Self-Powered In Vivo Joint Load and Angle Sensing in Total Knee Replacement - Project Summary Total knee arthroplasty (TKA) is one of the most common surgical procedures in all of medicine and despite technical advances, about 10-20% of patients remain dissatisfied with their outcomes and about 9% of patients require revision. Leading causes of dissatisfaction and revision include postoperative pain, infection, aseptic loosening, and instability. Novel technologies, such as 3D surgical planning, patient-specific instrumentation, and sensor-guided and robotic-assisted arthroplasty, have changed the landscape of modern TKA, yet success rates have not improved over the past 20 years. Currently, there is no consensus in the arthroplasty community regarding ideal implant alignment, soft tissue balance, or implant design, and our understanding of aseptic failure mechanisms in knee arthroplasty is poor. Overall, there is a lack of technology to allow continuous postoperative in vivo measurement of joint motions and forces, thus precluding advances in knee arthroplasty. To address this problem, we propose to develop an innovative self-powered smart piezoelectric TKA implant platform that will enable continuous in vivo measurement of joint kinematics and compartmental joint kinetics, and allow expandability for future sensors. Our preliminary results demonstrate feasibility of piezoelectric transducers integrated into knee prosthesis to (a) sense compartmental forces with error <3%, (b) sense compartmental contact locations with error <1.6 mm, (c) generate around 300 μW of power, and (d) survive at least 10,000 simulated gait cycles. Our visionary design requires further optimization of the piezoelectric system, development of a magnetic joint angle sensing system, and pre-clinical evaluation, which is the focus of the proposed work. Aim 1: we will develop computational finite element models to predict the behavior of smart piezoelectric TKR force sensors during gait, and develop circuitry for energy harvesting, sensing, and wireless data transmission. We will experimentally validate the models and circuits via testing of prototypes under simulated in vitro 6 degree-of-freedom (DOF) joint motion. We will utilize the experimentally-validated models to optimize the design of the smart piezoelectric implant considering sensing, energy harvesting, and long-term survivability of the device. We will evaluate the accuracy and reproducibility of final optimized prototypes under various ADLs, and determine long-term performance over 1 million cycles. Aim 2: we will develop a magnetic joint flexion angle sensing system by creating computational models and testing prototypes. Magnetic flexion sensing will be fused with the aforementioned piezoelectric force sensing to resolve all six kinematic DOFs. Aim 3: we will implant our prototype smart knees into cadavers and determine performance over 100 cycles of various ADLs, and determine ability to sense abnormalities including cement loosening, ligamentous instability, condylar liftoff, and third-body contamination of the joint surface. The ultimate goal of this research is to fill the technological gap in postoperative monitoring of TKA to provide the community with valuable data to advance orthopedic surgical techniques and implant designs to ultimately improve patient satisfaction and human health.
