Improved Tactile Resonance Sensor for Robotic Assisted Surgery

TL;DR

This paper introduces an improved piezoelectric tactile sensor capable of distinguishing soft materials with similar properties, aiming to enhance tissue differentiation in robotic-assisted brain tumor surgeries.

Contribution

The paper develops a novel tactile sensor using a bimorph piezoelectric element and demonstrates its effectiveness in differentiating soft tissues for surgical applications.

Findings

Sensor can identify minimal differences in tissue consistency.

Linear model is sufficient for contact property measurement.

Sensor shows high reliability in tests with gelatine phantoms.

Abstract

This paper presents an improved tactile sensor using a piezoelectric bimorph able to differentiate soft materials with similar mechanical characteristics. The final aim is to develop intelligent surgical tools for brain tumour resection using integrated sensors in order to improve tissue tumour delineation and tissue differentiation. The bimorph sensor is driven using a random phase multisine and the properties of contact between the sensor's tip and a certain load are evaluated by means of the evaluation of the nonparametric FRF. An analysis of the nonlinear contributions is presented to show that the use of a linear model is feasible for the measurement conditions. A series of gelatine phantoms were tested. The tactile sensor is able to identify minimal differences in the consistency of the measured samples considering viscoelastic behaviour. A variance analysis was performed to evaluate the reliability of the sensors and to identify possible error sources due to inconsistencies in the preparation method of the phantoms. The results of the variance analysis are discussed showing that ability of the proposed tactile sensor to perform high quality measurements.