A novel toolpath force prediction algorithm using CAM volumetric data for optimizing robotic arthroplasty

• Published in: International journal for computer assisted radiology and surgery Vol. 11; no. 10; pp. 1871 - 1880
• Main Authors: Kianmajd, Babak, Carter, David, Soshi, Masakazu
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2016; Springer Nature B.V
• Subjects: Algorithms; Application programming interface; Arthroplasty, Replacement, Hip - methods; Biomedical materials; CAM; Computer aided manufacturing; Computer Imaging; Computer Science; Computer-Aided Design; Cutting force; Cutting parameters; Cutting tool paths; Femur; Femur - surgery; Health Informatics; Hip; Humans; Imaging; Medicine; Medicine & Public Health; Milling (machining); Motion control; Original Article; Orthopedics; Pattern Recognition and Graphics; Prostheses; Radiology; Robotic Surgical Procedures - methods; Software; Surgery; Vision; Toolpath prediction; Orthopedic milling; Cutting forces; CAM software
• ISSN: 1861-6410; 1861-6429
• DOI: 10.1007/s11548-016-1355-x

Purpose Robotic total hip arthroplasty is a procedure in which milling operations are performed on the femur to remove material for the insertion of a prosthetic implant. The robot performs the milling operation by following a sequential list of tool motions, also known as a toolpath, generated by a computer-aided manufacturing (CAM) software. The purpose of this paper is to explain a new toolpath force prediction algorithm that predicts cutting forces, which results in improving the quality and safety of surgical systems. Methods With a custom macro developed in the CAM system’s native application programming interface, cutting contact patch volume was extracted from CAM simulations. A time domain cutting force model was then developed through the use of a cutting force prediction algorithm. The second portion validated the algorithm by machining a hip canal in simulated bone using a CNC machine. Average cutting forces were measured during machining using a dynamometer and compared to the values predicted from CAM simulation data using the proposed method. Results The results showed the predicted forces matched the measured forces in both magnitude and overall pattern shape. However, due to inconsistent motion control, the time duration of the forces was slightly distorted. Nevertheless, the algorithm effectively predicted the forces throughout an entire hip canal procedure. Conclusion This method provides a fast and easy technique for predicting cutting forces during orthopedic milling by utilizing data within a CAM software.