ABSTRACT
Elevated intracranial fluid volume can drive intracranial pressure increases, which can potentially result in numerous neurological complications or death. This study's focus was to develop a passive skin patch sensor for the head that would non-invasively measure cranial fluid volume shifts. The sensor consists of a single baseline component configured into a rectangular planar spiral with a self-resonant frequency response when impinged upon by external radio frequency sweeps. Fluid volume changes (10 mL increments) were detected through cranial bone using the sensor on a dry human skull model. Preliminary human tests utilized two sensors to determine feasibility of detecting fluid volume shifts in the complex environment of the human body. The correlation between fluid volume changes and shifts in the first resonance frequency using the dry human skull was classified as a second order polynomial with R² = 0.97. During preliminary and secondary human tests, a ≈24 MHz and an average of ≈45.07 MHz shifts in the principal resonant frequency were measured respectively, corresponding to the induced cephalad bio-fluid shifts. This electromagnetic resonant sensor may provide a non-invasive method to monitor shifts in fluid volume and assist with medical scenarios including stroke, cerebral hemorrhage, concussion, or monitoring intracranial pressure.
ABSTRACT
The most accurate and precise methods for the assessment of age and stature often require knowledge of sex. Thus, being able to correctly identify sex from skeletal remains is critical in the forensic context. The presence of the os coxae or skull can never be guaranteed, making the development of reliable methods of sex estimation using other skeletal elements necessary. Using a 724 individual calibration sample from the Hamann-Todd collection, this study identifies sexual dimorphism in the human scapula, and presents a new five-variable discriminant function for sex estimation. The overall accuracy of this method proved to be 95.7% on the cross-validated calibration sample, 92.5% on an 80 individual test sample from the Hamann-Todd collection, and 84.4% on a 32 individual test sample from the skeletal collection of the Wichita State University Biological Anthropology Laboratory. Additionally, a slightly less accurate two-variable model was developed and has cross-validated accuracy of 91.3%.
