Osseointegrated prosthesis is essentially a prosthetic fixture surgically implanted into the bone that extends out of the limb so that an artificial limb can be attached. While osseointegrated prostheses can dramatically improve the quality of life of amputees, there remains a lack of quantitative evidence of the osseointegration process that occurs at the bone–prosthesis surface after surgery. This study advances a sensing strategy that employs piezoelectric elements mounted to the percutaneous end of the prosthesis to generate guided waves that propagate along the length of the prosthesis fixture. The properties of the guided waves exhibit sensitivity to both the degree of bone healing that occurs at the prosthesis surface and the movement of the prosthesis due to loss of osseointegration. Use of the prosthesis as a wave guide offers care providers a quantitative approach to determining when an osseointegrated prosthesis can be loaded and tracks the integrity of osseointegration over the lifespan of the amputee. The study validates the proposed guided wave strategy using a prosthesis model consisting of a solid titanium rod implanted in an adult femoral bone. First, a high-fidelity finite element model is created to study changes in guided waves as a result of bone healing. A laboratory model is also adopted using a synthetic femoral bone identical to that modeled in the finite element model. The energy of the first longitudinal wave mode introduced at the percutaneous end of the prosthesis provides a repeatable metric for accurate assessment of both osseointegration and prosthesis pullout from the bone. The results of this study reveal that the energy of the longitudinal wave mode decreases by nearly half during the osseointegration healing process. In addition, the wave energy is also found to increase as the osseointegrated fixture loosens and is withdrawn from the bone.

This paper explores a new method for rapid structural damage inspection of steel tube slab (STS) structures along randomly measured paths based on a combination of compressive sampling (CS) and ultrasonic computerized tomography (UCT). In the measurement stage, using fewer randomly selected paths rather than the whole measurement net is proposed to detect the underlying damage of a concrete-filled steel tube. In the imaging stage, the ℓ1-minimization algorithm is employed to recover the information of the microstructures based on the measurement data related to the internal situation of the STS structure. A numerical concrete tube model, with the various level of damage, was studied to demonstrate the performance of the rapid UCT technique. Real-world concrete-filled steel tubes in the Shenyang Metro stations were detected using the proposed UCT technique in a CS framework. Both the numerical and experimental results show the rapid UCT technique has the capability of damage detection in an STS structure with a high level of accuracy and with fewer required measurements, which is more convenient and efficient than the traditional UCT technique.