Computer Sciences Commons^™

Seizure Prediction In Epilepsy Patients, Gary Dean Cravens

NSU REACH and IPE Day

Purpose/Objective: Characterize rigorously the preictal period in epilepsy patients to improve the development of seizure prediction techniques. Background/Rationale: 30% of epilepsy patients are not well-controlled on medications and would benefit immensely from reliable seizure prediction. Methods/Methodology: Computational model consisting of in-silico Hodgkin-Huxley neurons arranged in a small-world topology using the Watts-Strogatz algorithm is used to generate synthetic electrocorticographic (ECoG) signals. ECoG data from 18 epilepsy patients is used to validate the model. Unsupervised machine learning is used with both patient and synthetic data to identify potential electrophysiologic biomarkers of the preictal period. Results/Findings: The model has shown states corresponding to …

Using Experiential Learning In Course Curriculum: The Case Of A Core Engineering Graphics Course, Martha Marie Snyder, Manuel Salinas, Molly J. Scanlon

CCE Faculty Proceedings, Presentations, Speeches and Lectures

This work-in-progress paper overviews how an experiential education program was established at a private, non-profit university in the southeast, describes the process for certifying experiential courses using a formal course review process and qualification rubric, and details the case of a freshman engineering graphics course.

Grounded in the early works of Dewey, Lewin, and Piaget, experiential learning theory has become increasingly popular in higher education. Experiential learning serves as a foundation for lifelong learning and the development of the whole self as a citizen, family member and human being (Kolb, 2015). Austin and Rust (2015) define experiential learning as “‘hands-on’ …