4.7 Article

Optimized Motor Imagery Paradigm Based on Imagining Chinese Characters Writing Movement

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNSRE.2017.2655542

Keywords

Motor imagery; brain-computer interface (BCI); CSP; paradigm

Funding

  1. Grant National Natural Science Foundation of China [61573142, 61203127, 91420302, 61305028]
  2. 13 Fundamental Research Funds for the Central Universities [WG1414005, WH1314023, WH1516018]
  3. Shanghai Chenguang Program [14CG31]

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Background: motor imagery (MI) is a mental representation of motor behavior. The MI-based brain computer interfaces (BCIs) can provide communication for the physically impaired. The performance of MI-based BCI mainly depends on the subject's ability to self-modulate electroencephalogram signals. Proper training can help naive subjects learn to modulate brain activity proficiently. However, training subjects typically involve abstract motor tasks and are time-consuming. Methods: to improve the performance of naive subjects during motor imagery, a novel paradigm was presented that would guide naive subjects to modulate brain activity effectively. In this new paradigm, pictures of the left or right hand were used as cues for subjects to finish the motor imagery task. Fourteen healthy subjects (11 male, aged 22-25 years, and mean 23.6 +/- 1.16) participated in this study. The task was to imagine writing a Chinese character. Specifically, subjects could imagine hand movements corresponding to the sequence of writing strokes in the Chinese character. This paradigm was meant to find an effective and familiar action formost Chinese people, to provide them with a specific, extensively practiced task and help them modulate brain activity. Results: results showed that the writing task paradigm yielded significantly better performance than the traditional arrow paradigm (p < 0.001). Questionnaire replies indicated that most subjects thought that the new paradigm was easier. Conclusion: the proposed new motor imagery paradigm could guide subjects to help them modulate brain activity effectively. Results showed that there were significant improvements using new paradigm, both in classification accuracy and usability.

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