Developing a high-performance patient-to-image registration system for robotic cochlear implant surgery

Abstract

This thesis presents the research to design a successful high-accuracy, sub-millimetric registration method for an autonomous robot equipped to drill bone for cochlear implant (CI) surgery. Its performance, and thus success, is measured in accuracy, workload, usability and trust. While state-of-the-art (STOTA) research lacks the inclusion of human-robot interaction (HRI) related design requirements, this thesis demonstrates its significance. The HRI-focused design led to a successful multi-modal, multi-feedback admittance control, touch-based pair-point bone-anchored fiducial registration method.
A successful high-accuracy registration method is critical for image-guided robotic microsurgery as it contributes directly to its overall surgical precision. The inclusion of HRI-related requirements is concluded to be essential for the success of registration methods for surgical robots due to their inevitable involvement in a hospital workflow consisting of human teams and their lack of autonomous capabilities in all required tasks.
Gaining knowledge through theoretical and empirical research; utilising exclusion and scoring criteria to select the best specific registration method concept; and performing an extensive error- and human-factor analysis to determine the design implementations led to the design of a multi-modal multi-feedback admittance control, touch-based pair-point bone-anchored fiducial registration method. The design allows operators to execute a localisation task in collaboration with the robot. This design concerned a human operator physically guiding the robot end-effector to four bone-anchored fiducials attached to a skull-resembling setup to execute their localisation. The robot control was based on an admittance controller that enables the human to move the robot through the sensed interaction force at the robot’s end-effector. Consequently, if the operator exerted a forwarded force on the robot, it moved in that direction proportionally with the preset admittance parameters.
This guidance control contained five modes of control: (1) translational, (2) rotational, (3) fixed, (4) safety and (5) registration mode. Each mode allows the operator to control the robot as needed to achieve high accuracy, usability, trust, and a low workload. To switch between modes, the human operator utilised a foot-operated interface with several buttons, each dedicated to a specific function.
The translational mode had a fixed orientation and permitted free movements of various speeds along translational axes and was used for correctly arranging the end-effector to the fiducial centre in the x-, y- and z-axis. The rotational mode allowed orientation movement while preserving a fixed translational position and was employed for aligning the end-effector perpendicular to the fiducial centre. The fixed mode included a fixed orientation and translational position and was used for filtering out perturbations presented by the human operator. The safety mode allowed the robot to with-tract to a safety position and orientation in case of operator inactivity and was utilised to ensure patient safety. The registration mode allows for saving the end-effector position, hence localising the fiducials.
The feedback provided to the operator consisted of visual feedback, auditory feedback and a step-by-step graphical user interface (GUI). The visual feedback permitted colour coding of the modes of control and safety thresholds regarding force, torque and workspace. This was used to build operator awareness and control large errors introduced by operator input. The auditory feedback included a sound when localisation of the end-effector was completed and was utilised to form operator awareness and prevent timing errors. The GUI contained safety checklists, workflow guidance and operator performance feedback and was used to minimise operator variations.
To compare and benchmark our design, the baseline included a similar STOTA non-HRI focused single-mode no feedback admittance control touch-based pair-point bone-anchored registration method. This baseline method allowed a human operator to guide the robot end-effector in the translational axis and save fiducial localisation positions in cooperation with a second human operator. The comparison study involved a quasi-experiment of two groups with 13 and 14 participants, respectively. The groups executed repeated fiducial localisation and were compared on their system accuracy, workload, usability and trust.
The system accuracy was measured in fiducial localisation error (FLE) and target registration error (TRE) based on repeated measurements of each fiducial. The workload was estimated quantitatively in average operator force and qualitatively with a NASA TLX survey. Usability was calculated with the Computer System Usability Questionnaire (CSUQ) and System Usability Scale (SUS). The Trust Perception Scale-HRI measured trust. The design achieved the second-highest accuracy from all discovered STOTA registration methods. Furthermore, it reduced the operator workload and improved usability and accuracy compared to a non-HRI-focused design.
This thesis concludes that an HRI-focused symbiotic design provides a successful high-accuracy sub-millimetric registration method for robotic surgery as measured by accuracy, workload and usability.

To a future where humans and machines live together in harmony.



The comparison study in this thesis is performed in agreement with the TU Delft Human Research Ethics Committee (HREC).