An Intelligent Image-Based Force Sensing System Development to Assist Robot-Arm Surgery

It is generally accepted that robotic surgery has increased in popularity which has revolutionized the medical field over the past few decades. Despite many successes and development, there are still a lot of challenges what was remained in the surgeries such as the requirement of haptic feedback system has become a raising issue due to a lot of failure cases during robotic surgery processes, for example: suture breakage because of pulling action in knot-tying, slipped on a needle of grasping action or inadequate of force. In this paper, an image-based force sensing feedback system is presented. The force feedback system can provide unmistakable for the surgeon how much force they are utilizing by showing corresponding colors, which can reduce instances of surgery failure without negatively impacting the surgeon 's performance. Visual images-based were employed to watching the distance changing of plasticity sensor during the time it was suffering an opposite reaction force from grasping action of a surgery robot arm. From the experiments, this visual images-based evaluation method can detect a minimum force value of 0.01 Newton. This system provides extraordinary accuracy of force sensing feedback and also hands controlling for a robot arm, due to the accuracy shows up to 99.96% (hands action recognition). The main distribution of this studying is to give robot-arm can use the proposed technique to estimate and utilize force values for surgical operation.