Browsing by Subject "Fracture healing"

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    Implantable microelectromechanical sensors for diagnostic monitoring and post-surgical prediction of bone fracture healing
    (John Wiley and Sons Inc., 2015) McGilvray, K. C.; Ünal, E.; Troyer, K. L.; Santoni, B. G.; Palmer, R. H.; Easley, J. T.; Demir, Hilmi Volkan; Puttlitz, C. M.
    The relationship between modern clinical diagnostic data, such as from radiographs or computed tomography, and the temporal biomechanical integrity of bone fracture healing has not been well-established. A diagnostic tool that could quantitatively describe the biomechanical stability of the fracture site in order to predict the course of healing would represent a paradigm shift in the way fracture healing is evaluated. This paper describes the development and evaluation of a wireless, biocompatible, implantable, microelectromechanical system (bioMEMS) sensor, and its implementation in a large animal (ovine) model, that utilized both normal and delayed healing variants. The in vivo data indicated that the bioMEMS sensor was capable of detecting statistically significant differences (p-value <0.04) between the two fracture healing groups as early as 21 days post-fracture. In addition, post-sacrifice micro-computed tomography, and histology data demonstrated that the two model variants represented significantly different fracture healing outcomes, providing explicit supporting evidence that the sensor has the ability to predict differential healing cascades. These data verify that the bioMEMS sensor can be used as a diagnostic tool for detecting the in vivo course of fracture healing in the acute post-treatment period. © 2015 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.
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    Metamaterial-based wireless strain sensors
    (American Institute of Physics, 2009-07-07) Melik, R.; Unal, E.; Perkgoz, N. K.; Puttlitz, C.; Demir, Hilmi Volkan
    We proposed and demonstrated metamaterial-based strain sensors that are highly sensitive to mechanical deformation. Their resonance frequency shift is correlated with the surface strain of our test material and the strain data are reported telemetrically. These metamaterial sensors are better than traditional radio-frequency (rf) structures in sensing for providing resonances with high quality factors and large transmission dips. Using split ring resonators (SRRs), we achieve lower resonance frequencies per unit area compared to other rf structures, allowing for bioimplant sensing in soft tissue (e.g., fracture healing). In 5×5 SRR architecture, our wireless sensors yield high sensitivity (109 kHz/kgf, or 5.148 kHz/microstrain) with low nonlinearity error (<200 microstrain).
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    Nested metamaterials for wireless strain sensing
    (IEEE, 2009-12-28) Melik, R.; Unal, E.; Perkgoz, N. K.; Santoni, B.; Kamstock, D.; Puttlitz, C.; Demir, Hilmi Volkan
    We designed, fabricated, and characterized metamaterial-based RF-microelectromechanical system (RF-MEMS) strain sensors that incorporate multiple split ring resonators (SRRs) in a compact nested architecture to measure strain telemetrically. We also showed biocompatibility of these strain sensors in an animal model. With these devices, our bioimplantable wireless metamaterial sensors are intended, to enable clinicians, to quantitatively evaluate the progression of long-bone fracture healing by monitoring the strain on the implantable fracture fixation hardware in real time. In operation, the transmission spectrum of the metamaterial sensor attached to the implantable fixture is changed when an external load is applied to the fixture, and from this change, the strain is recorded remotely. By employing telemetric characterizations, we reduced the operating frequency and enhanced the sensitivity of our novel nested SRR architecture compared to the conventional SRR structure. The nested SRR structure exhibited a higher sensitivity of 1.09 kHz/kgf operating at lower frequency compared to the classical SRR that demonstrated a sensitivity of 0.72 kHz/kgf. Using soft tissue medium, we achieved the best sensitivity level of 4.00 kHz/kgf with our nested SRR sensor. Ultimately, the laboratory characterization and in vivo biocompatibility studies support further development and characterization of a fracture healing system based on implantable nested SRR.
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    Utilizing multiple bioMEMS sensors to monitor orthopaedic strain and predict bone fracture healing
    (Wiley Periodicals, Inc., 2019) Wolynski, J.; Sutherland, C.; Demir, Hilmi Volkan; Ünal, Emre; Alipour, A.; Puttlitz, C.; McGilvray, K.
    Current diagnostic modalities, such as radiographs or computed tomography, exhibit limited ability to predict the outcome of bone fracture healing. Failed fracture healing after orthopaedic surgical treatments are typically treated by secondary surgery; however, the negative correlation of time between primary and secondary surgeries with resultant health outcome and medical cost accumulation drives the need for improved diagnostic tools. This study describes the simultaneous use of multiple (n = 5) implantable flexible substrate wireless microelectromechanical (fsBioMEMS) sensors adhered to an intramedullary nail (IMN) to quantify the biomechanical environment along the length of fracture fixation hardware during simulated healing in ex vivo ovine tibiae. This study further describes the development of an antenna array for interrogation of five fsBioMEMS sensors simultaneously, and quantifies the ability of these sensors to transmit signal through overlaying soft tissues. The ex vivo data indicated significant differences associated with sensor location on the IMN (p < 0.01) and fracture state (p < 0.01). These data indicate that the fsBioMEMS sensor can serve as a tool to diagnose the current state of fracture healing, and further supports the use of the fsBioMEMS as a means to predict fracture healing due to the known existence of latency between changes in fracture site material properties and radiographic changes. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 37:1873–1880, 2019