Implantable microelectromechanical sensors for diagnostic monitoring and post-surgical prediction of bone fracture healing

buir.contributor.authorDemir, Hilmi Volkan
buir.contributor.orcidDemir, Hilmi Volkan|0000-0003-1793-112X
dc.citation.epage1446en_US
dc.citation.issueNumber10en_US
dc.citation.spage1439en_US
dc.citation.volumeNumber33en_US
dc.contributor.authorMcGilvray, K. C.en_US
dc.contributor.authorÜnal, E.en_US
dc.contributor.authorTroyer, K. L.en_US
dc.contributor.authorSantoni, B. G.en_US
dc.contributor.authorPalmer, R. H.en_US
dc.contributor.authorEasley, J. T.en_US
dc.contributor.authorDemir, Hilmi Volkanen_US
dc.contributor.authorPuttlitz, C. M.en_US
dc.date.accessioned2016-02-08T09:35:51Z
dc.date.available2016-02-08T09:35:51Z
dc.date.issued2015en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.departmentDepartment of Physicsen_US
dc.departmentInstitute of Materials Science and Nanotechnology (UNAM)en_US
dc.description.abstractThe 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.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T09:35:51Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2015en
dc.identifier.doi10.1002/jor.22918en_US
dc.identifier.issn0736-0266
dc.identifier.urihttp://hdl.handle.net/11693/20815
dc.language.isoEnglishen_US
dc.publisherJohn Wiley and Sons Inc.en_US
dc.relation.isversionofhttp://dx.doi.org/10.1002/jor.22918en_US
dc.source.titleJournal of Orthopaedic Researchen_US
dc.subjectImplanteden_US
dc.subjectBiomechanicsen_US
dc.subjectHistologyen_US
dc.subjectMicro computed tomographyen_US
dc.subjectMicroelectromechanical system (MEMS)en_US
dc.subjectAnimal experimenten_US
dc.subjectAnimal modelen_US
dc.subjectAnimal tissueen_US
dc.subjectBiocompatibilityen_US
dc.subjectBiosensoren_US
dc.subjectControlled studyen_US
dc.subjectDiagnosisen_US
dc.subjectFracture healingen_US
dc.subjectHistopathologyen_US
dc.subjectIn vivo studyen_US
dc.subjectMicro - computed tomographyen_US
dc.subjectMicroelectromechanical systemen_US
dc.subjectMolecular sensoren_US
dc.subjectNonhumanen_US
dc.subjectPriority journalen_US
dc.subjectSheepen_US
dc.subjectStatistical significanceen_US
dc.subjectWound healing impairmenten_US
dc.subjectAmbulatory monitoringen_US
dc.subjectDevicesen_US
dc.subjectElectrode implanten_US
dc.subjectEvaluation studyen_US
dc.subjectMaterials testingen_US
dc.subjectAnimalsen_US
dc.subjectElectrodesen_US
dc.subjectMaterials testingen_US
dc.subjectMicro - electrical - mechanical systemsen_US
dc.subjectMonitoringen_US
dc.subjectTelemetryen_US
dc.titleImplantable microelectromechanical sensors for diagnostic monitoring and post-surgical prediction of bone fracture healingen_US
dc.typeArticleen_US

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