Surgical Grasping Forceps With Enhanced Sensorimotor Capability via the Stochastic Resonance Effect

Abstract

Haptic information is crucial in the execution of precise dexterous manipulations. Laparoscopic surgery, a type of minimally invasive surgery, requires that the surgeon senses force information about tissue through forceps, because he or she cannot touch the organs directly. We propose the concept of surgical grasping forceps with enhanced sensorimotor capability based on attaching a vibrator to the forceps’ grip by evoking a stochastic resonance (SR) effect. To apply appropriate vibrations, a summing network of FitzHugh–Nagumo neurons was built to investigate the system's response when white noise was applied to each of the four types of tactile receptor. The relation among the tactile sensitivity, noise intensity, and amplitude of input signal is discussed by the simulation with the neural network composed of different tactile receptors. The simulation results revealed that the working range of the SR effect is extended by taking advantage of having multiple receptors with different characteristics in skins. It was also found that improved tactile sensitivity could be obtained even without a strict set of vibration intensity values. Based on the findings from the simulation, we developed surgical forceps with sensorimotor-enhancing capability taking advantage of the SR effect. The forceps are equipped with a lead zirconate titanate actuator at the grip as a vibration source. We conducted touch testing, texture discrimination testing, and tumor detection testing to verify their improved tactile sensitivity. The experiments conducted with the proposed forceps showed that maintaining the noise intensity within the optimal range could improve tactile sensitivity, and confirmed the usefulness of the SR application for medical devices.