Reproducibility challenges in robotic surgery.

Reproducibility of results is, in all research fields, the cornerstone of the scientific method and the minimum standard for assessing the value of scientific claims and conclusions drawn by other scientists. It requires a systematic approach and accurate description of the experimental procedure and data analysis, which allows other scientists to follow the steps described in the published work and obtain the "same results." In general and in different research contexts with "same" results, we mean different things. It can be almost identical measures in a fully deterministic experiment or "validation of a hypothesis" or statistically similar results in a non-deterministic context. Unfortunately, it has been shown by systematic meta-analysis studies that many findings in fields like psychology, sociology, medicine, and economics do not hold up when other researchers try to replicate them. Many scientific fields are experiencing what is generally referred to as a "reproducibility crisis," which undermines the trust in published results, imposes a thorough revision of the methodology in scientific research, and makes progress difficult. In general, the reproducibility of experiments is not a mainstream practice in artificial intelligence and robotics research. Surgical robotics is no exception. There is a need for developing new tools and putting in place a community effort to allow the transition to more reproducible research and hence faster progress in research. Reproducibility, replicability, and benchmarking (operational procedures for the assessment and comparison of research results) are made more complex for medical robotics and surgical systems, due to patenting, safety, and ethical issues. In this review paper, we selected 10 relevant published manuscripts on surgical robotics to analyze their clinical applicability and underline the problems related to reproducibility of the reported experiments, with the aim of finding possible solutions to the challenges that limit the translation of many scientific research studies into real-world applications and slow down research progress.

Disposable Stiffness Sensor for Endoscopic Examination.

Since direct manual palpation is not possible in minimally invasive procedures, there is an active field of applied research which aims to retrieve the human sense of touch and feedback tissue properties through artificial tactile feedback. This paper presents an innovative stiffness sensor to be embedded at the tip of a commercial endoscopic camera. The sensor structure is based on multiple cantilever beams, which act as springs with different stiffness when indented into soft tissue. Geometric features mounted on the beams are tracked during physical contact. Movements of thecantilevers result in shape variations of the features in the camera images. The feature size is then segmented and related to the force exerted into the contact location. As beams of different elasticity are integrated, it is possible to estimate the stiffness properties of the soft tissue by employing only visual information. In this paper, Finite Element Analysis (FEA) was implemented to simulate and estimate how contact forces will affect the material and design of the prototype. A calibration device has been developed and used to validate the outcome of the FEA simulations. An experimental test showed the ability of the proposed mechanism to compute the stiffness of a soft phantom.

Real-Time Vision-Based Stiffness Mapping †.

This paper presents new findings concerning a hand-held stiffness probe for the medical diagnosis of abnormalities during palpation of soft-tissue. Palpation is recognized by the medical community as an essential and low-cost method to detect and diagnose disease in soft-tissue. However, differences are often subtle and clinicians need to train for many years before they can conduct a reliable diagnosis. The probe presented here fills this gap providing a means to easily obtain stiffness values of soft tissue during a palpation procedure. Our stiffness sensor is equipped with a multi degree of freedom (DoF) Aurora magnetic tracker, allowing us to track and record the 3D position of the probe whilst examining a tissue area, and generate a 3D stiffness map in real-time. The stiffness probe was integrated in a robotic arm and tested in an artificial environment representing a good model of soft tissue organs; the results show that the sensor can accurately measure and map the stiffness of a silicon phantom embedded with areas of varying stiffness.

Embedded electro-conductive yarn for shape sensing of soft robotic manipulators.

Flexible soft and stiffness-controllable surgical manipulators enhance the manoeuvrability of surgical tools during Minimally Invasive Surgery (MIS), as opposed to conventional rigid laparoscopic instruments. These flexible and soft robotic systems allow bending around organs, navigating through complex anatomical pathways inside the human body and interacting inherently safe with its soft environment. Shape sensing in such systems is a challenge and one essential requirement for precise position feedback control of soft robots. This paper builds on our previous work integrating multiple optical fibres into a soft manipulator to estimate the robot's pose using light intensity modulation. Here, we present an enhanced version of our embedded bending/shape sensor based on electro-conductive yarn. The new system is miniaturised and able to measure bending behaviour as well as elongation. The integrated yarn material is helically wrapped around an elastic strap and protected inside a 1.5mm outer-diameter stretchable pipe. Three of these resulting stretch sensors are integrated in the periphery of a pneumatically actuated soft manipulator for direct measurement of the actuation chamber lengths. The capability of the sensing system in measuring the bending curvature and elongation of the arm is evaluated.

A continuum body force sensor designed for flexible surgical robotics devices.

This paper presents a novel three-axis force sensor based on optical photo interrupters and integrated with the robot arm STIFF-FLOP (STIFFness controllable Flexible and Learnable Manipulator for Surgical Operations) to measure external interacting forces and torques. The ring-shape bio-compatible sensor presented here embeds the distributed actuation and sensing system of the STIFF-FLOP manipulator and is applicable to the geometry of its structure as well to the structure of any other similar soft robotic manipulator. Design and calibration procedures of the device are introduced: experimental results allow defining a stiffness sensor matrix for real-time estimation of force and torque components and confirm the usefulness of the proposed optical sensing approach.