Remote Ultrasound Scan Procedures with Medical Robots: Towards New Perspectives between Medicine and Engineering

Prioritisation of functional needs for ICU intelligent robots in China: a consensus study based on the national survey and nominal group technique

OBJECTIVE

This study aims to define the prioritisation of the needs for an intelligent robot's functions in the intensive care unit (ICU) from a clinical perspective.

DESIGN

This study introduces a nominal group technique.

SETTING

This study uses national setting.

PARTICIPANTS

This study includes a total of 851 respondents from 34 provinces in China who participated in the survey. A nominal group of 12 members was organised by the research group; there were seven experts with a background in critical care, two junior attending physicians with a background in critical care and three experienced nurses.

RESULTS

A total of 50 needed intelligent robot functions in ICUs were obtained from the questionnaire data. Through three rounds of nominal group voting and discussion, a consensus was reached on 44 items, which were categorised into 29 high-priority needs, 13 medium-priority needs and two low-priority needs. The functionalities in areas such as 'sleep and pain assessment,' 'monitoring of sedation, agitation, and delirium,' and 'robot-assisted rehabilitation and physical therapy' were particularly favoured by the ICU medical and nursing staff.

CONCLUSIONS

This study has defined the functional needs and priorities for ICU intelligent robots from the perspective of ICU clinical medical and nursing staff. It has been concluded that 'disease assessment function' and 'rehabilitation and physical therapy' are most needed by clinical doctors and nurses. The results presented in this study could serve as a useful reference for future research and development of medical robots.

Visual Perception and Convolutional Neural Network-Based Robotic Autonomous Lung Ultrasound Scanning Localization System

Under the situation of severe COVID-19 epidemic, lung ultrasound (LUS) has been proved to be an effective and convenient method to diagnose and evaluate the extent of respiratory disease. However, the traditional clinical ultrasound (US) scanning requires doctors not only to be in close contact with patients but also to have rich experience. In order to alleviate the shortage of medical resources and reduce the work stress and risk of infection for doctors, we propose a visual perception and convolutional neural network (CNN)-based robotic autonomous LUS scanning localization system to realize scanned target recognition, probe pose solution and movement, and the acquisition of US images. The LUS scanned targets are identified through the target segmentation and localization algorithm based on the improved CNN, which is using the depth camera to collect the image information; furthermore, the method based on multiscale compensation normal vector is used to solve the attitude of the probe; finally, a position control strategy based on force feedback is designed to optimize the position and attitude of the probe, which can not only obtain high-quality US images but also ensure the safety of patients and the system. The results of human LUS scanning experiment verify the accuracy and feasibility of the system. The positioning accuracy of the scanned targets is 15.63 ± 0.18 mm, and the distance accuracy and rotation angle accuracy of the probe position calculation are 6.38 ± 0.25 mm and 8.60° ±2.29° , respectively. More importantly, the obtained high-quality US images can clearly capture the main pathological features of the lung. The system is expected to be applied in clinical practice.

Positive Impact of Home ERT for Mucopolysaccharidoses and Pompe Disease: The Lesson Learnt from the COVID-19 Pandemic

OBJECTIVE

Patients with Lysosomal disorders (LSDs) are treated with regular infusions of enzyme replacement therapy (ERT). During the COVID-19 pandemic, home treatment was permitted. This study aimed at monitoring the patients' compliance with home therapy and its effects on physical, psychological, and relational issues. Moreover, we also tested the possible impact of home therapy on familial relationships and contacts with the referral hospital.

MATERIALS AND METHODS

Thirteen patients with Pompe disease (N = 8) and MPS (N = 5) were tested through an online questionnaire designed to assess their level of appreciation and satisfaction with home therapy and their feelings about the referral centre and psychological support provided.

RESULTS

Most of the patients (84%) stressed the positive impact of home therapy. All patients described a significant reduction in stressful conditions associated with the need to attend the hospital every week or two.

CONCLUSIONS

Home ERT leads to a clear improvement in "daily life skills", as represented in our by sample by positive feelings, better emotional self-control, and an increased ability to understand the feelings of relatives. Our data underline the paramount positive effect home ERT has on both patients and their families.

Feasibility study of personalized speed adaptation method based on mental state for teleoperated robots

The teleoperated robotic system can support humans to complete tasks in high-risk, high-precision and difficult special environments. Because this kind of special working environment is easy to cause stress, high mental workload, fatigue and other mental states of the operator, which will reduce the quality of operation and even cause safety accidents, so the mental state of the people in this system has received extensive attention. However, the existence of individual differences and mental state diversity is often ignored, so that most of the existing adjustment strategy is out of a match between mental state and adaptive decision, which cannot effectively improve operational quality and safety. Therefore, a personalized speed adaptation (PSA) method based on policy gradient reinforcement learning was proposed in this paper. It can use electroencephalogram and electro-oculogram to accurately perceive the operator’s mental state, and adjust the speed of the robot individually according to the mental state of different operators, in order to perform teleoperation tasks efficiently and safely. The experimental results showed that the PSA method learns the mapping between the mental state and the robot’s speed regulation action by means of rewards and punishments, and can adjust the speed of the robot individually according to the mental state of different operators, thereby improving the operating quality of the system. And the feasibility and superiority of this method were proved. It is worth noting that the PSA method was validated on 6 real subjects rather than a simulation model. To the best of our knowledge, the PSA method is the first implementation of online reinforcement learning control of teleoperated robots involving human subjects.

An introductory review of robotically assisted surgical systems

Purpose

The scope of the work is to present the state of the art of robotically assisted surgical systems and to give a general idea about how technology can help today and tomorrow robotic surgery. The road to innovation passes through research and on field trials; for this reason, not only commercial surgery robots, but also innovative prototype robots, proposed by the Academic world, are presented.

Design/methodology/approach

Following a short introduction, robotically assisted surgery systems are introduced discussing their architectures and main peculiarities. A further section is dedicated to the key enabling technologies that will make possible to improve current systems and that will lead to a new generation of surgical robotic systems able to meet the patient's needs and facilitate the surgeon's task. Finally, brief concluding comments are given.

Findings

The idea of using robots for surgery was born many years ago and in a short time a market demand was created. Today the market is very dynamic, and several new products are updated and created for the execution of both traditional and new procedures. The article provides a guide for the reader who has an interest in this area.

Originality/value

This paper provides an insight into the commercial robotic surgical systems and a look on research prototypes from academic and industrial worlds.

Teleoperation Robot Control of a Hybrid EEG-Based BCI Arm Manipulator Using ROS

The development of assistive robots is gaining momentum in the robotic and biomedical fields. An assistive robotic system is presented in this research paper for object manipulation to aid people with physical disabilities. The robotic arm design is imported to a simulated environment and tested in a virtual world. This research includes the development of a versatile design and testing platform for robotic applications with joint torque requirements, workspace restrictions, and control tuning parameters. Live user inputs and camera feeds are used to test the movement of the robot in the virtual environment. To create the environment and user interface, a robot operating system (ROS) is used. Live brain computer interface (BCI) commands from a trained user are successfully harvested and used as an input signal to pick a goal point from 3D point cloud data and calculate the goal position of the robots’ mobile base, placing the goal point in the robot arms workspace. The platform created allows for quick design iterations to meet different application criteria and tuning of controllers for desired motion.