A general framework for characterizing studies of brain interface technology.
The development of brain interface (BI) technology continues to attract researchers with a wide range of backgrounds and expertise. Though the BI community is committed to accurate and objective evaluation of methods, systems, and technology, the very diversity of the methods and terminology used in the field hinders understanding and impairs technology cross-fertilization and cross-group validation of findings. Underlying this dilemma is a lack of common perspective and language. As seen in our previous works in this area, our approach to remedy this problem is to propose language in the form of taxonomy and functional models. Our intent is to document and validate our best thinking in this area and publish a perspective that will stimulate discussion. We encourage others to do the same with the belief that focused discussion on language issues will accelerate the inherently slow natural evolution of language selection and thus alleviate related problems. In this work, we propose a theoretical framework for describing BI-technology-related studies. The proposed framework is based on the theoretical concepts and terminology from classical science, assistive technology development, human-computer interaction, and previous BI-related works. Using a representative set of studies from the literature, the proposed BI study framework was shown to be complete and appropriate perspective for thoroughly characterizing a BI study. We have also demonstrated that this BI study framework is useful for (1) objectively reviewing existing BI study designs and results, (2) comparing designs and results of multiple BI studies, (3) designing new studies or objectively reporting BI study results, and (4) facilitating intra- and inter-group communication and the education of new researchers. As such, it forms a sound and appropriate basis for community discussion.
Mason
S G
SG
Neil Squire Society, 220-2250 Boundary Rd., Burnaby, BC, Canada, V5M 4L9. smason@telus.net
Jackson
M M Moore
MM
Birch
G E
GE
D001921:Brain / Q000502:physiology; D016287:Computer Peripherals; D006801:Humans; D008962:Models, Theoretical; D016571:Neural Networks, Computer