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Analyzing Trends in Brain Interface Technology: A Method to Compare Studies

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Continued progress in the field of Brain Interface (BI) research has encouraged the rapid expansion of the BI community over the last two decades. As the number of BI researchers and organizations steadily increases, newer and more advanced technologies are constantly produced, evaluated, and reported. Though the BI community is committed to accurate and objective evaluation of methods, systems, and technology, the diversity of the field has hindered the development of objective methods of comparison. This paper introduces a new method for directly comparing studies of BI technology based on the theoretical models and taxonomy proposed by Mason, Moore, and Birch. The effectiveness of the proposed method was demonstrated by interpreting and comparing a representative set of 21 BI studies. The method allowed us to 1) identify the salient aspects of a specific BI study, 2) identify what has been reported and what has been omitted, 3) facilitate a complete and objective comparison with other studies, and 4) characterize overall trends, areas of inactivity, and reporting practices.

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Notes

  1. In this work, the terms Brain–Computer Interface (BCI) research, Brain–Machine Interface (BMI) research, and Direct Brain Interface (DBI) research are included under the umbrella term Brain Interface (BI) research.

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ACKNOWLEDGMENTS

This work was supported by the National Science Foundation's Universal Access program, under NSF Project number 0118917, the Canadian Institutes of Health Research grant MOP-62711, the Natural Sciences and Engineering Research Council of Canada, grant 90278-02. We would like to thank Gordon Handford, Adriane Davis, Brendan Allison, Jaimie Borisoff and Regi Bohringer for their insightful feedback during the preparation of the manuscript.

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Authors and Affiliations

  1. College of Computing, Georgia Institute of Technology, Atlanta, Georgia, USA

    M. M. Moore Jackson

  2. Neil Squire Foundation, 220-2250 Boundary Road, Burnaby, BC, Canada, V5M 4L9

    S. G. Mason & G. E. Birch

  3. Department of Electrical and Computer Engineering, The University of British Columbia, 2356 Main Mall, Vancouver, Canada, V6T 1Z4

    G. E. Birch

Authors
  1. M. M. Moore Jackson
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  2. S. G. Mason
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  3. G. E. Birch
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Corresponding author

Correspondence to M. M. Moore Jackson.

APPENDIX: TEST SET

APPENDIX: TEST SET

The representative test set used for method demonstration is summarized in Table A1. For space efficiency, we will use the following abbreviations: TNSRE, IEEE Transactions on Neural Systems and Rehabilitation Engineering and TRE, IEEE Transactions on Rehabilitation Engineering.

TABLE A1. Representative test set used for method demonstration.
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Jackson, M.M.M., Mason, S.G. & Birch, G.E. Analyzing Trends in Brain Interface Technology: A Method to Compare Studies. Ann Biomed Eng 34, 859–878 (2006). https://doi.org/10.1007/s10439-005-9055-7

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  • DOI: https://doi.org/10.1007/s10439-005-9055-7

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