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Moore, Levi M.An Enhanced Body Area Network to Wirelessly Monitor Biometric Information
Master of Science (MS), Ohio University, 2017, Electrical Engineering & Computer Science (Engineering and Technology)
Body Area Networks are beneficial in many applications including fitness tracking and remote healthcare monitoring. This thesis discusses system enhancements to the award-winning Ohio University Body Area Network system which senses heart rate, integrates an inertial measurement unit, and measures ambient temperature. An upgraded ARM-based Nordic microprocessor was implemented to collect and process biometric sensor data and utilize low-energy Bluetooth (BLE) to transmit data via a Bluetooth antenna. Data is received on an updated Android application running on a handheld Nexus 5 Smartphone. Power received measurements were performed to compare the Baseline and Enhanced systems using several Bluetooth antenna solutions including an e-textile spiral antenna, a traditional inset-fed patch antenna, and a printed monopole antenna.

Committee:

Chris Bartone (Advisor); Savas Kaya (Committee Member); Maarten Uijt De Haag (Committee Member); David Drozek (Committee Member)

Subjects:

Computer Engineering; Electrical Engineering

Keywords:

Body Area Network; Remote Healthcare Monitoring; Biometric Sensors; Bluetooth Low Energy; ARM-based Microcontroller

Bhalchandra, AnishA Mobile Interface for Real-Time EEG Monitoring
MS, University of Cincinnati, 2017, Engineering and Applied Science: Computer Engineering
Electroencephalography (EEG), a technology used to measure electrical activity in the brain through measurement of voltage fluctuations on the scalp, has been studied since the late 19th century. In the clinical setting, EEG is used to diagnose a host of psychophysiological ailments and brain injuries. Up until a few years ago, EEG measurement required subjects to sit idle with a huge number of wires tethered to their scalps through electrodes. With the advent of wireless EEG, many portable systems have been developed that can measure and transmit EEG data wirelessly with varying degrees of fidelity and accuracy. However, most of these wireless EEG systems still require a desktop or laptop computer to analyze the wirelessly received EEG data in real time. To make the system truly mobile, it is essential to develop a mobile phone/ tablet based application that plots and does basic analysis of this data. This application demonstrates a way to highly improve the portability of wireless EEG systems with minimal impact on their accuracy. The mobile application described in this thesis has been developed on the basis of a custom wireless EEG headset developed by Dr. Fred Beyette Jr. and his team at the Laboratory of Advanced Healthcare Technologies at the University of Cincinnati. The application was developed for iOS devices and is based off the Core-Plot 2D plotting framework. It provides two environments – first, a light environment for real time EEG acquisition and display and the second, a more feature rich environment for post-test analysis and filtering acquired data. This thesis details the design, implementation and experimental verification of the EEG plotter and analyzer application.

Committee:

Fred Beyette, Ph.D. (Committee Chair); Jason Heikenfeld, Ph.D. (Committee Member); Carla Purdy, Ph.D. (Committee Member)

Subjects:

Computer Engineering

Keywords:

Mobile;EEG;Bluetooth Low Energy;Real time;iOS;Plot