A literature review of robotic systems showed that these systems can , similarly to computer navigation , reliably improve lower leg alignment , component positioning and soft tissues balancing .
Findings in this study suggest that computer navigation or robotic assistance may help managing these multiple variables and could improve outcomes .
Recently , there is a growing interest in surgical variables that are intraoperatively controlled by orthopaedic surgeons , including lower leg alignment , component positioning and soft tissues balancing .
Since more tight control over these factors is associated with improved outcomes of unicompartmental knee arthroplasty and total knee arthroplasty ( TKA ) , several computer navigation and robotic-assisted systems have been developed .
Although mechanical axis accuracy and component positioning have been shown to improve with computer navigation , no superiority in functional outcomes has yet been shown .
This could be explained by the fact that many differences exist between the number and type of surgical variables these systems control .
Most systems control lower leg alignment and component positioning , while some in addition control soft tissue balancing .
Finally , robotic-assisted systems have the additional advantage of improving surgical precision .
Manually controlling all these surgical variables can be difficult for the orthopaedic surgeon .
Early experiences with robot-assisted total knee arthroplasty using the DigiMatch™ ROBODOC® surgical system.
INTRODUCTION The use of robotics in total knee arthroplasty ( TKA ) has been shown to minimise human error , as well as improve the accuracy and precision of component implantation and mechanical axis alignment . The present study aim ed to demonstrate that robot-assisted TKA using ROBODOC ® is safe and capable of producing a consistent and accurate postoperative mechanical axis . METHODS We prospect ively recruited 27 consecutive patients who underwent robot-assisted TKA between May and December 2012 . Two patients were excluded from the study due to intraoperative technical problems with the robot .  Long-leg radiography and computed tomography were performed prior to surgery , and used for mechanical axis measurements and component sizing . DigiMatch ™ ROBODOC ® Surgical System software version 4.3.6 ( Curexo Technology Corp , Fremont , CA , USA ) was used in all cases to perform bone cuts in accordance with the preoperative plan . RESULTS The postoperative coronal mechanical alignment was within 3 degrees , with a mean alignment of -0.4 ± 1.7 degrees , confirming the accuracy of the preoperative surgical plan and bone cuts . The mean operating time was 96 ± 15 min , and preoperative planning yielded 100 % implant sizing accuracy . CONCLUSION Robotics has the potential to enable surgeons to consistently attain ideal postoperative alignment . The use of bone movement monitors and an integrated navigation system enhances the safety profile of ROBODOC ® by minimising errors . However , the role of the surgeon in TKA is still vital , as the surgeon is ultimately in charge of planning the surgery , its execution and ensuring soft tissue balance during TKA
A literature review of robotic systems showed that these systems can , similarly to computer navigation , reliably improve lower leg alignment , component positioning and soft tissues balancing .
Findings in this study suggest that computer navigation or robotic assistance may help managing these multiple variables and could improve outcomes .
Recently , there is a growing interest in surgical variables that are intraoperatively controlled by orthopaedic surgeons , including lower leg alignment , component positioning and soft tissues balancing .
Since more tight control over these factors is associated with improved outcomes of unicompartmental knee arthroplasty and total knee arthroplasty ( TKA ) , several computer navigation and robotic-assisted systems have been developed .
Although mechanical axis accuracy and component positioning have been shown to improve with computer navigation , no superiority in functional outcomes has yet been shown .
This could be explained by the fact that many differences exist between the number and type of surgical variables these systems control .
Most systems control lower leg alignment and component positioning , while some in addition control soft tissue balancing .
Finally , robotic-assisted systems have the additional advantage of improving surgical precision .
Manually controlling all these surgical variables can be difficult for the orthopaedic surgeon .