A Prototype Device for Isolating and Wirelessly Transmitting Neural Action Potentials

• Main Author: Slominski, Eric Christopher
• Other Authors: Mechanical Engineering
• Format: Others
• Published: Virginia Tech 2011
• Subjects: bluetooth; microcontroller; action potential; electrophysiology; instrumentation
• Online Access: http://hdl.handle.net/10919/9652; http://scholar.lib.vt.edu/theses/available/etd-12182003-170050

An electrophysiology research laboratory at the Wake Forest University School of Medicine in the Physiology/Pharmacology Department currently carries out memory research by recording neural signals from laboratory animals with a wire tethering the animal to nearby signal conditioning and recording equipment. A wireless neural signal recording system is desirable because it removes the cumbersome wires from the animal, allowing it to roam more freely. The result is an animal that is more able to behave as it would in its natural habitat, thus opening the possibility of testing procedures that are not possible with wired recording systems. While there are wireless neural recording systems in existence, this thesis presents a new approach to recording neural signals wirelessly. The firings of neurons in the hippocampus are manifested as action potentials or voltage "spikes" on the order of 100 to 400uV in magnitude. Though the information content of the neural signal is riding on these action potentials, the spikes comprise a small fraction of the complete neural signal. A unique feature of the neural signal transceiver presented in this thesis is its ability to digitally isolate and transmit the action potentials, leaving out the remaining, unimportant part of the neural signal. This approach to recording neural signals makes efficient use of the limited bandwidth available with portable short range wireless devices. This thesis will present the spike isolating neural transmitter, which was built using commercially available electronic components. Then, the proper function of assembly language code written for a PIC18F458 microcontroller will be demonstrated. Finally, a discussion of the performance of the neural signal transmitter will be provided. === Master of Science