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Full-Text Articles in Engineering
Justrun - Social Gps Running Game, Riley Bergin, Maggie Cai, Simran Judge, Grace Ling
Justrun - Social Gps Running Game, Riley Bergin, Maggie Cai, Simran Judge, Grace Ling
Interdisciplinary Design Senior Theses
With advances in technology allowing people to live more sedentary lives, more and more people are struggling to live a healthy active lifestyle. In the efforts to combat unhealthy styles of living, we wish to introduce a mobile app that takes advantage of motivational game mechanics to motivate players will make go on runs regularly.
Lactic Acid Threshold Stimulator, Justin Brackett, Karen Carreon, Fernando Guerra, Malyna Sanchez
Lactic Acid Threshold Stimulator, Justin Brackett, Karen Carreon, Fernando Guerra, Malyna Sanchez
Interdisciplinary Design Senior Theses
As a person works out, the threshold of lactic acid will build causing anywhere from discomfort to pain. Reducing the discomfort caused by lactic acid could greatly improve an individual’s performance while working out. Reducing this discomfort may be done through Electrical Muscle Stimulation (EMS), which is the procedure of contracting muscles through sending electrical signals. Our team’s goal is to create LATS, a wearable and mobile application that alleviates discomfort and aids muscle recovery during the intense parts of a workout. The system consists of a heart rate monitor to measure lactic acid levels, a garment that is worn …
Machine Learning Solution To Organ-At-Risk Segmentation For Radiation Treatment Planning, Brie Goo, Katrina May, Haobo Zhang, James Olivas
Machine Learning Solution To Organ-At-Risk Segmentation For Radiation Treatment Planning, Brie Goo, Katrina May, Haobo Zhang, James Olivas
Interdisciplinary Design Senior Theses
In the treatment of cancer using ionizing radiation, it is important to design a treatment plan such that dose to normal, healthy organs is sufficiently low. Today, segmentation requires a trained human to carefully outline, or segment, organs on each slice of a treatment planning computed tomography (CT) scan but it is laborious, time-consuming, and contains intra- and inter-rater variability. Currently, existing clinical automation technology relies on atlas-based automation, which has limited segmentation accuracy. Thus the auto-segmentations require post process editing by an expert. In this paper, we propose a machine learning solution that shortens the segmentation time of organs-at-risk …