Cross-frequency information transfer from EEG to EMG in grasping

Winnie Ka Yan SO, Lingling YANG, Beth JELFS, Qi SHE, Wai Ho Savio WONG, Joseph N.F. MAK, Rosa H. M. CHAN

Research output: Contribution to conferencePaper

7 Citations (Scopus)

Abstract

This paper presents an investigation into the cortico-muscular relationship during a grasping task by evaluating the information transfer between EEG and EMG signals.Information transfer was computed via a non-linear model-free measure, transfer entropy (TE). To examine the cross-frequency interaction, TEs were computed after the times series were decomposed into various frequency ranges via wavelet transform. Our results demonstrate the capability of TE to capture the direct interaction between EEG and EMG. In addition, the cross-frequency analysis revealed instantaneous decrease in information transfer from EEG to the high frequency component of EMG (100-200Hz) during the onset of movement.
Original languageEnglish
Publication statusPublished - Aug 2016

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Electroencephalography
Entropy
Wavelet transforms
Time series

Citation

So, K. Y., Yang, L., Jelfs, B., She, Q., Wong, S. W. H., Mak, J., et al. (2016, August). Cross-frequency information transfer from EEG to EMG in grasping. Paper presented at The 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’16), Disney’s Contemporary Resort, Florida, USA.

Keywords

  • Brain functional imaging - EEG
  • Neuromuscular systems - EMG processing and applications
  • Brain functional imaging - Connectivity and information flow