Author's School

School of Engineering & Applied Science

Author's Department/Program

Biomedical Engineering

Language

English (en)

Date of Award

1-1-2010

Degree Type

Thesis

Degree Name

Master of Arts (MA)

Chair and Committee

Dennis Barbour

Abstract

An implantable brain computer interface: BCI) includes tissue interface hardware, signal conditioning circuitry, analog-to-digital conversion: ADC) circuitry and some sort of computing hardware to discriminate desired waveforms from noise. Within an experimental paradigm the tissue interface and ADC hardware will rarely change. Recent literature suggests it is often the specific implementation of waveform discrimination that can limit the usefulness and lifespan of a particular BCI design. If the discrimination techniques are implemented in on-board software, experimenters gain a level of flexibility not currently available in published designs. To this end, I have developed a firmware library to acquire data sampled from an ADC, discriminate the signal for desired waveforms employing a user-defined function, and perform arbitrary tasks. I then used this design to develop an embedded BCI built upon the popular Texas Instruments MSP430 microcontroller platform. This system can operate on multiple channels simultaneously and is not fundamentally limited in the number of channels that can be processed. The resulting system represents a viable platform that can ease the design, development and use of BCI devices for a variety of applications.

DOI

https://doi.org/10.7936/K7Z0365S

Comments

Permanent URL: http://dx.doi.org/10.7936/K7Z0365S

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