Smart knee prosthesis kinematics estimation and validation in a robotic knee simulator

In this work we present the smart knee prosthesis designed for in-vivo kinematics measurement and its validation in two knee simulators, i.e. a robotic knee simulator to provide realistic condition, and a manual simulator with more degrees of freedom. The sensor configuration including three magnetic sensors was designed, and the machine learning techniques were used to translate the magnetic measurements to knee rotations. First the concurrent flexion-extension and internal-external rotations were estimated via linear and nonlinear estimators, and technically validated in a manual knee simulator against motion capture system. Then the flexion-extension estimation was validated in a robotic knee simulator providing the realistic sagittal kinematics of treadmill and over-ground walking. The obtained results showed the high accuracy and precision of the estimates

Accurate angle estimation in smart knee prostheses via magnetic implantable and skin-mounted sensors

In this work we investigated how to measure concurrently flexion-extension and internal-external rotations in a smart knee prosthesis. A configuration of magnetic sensors and magnets were designed and embedded in knee prostheses in which each sensor measures a mixture of information related to both rotations. Using correlation analyses, angle estimators were designed to separate the flexion-extension and internal-external rotations information. The estimators were validated in a mechanical knee simulator towards a reference system. The effect of imposed abduction-adduction was also analyzed on the estimations performances. To reduce the power consumption of the internal system, we reduced the sampling rate and duty cycled the sensors and compensated the lack of information with skin-mounted sensors on four subjects. The fusion between implantable and skin-mounted sensors drastically improved the flexion-extension angle estimation, but not the internal-external estimation

Smart Knee Prosthesis for Orthopedic Surgery: the implantable and wearable Measurement System

Recent advances in remote powering and telemetry permitted the use of sensors inside body. A few studies have been already done on smart knee prostheses, but all focused on monitoring the in-vivo contact forces and moments. A smart design, compatible with mechanical structure of commercially-available knee prostheses, that provides force and accurate kinematics feedback was suggested with all electronics housed in the polyethylene insert (PE). The current work addresses the designed kinematics and force measurement system of that smart implant and its validation in a robotic knee simulator

An Implantable System for Angle Measurement in Prosthetic Knee

In this work we designed and tested an in-vivo measurement system of prosthetic knee joint angles. The system included a small permanent magnet in the femoral part and three magneto resistance sensors placed in the polyethylene part. The sensor configuration was defined based on sensitivity analysis, signal to noise ratio, saturation of sensors and movements constraints. A mapping algorithm was designed to estimate the orientation of the femoral part in sagittal and coronal plane. For validation the prosthesis was placed in a mechanical simulator equipped with reflective markers tracked by optical motion capture

Real Time Emotional Control for Anti-Swing and Positioning Control of SIMO Overhead Traveling Crane

Jamali MR, Arami A, Hosseini B, Moshiri B, Lukas C. Real Time Emotional Control for Anti-Swing and Positioning Control of SIMO Overhead Traveling Crane. International Journal of Innovative Computing, Information, and Control. 2008;4(9):2333-2344

Patellar kinematics after knee arthroplasty: experimental validation of a numerical model

Subject-specific modelling of Total Knee Arthroplasty could be an efficient method to preoperatively evaluate surgical options. In particular, the question of the necessity of patellar resurfacing is still a debatable issue. The aim of this work was to validate a numerical model of Total Knee Arthroplasty using an instrumented robotic knee simulator equipped with kinematic sensors. The patellar kinematics during a loaded knee flexion were measured with the knee simulator and compared with the values predicted by the model. The mean absolute difference between measured and predicted patellar translations and rotations was respectively 1.4 mm and 2.4 deg. This numerical model will be later used for subject-specific predictions of patellar kinematics and strain state after Total Knee Arthroplasty

A patient-specific model of total knee arthroplasty to estimate patellar strain: A case study

Inappropriate patellar cut during total knee arthroplasty can lead to patellar complications due to increased bone strain. In this study, we evaluated patellar bone strain of a patient who had a deeper patellar cut than the recommended. A patient-specific model based on patient preoperative data was created. The model was decoupled into two levels: knee and patella. The knee model predicted kinematics and forces on the patella during squat movement. The patella model used these values to predict bone strain after total knee arthroplasty. Mechanical properties of the patellar bone were identified with micro-finite element modeling testing of cadaveric samples. The model was validated with a robotic knee simulator and postoperative X-rays. For this patient, we compared the deeper patellar cut depth to the recommended one, and evaluated patellar bone volume with octahedral shear strain above 1%. Model predictions were consistent with experimental measurements of the robotic knee simulator and postoperative X-rays. Compared to the recommended cut, the deeper cut increased the critical strain bone volume, but by less than 3% of total patellar volume. We thus conclude that the predicted increase in patellar strain should be within an acceptable range, since this patient had no complaints 8 months after surgery. This validated patient-specific model will later be used to address other questions on groups of patients, to eventually improve surgical planning and outcome of total knee arthroplasty