Literature DB >> 23366626

Self-paced movement intention detection from human brain signals: Invasive and non-invasive EEG.

Eileen Lew1, Ricardo Chavarriaga, Huaijian Zhang, Margitta Seeck, Jose del R Millan.   

Abstract

Neural signatures of humans' movement intention can be exploited by future neuroprosthesis. We propose a method for detecting self-paced upper limb movement intention from brain signals acquired with both invasive and non-invasive methods. In the first study with scalp electroencephalograph (EEG) signals from healthy controls, we report single trial detection of movement intention using movement-related potentials (MRPs) in a frequency range between 0.1 to 1 Hz. Movement intention can be detected above chance level (p<0.05) on average 460 ms before the movement onset with low detection rate during the non-movement intention period. Using intracranial EEG (iEEG) from one epileptic subject, we detect movement intention as early as 1500 ms before movement onset with accuracy above 90% using electrodes implanted in the bilateral supplementary motor area (SMA). The coherent results obtained with non-invasive and invasive method and its generalization capabilities across different days of recording, strengthened the theory that self-paced movement intention can be detected before movement initiation for the advancement in robot-assisted neurorehabilitation.

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Year:  2012        PMID: 23366626     DOI: 10.1109/EMBC.2012.6346665

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  3 in total

Review 1.  Motor Intention/Intentionality and Associationism - A conceptual review.

Authors:  Denis Ebbesen; Jeppe Olsen
Journal:  Integr Psychol Behav Sci       Date:  2018-12

2.  Single trial prediction of self-paced reaching directions from EEG signals.

Authors:  Eileen Y L Lew; Ricardo Chavarriaga; Stefano Silvoni; José Del R Millán
Journal:  Front Neurosci       Date:  2014-08-01       Impact factor: 4.677

Review 3.  What Is the Readiness Potential?

Authors:  Aaron Schurger; Pengbo 'Ben' Hu; Joanna Pak; Adina L Roskies
Journal:  Trends Cogn Sci       Date:  2021-04-27       Impact factor: 20.229

  3 in total

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