ABSTRACT
Background: The analysis of gait is an important tool for evaluating postoperative outcomes of a Total Knee Replacement (TKR). There are few studies which have evaluated the gait parameters of a Kinematic retaining (Kr) prosthesis. This study therefore aims to investigate the kinetic and kinematic differences of running and walking, in the ankle, knee and hip joints in patients who underwent a Kr TKR. Methods: This study assessed the gait of 12 patients with physica lima Kr TKRs at 1 year follow up and 8 healthy controls using 3D video analysis. Data was collected on the kinetics and kinematics of walking and running at the ankle, knee and hip. Comparison was made between the operated and non-operated limbs of the patients, and between the operated and control limbs. Results: Gait analysis showed no statistically significant difference in the hip, ankle and knee angles or moments between the non-operated and operated legs during walking and running. However, there was a statistically significant difference between the knee angles of initial contact, maximum flexion during stance and swing in the TKR knees vs controls in walking and running. Similarly, there was also a statistically significantly higher max knee flexion moment between operated knees and controls in both walking and running. Conclusion: This study has shown that a quadriceps avoidance gait persists in patients after TKR, and that there was symmetry and reciprocated gait parameters in non-operated limbs. These findings suggest that Kr TKRs could be capable of replicating normal knee kinematics when running and walking.
ABSTRACT
Using tibial sensors in total knee replacements (TKRs) can enhance patient outcomes and reduce early revision surgeries, benefitting hospitals, the National Health Services (NHS), stakeholders, biomedical companies, surgeons, and patients. Having a sensor that is accurate, precise (over the whole surface), and includes a wide range of loads is important to the success of joint force tracking. This research aims to investigate the accuracy of a novel intraoperative load sensor for use in TKRs. This research used a self-developed load sensor and artificial intelligence (AI). The sensor is compatible with Zimmer's Persona Knee System and adaptable to other knee systems. Accuracy and precision were assessed, comparing medial/lateral compartments inside/outside the sensing area and below/within the training load range. Five points were tested on both sides (medial and lateral), inside and outside of the sensing region, and with a range of loads. The average accuracy of the sensor was 83.41% and 84.63% for the load and location predictions, respectively. The highest accuracy, 99.20%, was recorded from inside the sensing area within the training load values, suggesting that expanding the training load range could enhance overall accuracy. The main outcomes were that (1) the load and location predictions were similar in accuracy and precision (p > 0.05) in both compartments, (2) the accuracy and precision of both predictions inside versus outside of the triangular sensing area were comparable (p > 0.05), and (3) there was a significant difference in the accuracy of load and location predictions (p < 0.05) when the load applied was below the training loading range. The intraoperative load sensor demonstrated good accuracy and precision over the whole surface and over a wide range of load values. Minor improvements to the software could greatly improve the results of the sensor. Having a reliable and robust sensor could greatly improve advancements in all joint surgeries.