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Please use this identifier to cite or link to this item: http://hdl.handle.net/1807/19309

Title: Near-infrared Spectroscopy Signal Classification: Towards a Brain-computer Interface
Authors: Tai, Kelly
Advisor: Chau, Tom
Department: Biomedical Engineering
Keywords: Near-infrared spectroscopy
Brain-computer interface
Locked-in syndrome
Emotional induction
Issue Date: 4-Mar-2010
Abstract: A brain-computer interface (BCI) allows individuals to communicate through the modulation of regional brain activity. Clinical near-infrared spectroscopy (NIRS) is used to monitor changes in cerebral blood oxygenation due to functional activation. It was hypothesized that visually-cued emotional induction tasks can elicit detectable activity in the prefrontal cortex. Data were collected from eleven participants as they performed positively and negatively-valenced emotional induction tasks. Baseline and activation trials were classified offline with accuracies from 75.0-96.7% after applying a feature selection algorithm to determine optimal performance parameters for each participant. Feature selection identified common discriminatory features across participants and relationships between performance parameters. Additionally, classification accuracy was used to quantify NIRS hemodynamic response latency. Significant increases in classification rates were found as early as 2.5 s after initial stimulus presentation. These results suggest the potential application of emotional induction as a NIRS-BCI control paradigm.
URI: http://hdl.handle.net/1807/19309
Appears in Collections:Master
Institute of Biomaterials and Biomedical Engineering - Master theses

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