JUNO Project: Deployment and Validation of a Low-Cost Cloud-Based Robotic Platform for Reliable Smart Navigation and Natural Interaction with Humans in an Elderly Institution.

This paper describes the main results of the JUNO project, a proof of concept developed in the Region of Murcia in Spain, where a smart assistant robot with capabilities for smart navigation and natural human interaction has been developed and deployed, and it is being validated in an elderly institution with real elderly users. The robot is focused on helping people carry out cognitive stimulation exercises and other entertainment activities since it can detect and recognize people, safely navigate through the residence, and acquire information about attention while users are doing the mentioned exercises. All the information could be shared through the Cloud, if needed, and health professionals, caregivers and relatives could access such information by considering the highest standards of privacy required in these environments. Several tests have been performed to validate the system, which combines classic techniques and new Deep Learning-based methods to carry out the requested tasks, including semantic navigation, face detection and recognition, speech to text and text to speech translation, and natural language processing, working both in a local and Cloud-based environment, obtaining an economically affordable system. The paper also discusses the limitations of the platform and proposes several solutions to the detected drawbacks in this kind of complex environment, where the fragility of users should be also considered.

Ferrobotic swarms enable accessible and adaptable automated viral testing.

Expanding our global testing capacity is critical to preventing and containing pandemics^1-9. Accordingly, accessible and adaptable automated platforms that in decentralized settings perform nucleic acid amplification tests resource-efficiently are required^10-14. Pooled testing can be extremely efficient if the pooling strategy is based on local viral prevalence^15-20; however, it requires automation, small sample volume handling and feedback not available in current bulky, capital-intensive liquid handling technologies^21-29. Here we use a swarm of millimetre-sized magnets as mobile robotic agents ('ferrobots') for precise and robust handling of magnetized sample droplets and high-fidelity delivery of flexible workflows based on nucleic acid amplification tests to overcome these limitations. Within a palm-sized printed circuit board-based programmable platform, we demonstrated the myriad of laboratory-equivalent operations involved in pooled testing. These operations were guided by an introduced square matrix pooled testing algorithm to identify the samples from infected patients, while maximizing the testing efficiency. We applied this automated technology for the loop-mediated isothermal amplification and detection of the SARS-CoV-2 virus in clinical samples, in which the test results completely matched those obtained off-chip. This technology is easily manufacturable and distributable, and its adoption for viral testing could lead to a 10-300-fold reduction in reagent costs (depending on the viral prevalence) and three orders of magnitude reduction in instrumentation cost. Therefore, it is a promising solution to expand our testing capacity for pandemic preparedness and to reimagine the automated clinical laboratory of the future.

Developing an Upper Limb Kinematics Database of Activities of Daily Living.

Open-access databases can facilitate data sharing among researchers and provide normative data for objective clinical assessment development, robotic design, and biomechanical modeling. However, most existing databases focus on gait, balance, and hand gestures without providing elbow and shoulder kinematics that are required in activities of daily living. Furthermore, the few existing upper limb datasets include small sample sizes without consistent data collection protocols, which hinder robotic engineers' ability to design robotic devices that accommodate the general population. To address the literature gap, an open-access upper limb kinematic database was proposed. Due to the impact of COVID-19 on human research, only data from 16 participants were collected. Clinical Relevance-This provides baseline kinematics for developing objective clinical assessments and rehabilitation robots.

Teleoperated Probe Manipulator for Prone-Position Echocardiography Examination.

Echocardiography probe manipulation is a strenuous task. During a procedure, the operator must hold the probe, extend their arm, bend their elbow, and monitor the resulting image simultaneously, which causes strain and introduces variability to the measurement. We propose a teleoperated probe manipulation robot to reduce the burden of handling the probe and minimize the infection risk during the COVID pandemic. The proposed robot utilizes prone position scanning that could enlarge the cardiac windows for easier scanning and eliminate the risk of the robot pressing down on the patient. We derived the robot's requirements based on a real clinical scenario. Initial evaluation showed that the robot could achieve the required range of motion, force, and control. The robot's functionality was tested by a non-clinician, in which the tester could obtain heart images of a volunteer in under one minute.

Application of an EMG-Rehabilitation Robot in Patients with Post-Coronavirus Fatigue Syndrome (COVID-19)-A Feasibility Study.

This pilot study aimed to assess the safety and feasibility of an EMG-driven rehabilitation robot in patients with Post-Viral Fatigue (PVF) syndrome after COVID-19. The participants were randomly assigned to two groups (IG-intervention group and CG-control group) in an inpatient neurological rehabilitation unit. Both groups were assessed on admission and after six weeks of rehabilitation. Rehabilitation was carried out six days a week for six weeks. The patients in the IG performed additional training using an EMG rehabilitation robot. Muscle fatigue was assessed using an EMG rehabilitation robot; secondary outcomes were changes in hand grip strength, Fatigue Assessment Scale, and functional assessment scales (Functional Independence Measure, Barthel Index). Both groups improved in terms of the majority of measured parameters comparing pre- and post-intervention results, except muscle fatigue. Muscle fatigue scores presented non-significant improvement in the IG and non-significant deterioration in the CG. Using an EMG rehabilitation robot in patients with PVF can be feasible and safe. To ascertain the effectiveness of such interventions, more studies are needed, particularly involving a larger sample and also assessing the participants' cognitive performance.

Telerobotic ultrasound to provide obstetrical ultrasound services remotely during the COVID-19 pandemic.

INTRODUCTION: Obstetrical ultrasound imaging is critical in identifying at-risk pregnancies and informing clinical management. The coronavirus disease 2019 (COVID-19) pandemic has exacerbated challenges in accessing obstetrical ultrasound for patients in underserved rural and remote communities where this service is not available. This prospective descriptive study describes our experience of providing obstetrical ultrasound services remotely using a telerobotic ultrasound system in a northern Canadian community isolated due to a COVID-19 outbreak. METHODS: A telerobotic ultrasound system was used to perform obstetrical ultrasound exams remotely in La Loche, Canada, a remote community without regular access to obstetrical ultrasound. Using a telerobotic ultrasound system, a sonographer 605 km away remotely controlled an ultrasound probe and ultrasound settings. Twenty-one exams were performed in a five-week period during a COVID-19 outbreak in the community, including limited first-, second- and third-trimester exams (n = 11) and complete second-trimester exams (n = 10). Participants were invited to complete a survey at the end of the telerobotic ultrasound exam describing their experiences with telerobotic ultrasound. Radiologists subsequently interpreted all exams and determined the adequacy of the images for diagnosis. RESULTS: Of 11 limited obstetrical exams, radiologists indicated images were adequate in nine (81%) cases, adequate with some reservations in one (9%) case and inadequate in one (9%) case. Of 10 second-trimester complete obstetrical exams, radiologists indicated images were adequate in two (20%) cases, adequate with some reservations in three (30%) cases and inadequate in five (50%) cases. Second-trimester complete obstetrical exams were limited due to a combination of body habitus, foetal lie and telerobotic technology. DISCUSSION: A telerobotic ultrasound system may be used to answer focused clinical questions such as foetal viability, dating and foetal presentation in a timely manner while minimising patient travel to larger centres and potential exposure to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), during the COVID-19 pandemic.

InjectMeAI-Software Module of an Autonomous Injection Humanoid.

The recent pandemic outbreak proved social distancing effective in helping curb the spread of SARS-CoV-2 variants along with the wearing of masks and hand gloves in hospitals and assisted living environments. Health delivery personnel having undergone training regarding the handling of patients suffering from Corona infection have been stretched. Administering injections involves unavoidable person to person contact. In this circumstance, the spread of bodily fluids and consequently the Coronavirus become eminent, leading to an upsurge of infection rates among nurses and doctors. This makes enforced home office practices and telepresence through humanoid robots a viable alternative. In providing assistance to further reduce contact with patients during vaccinations, a software module has been designed, developed, and implemented on a Pepper robot that estimates the pose of a patient, identifies an injection spot, and raises an arm to deliver the vaccine dose on a bare shoulder. Implementation was done using the QiSDK in an android integrated development environment with a custom Python wrapper. Tests carried out yielded positive results in under 60 s with an 80% success rate, and exposed some ambient lighting discrepancies. These discrepancies can be solved in the near future, paving a new way for humans to get vaccinated.

Dual Mode pHRI-teleHRI Control System with a Hybrid Admittance-Force Controller for Ultrasound Imaging.

The COVID-19 pandemic has brought unprecedented extreme pressure on the medical system due to the physical distance policy, especially for procedures such as ultrasound (US) imaging, which are usually carried out in person. Tele-operation systems are a promising way to avoid physical human-robot interaction (pHRI). However, the system usually requires another robot on the remote doctor side to provide haptic feedback, which makes it expensive and complex. To reduce the cost and system complexity, in this paper, we present a low-cost, easy-to-use, dual-mode pHRI-teleHRI control system with a custom-designed hybrid admittance-force controller for US imaging. The proposed system requires only a tracking camera rather than a sophisticated robot on the remote side. An audio feedback is designed for replacing haptic feedback on the remote side, and its sufficiency is experimentally verified. The experimental results indicate that the designed hybrid controller can significantly improve the task performance in both modes. Furthermore, the proposed system enables the user to conduct US imaging while complying with the physical distance policy, and allows them to seamlessly switch modes from one to another in an online manner. The novel system can be easily adapted to other medical applications beyond the pandemic, such as tele-healthcare, palpation, and auscultation.

A Robot-Mediated Activity Using the Nao Robot to Promote COVID-19 Precautionary Measures among Older Adults in Geriatric Facilities.

Precautionary measures (e.g., social distancing, mask wearing, washing hands regularly) to limit the transmission of the Coronavirus 19 (COVID-19) have been put in place worldwide. However, a limited understanding of precautionary measures and low compliance with them has been observed in older adults with neurocognitive disorders, persons with intellectual disability, or mental illness. The objective of this study is to create and evaluate a robot-mediated activity to deliver information on COVID-19 precautionary measures in an accessible and engaging way using the humanoid robot Nao. An interactive scenario explaining and demonstrating COVID-19 precautionary measures is created using the verbal and non-verbal behaviours of the robot. The scenario (≈5 min) is presented to 124 users of a geriatric hospital, including the following: older patients (n = 45), accompanying persons (n = 39), and health professionals (n = 40). The data regarding perceived usefulness, acceptability, and accessibility are collected using a questionnaire. A video analysis of the participants' behaviour during the interaction with the robot is performed to examine the quality of engagement in the activity. The results show a good acceptance, satisfaction, and perceived usefulness of the robot-mediated activity. These findings suggest that robot-mediated interventions using humanoid robots can be an effective tool for the delivery of health promotion information.

Automatic system for high-throughput and high-sensitivity diagnosis of SARS-CoV-2.

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had severe consequences for health and the global economy. To control the transmission, there is an urgent demand for early diagnosis and treatment in the general population. In the present study, an automatic system for SARS-CoV-2 diagnosis is designed and built to deliver high specification, high sensitivity, and high throughput with minimal workforce involvement. The system, set up with cross-priming amplification (CPA) rather than conventional reverse transcription-polymerase chain reaction (RT-PCR), was evaluated using more than 1000 real-world samples for direct comparison. This fully automated robotic system performed SARS-CoV-2 nucleic acid-based diagnosis with 192 samples in under 180 min at 100 copies per reaction in a "specimen in data out" manner. This throughput translates to a daily screening capacity of 800-1000 in an assembly-line manner with limited workforce involvement. The sensitivity of this device could be further improved using a CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)-based assay, which opens the door to mixed samples, potentially include SARS-CoV-2 variants screening in extensively scaled testing for fighting COVID-19.

A Review of Robotic Interventional Neuroradiology.

Robotic interventional neuroradiology is an emerging field with the potential to enhance patient safety, reduce occupational hazards, and expand systems of care. Endovascular robots allow the operator to precisely control guidewires and catheters from a lead-shielded cockpit located several feet (or potentially hundreds of miles) from the patient. This has opened up the possibility of expanding telestroke networks to patients without access to life-saving procedures such as stroke thrombectomy and cerebral aneurysm occlusion by highly-experienced physicians. The prototype machines, first developed in the early 2000s, have evolved into machines capable of a broad range of techniques, while incorporating newly automated maneuvers and safety algorithms. In recent years, preliminary clinical research has been published demonstrating the safety and feasibility of the technology in cerebral angiography and intracranial intervention. The next step is to conduct larger, multisite, prospective studies to assess generalizability and, ultimately, improve patient outcomes in neurovascular disease.

Robotic RNA extraction for SARS-CoV-2 surveillance using saliva samples.

Saliva is an attractive specimen type for asymptomatic surveillance of COVID-19 in large populations due to its ease of collection and its demonstrated utility for detecting RNA from SARS-CoV-2. Multiple saliva-based viral detection protocols use a direct-to-RT-qPCR approach that eliminates nucleic acid extraction but can reduce viral RNA detection sensitivity. To improve test sensitivity while maintaining speed, we developed a robotic nucleic acid extraction method for detecting SARS-CoV-2 RNA in saliva samples with high throughput. Using this assay, the Free Asymptomatic Saliva Testing (IGI FAST) research study on the UC Berkeley campus conducted 11,971 tests on supervised self-collected saliva samples and identified rare positive specimens containing SARS-CoV-2 RNA during a time of low infection prevalence. In an attempt to increase testing capacity, we further adapted our robotic extraction assay to process pooled saliva samples. We also benchmarked our assay against nasopharyngeal swab specimens and found saliva methods require further optimization to match this gold standard. Finally, we designed and validated a RT-qPCR test suitable for saliva self-collection. These results establish a robotic extraction-based procedure for rapid PCR-based saliva testing that is suitable for samples from both symptomatic and asymptomatic individuals.

Assessment of the Acceptability and Feasibility of Using Mobile Robotic Systems for Patient Evaluation.

Importance: Before the widespread implementation of robotic systems to provide patient care during the COVID-19 pandemic occurs, it is important to understand the acceptability of these systems among patients and the economic consequences associated with the adoption of robotics in health care settings. Objective: To assess the acceptability and feasibility of using a mobile robotic system to facilitate health care tasks. Design, Setting, and Participants: This study included 2 components: a national survey to examine the acceptability of using robotic systems to perform health care tasks in a hospital setting and a single-site cohort study of patient experiences and satisfaction with the use of a mobile robotic system to facilitate triage and telehealth tasks in the emergency department (ED). The national survey comprised individuals living in the US who participated in a sampling-based survey via an online analytic platform. Participants completed the national survey between August 18 and August 21, 2020. The single-site cohort study included patients living in the US who presented to the ED of a large urban academic hospital providing quaternary care in Boston, Massachusetts between April and August 2020. All data were analyzed from August to October 2020. Exposures: Participants in the national survey completed an online survey to measure the acceptability of using a mobile robotic system to perform health care tasks (facilitating telehealth interviews, acquiring vital signs, obtaining nasal or oral swabs, placing an intravenous catheter, performing phlebotomy, and turning a patient in bed) in a hospital setting in the contexts of general interaction and interaction during the COVID-19 pandemic. Patients in the cohort study were exposed to a mobile robotic system, which was controlled by an ED clinician and used to facilitate a triage interview. After exposure, patients completed an assessment to measure their satisfaction with the robotic system. Main Outcomes and Measures: Acceptability of the use of a mobile robotic system to facilitate health care tasks in a hospital setting (national survey) and feasibility and patient satisfaction regarding the use of a mobile robotic system in the ED (cohort study). Results: For the national survey, 1154 participants completed all acceptability questions, representing a participation rate of 35%. After sample matching, a nationally representative sample of 1000 participants (mean [SD] age, 48.7 [17.0] years; 535 women [53.5%]) was included in the analysis. With regard to the usefulness of a robotic system to perform specific health care tasks, the response of "somewhat useful" was selected by 373 participants (37.3%) for facilitating telehealth interviews, 350 participants (35.0%) for acquiring vital signs, 307 participants (30.7%) for obtaining nasal or oral swabs, 228 participants (22.8%) for placing an intravenous catheter, 249 participants (24.9%) for performing phlebotomy, and 371 participants (37.1%) for turning a patient in bed. The response of "extremely useful" was selected by 287 participants (28.7%) for facilitating telehealth interviews, 413 participants (41.3%) for acquiring vital signs, 192 participants (19.2%) for obtaining nasal or oral swabs, 159 participants (15.9%) for placing an intravenous catheter, 167 participants (16.7%) for performing phlebotomy, and 371 participants (37.1%) for turning a patient in bed. In the context of the COVID-19 pandemic, the median number of individuals who perceived the application of robotic systems to be acceptable for completing telehealth interviews, obtaining nasal and oral swabs, placing an intravenous catheter, and performing phlebotomy increased. For the ED cohort study, 51 individuals were invited to participate, and 41 participants (80.4%) enrolled. One participant was unable to complete the study procedures because of a signaling malfunction in the robotic system. Forty patients (mean [SD] age, 45.8 [2.7] years; 29 women [72.5%]) completed the mobile robotic system-facilitated triage interview, and 37 patients (92.5%) reported that the interaction was satisfactory. A total of 33 participants (82.5%) reported that their experience of receiving an interview facilitated by a mobile robotic system was as satisfactory as receiving an in-person interview from a clinician. Conclusions and Relevance: In this study, a mobile robotic system was perceived to be acceptable for use in a broad set of health care tasks among survey respondents across the US. The use of a mobile robotic system enabled the facilitation of contactless triage interviews of patients in the ED and was considered acceptable among participants. Most patients in the ED rated the quality of mobile robotic system-facilitated interaction to be equivalent to in-person interaction with a clinician.

Ultraviolet disinfection robots to improve hospital cleaning: Real promise or just a gimmick?

The global COVID-19 pandemic due to the novel coronavirus SARS-CoV-2 has challenged the availability of traditional surface disinfectants. It has also stimulated the production of ultraviolet-disinfection robots by companies and institutions. These robots are increasingly advocated as a simple solution for the immediate disinfection of rooms and spaces of all surfaces in one process and as such they seem attractive to hospital management, also because of automation and apparent cost savings by reducing cleaning staff. Yet, there true potential in the hospital setting needs to be carefully evaluated. Presently, disinfection robots do not replace routine (manual) cleaning but may complement it. Further design adjustments of hospitals and devices are needed to overcome the issue of shadowing and free the movement of robots in the hospital environment. They might in the future provide validated, reproducible and documented disinfection processes. Further technical developments and clinical trials in a variety of hospitals are warranted to overcome the current limitations and to find ways to integrate this novel technology in to the hospitals of to-day and the future.

The implementation of a rapid sample preparation method for the detection of SARS-CoV-2 in a diagnostic laboratory in South Africa.

The SARS-CoV-2 pandemic has resulted in shortages of both critical reagents for nucleic acid purification and highly trained staff as supply chains are strained by high demand, public health measures and frequent quarantining and isolation of staff. This created the need for alternate workflows with limited reliance on specialised reagents, equipment and staff. We present here the validation and implementation of such a workflow for preparing samples for downstream SARS-CoV-2 RT-PCR using liquid handling robots. The rapid sample preparation technique evaluated, which included sample centrifugation and heating prior to RT-PCR, showed a 97.37% (95% CI: 92.55-99.28%) positive percent agreement and 97.30% (95% CI: 90.67-99.52%) negative percent agreement compared to nucleic acid purification-based testing. This method was subsequently adopted as the primary sample preparation method in the Groote Schuur Hospital Virology Diagnostic Laboratory in Cape Town, South Africa.

Can Disinfection Robots Reduce the Risk of Transmission of SARS-CoV-2 in Health Care and Educational Settings?

We explore the opportunities and challenges surrounding the use of disinfection robots to reduce the risk of SARS-CoV-2 transmission in health care and educational settings. Although there is some potential for deploying robots to help with manual cleaning, the evidence base is mixed, and we highlight that there needs to be work to establish and enhance the effectiveness of these robots in inactivating the virus.

Pilot Study of Robot-Assisted Teleultrasound Based on 5G Network: A New Feasible Strategy for Early Imaging Assessment During COVID-19 Pandemic.

Early diagnosis is critical for the prevention and control of the coronavirus disease 2019 (COVID-19). We attempted to apply a protocol using teleultrasound, which is supported by the 5G network, to explore the feasibility of solving the problem of early imaging assessment of COVID-19. Four male patients with confirmed or suspected COVID-19 were hospitalized in isolation wards in two different cities. Ultrasound specialists, located in two other different cities, carried out the robot-assisted teleultrasound and remote consultation in order to settle the problem of early cardiopulmonary evaluation. Lung ultrasound, brief echocardiography, and blood volume assessment were performed. Whenever difficulties of remote manipulation and diagnosis occurred, the alternative examination was repeated by a specialist from another city, and in sequence, remote consultation was conducted immediately to meet the consensus. The ultrasound specialists successfully completed the telerobotic ultrasound. Lung ultrasound indicated signs of pneumonia with varying degrees in all cases and mild pleural effusion in one case. No abnormalities of cardiac structure and function and blood volume were detected. Remote consultation on the issue of manipulation practice, and the diagnosis in one case was conducted. The cardiopulmonary information was delivered to the frontline clinicians immediately for further treatment. The practice of teleultrasound protocol makes early diagnosis and repeated assessment available in the isolation ward. Ultrasound specialists can be protected from infection, and personal protective equipment can be spared. Quality control can be ensured by remote consultations among doctors. This protocol is worth consideration as a feasible strategy for early imaging assessment in the COVID-19 pandemic.

Application of a Robotic Tele-Echography System for COVID-19 Pneumonia.

To date, coronavirus disease 2019 (COVID-19) has infected millions of people worldwide. Ultrasound plays an indispensable role in the diagnosis, monitoring, and follow-up of patients with COVID-19. In this study, we used a robotic tele-echography system based on a 5G communication network for remote diagnosis. The system has great potential for lung, heart, and vasculature information, medical staff protection, and resource sharing, can be a valuable tool for treating patients during the pandemic, and can be expected to expand to more specialized fields.

A Human Support Robot for the Cleaning and Maintenance of Door Handles Using a Deep-Learning Framework.

The role of mobile robots for cleaning and sanitation purposes is increasing worldwide. Disinfection and hygiene are two integral parts of any safe indoor environment, and these factors become more critical in COVID-19-like pandemic situations. Door handles are highly sensitive contact points that are prone to be contamination. Automation of the door-handle cleaning task is not only important for ensuring safety, but also to improve efficiency. This work proposes an AI-enabled framework for automating cleaning tasks through a Human Support Robot (HSR). The overall cleaning process involves mobile base motion, door-handle detection, and control of the HSR manipulator for the completion of the cleaning tasks. The detection part exploits a deep-learning technique to classify the image space, and provides a set of coordinates for the robot. The cooperative control between the spraying and wiping is developed in the Robotic Operating System. The control module uses the information obtained from the detection module to generate a task/operational space for the robot, along with evaluating the desired position to actuate the manipulators. The complete strategy is validated through numerical simulations, and experiments on a Toyota HSR platform.