Computer-assisted robotic system for autonomous unicompartmental knee arthroplasty
Shalash, Omar and Rowe, Philip (2023) Computer-assisted robotic system for autonomous unicompartmental knee arthroplasty. Alexandria Engineering Journal, 70. pp. 441-451. ISSN 1110-0168 (https://doi.org/10.1016/j.aej.2023.03.005)
Preview |
Text.
Filename: Shalash_Rowe_AEJ_2023_Computer_assisted_robotic_system_for_autonomous.pdf
Final Published Version License: Download (2MB)| Preview |
Abstract
Robotic-assisted technology has proven to enhance the accuracy of bone resection and implant placement. However, robotic-assisted technology suffers from slow speed and high cost. Moreover, usually surgeries require the performance of radioactive scans. Therefore, the aim of this research is to build a low-cost autonomous system to perform rUKA (robotic Unicompartmental Knee Arthroplasty). A novel image-free registration process has been developed to eliminate the need for radioactive scans. Additionally, a CNC machine was built to perform autonomous resection. The proposed system was tested on a set of artificial tibia bones, and analysing their surfaces of the proposed system on the tibia bones was compared to Mako and BlueBelt systems. Mean error of the tibial resections was 1.9 mm compared to 2.87 mm for the Mako system, and 3.07 mm for the BlueBelt. The maximum error for the proposed system was 2.9 mm compared to 4.99 mm in the Mako and 4.5 mm in BlueBelt. To access the code, click here https://github.com/OmarShalash/TelesurgeryAutonomousControl.git
ORCID iDs
Shalash, Omar and Rowe, Philip ORCID: https://orcid.org/0000-0002-4877-8466;-
-
Item type: Article ID code: 85266 Dates: DateEvent1 May 2023Published9 March 2023Published Online1 March 2023AcceptedSubjects: Medicine > Biomedical engineering. Electronics. Instrumentation Department: Strategic Research Themes > Health and Wellbeing
Faculty of Engineering > Biomedical EngineeringDepositing user: Pure Administrator Date deposited: 25 Apr 2023 11:00 Last modified: 11 Nov 2024 13:54 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/85266