Woon Jong Yoon

Force Sensor Integrated Surgical Forceps for Minimally Invasive Robotic Surgery

This paper presents a novel surgical instrument integrated with a four-degree-of-freedom (DOF) force sensor. By adopting the capacitive transduction principle, the sensor enables the direct sensing of normal and shear forces at surgical instrument tips. Thus, three-DOF pulling forces and a single-DOF grasping force can be measured for haptic feedback control of robotic minimally invasive surgery systems. The sensor consists of four capacitive transducers, and all the transducers including analog signal processing units are embedded in small surgical instrument tips. The four-DOF force sensing is enabled thanks to the four capacitive transducers by using the force transformation method. In this study, the instrument is designed and manufactured to be adaptable to the open-source surgical robot platform, called Raven-II. In addition, the sensing system is experimentally validated through its application to the Raven-II by using a reference force sensor.

A Laparoscopic Grasping Tool With Force Sensing Capability

This paper presents a laparoscopic grasping tool for minimally invasive surgery with the capability of multiaxis force sensing. The tool is able to sense three-axis Cartesian manipulation force and a single-axis grasping force. The forces are measured by a wrist force sensor located at the distal end of the tool, and two torque sensors at the tool base, respectively. We propose an innovative design of a miniature force sensor achieving structural simplicity and potential cost effectiveness. A prototype is manufactured and experiments are conducted in a simulated surgical environment by using an open platform for surgical robot research, called Raven-II.

Preliminary design of multi-axial contact force sensor for minimally invasive robotic surgery grasper

This paper presents a preliminary design and experimental results of a multi-axial contact force sensor for robotic surgery graspers. The sensor is a thin-film type capacitive one with a multiple cell structure capable of measuring normal and shear forces at contacts simultaneously. The structure of the sensor is determined via numerical optimization for maximizing sensitivity and based on the results, a prototype is fabricated by employing the silk-screening method. The characteristics of the sensor are evaluated with a multi-axial sensor calibration set-up and the sensitivities for two directional shear forces and a normal forces are measured to be 10.1, 10.3 and 6.1%, respectively. In this study, the feasibility of the sensor is confirmed as the proof-of-concept. In our future studies, a miniaturized pair of the proposed sensor will be embedded to a surgery grasper for in vitro validation.

Controlling the Trajectory of a Flexible Ultrathin Endoscope for Fully Automated Bladder Surveillance

During cystoscopy, the urologist manually steers a cyst scope inside a patients bladder to visually inspect the inner surface. Cystoscopies are performed as part of surveillance for bladder cancer, making it the most expensive cancer to treat over a patients lifetime. An automated bladder scanning system has been devised to reduce workload and cost by relieving the urologist from performing surveillance. Presented here is a proof-of-concept apparatus that controls the motion of a miniature flexible endoscope. Image-based feedback is used to adjust the endoscopes movement so that captured images overlap with one another, ensuring that the entire inner surface of the bladder is imaged. Within a bladder phantom, the apparatus adaptively created and followed a spherical scan pattern comprised of 13 individual latitudes and 508 captured images, while accepting between 60% and 90% image overlap between adjacent images. The elapsed time and number of captured images were sensitive to the apparatuss placement within the phantom and the acceptable image overlap percentage range. A mosaic of captured images was generated to validate comprehensive surveillance. Overall, a robotically controlled endoscope used in conjunction with image-based feedback may permit fully automated and comprehensive bladder surveillance to be conducted without direct clinician oversight.

A Flexible Gastric Gas Sensor Based on Functionalized Optical Fiber

We present a gastric gas sensor based on conjoined dual optical fibers functionalized with sensitive optical dyes for sensing gases in both fluidic and gaseous environments. The sensor aims to sense various concentrations of carbon dioxide (CO2) and ammonia (NH3), which are two significant biomarkers of H. pylori infection in the stomach. It is known that CO2 and NH3 are released during the hydrolysis of urea by H. pylori, a bacterium that may cause stomach cancer with relatively high probability. CO2 and NH3 sensitive optical dyes, cresol red ion pair and zinc tetraphenylporphyrin, are embedded in silica beads and then functionalized onto the thin PDMS-coated fiber tip. Each type of dye provides a unique spectral emission response when excited with light ranging from 450 to 700 nm. Two SMA connector legs of the as-functionalized sensor are connected to an external light source for illumination and a ultraviolet-visible-near infrared (UV-Vis-NIR) spectrometer for signal collection/readout. To perform the measurements, one fiber illuminates while the other fiber collects the back-scattered light and feeds it to the UV-Vis-NIR spectrometer to measure the change in light spectrum as a function of CO2 or NH3 concentration. This method is easy and flexible and achieves ppm level sensitivity to targeted gas analytes. The proposed sensor can be integrated into a customized tethered capsule for adjunctive diagnosis of H. pylori infection to improve the accuracy of visual endoscopic inspection.

A study on surgical robot image stabilization

This study aims to investigate and analyze various image stabilization methods used in surgical robotics. An in-vitro phantom experiment was conducted using a master slave tele-manipulated system. An articulable image probe on a tool (eye-on-tool) was installed on an open-source surgical robot, RAVEN. The 2D non-stereo camera image was used to validate the image stabilization methods, which were evaluated individually for each processing step: preprocessing, motion estimation, and motion compensation. During the preprocessing procedure, the performance of three different filters was tested for effective noise suppression. Various algorithms were compared to estimate the global motion vectors (GMVs) in the motion estimation step. Finally, three filters were analyzed to estimate the compensation motion vector (CMV) during the motion estimation procedure.