Brain computer interface (BCI) systems aim at helping individuals with motor disabilities by providing them the ability to control devices such as wheelchairs and computers, using their brain activity only.

The majority of BCI research to-date has focused on developing technology for "synchronous" BCIs. These systems allow the user to affect control during specified time periods only. Self-paced (asynchronous) BCIs on the other hand, are designed to respond whenever the user intends to control the system, otherwise they remain in the so called "inactive output state".

This dissertation pursues two main objectives:​ (1) improving the performance of the existing 2-state self-paced BCI system developed at the Neil Squire Society, Vancouver, Canada (initial evaluations of this system on eight subjects showed mean true positive (TP) rates of 51.3% and 27.5% at false positive (FP) rates of 2% and 1%, respectively.) and (2) designing the first 3-state self-paced BCI.

At first, a comprehensive survey of signal processing algorithms in BCI systems is conducted. This survey is the first comprehensive review that covers more than 300 BCI published papers and introduces a taxonomy for signal processing in BCI systems.

To achieve the first objective, four separate studies related to the feature extraction and feature classification blocks of the 2-state self-paced BCI are conducted. These studies increase the mean TP rate of the existing system to 73.5% and 47.3% at the FP rates of 2% and 1%, respectively. In these studies, the users were not allowed to control the BCI in 15-34% of the time due to the presence of eye blinks. Thus, another study is also conducted to evaluate the system when the users were allowed to control the output even during eye blinks. Results show slight decrease in TP rates (mean TP rates of 68.0% and 40.6% at the FP rates of 2% and 1%, respectively) with the advantage of providing full control of the system

. To achieve the second objective, two new set of movements (right and left hand extension movements) which have not been previously used in the context of BCI systems are used to control the new 3-state self-paced BCI. Results on four able-bodied subjects show significant improvements in detecting the presence of a movement when the system is used in the context of a 2-state self-paced BCI. The mean TP rate is 73.4% at the FP rate of 1%. Initial evaluations of the proposed 3-state self-paced BCI show promise with mean right and left true positive rates of 42.2% and 51.9% at a false positive rate of 1%.