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Brain-computer interface technology establishes communication between the brain and a computer, allowing users to control devices, machines, or virtual objects using their thoughts. This study investigates optimal conditions to facilitate learning to operate this interface. It compares two biofeedback methods, which dictate the relationship between brain activity and the movement…

Brain-computer interface technology establishes communication between the brain and a computer, allowing users to control devices, machines, or virtual objects using their thoughts. This study investigates optimal conditions to facilitate learning to operate this interface. It compares two biofeedback methods, which dictate the relationship between brain activity and the movement of a virtual ball in a target-hitting task. Preliminary results indicate that a method in which the position of the virtual object directly relates to the amplitude of brain signals is most conducive to success. In addition, this research explores learning in the context of neural signals during training with a BCI task. Specifically, it investigates whether subjects can adapt to parameters of the interface without guidance. This experiment prompts subjects to modulate brain signals spectrally, spatially, and temporally, as well differentially to discriminate between two different targets. However, subjects are not given knowledge regarding these desired changes, nor are they given instruction on how to move the virtual ball. Preliminary analysis of signal trends suggests that some successful participants are able to adapt brain wave activity in certain pre-specified locations and frequency bands over time in order to achieve control. Future studies will further explore these phenomena, and future BCI projects will be advised by these methods, which will give insight into the creation of more intuitive and reliable BCI technology.

ContributorsLancaster, Jenessa Mae (Co-author) / Appavu, Brian (Co-author) / Wahnoun, Remy (Co-author, Committee member) / Helms Tillery, Stephen (Thesis director) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor) / Department of Psychology (Contributor)

Created2014-05

Yuhui Li, piano

ContributorsLi, Yuhui (Contributor) / ASU Library. Music Library (Publisher)

Created2018-10-04

Kara Lee, piano

ContributorsLee, Kara (Performer) / ASU Library. Music Library (Publisher)

Created2018-03-24

A recording and performance guide for three new works featuring clarinet and electronics, clarinet and piano, and clarinet, bass clarinet, and piano

Description

This project includes a recording and performance guide for three newly commissioned pieces for the clarinet. The first piece, shimmer, was written by Grant Jahn and is for B-flat clarinet and electronics. The second piece, Paragon, is for B-flat clarinet and piano and was composed by Dr. Theresa Martin. The…

This project includes a recording and performance guide for three newly commissioned pieces for the clarinet. The first piece, shimmer, was written by Grant Jahn and is for B-flat clarinet and electronics. The second piece, Paragon, is for B-flat clarinet and piano and was composed by Dr. Theresa Martin. The third and final piece, Duality in the Eye of a Bovine, was written by Kurt Mehlenbacher and is for B-flat clarinet, bass clarinet, and piano. In addition to the performance guide, this document also includes background information and program notes for the compositions, as well as composer biographical information, a list of other works featuring the clarinet by each composer, and transcripts of composer and performer interviews. This document is accompanied by a recording of the three pieces.

ContributorsPoupard, Caitlin Marie (Author) / Spring, Robert (Thesis advisor) / Gardner, Joshua (Thesis advisor) / Hill, Gary (Committee member) / Oldani, Robert (Committee member) / Schuring, Martin (Committee member) / Arizona State University (Publisher)

Created2016

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