Parametric analysis of electromechanical and fatigue performance of total knee replacement bearing with embedded piezoelectric transducers

Smart Mater Struct. 2017 Sep;26(9):094002. doi: 10.1088/1361-665X/aa814e. Epub 2017 Aug 17.

Abstract

Total knee arthroplasty (TKA) is a common procedure in the United States; it has been estimated that about 4 million people are currently living with primary knee replacement in this country. Despite huge improvements in material properties, implant design, and surgical techniques, some implants fail a few years after surgery. A lack of information about in vivo kinetics of the knee prevents the establishment of a correlated intra- and postoperative loading pattern in knee implants. In this study, a conceptual design of an ultra high molecular weight (UHMW) knee bearing with embedded piezoelectric transducers is proposed, which is able to measure the reaction forces from knee motion as well as harvest energy to power embedded electronics. A simplified geometry consisting of a disk of UHMW with a single embedded piezoelectric ceramic is used in this work to study the general parametric trends of an instrumented knee bearing. A combined finite element and electromechanical modeling framework is employed to investigate the fatigue behavior of the instrumented bearing and the electromechanical performance of the embedded piezoelectric. The model is validated through experimental testing and utilized for further parametric studies. Parametric studies consist of the investigation of the effects of several dimensional and piezoelectric material parameters on the durability of the bearing and electrical output of the transducers. Among all the parameters, it is shown that adding large fillet radii results in noticeable improvement in the fatigue life of the bearing. Additionally, the design is highly sensitive to the depth of piezoelectric pocket. Finally, using PZT-5H piezoceramics, higher voltage and slightly enhanced fatigue life is achieved.

Keywords: Total knee replacement; UHMW fatigue; embedded sensors; energy harvesting; orthopedic implant; piezoelectric sensing.