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Noninvasive BMI Unit
Andrzej CICHOCKI
Unit Leader
Andrzej CICHOCKI (Ph.D.)
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Research Areas

The Noninvasive BMI Unit investigates and develops tools and software for analysis, extraction, enhancement, de-noising, detection, localization, recognition and classification of brain signals and patterns, especially measured by high density array EEG and EMG systems.
We are actually developing multi-command on-line BMI platforms and a system for estimating some mental states.

Research Subject

  1. Nonivasive Brain Machine Interface, affective BMI
  2. Estimation of human emotions ussing EEG and NIRS
  3. Multiway array (tensor) decompositions for brain data
  4. Evaluation of coognitive impairment of elderly drivers
  5. Reahabilitaion using hyperscanning and brain to brain interface

Related links

  1. RIKEN Brain Science Institute Website_Laboratories PageNew Window
  2. Individual Website Laboratory PageNew Window
  3. Dr. Andrzej Cichocki's Home PageNew Window

Press release

June 29, 2009
Real-time control of wheelchairs with brain waves
- A new signal processing technology for brain machine interface (BMI) application -

List of Selected Publications

  1. A. Cichocki, R. Zdunek, A.H. Phan and S. Amari,:
    "Nonnegative Matrix and Tensor Factorization: In Aplications to Exploratory Multway Data Analysis"
    Monograph (477 pages) Joohn Wiley, 2009
  2. A. Cichocki. and A-H Phan:
    "Fast Local Algorithms for Large Scale Nonnegative Matrix and Tensor Factorizations"
    IEICE Trans. Fundamentals, (Invited paper) ( March 2009).
  3. Cichocki, A., Washizawa, Y., Rutkowski, T., Bakardjian, H., Phan, H-A., Choi, S., Lee, H., Zhao, Q., Liqing, Z., and Li, Y.:
    "Noninvasive BCIs: Multiway Signal-preocessing Array Decompsitions"
    Computer, Vol. 41, No. 10, 34-42 (2008).
  4. Martinez, P., Bakardjian, H., Vallverdu, M., and Cichocki, A.:
    "Fast Multi-command SSVEP Brain Machine Interface without Training"
    Lecture Notes in Computer Science (ICANN 2008), 300-307 (2008).
  5. H. Bakardijan, T. Tanaka and A. Cichocki,:
    "Optimization of SSVEP Brain Responses with Application to Eight-command Brain-Computer"
    Interface. Neuroscience Letters, 469 (1), 34-38 (2010).
  6. Rutkowski T, Tanaka T, Cichocki A, Erickson D, Cao J, Mandic D. P.:
    "Interactive components extraction from fEEG and fNIRS for affective brain machine interfacing paradigms"
    Computers in Human Behavior (in press). (2011)
  7. Rutkowski T, Mandic D, Cichocki A, Przybyszewski A.:
    "EMD Approach to Multichannel EEG Data - The Amplitude and Phase Components Clustering Analysis"
    Journal of Circuits, Systems, and Computers 19(1), 215-229 (2010).
  8. Phan A-H, Cichocki A.:
    "Tensor Decompositions for Feature Extraction and Classification of High Dimensional Datasets".
    Nonlinear Theory and Its Applications, IEICE, 1(1), 37-68 (2010).
  9. Zhao Q, Rutkowski T, Zhang L, Cichocki A.:
    "Generalized Optimal Spatial Filtering Using a Kernel Approach with Application to EEG Classification"
    Cognitive Neurodynamiccs, 4(4), 355-358 (2010).
  10. He Z, Cichocki A, Xie S, Choi K.:
    "Detecting the Number of Clusters in n-way Probabilistic Clustering".
    IEEE Transactions on Pattern Analysis and Machine Intelligence 32(11), 2006-2021 (2010).
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