A comparative study on generating training-data for self-paced brain interfaces.

Direct brain interface (BI) systems provide an alternative communication and control solution for individuals with severe motor disabilities, bypassing impaired interface pathways. Most BI systems are aimed to be operated by individuals with severe disabilities. With these individuals, there is no observable indicator of their intent to control or communicate with the BI system. In contrast, able-bodied subjects can perform the desired physical movements such as finger flexion and one can observe the movement as the indicator of intent. Since no external knowledge of intention is available for individuals with severe motor disabilities, generating the data for system training is problematic. This paper introduces three methods for generating training-data for self-paced BI systems and compares their performances with four alternative methods of training-data generation. Results of the offline analysis on the electroencephalogram data of eight subjects during self-paced BI experiments show that two of the proposed methods increase true positive rates (at fixed false positive rate of 2%) over that of the four alternative methods from 50.8%-58.4% to about 62% which corresponds to 3.6%-11.2% improvement.

Brain-computer interface design for asynchronous control applications: improvements to the LF-ASD asynchronous brain switch.

The low-frequency asynchronous switch design (LF-ASD) was introduced as a direct brain-computer interface (BCI) technology for asynchronous control applications. The LF-ASD operates as an asynchronous brain switch (ABS) which is activated only when a user intends control and maintains an inactive state output when the user is not meaning to control the device (i.e., they may be idle, thinking about a problem, or performing some other action). Results from LF-ASD evaluations have shown promise, although the reported error rates are too high for most practical applications. This paper presents the evaluation of four new LF-ASD designs with data collected from individuals with high-level spinal cord injuries and able-bodied subjects. These new designs incorporated electroencephalographic energy normalization and feature space dimensionality reduction. The error characteristics of the new ABS designs were significantly better than the LF-ASD design with true positive rate increases of approximately 33% for false positive rates in the range of 1%-2%. The results demonstrate that the dimensionality of the LF-ASD feature space can be reduced without performance degradation. The results also confirm previous findings that spinal cord-injured subjects can operate ABS designs to the same ability as able-bodied subjects.

Initial on-line evaluations of the LF-ASD brain-computer interface with able-bodied and spinal-cord subjects using imagined voluntary motor potentials.

Previous research has focused on developing a brain-controlled switch named the low frequency asynchronous switch design (LF-ASD) that is suitable for intermittent control of devices such as environmental control systems, computers, and neural prostheses. On-line implementations of the LF-ASD have shown promising results in response to actual index finger flexions with able-bodied subjects. This paper reports the results of initial on-line evaluations of the LF-ASD brain-controlled switch with both able-bodied subjects and subjects with high-level spinal-cord injuries. This paper has demonstrated that users can activate the LF-ASD switch by imaging movement. In this paper, two able-bodied subjects were able to control the LF-ASD with imagined voluntary movements with hit (true positive) rates above 70% and false positive rates below 3% while two subjects with high-level spinal-cord injuries demonstrated hit rates ranging from 45-48% and false positive rates below 1%.