemic society.

Scalable and heterogenous mobile robot fleet-based task automation in crowded hospital environments—a field test

In hospitals, trained medical staff are often, in addition to performing complex procedures, spending valuable time on secondary tasks such as transporting samples and medical equipment; or even guiding patients and visitors around the premises. If these non-medical tasks were automated by deploying mobile service robots, more time can be focused on treating patients or allowing well-deserved rest for the potentially overworked healthcare professionals. Automating such tasks requires a human-aware robotic mobility system that can among other things navigate the hallways of the hospital; predictively avoid collisions with humans and other dynamic obstacles; coordinate task distribution and area coverage within a fleet of robots and other IoT devices; and interact with the staff, patients and visitors in an intuitive way. This work presents the results, lessons-learned and the source code of deploying a heterogeneous mobile robot fleet at the Tartu University Hospital, performing object transportation tasks in areas of intense crowd movement and narrow hallways. The primary use-case is defined as transporting time-critical samples from an intensive care unit to the hospital lab. Our work builds upon Robotics Middleware Framework (RMF), an open source, actively growing and highly capable fleet management platform which is yet to reach full maturity. Thus this paper demonstrates and validates the real-world deployment of RMF in an hospital setting and describes the integration efforts.

Healthcare Workers’ Point of View on Medical Robotics During COVID-19 Pandemic – A Scoping Review

COVID-19 affected how healthcare workers interact with patients. Medical technology and robotics are developed in hospital settings to limit human contact. The aim of this review is to elucidate what kind of medical robotics is required for healthcare workers during COVID-19 pandemic. This review was obtained from electronic databases such as Google Scholar, PubMed, EBSCO, and Cochrane reviews were searched for articles using keywords such as “healthcare professional” OR “health worker” AND “COVID-19” AND “robot application” OR “robotics” OR “health technology” AND “needs assessment” OR “expectation” OR “perception” published during 2020 to 2021. Inclusion criteria were full-text articles related to assessment of healthcare workers’ need for medical robotics during COVID-19 pandemics. Exclusion criteria included abstracts, duplicate articles, blogs, news articles, promotional brochures, and conference proceedings. A total of 13,692 articles were identified through the search engines (PubMed 179, Cochrane Library 1300, EBSCO 13, Google Scholar 12,200). Five full-text articles fulfilled the inclusion criteria. Determining robotic functions is important to healthcare workers who will be user of such medical technology. This review divided robotic functions into medical, operational, movement, and social functions. Healthcare workers’ demands for robotics were also influenced by the types of robots, such as examination robots, robot-based sample test and medicine production, surgery and rehabilitation robots, disinfection and cleaning robots, delivery and logistic robot, telemedicine, and telepresence robots. Medical robotics is required for healthcare workers during the COVID-19 pandemic. The highest demands for medical robotics functions include cardiac measurements and oxygen saturation monitoring (medical functions); examination record delivery, video and image play, and medical information delivery (operational functions); and the ability to recognize and avoid obstacles (movement functions). Disinfection and cleaning robots were the type of robots with the highest demand among healthcare workers.

The Effect of Physician Communication on Inpatient Satisfaction

(1) Background: The importance of physician-patient communication and its effect on patient satisfaction has become a hot topic and has been studied from various aspects in recent years. However, there is a lack of systematic reviews to integrate recent research findings into patient satisfaction studies with physician communication. Therefore, this study aims to systematically examine physician communication’s effect on patient satisfaction in public hospitals. (2) Methods: Using a keywords search, data was collected from five databases for the papers published until October 2021. Original studies, observational studies, intervention studies, cross-sectional studies, cohort studies, experimental studies, and qualitative studies published in English, peer-reviewed research, and inpatients who communicated with the physician in a hospital met the inclusion criteria. (3) Results: Overall, 11 studies met the inclusion criteria from the 4810 articles found in the database. Physicians and organizations can influence two determinants of inpatient satisfaction in physician communication. Determinants of patient satisfaction that physicians influence consist of amounts of time spent with the patient, verbal and nonverbal indirect interpersonal communication, and understanding the demands of patients. The organization can improve patient satisfaction with physician communication by the organization’s availability of interpreter service and physician workload. Physicians’ communication with inpatients can affect patient satisfaction with hospital services. (4) Conclusions: To improve patient satisfaction with physician communication, physicians and organizational determinants must be considered.

Applications of Healthcare Robots in Combating the COVID-19 Pandemic

Due to the increasing number of COVID-19 cases, there is a remarkable demand for robots, especially in the clinical sector. SARS-CoV-2 mainly propagates due to close human interactions and contaminated surfaces, and hence, maintaining social distancing has become a mandatory preventive measure. This generates the need to treat patients with minimal doctor-patient interaction. Introducing robots in the healthcare sector protects the frontline healthcare workers from getting exposed to the coronavirus as well as decreases the need for medical personnel as robots can partially take over some medical roles. The aim of this paper is to highlight the emerging role of robotic applications in the healthcare sector and allied areas. To this end, a systematic review was conducted regarding the various robots that have been implemented worldwide during the COVID-19 pandemic to attenuate and contain the virus. The results obtained from this study reveal that the implementation of robotics into the healthcare field has a substantial effect in controlling the spread of SARS-CoV-2, as it blocks coronavirus propagation between patients and healthcare workers, along with other advantages such as disinfection or cleaning.

Recommending Suitable Smart Technology Applications to Support Mobile Healthcare after the COVID-19 Pandemic Using a Fuzzy Approach

The COVID-19 pandemic seems to be entering its final stage. However, to restore normal life, the applications of smart technologies are still necessary. Therefore, this research is dedicated to exploring the applications of smart technologies that can support mobile healthcare after the COVID-19 pandemic. To this end, this study compares smart technology applications to support mobile healthcare within the COVID-19 pandemic with those before the pandemic, so as to estimate possible developments in this field. In addition, to quantitatively assess and compare smart technology applications that may support mobile healthcare after the COVID-19 pandemic, the calibrated fuzzy geometric mean (CFGM)-fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) approach is applied. The proposed methodology has been applied to evaluate and compare nine potential smart technology applications for supporting mobile healthcare after the COVID-19 pandemic. According to the experimental results, "vaccine passport and related applications" and "smart watches" were the most suitable smart technology applications for supporting mobile healthcare after the COVID-19 pandemic.

Public Perception and Reception of Robotic Applications in Public Health Emergencies Based on a Questionnaire Survey Conducted during COVID-19

Various intelligent technologies have been applied during COVID-19, which has become a worldwide public health emergency and brought significant challenges to the medical systems around the world. Notably, the application of robots has played a role in hospitals, quarantine facilities and public spaces and has attracted much attention from the media and the public. This study is based on a questionnaire survey on the perception and reception of robots used for medical care in the pandemic among the Chinese population. A total of 1667 people participated in the survey, 93.6% of respondents were pursuing or had completed a bachelor, master or even doctorate degree. The results show that Chinese people generally held positive attitudes towards "anti-pandemic robots" and affirmed their contribution to reducing the burden of medical care and virus transmission. A few respondents were concerned about the issues of robots replacing humans and it was apparent that their ethical views on robots were not completely consistent across their demographics (e.g., age, industry). Nevertheless, most respondents tended to be optimistic about robot applications and dialectical about the ethical issues involved. This is related to the prominent role robots played during the pandemic, the Chinese public's expectations of new technologies and technology-friendly public opinion in China. Exploring the perception and reception of anti-pandemic robots in different countries or cultures is important because it can shed some light on the future applications of robots, especially in the field of infectious disease control.

A Survey on Socially Assistive Robotics: Clinicians' and Patients' Perception of a Social Robot within Gait Rehabilitation Therapies

A growing interest in Socially Assistive Robotics in Physical Rehabilitation is currently observed; some of the benefits highlight the capability of a social robot to support and assist rehabilitation procedures. This paper presents a perception study that aimed to evaluate clinicians’ and patients’ perception of a social robot that will be integrated as part of Lokomat therapy. A total of 88 participants were surveyed, employing an online questionnaire based on the Unified Theory of Acceptance and Use of Technology (UTAUT). The participants belong to two health care institutions located in different countries (Colombia and Spain). The results showed an overall positive perception of the social robot (>60% of participants have a positive acceptance). Furthermore, a difference depending on the nature of the user (clinician vs. patient) was found.