Medicine and Health Sciences Commons^™

A Scalable Automated Diagnostic Feature Extraction System For Eegs, Prakhar Agrawal, Divya Bhargavi, Gokul Krishna, Xiao Han, Neha Tevathia, Abbie M. Popa, Nicholas Ross, Diane Myung-Kyung Woodbridge, Barbie Zimmerman-Bier, William Bosl

Nursing and Health Professions Faculty Research and Publications

Researchers using Electroencephalograms (“EEGs”) to diagnose clinical outcomes often run into computational complexity problems. In particular, extracting complex, sometimes nonlinear, features from a large number of time-series often require large amounts of processing time. In this paper we describe a distributed system that leverages modern cloud-based technologies and tools and demonstrate that it can effectively, and efficiently, undertake clinical research. Specifically we compare three types of clusters, showing their relative costs (in both time and money) to develop a distributed machine learning pipeline for predicting gestation time based on features extracted from these EEGs.

The Emerging Role Of Neurodiagnostic Informatics In Integrated Neurological And Mental Health Care, William Bosl

Nursing and Health Professions Faculty Research and Publications

Mental, neurological, and neurodevelopmental (MNN) disorders impose an enormous burden of disease globally. Many MNN disorders follow a developmental trajectory. Thus, defining symptoms of MNN disorders may be conceived as the end product of a long developmental process. Many pharmaceutical therapies are aimed at the end symptoms, essentially attempting to reverse pathological brain function that has developed over a long time. A new paradigm is needed to leverage the developmental trajectory of MNN disorders, based on measuring brain function through the life span. Electroencephalography (EEG) is ideally suited for this task. New developments in several fields, including consumer EEG hardware, …

Nonlinear Eeg Biomarker Profiles For Autism And Absence Epilepsy, William Bosl, Tobias Loddenkemper, Charles A. Nelson

Nursing and Health Professions Faculty Research and Publications

Background

Although autism and epilepsy are considered to be different disorders, epileptiform EEG activity is common in people with autism even when overt seizures are not present. The relatively high comorbidity between autism and all epilepsy syndromes suggests the possibility of common underlying neurophysiological mechanisms. Although many different epilepsies may be comorbid with autism, absence epilepsy is a generalized epilepsy syndrome with seizures that appear as staring spells, with no motor signs and no focal lesions, making it more difficult to diagnose. Application of nonlinear methods for EEG signal analysis may enable characterization of brain activity that can help to …