OpenBMI

A real-time data analysis toolbox for Brain-Machine Interfaces

Min Ho Lee, Keun Tae Kim, Yeong Jin Kee, Ji Hoon Jeong, Seon Min Kim, Siamac Fazli, Seong Whan Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

Recently, there has been an increased demand for Brain-Machine Interface (BMI) toolboxes for neuroscientifc research. In many BMI applications, speller systems can provide an efficient communication channel for users with disabilities. Here, we introduce an open-source BMI toolbox termed 'OpenBMI', which supports the various signal processing chains for common BMI paradigms, such as event-related potentials (ERPs) and steady-state visual evoked potentials (SSVEP). The OpenBMI framework consists of ready-to-use experimental paradigms, offline data analysis techniques, online feedback as well as evaluation modules. The data analysis modules provide essential pre-processing steps (segmentation, baseline correction, etc.) as well as signal processing algorithms such as temporal and spatial filtering, artifact rejection, among others. The experimental paradigms of ERP and SSVEP are available with fully open-sourced demo scripts. Users can easily modify or extend the demo scripts for their needs. In this article, the OpenBMI framework, its features as well as its future development plan is introduced.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1884-1887
Number of pages4
ISBN (Electronic)9781509018970
DOIs
Publication statusPublished - Feb 6 2017
Externally publishedYes
Event2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Budapest, Hungary
Duration: Oct 9 2016Oct 12 2016

Publication series

Name2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings

Conference

Conference2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016
CountryHungary
CityBudapest
Period10/9/1610/12/16

Fingerprint

Bioelectric potentials
Brain
Data analysis
Event-related Potentials
Real-time
Paradigm
Signal Processing
Signal processing
Spatial Filtering
Module
Disability
Communication Channels
Rejection
Open Source
Preprocessing
Baseline
Segmentation
Feedback
Evaluation
Processing

Keywords

  • Brain-Machine Interface
  • Event-Related Potential
  • Evoked Potential
  • Open-Source Software
  • OpenBMI
  • Signal Processing
  • Steady-State Visual

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Control and Optimization
  • Human-Computer Interaction

Cite this

Lee, M. H., Kim, K. T., Kee, Y. J., Jeong, J. H., Kim, S. M., Fazli, S., & Lee, S. W. (2017). OpenBMI: A real-time data analysis toolbox for Brain-Machine Interfaces. In 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings (pp. 1884-1887). [7844513] (2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SMC.2016.7844513

OpenBMI : A real-time data analysis toolbox for Brain-Machine Interfaces. / Lee, Min Ho; Kim, Keun Tae; Kee, Yeong Jin; Jeong, Ji Hoon; Kim, Seon Min; Fazli, Siamac; Lee, Seong Whan.

2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1884-1887 7844513 (2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Lee, MH, Kim, KT, Kee, YJ, Jeong, JH, Kim, SM, Fazli, S & Lee, SW 2017, OpenBMI: A real-time data analysis toolbox for Brain-Machine Interfaces. in 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings., 7844513, 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 1884-1887, 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016, Budapest, Hungary, 10/9/16. https://doi.org/10.1109/SMC.2016.7844513
Lee MH, Kim KT, Kee YJ, Jeong JH, Kim SM, Fazli S et al. OpenBMI: A real-time data analysis toolbox for Brain-Machine Interfaces. In 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1884-1887. 7844513. (2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings). https://doi.org/10.1109/SMC.2016.7844513
Lee, Min Ho ; Kim, Keun Tae ; Kee, Yeong Jin ; Jeong, Ji Hoon ; Kim, Seon Min ; Fazli, Siamac ; Lee, Seong Whan. / OpenBMI : A real-time data analysis toolbox for Brain-Machine Interfaces. 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1884-1887 (2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings).
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