Wireless Implantable Sensor for Noninvasive, Longitudinal Quantification of Axial Strain Across Rodent Long Bone Defects.

Bone development, maintenance, and regeneration are remarkably sensitive to mechanical cues. Consequently, mechanical stimulation has long been sought as a putative target to promote endogenous healing after fracture. Given the transient nature of bone repair, tissue-level mechanical cues evolve rapidly over time after injury and are challenging to measure noninvasively. The objective of this work was to develop and characterize an implantable strain sensor for noninvasive monitoring of axial strain across a rodent femoral defect during functional activity. Herein, we present the design, characterization, and in vivo demonstration of the device's capabilities for quantitatively interrogating physiological dynamic strains during bone regeneration. Ex vivo experimental characterization of the device showed that it possessed promising sensitivity, signal resolution, and electromechanical stability for in vivo applications. The digital telemetry minimized power consumption, enabling extended intermittent data collection. Devices were implanted in a rat 6 mm femoral segmental defect model, and after three days, data were acquired wirelessly during ambulation and synchronized to corresponding radiographic videos, validating the ability of the sensor to noninvasively measure strain in real-time. Together, these data indicate the sensor is a promising technology to quantify tissue mechanics in a specimen specific manner, facilitating more detailed investigations into the role of the mechanical environment in dynamic bone healing and remodeling processes.

Application of magnetoelastic sensors for quantifying sediment deposition rates and sizes.

This paper describes the application of magnetoelastic sensors for quantifying the size and deposition rate of sediment samples in costal areas, lakes, and rivers. The magnetoelastic sensor, which is made of inexpensive amorphous ferromagnetic alloy, measures parameters of interest by tracking the changes in its resonant frequency and/or amplitude. Since an increase in mass loading on the sensor surface changes its resonant frequency and amplitude, the deposition rate of sediment particles can be determined in real time by tracking these two quantities. Based on a theoretical model, the size distribution of the sediment particles was also estimated from the deposition rate.