Biomedical Engineering and Bioengineering Commons^™

Using Natural Language Processing And Sentiment Analysis To Augment Traditional User-Centered Design: Development And Usability Study, Curtis L. Petersen, Ryan Halter, David Kotz, Lorie Loeb, Summer B. Cook, Dawna M. Pidgeon, Brock Christensen, John A. Batsis

Dartmouth Scholarship

Background: Sarcopenia, defined as the age-associated loss of muscle mass and strength, can be effectively mitigated through resistance-based physical activity. With compliance at approximately 40% for home-based exercise prescriptions, implementing a remote sensing system would help patients and clinicians to better understand treatment progress and increase compliance. The inclusion of end users in the development of mobile apps for remote-sensing systems can ensure that they are both user friendly and facilitate compliance. With advancements in natural language processing (NLP), there is potential for these methods to be used with data collected through the user-centered design process.

Objective: This study aims …

Bio Circuits For Evolutionary Biotech, Camilo Toruno

ENGS 86 Independent Projects (AB Students)

The field of bioengineering has much promise for renewable chemical production, bioremediation, and of course medical applications. Developing new useful microorganisms is extremely time and capital intensive, typically taking 50 million USD and eight years. This is due in large part to the low throughput techniques that are characteristic of the field of metabolic engineering. Here we describe the modification of an existing synthetic biosensor to measure the pharmaceutical dopamine, and the use of a circuit simulator Cadence to predict improvements to the biosensor. This biosensor paired with directed evolution techniques could reach throughputs of 5 million cells per day …

A Convolutional Neural Network For Fast Fluence Estimation In Complex Tissues, Nicholas Blasey, Geoffrey P. Luke

ENGS 88 Honors Thesis (AB Students)

Photoacoustic (PA) imaging is a non-invasive diagnostic imaging technique that gives images of photoabsorbers based on their absorption of optical energy. These optical absorption properties can then be linked to important tissue properties. For the method to be quantitative, however, it is necessary to have an accurate estimation of the light fluence in the tissue. The current gold standard in addressing the fluence estimation problem, a Monte Carlo Simulation, is costly in time and computation. In this work, we developed a deep neural network to quickly and accurately estimate light fluence in arbitrary tissue types and geometries. The network was …

Utilizing Neural Networks And Wearables To Quantify Hip Joint Angles And Moments During Walking And Stair Ascent, Megan V. Mccabe

ENGS 88 Honors Thesis (AB Students)

Wearable sensors were leveraged to develop two methods for computing hip joint angles and moments during walking and stair ascent that are more portable than the gold standard. The Insole-Standard (I-S) approach replaced force plates with force-measuring insoles and achieved results that match the curvature of results from similar studies. Peaks in I-S kinetic results are high due to error induced by applying the ground reaction force to the talus. The Wearable-ANN (W-A) approach combines wearables with artificial neural networks to compute the same results. Compared against the I-S, the W-A approach performs well (average rRMSE = 18%, R^{2 …}