Applying Palpation Forces on a Lower Jaw Model Using a Collaborative Robotic Arm.

Abstract

Traditional medical diagnostics heavily rely on the subjective expertise of physicians during palpation procedures, where muscles or tissues are examined by manually applying pressure. This work presents a robotic solution using a KUKA iiwa 14 R820 to replicate this diagnostic technique, for addressing the physician shortage, enhancing physician training, and integrating robotic arms into diagnostics. We emulate the palpation process, measure and analyze the forces applied by the robot on a test bench, and compare the uncertainty with palpation forces applied by physicians and the palpometer. As pain perception during palpation can indicate potential underlying conditions, we further incorporate a pain equivalence measurement into our system using a hand grip force sensor, completing it by developing a graphical user interface for visualization and control. Our results indicate that, while errors within the robot dominate the accuracy of the force application, a well-chosen robot configuration achieves comparable force application errors at typical palpation forces of approximately 5 N, 10 N, and 20 N. The resulting maximum errors are 1.24 N, 0.67 N, and 0.565 N, respectively, which are smaller for both larger forces than the palpation uncertainties of trained physicians. Our findings demonstrate that robotic systems can effectively emulate and refine palpation techniques, providing a foundation for their broader adoption in healthcare.