Design, testing and modelling of a novel robotic system for trans-oesophageal ultrasound: Novel robotic system for trans-oesophageal ultrasound

Design of a Novel Haptic Joystick for the Teleoperation of Continuum-Mechanism-Based Medical Robots

Continuum robots are increasingly used in medical applications and the master–slave-based architectures are still the most important mode of operation in human–machine interaction. However, the existing master control devices are not fully suitable for either the mechanical mechanism or the control method. This study proposes a brand-new, four-degree-of-freedom haptic joystick whose main control stick could rotate around a fixed point. The rotational inertia is reduced by mounting all powertrain components on the base plane. Based on the design, kinematic and static models are proposed for position perception and force output analysis, while at the same time gravity compensation is also performed to calibrate the system. Using a continuum-mechanism-based trans-esophageal ultrasound robot as the test platform, a master–slave teleoperation scheme with position–velocity mapping and variable impedance control is proposed to integrate the speed regulation on the master side and the force perception on the slave side. The experimental results show that the main accuracy of the design is within 1.6°. The workspace of the control sticks is −60° to 110° in pitch angle, −40° to 40° in yaw angle, −180° to 180° in roll angle, and −90° to 90° in translation angle. The standard deviation of force output is within 8% of the full range, and the mean absolute error is 1.36°/s for speed control and 0.055 N for force feedback. Based on this evidence, it is believed that the proposed haptic joystick is a good addition to the existing work in the field with well-developed and effective features to enable the teleoperation of continuum robots for medical applications.

Towards Standardized Acquisition with a Dual-probe Ultrasound Robot for Fetal Imaging

Standardized acquisitions and diagnoses using robots and AI would potentially increase the general usability and reliability of medical ultrasound. Working towards this prospect, this paper presents the recent developments of a standardized acquisition workflow using a novel dual-probe ultrasound robot, for a project known as intelligent Fetal Imaging and Diagnosis (iFIND). The workflow includes an abdominal surface mapping step to obtain a non-parametric spline surface, a rule-based end-point calculation method to position each individual joint, and a motor synchronization method to achieve a smooth motion towards a target point. The design and implementation of the robot are first presented in this paper and the proposed workflow is then explained in detail with simulation and volunteer experiments performed and analyzed. The closed-form analytical solution to the specific motion planning problem has demonstrated a reliable performance controlling the robot to move towards the expected scanning areas and the calculated proximity of the robot to the surface shows that the robot maintains a safe distance while moving around the abdomen. The volunteer study has successfully demonstrated the reliable working and controllability of the robot in terms of acquiring desired ultrasound views. Our future work will focus on improving the motion planning, and on integrating the proposed standardized acquisition workflow with newly- developed ultrasound image processing methods to obtain diagnostic results in an accurate and consistent way.

Autopilots in the Operating Room

Automated medical technology is becoming an integral part of routine anesthetic practice. Automated technologies can improve patient safety, but may create new workflows with potentially surprising adverse consequences and cognitive errors that must be addressed before these technologies are adopted into clinical practice. Industries such as aviation and nuclear power have developed techniques to mitigate the unintended consequences of automation, including automation bias, skill loss, and system failures. In order to maximize the benefits of automated technology, clinicians should receive training in human–system interaction including topics such as vigilance, management of system failures, and maintaining manual skills. Medical device manufacturers now evaluate usability of equipment using the principles of human performance and should be encouraged to develop comprehensive training materials that describe possible system failures. Additional research in human–system interaction can improve the ways in which automated medical devices communicate with clinicians. These steps will ensure that medical practitioners can effectively use these new devices while being ready to assume manual control when necessary and prepare us for a future that includes automated health care.

Adaptive Neuro-Fuzzy Inference System Based Orientation Control of an Intra-operative Ultrasound Robot

Trans-esophageal echocardiography (TEE) is a miniatured intra-operative ultrasound system, widely used in routine diagnosis and interventional procedure monitoring, to assess cardiac structures and functions. As a way to assist the operation of TEE remotely, we have developed an add-on robotic system to actuate a commercial TEE probe. For the proposed robot, understanding the inverse kinematics (IK) which relates the probe pose to the joint parameters is the fundamental step towards automatic control of the system. Rather than using conventional numerical-based techniques which may have problems with speed, convergence, and stability when applying to the TEE robot, this paper explores a soft computing approach by constructing an Adaptive Neuro-Fuzzy Inference System (ANFIS) to learn from training data generated by the forward kinematics (FK) and then computing the inverse kinematics in order to control the orientation of the TEE probe. With 1900 training data over 40 epochs, the minimum training error for each joint parameter was found to be less than 0.1 degree. Validation using a separate data set has indicated that the maximum error was less than 0.3 degree for each joint parameter. It is therefore concluded that the ANFIS-based approach is an effective way, with acceptable accuracy, to compute the inverse kinematics of the TEE robot.

Strategy for Monitoring Cardiac Interventions with an Intelligent Robotic Ultrasound Device

In recent years, 3D trans-oesophageal echocardiography (TOE) has become widely used for monitoring cardiac interventions. The control of the TOE probe during the procedure is a manual task which is tedious and harmful for the operator when exposed to radiation. To improve this technique, an add-on robotic system has been developed for holding and manipulating a commercial TOE probe. This paper focuses on the probe adjustment strategy in order to accurately monitor the moving intra-operative catheters. The positioning strategy is divided into an initialization step based on a pre-planning method, and a localized adjustment step based on the robotic differential kinematics. A series of experiments was performed to evaluate the initialization and the localized adjustment steps. The results indicate a mean error less than 10 mm from the phantom experiments for the initialization step, and a median error less than 1.5 mm from the computer-based simulation experiments for the localized adjustment step. Compared to the much bigger image volume, it is concluded that the proposed methods are feasible for this application. Future work will focus on evaluating the method in a more realistic TOE scanning scenario.