Biomedical subjects

Gary E Birch

Publications and source records attributed to Gary E Birch.

4 recordsLinked to original sources

PubMed2003

A general framework for brain-computer interface design.

The Brain-Computer Interface (BCI) research community has acknowledged that researchers are experiencing difficulties when they try to compare the BCI techniques described in the literature. In response to this situation, the community has stressed the need for objective methods to compare BCI technologies. Suggested improvements have included the development and use of benchmark applications and standard data sets. However, as a young, multidisciplinary research field, the BCI community lacks a common vocabulary. As a result, this deficiency leads to poor intergroup communication, which hinders the development of the desired methods of comparison. One of the principle reasons for the lack of common vocabulary is the absence of a common functional model of a BCI System. This paper proposes a new functional model for BCI System design. The model supports many features that facilitate the comparison of BCI technologies with other BCI and non-BCI user interface technologies. From this model, taxonomy for BCI System design is developed. Together the model and taxonomy are considered a general framework for BCI System design. The representational power of the proposed framework was evaluated by applying it to a set of existing BCI technologies. The framework could effectively describe all of the BCI System designs tested.

Algorithms↗

PubMed2003

Current trends in brain-computer interface research at the Neil Squire Foundation.

The Neil Squire Foundation (NSF) is a Canadian nonprofit organization whose purpose is to create opportunities for independence for individuals who have significant physical disabilities. Over the last ten years, our team in partnership with researchers at the Electrical and Computer Engineering Department, the University of British Columbia, has been working to develop a direct brain-controlled switch for individuals with significant physical disabilities. The NSF Brain Interface Project primarily focuses on the development of brain-computer interface switch technologies for intermittent (or asynchronous) control in natural environments. That is, technologies that will work when the User intends control but also remains in a stable off state when there is no intent to control. A prototype of such a switch has successfully been developed. This switch has demonstrated classification accuracies greater than 94%. The initial results are promising, but further research is required to improve switch accuracies and reliability and to test these switch technologies over a larger population of users and operating conditions. This paper provides an overview of the NSF brain-switch technologies and details our approach to future work in this area.

Adult↗

PubMed2003

Linear and nonlinear methods for brain-computer interfaces.

At the recent Second International Meeting on Brain-Computer Interfaces (BCIs) held in June 2002 in Rensselaerville, NY, a formal debate was held on the pros and cons of linear and nonlinear methods in BCI research. Specific examples applying EEG data sets to linear and nonlinear methods are given and an overview of the various pros and cons of each approach is summarized. Overall, it was agreed that simplicity is generally best and, therefore, the use of linear methods is recommended wherever possible. It was also agreed that nonlinear methods in some applications can provide better results, particularly with complex and/or other very large data sets.

Algorithms↗

PubMed2002

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%.

Action Potentials↗