Development and evaluation of an online Transcranial Doppler Ultrasonographic brain- computer interface for communication

Development and evaluation of an online transcranial Doppler ultrasonographic brain-computer interface for communication Jie Lu Master of Applied Science Graduate Department of Institute of Biomaterials and Biomedical Engineering University of Toronto 2013 We investigated an emerging brain-computer interface (BCI) modality, namely, transcranial Doppler ultrasonography (TCD), which measures cerebral blood flow velocity. We hypothesized that a bilateral TCD-driven online BCI would be able to dichotomously classify a user’s intentions with at least 70% accuracy. To test this hypothesis, we had three objectives: (1) to develop a signal classifier that yielded high (>80%) offline accuracies; (2) to develop an online TCD-BCI system with an onscreen keyboard; and, (3) to determine the achievable online accuracy with able-bodied participants. ii With a weighted, forward feature selection and a Naïve Bayes classifier, sensitivity and specificity of 81.44 ± 8.35% and 82.30 ± 7.39%, respectively, were achieved in the online differentiation of two mental tasks. The average information transfer rate and throughput of the system were 0.87 bits/min and 0.35 ± 0.18 characters/min, respectively. These promising online results encourage future testing of TCD-BCI systems with the target population.