Image-Based Optical-Fiber Force Sensor for Minimally Invasive Surgery with ex-vivo Validation

Abstract

During minimally invasive surgery, surgeons insert specially-designed instruments through a small incision into the patient’s body. Despite all the advantages of this procedure, surgeons do not have the natural force feedback in the surgery. Force feedback helps the surgeon to apply an appropriate force to avoid tissue damage. As a solution, this study was aimed at the ex-vivo validation of a proposed image-based optical force sensor with light intensity modulation principle. The sensor was to be integrated with conventional minimally invasive instruments and was working based on variable bending radius sensing principle. To this end, the sensor was integrated on the jaw of a custom-designed minimally invasive grasper and its performance was assessed ex-vivo. Furthermore, the light intensity measurement of this study was performed utilizing an image-based technique to avoid the complexities of using photodetectors. The sensor was calibrated using a rate-dependent learning-based support-vector-regression model, which showed an adjusted−R 2 of 94%. The results of the ex-vivo test on a freshly excised bovine muscle tissue showed fair agreement between sensor measurements and ground truth. Therefore, the proposed sensor was concluded as applicable for minimally invasive surgeries by comparing the minimum performance requirements of force sensors for surgical applications.