Abstract
Motor imagination (MI) is the mental process of only imagining an action without an actual movement. Research on MI has made significant progress in feature information detection and machine learning decoding algorithms, but there are still problems, such as a low overall recognition rate and large differences in individual execution effects, which make the development of MI run into a bottleneck. Aiming at solving this bottleneck problem, the current study optimized the quality of the MI original signal by “enhancing the difficulty of imagination tasks,” conducted the qualitative and quantitative analyses of EEG rhythm characteristics, and used quantitative indicators, such as ERD mean value and recognition rate. Research on the comparative analysis of the lower limb MI of different tasks, namely, high-frequency motor imagination (HFMI) and low-frequency motor imagination (LFMI), was conducted. The results validate the following: the average ERD of HFMI (−1.827) is less than that of LFMI (−1.3487) in the alpha band, so did (−3.4756 < −2.2891) in the beta band. In the alpha and beta characteristic frequency bands, the average ERD of HFMI is smaller than that of LFMI, and the ERD values of the two are significantly different (p=0.0074 < 0.01; r = 0.945). The ERD intensity STD values of HFMI are less than those of LFMI. which suggests that the ERD intensity individual difference among the subjects is smaller in the HFMI mode than in the LFMI mode. The average recognition rate of HFMI is higher than that of LFMI (87.84% > 76.46%), and the recognition rate of the two modes is significantly different (p=0.0034 < 0.01; r = 0.429). In summary, this research optimizes the quality of MI brain signal sources by enhancing the difficulty of imagination tasks, achieving the purpose of improving the overall recognition rate of the lower limb MI of the participants and reducing the differences of individual execution effects and signal quality among the subjects.
Highlights
The method of simulating exercise has received extensive attention from the brain science and neuroscience fields
−2.3827 −2.5407 −1.6239 −2.4161 −3.4839 −2.3341 −2.0094 −1.2393 −1.7632 −3.0973 −2.2891 0.6725 reached 87.84%, and that of LFMI has reached 76.46%, which have exceeded the globally recognized available level (70%). e standard deviation (STD) of recognition rates in HFMI is 0.00318, less than that of LFMI (0.00669), which suggests that individual difference of recognition rates among the subjects is smaller in the HFMI mode than in the LFMI mode
The experimental paradigms of HFMI and LFMI are compared, and the research results confirm that the rhythm characteristics of HFMI EEG are more significant than those of LFMI
Summary
The method of simulating exercise has received extensive attention from the brain science and neuroscience fields. A mode similar to simulated exercise is a kind of self-movement in the brain, that is, motor imagination [1,2,3]. Motor imagination (MI) is defined as having no movement of oneself, relying on one’s own brain to perform the movement of imagining oneself [4]. In the process of MI, it can enhance the ability to activate a specific motor function area in the brain and achieve the purpose of improving the motor function [5, 6]. Motor imagination and actual action execution have similar cognitive processes, which can reveal the inner relationship between the neural mechanism of motor imagination and actual action execution [7]. MI has the characteristics of independence and spontaneity that do not depend on external stimuli and has been widely used in the neurorehabilitation of stroke patients, sports training, brain-computer interface, and other fields and has become a research hotspot [8]
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