Brain-Machine Interface (BMI) based on Electroencephalogra​phy (EEG)

Real-Time Discrete Wavelet Transform and ANFIS classifier for Brain-Machine Interface based on EEG

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Main program: bmi_three_channels

The explanation of the project methodology and results is presented on:
http://www.youtube.com/watch?v=4IodfA_fHUM

The signal processing algorithm and pattern recognition system are presented in the IEEE publication:
Eduardo López-Arce Vivas, Alejandro García-González, Iván Figueroa, and Rita Fuentes. Discrete Wavelet Transform and ANFIS Classifier for Brain-Machine Interface based on EEG. International Conference on Human System Interaction, 2013. (THE BEST PAPER AWARD in the area of Human Machine Interaction)
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6577814&tag=1

Special Features:
*Algorithm for Real-Time Discrete Wavelet Transform.
*NI DAQ USB-6009 for Matlab 64-bits using listener and event.
*NI DAQ USB-6009 for Matlab 64-bits: analog input and digital output simultaneous sessions.
*On-line data plotted on GUI.
*Off-line Short-Time Fourier Transform data analysis.
*Save data acquired on GUI.

Cite As

Eduardo (2026). Brain-Machine Interface (BMI) based on Electroencephalography (EEG) (https://www.mathworks.com/matlabcentral/fileexchange/43795-brain-machine-interface-bmi-based-on-electroencephalography-eeg), MATLAB Central File Exchange. Retrieved .

General Information

MATLAB Release Compatibility

  • Compatible with any release

Platform Compatibility

  • Windows
  • macOS
  • Linux
Version Published Release Notes Action
1.0.0.0