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. 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.

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. 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.

No description available.

No description available.

No description available.

No description available.

No description available.

No description available.

No description available.

Purpose: The RTVue-100 is a new instrument for measuring retinal blood flow (RBF), but image quality needs to be optimized in order for valid blood flow results. The primary aim of this thesis was to assess the presence of learning effects with novice and experienced operators. Methods: Twelve upper-year optometric students from the University of Waterloo, School of Optometry and Vision Science, were trained in operating RTVue-100. Nine healthy participants, with a mean age (?? SD) of 25.7 ?? 3.8 years, underwent OCT imaging. Using the Doppler OCT of Retinal Circulation (DOCTORC) software, images were assessed by computer for various image quality parameters. Results: Paired samples t-tests showed significant statistical differences between the novice and experienced operators for the following image acquisition parameters: total acquisition time (TAT), number of attempts to complete total scan protocol, and number of valid images. Mean values for TAT and the number of attempts decreased, whereas the mean number of valid images increased from novice to experienced level. Conclusions: The results confirm that there are learning effects observed within the image acquisition process using the RTVue-100 SD-OCT.