Biomedical Engineering Society: Presentation by Sheila Galbreath - Anthropometric Measurements

Sheila Galbreath, one of our BIE department PhD candidates, will be presenting some of her research to BMES members. This is a great time to see the opportunities available for students who may be interested in pursuing a graduate degree in biomedical engineering, after completing their undergrad requirements.

Here is her abstract:

Anthropometric utilizes noninvasive methods to study human measurements.  Differences in human measurements are apparent during stages of development and gender; thereby necessitating the need to quantify specific anatomical measurements. Anthropometric data is applicable to manufacturing (i.e. clothing, equipment, etc.), work environments, and healthcare. Although there is a plethora of manual instruments employed to take quantitative measurements, recent technology can obtain scans minimizing direct contact with the subject. 3D scanners (i.e. Kinect, Artec, etc.) can model the human shape, allowing evaluation after the participant is no longer present with good accuracy.
 
Additional research is required to explore the anthropometric variations between genders, growth and development stages, and ethnic composition. The exciting component of this project is integrating human factors engineering and biomedical engineering. The interdisciplinary component of this field of science requires interaction with participants, learning the data flow, and integrating multiple disciplines. Anthropometrics is necessary from the inception of designing a protype to the end product.  Experiments and data collection design fall more in line with human factors.  Biomedical engineering is applied during data analysis using machine learning strategies that will reflect the 3D scanned images.  The design of experiments will produce ~281 data points with an option of ~ 78,680 combinations if the measurement order does matter when using two measurements. A biomedical engineer can create a model of the chest and conduct simulated experiments on CAD programs to better understand biological behavior under various conditions. The most significant part of this study is that the data will support our female military members and may have profound applications in the clinical setting, manufacturing, and work environments.