A novel pattern with high-level commands for encoding motor imagery-based brain computer interface

Shuailei Zhang, Shuai Wang*, Dezhi Zheng, Kai Zhu, Mengxi Dai

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

Abstract

Motor Imagery (MI)-based Brain Computer Interface (BCI) has received increasing attention from academicians for its practicability and convenience. With the development of classification algorithms, many traditional patterns based on low-level commands, such as the movement of hands, feet, tongue, or shoulders, can be decoded quite well. However, when encoded by low-level commands, each body part can perform only one imaginary command. This not only limits the number of tasks that a user's body can encode, but also makes the system less user-centered. In this paper, we proposed a novel pattern based on high-level commands for encoding MI BCI. This pattern combines clockwise and anticlockwise movements of both hands. Compared with a typical traditional pattern based on low-level commands, this pattern shows insignificant differences with regard to distinctiveness and stability for some of the tested subjects (p > 0.05). Thus, the proposed pattern can potentially allow additional tasks by human body without reducing their distinctiveness and stability. The results of this study also provide insights into the creation of high-level commands and improvements toward more intelligent and user-centered systems.

Original languageEnglish
Pages (from-to)28-34
Number of pages7
JournalPattern Recognition Letters
Volume125
DOIs
Publication statusPublished - 1 Jul 2019
Externally publishedYes

Keywords

  • Brain-computer interface
  • Distinctiveness
  • High-level commands
  • Motor imagery
  • Stability

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