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

doi:10.1109/SMC.2016.7844513

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 proceeding › Conference contribution

14 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 language	English
Title of host publication	2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1884-1887
Number of pages	4
ISBN (Electronic)	9781509018970
DOIs	https://doi.org/10.1109/SMC.2016.7844513
Publication status	Published - 2017 Feb 6
Event	2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Budapest, Hungary Duration: 2016 Oct 9 → 2016 Oct 12

Other

Other	2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016
Country/Territory	Hungary
City	Budapest
Period	16/10/9 → 16/10/12

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

Access to Document

10.1109/SMC.2016.7844513

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). Article 7844513 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 et al.
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.

Research output: Chapter in Book/Report/Conference proceeding › Conference 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, Institute of Electrical and Electronics Engineers Inc., pp. 1884-1887, 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016, Budapest, Hungary, 16/10/9. https://doi.org/10.1109/SMC.2016.7844513

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

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Keywords

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