UCLA

Minimally invasive surgery (MIS) has gained popularity over traditional open surgery due to its advantages of decreased incision size and pain to the patient, lower risk of infection, and shorter recovery time. Recent developments in robotic surgical systems have shown promise to further advance MIS by offering the surgeons with increased manipulability and dexterity along with 3D vision.

However, the lack of tactile feedback is the key feature that is needed for robotic surgery to reach its full potential. Recent research efforts have successfully integrated some degree of tactile feedback components onto surgical robotic instruments, and have shown significant improvement of the outcome of the surgical performance. The primary barrier to the adoption of tactile feedback in clinical use is the unavailability of suitable tri-axial force sensing technologies that can be integrated with the medical instruments. Besides well-understood normal force sensing, shear force sensing is also critical in clinical tasks, such as suturing, where shear sensing could prevent breakage of sutures due to excessive shear force.

This paper describes the design, batch microfabrication, and characterization of a miniature force sensor for providing haptic feedback in robotic surgical systems. We demonstrate for the first time a microfabricated sensor that can provide triaxial sensing (normal, x-shear, y-shear) in a single sensor element that is integrated with commercial robotic surgical graspers. Features of this capacitive force sensor include differential sensing in the shear directions as well as a design where all electrical connections are on one side, leaving the backside pristine as the sensing face for surgical tasks.

The sensor readout is performed by a custom-designed printed circuit board with 24-bit resolution. The integration of read-out circuits with the capacitive sensor is designed on two printed circuit boards that can be clipped together, providing the possibility for disposable sensors. The sensing system is first connected to the LabVIEW-based controller, to convert the analog capacitor signal to a digital signal representing force. After the functionality of the sensor is proven, the tactile sensor system is then integrated with our custom Visual Studio based feedback control system.

Initial LabVIEW results validate the batch fabrication of the capacitive sensors and the design of the control circuit. The sensor is characterized using a sensing circuit with a 24-bit resolution at 11 Hz-109 Hz. With the LabVIEW program, the sensor and the readout circuitry contribute to a noise down to 0.8 fF to the normal z-direction, 0.2 fF to the shear x-direction, and 0.9 fF to the shear y-direction at 8 Hz bandwidth.

The grasper integrated sensor system uses an Arduino based controller to multiplex between x, y, and z directions, providing 24 packets of tri-axial data per second to the Visual Studio-based computer application, with down to 0.094 fF capacitance noise to the normal z-direction, 0.078 fF to the shear x-direction, and 0.0825 fF to the shear y-direction at 87.2 Hz bandwidth. The sensitivity measured for the sensor is 14.58 fF/N for normal z direction, 0.83 fF/N for the shear x direction, and 0.62 fF/N for the shear y direction. We report a normal resolution of 6.45 mN, x-shear resolution of 94.7 mN, and y-shear resolution of 133 mN, all of which are more than sufficient for clinically relevant forces. A data latency of less than 42 ms is achieved to obtain a triaxial data package and transmit it to the computer through the WiFi network.

A user study has been performed to tackle the suture breakage phenomenon that occurs during robotic surgery with the application of excessive forces due to lack of haptic feedback. The work aims to develop and validate a bi-axial shear feedback system that warns the operator to anticipated suture breakage. The benefits of a suture breakage warning system may be a reduced incidence of suture failure with otherwise equivalent knot quality during the tying procedure.

Biaxial shear sensors were placed on the Cadiere grasper tips of a da Vinci robotic surgical system. 17 novice subjects were then instructed to tighten 10 knots made from Silk 3-0 sutures, five times with the Haptic Feedback System (HFS) enabled, and five times with the system disabled (i.e., without any feedback). During each trial, the number of suture breakages was recorded. After trial completion, knots were evaluated for tightness. This was accomplished by measuring the amount of knot slippage following knot tying. Additional metrics recorded were the time required for completing each trial and both the average force and peak force applied in each trial.

Seven suture failures occurred in trials with HFS enabled while seventeen occurred in trials without feedback. The biaxial shear sensing system reduced the incidence of suture failure by 59% (). It also resulted in 25% lower average applied force in comparison to trials without feedback (), which is relevant because average force was observed to play a role in suture breakage (p=0.03925). Results of a 55% decrease in standard deviation of quality knots tied with HFS also indicate an improvement in consistency when using the feedback system.

These results suggest this system may improve outcomes related to knot tying tasks in robotic surgery and reduce instances of suture failure while not degrading the quality of knots produced.