Year: 2018
Type: dissertation
Abstract: Individuals with severe motor impairment have little motor control, making them unable to perform everyday tasks independently. Brain computer interfaces (BCIs) use detectable changes in neurophysiological signals to control external communication and mobility enhancing devices in the absence of speech and body language. A limitation of current BCIs is their dependence on the performance of mental tasks which can be non-intuitive in the context of a communication activity. This study explored self-regulation BCIs using near- infrared spectroscopy (NIRS) in an adolescent population. Fifteen youth participants were able to control the BCI via voluntary self-regulation, achieving classification accuracy of 77.9 ± 8.8% after only two sessions of real-time user feedback. Self-reported ease-of-use ratings were statistically similar between self-regulation and pre-defined task paradigms. These findings suggest that voluntary self-regulation can be an effective means of BCI control in youth and is not perceived as more difficult than conventional task-based BCI.
Source: TSpace (University of Toronto)
Author: Rozita Abdoli
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2958728682