Toward Fully Automated Robotic Platform for Remote Auscultation

Since most developed countries are facing an increase in the number of patients per healthcare worker due to a declining birth rate and an aging population, relatively simple and safe diagnosis tasks may need to be performed using robotics and automation technologies, without specialists and hospitals. This study presents an automated robotic platform for remote auscultation, which is a highly cost-effective screening tool for detecting abnormal clinical signs. The developed robotic platform is composed of a 6-degree-of-freedom cooperative robotic arm, light detection and ranging (LiDAR) camera, and a spring-based mechanism holding an electric stethoscope. The platform enables autonomous stethoscope positioning based on external body information acquired using the LiDAR camera-based multi-way registration; the platform also ensures safe and flexible contact, maintaining the contact force within a certain range through the passive mechanism. Our preliminary results confirm that the robotic platform enables estimation of the landing positions required for cardiac examinations based on the depth and landmark information of the body surface. It also handles the stethoscope while maintaining the contact force without relying on the push-in displacement by the robotic arm.Comment: 8 pages, 11 figure

Design and integration of a parallel, soft robotic end-effector for extracorporeal ultrasound

Objective: In this work we address limitations in state-of-the-art ultrasound robots by designing and integrating a novel soft robotic system for ultrasound imaging. It employs the inherent qualities of soft fluidic actuators to establish safe, adaptable interaction between ultrasound probe and patient. Methods: We acquire clinical data to determine the movement ranges and force levels required in prenatal foetal ultrasound imaging and design the soft robotic end-effector accordingly. We verify its mechanical characteristics, derive and validate a kinetostatic model and demonstrate controllability and imaging capabilities on an ultrasound phantom. Results: The soft robot exhibits the desired stiffness characteristics and is able to reach 100% of the required workspace when no external force is present, and 95% of the workspace when considering its compliance. The model can accurately predict the end-effector pose with a mean error of 1.18+/-0.29mm in position and 0.92+/-0.47deg in orientation. The derived controller is, with an average position error of 0.39mm, able to track a target pose efficiently without and with externally applied loads. Ultrasound images acquired with the system are of equally good quality compared to a manual sonographer scan. Conclusion: The system is able to withstand loads commonly applied during foetal ultrasound scans and remains controllable with a motion range similar to manual scanning. Significance: The proposed soft robot presents a safe, cost-effective solution to offloading sonographers in day-to-day scanning routines. The design and modelling paradigms are greatly generalizable and particularly suitable for designing soft robots for physical interaction tasks

Robotic Ultrasound Tomography and Collaborative Control

Ultrasound computed tomography (USCT) offers quantitative anatomical tissue characterization for cancer detection, and has shown similar diagnostic power to MRI on ex vivo prostate tissue. While most USCT research and commercial development has focused on submerging target anatomy in a transducer-lined cylindrical water-tank, this approach is not practical for imaging deep anatomy like the prostate and an alternative acquisition system using aligned abdominal and endolumenal ultrasound probes is required. This work outlines a clinical workflow, calibration scheme, and motion framework for an innovative dual-robotic USCT acquisition system specific to in vivo prostate imaging – one arm wielding a linear abdominal probe, the other wielding a linear transrectal ultrasound (TRUS) probe. After a three-way calibration, the robotic system works to autonomously keep the abdominal probe collinear with the physician-rotated TRUS probe using a hybrid force-position convex contour tracking scheme, while impedance control enforces its gentle contact with the patient’s pubic region for capturing the transmission ultrasound slices needed for limited-angle tomographic reconstruction. TRUS rotation was induced by joystick control for precision during testing, however collaborative control via admittance control of hand forces presents a useful workflow option to the physician. An improved robot admittance control algorithm for transparent collaborative control utilizing Kalman filtering was developed and verified to smooth robot hand guidance. Such an improvement additionally has important implications for generally alleviating ultrasonographer musculoskeletal strain through cooperatively controlled robots. The ultimate dual-robotic USCT system proved repeatable and sufficiently accurate for tomography based on pelvic phantom testing. Future steps in system verification and validation are discussed, as is incorporation into feasibility studies to test the potential and utility of the system for future prostate malignancy diagnosis and staging in vivo

Towards the development of safe, collaborative robotic freehand ultrasound

The use of robotics in medicine is of growing importance for modern health services, as robotic systems have the capacity to improve upon human tasks, thereby enhancing the treatment ability of a healthcare provider. In the medical sector, ultrasound imaging is an inexpensive approach without the high radiation emissions often associated with other modalities, especially when compared to MRI and CT imaging respectively. Over the past two decades, considerable effort has been invested into freehand ultrasound robotics research and development. However, this research has focused on the feasibility of the application, not the robotic fundamentals, such as motion control, calibration, and contextual awareness. Instead, much of the work is concentrated on custom designed robots, ultrasound image generation and visual servoing, or teleoperation. Research based on these topics often suffer from important limitations that impede their use in an adaptable, scalable, and real-world manner. Particularly, while custom robots may be designed for a specific application, commercial collaborative robots are a more robust and economical solution. Otherwise, various robotic ultrasound studies have shown the feasibility of using basic force control, but rarely explore controller tuning in the context of patient safety and deformable skin in an unstructured environment. Moreover, many studies evaluate novel visual servoing approaches, but do not consider the practicality of relying on external measurement devices for motion control. These studies neglect the importance of robot accuracy and calibration, which allow a system to safely navigate its environment while reducing the imaging errors associated with positioning. Hence, while the feasibility of robotic ultrasound has been the focal point in previous studies, there is a lack of attention to what occurs between system design and image output. This thesis addresses limitations of the current literature through three distinct contributions. Given the force-controlled nature of an ultrasound robot, the first contribution presents a closed-loop calibration approach using impedance control and low-cost equipment. Accuracy is a fundamental requirement for high-quality ultrasound image generation and targeting. This is especially true when following a specified path along a patient or synthesizing 2D slices into a 3D ultrasound image. However, even though most industrial robots are inherently precise, they are not necessarily accurate. While robot calibration itself has been extensively studied, many of the approaches rely on expensive and highly delicate equipment. Experimental testing showed that this method is comparable in quality to traditional calibration using a laser tracker. As demonstrated through an experimental study and validated with a laser tracker, the absolute accuracy of a collaborative robot was improved to a maximum error of 0.990mm, representing a 58.4% improvement when compared to the nominal model. The second contribution explores collisions and contact events, as they are a natural by-product of applications involving physical human-robot interaction (pHRI) in unstructured environments. Robot-assisted medical ultrasound is an example of a task where simply stopping the robot upon contact detection may not be an appropriate reaction strategy. Thus, the robot should have an awareness of body contact location to properly plan force-controlled trajectories along the human body using the imaging probe. This is especially true for remote ultrasound systems where safety and manipulability are important elements to consider when operating a remote medical system through a communication network. A framework is proposed for robot contact classification using the built-in sensor data of a collaborative robot. Unlike previous studies, this classification does not discern between intended vs. unintended contact scenarios, but rather classifies what was involved in the contact event. The classifier can discern different ISO/TS 15066:2016 specific body areas along a human-model leg with 89.37% accuracy. Altogether, this contact distinction framework allows for more complex reaction strategies and tailored robot behaviour during pHRI. Lastly, given that the success of an ultrasound task depends on the capability of the robot system to handle pHRI, pure motion control is insufficient. Force control techniques are necessary to achieve effective and adaptable behaviour of a robotic system in the unstructured ultrasound environment while also ensuring safe pHRI. While force control does not require explicit knowledge of the environment, to achieve an acceptable dynamic behaviour, the control parameters must be tuned. The third contribution proposes a simple and effective online tuning framework for force-based robotic freehand ultrasound motion control. Within the context of medical ultrasound, different human body locations have a different stiffness and will require unique tunings. Through real-world experiments with a collaborative robot, the framework tuned motion control for optimal and safe trajectories along a human leg phantom. The optimization process was able to successfully reduce the mean absolute error (MAE) of the motion contact force to 0.537N through the evolution of eight motion control parameters. Furthermore, contextual awareness through motion classification can offer a framework for pHRI optimization and safety through predictive motion behaviour with a future goal of autonomous pHRI. As such, a classification pipeline, trained using the tuning process motion data, was able to reliably classify the future force tracking quality of a motion session with an accuracy of 91.82 %

Improving access to ultrasound imaging in northern, remote communities

Access to healthcare services—including access to medical imaging—is an important determinant of health outcomes. This thesis aims to improve understanding of and address gaps in access to ultrasound imaging for patients in northern, remote communities, and advance a novel ultrasound technology with the ultimate goal of improving patient care and health outcomes. This thesis first brings greater understanding of patients’ perceptions of access and factors which shape access to ultrasound imaging in northern, remote communities in Saskatchewan, Canada. A qualitative study was performed using interpretive description as a methodological approach and a multi-dimensional conceptualization of access to care as a theoretical framework. The study identified barriers which patients in northern, remote communities face in accessing ultrasound imaging, and demonstrated that geographic remoteness from imaging facilities was a central barrier. To determine whether disparities in access to ultrasound imaging resulted in disparities in utilization of ultrasound services, two population-based studies assessed the association between sociodemographic and geographic factors and obstetrical and non-obstetrical ultrasound utilization in Saskatchewan. In the first study investigating obstetrical ultrasound utilization, multivariate logistic regression analysis demonstrated that women living in rural areas, remote areas, and low income neighbourhoods, as well as status First Nations women, were less likely to have a second trimester ultrasound, an important aspect of prenatal care. In a second study investigating non-obstetrical ultrasound utilization across the entire provincial population, multivariate Poisson regression analysis similarly demonstrated lower rates of non-obstetrical ultrasound utilization among individuals living in rural and remote areas, individuals residing in low income neighbourhoods, and status First Nations persons. To address the barriers which patients in northern, remote communities face in accessing ultrasound imaging and to minimize disparities in ultrasound imaging utilization as identified in previous studies in this thesis, telerobotic ultrasound technology was investigated as a solution to improve access to ultrasound imaging. Using this technology, radiologists and sonographers could remotely manipulate an ultrasound probe via a robotic arm, thereby remotely performing an ultrasound exam while patients remained in their home community. A clinical trial comparing conventional and telerobotic ultrasound approaches was undertaken, validating this technology for obstetrical ultrasound imaging. To determine the feasibility of using telerobotic technology to establish an ultrasound service delivery model to remotely provide diagnostic ultrasound exams in underserved communities, pilot telerobotic ultrasound clinics were developed in three northern, remote communities. Telerobotic ultrasound exams were sufficient for diagnosis in the majority of cases, minimizing travel or reducing wait times for these patients. This technology was subsequently evaluated during a COVID-19 outbreak in northern Saskatchewan, demonstrating the potential of this technology to provide critical ultrasound services to an underserved northern population and minimize health inequities during the COVID-19 pandemic. An economic evaluation was performed to compare a service delivery model using telerobotic ultrasound technology to alternative service delivery models. Telerobotic ultrasound combined with an itinerant sonographer service was found to be the lowest cost option from both a publicly funded healthcare payer perspective and a societal perspective for many northern, remote communities. This thesis provides key insights for health system leaders seeking improved understanding and novel solutions to improve access to ultrasound imaging in northern, remote communities. Findings suggest that telerobotic ultrasound is a viable solution to improve access to ultrasound imaging and reduce costs associated with ultrasound service delivery. Evidence in this thesis may be used to help improve ultrasound services and health equity for patients in underserved northern, remote communities. Continued respectful collaboration with northern, remote, Indigenous peoples and communities will be a critical aspect to ensure that ultrasound services meet community needs

Enabling Technologies for Co-Robotic Translational Ultrasound and Photoacoustic Imaging

Among many medical imaging modalities, medical ultrasound possesses its unique advantages of non-ionizing, real-time, and non-invasive properties. With its safeness, ease of use, and cost-effectiveness, ultrasound imaging has been used in a wide variety of diagnostic applications. Photoacoustic imaging is a hybrid imaging modality merging light and ultrasound, and reveals the tissue metabolism and molecular distribution with the utilization of endo- and exogenous contrast agents. With the emergence of photoacoustic imaging, ultrasound and photoacoustic imaging can comprehensively depict not only anatomical but also functional information of biological tissue. To broaden the impact of translational ultrasound and photoacoustic imaging, this dissertation focuses on the development of enabling technologies and the exploration of associated applications. The goals of these technologies are; (1) Enabling Technologies for Translational Photoacoustic Imaging. We investigated the potential of maximizing the access to translational photoacoustic imaging using a clinical ultrasound scanner and a low-cost light source, instead of widely used customized data acquisition system and expensive high power laser. (2) Co-robotic Ultrasound and Photoacoustic Imaging. We introduced a co-robotic paradigm to make ultrasound/photoacoustic imaging more comprehensive and capable of imaging deeper with higher resolution and wider field-of-view.(3) Advancements on Translational Photoacoustic Imaging. We explored the new use of translational photoacoustic imaging for molecular-based cancer detection and the sensing of neurotransmitter activity in the brain. Together, these parts explore the feasibility of co-robotic translational ultrasound and photoacoustic imaging