Analysis of EEG signal by flicker-noise spectroscopy: identification of right-/left-hand movement imagination

Broniec, Anna

doi:10.1007/s11517-016-1491-z

Cited by 12 publications

(4 citation statements)

References 60 publications

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“…A comparison of the difference between C3 and C4 of the two subjects revealed that Subject A exhibited an obvious difference between C3 and C4. However, the results of this study were not completely consistent with the theory [ 28 , 41 ] and suggested that the brain wave measured by the C4 electrode was lower than that by C3 when imagining the movement of the left hand. Conversely, the brain wave measured by the C3 electrode was lower than that by C4 when imagining the movement of the right hand.…”

Section: Resultscontrasting

confidence: 99%

Improvement of brain–computer interface in motor imagery training through the designing of a dynamic experiment and FBCSP

Lin

Chen

2023

Heliyon

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Section: Resultscontrasting

confidence: 99%

Improvement of brain–computer interface in motor imagery training through the designing of a dynamic experiment and FBCSP

Lin

Chen

2023

Heliyon

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“…In summary, the available evidence collectively suggests that, for both motor skill performance and learning, both PP and CP approach tend to yield superior results compared to MP practiced alone.It has been suggested that MP and PP share similar neural mechanisms in the cognitive process, as evidenced by comparable brain activity during their execution (Jackson et al, 2003;Lee et al, 2019;Matsuo et al, 2020;Nakano, 2012). Specifically, MP has been shown to elicit brain activity in areas such as the primary motor area, premotor area, supplementary motor area, frontal area, parietal area, thalamus, and cerebellum, mirroring the patterns seen during PP (Broniec, 2016;Jackson et al, 2003;Lee et al, 2019;Wang et al, 2014;Zich et al, 2017). Nonetheless, some variations in brain activation have been noted in prior research, where different brain regions are engaged during MP (Di Nota et al, 2016;Macuga & Frey, 2012).…”

Section: Discussionmentioning

confidence: 89%

Physical practice, mental practice or both: a systematic review with meta-analysis

Jiménez-Díaz,

Chaves-Castro,

Morera-Castro

et al. 2024

J Physical Educ & Hum Mov

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Introduction: Previous research has reached positive conclusions regarding the effects of mental practice on performance and learning of a motor skill. The purpose of this study was to use the aggregate data meta-analytic approach to assess the impact of physical practice (PP), mental practice (MP), and the combination of both on acquisition, retention, and transfer tests in motor skill performance. Methodology: Twenty-seven studies published up to 2022 were included by searching six databases. Random effects model using the standardized mean difference effect size (ES) was used to pool results. Results: A total of 42 ES, were calculated and separated into pairwise comparisons for acquisition, retention, and transfer phase. In the acquisition phase, it was found that MP was more effective than no practice (ES=0.508; n=25; CI=0.29,0.72), PP was more effective than no practice (ES=1.78; n=15; CI=0.97,2.60), CP was more effective than no practice (ES=1.16; n=12; CI=0.57,1.75), PP was more effective than MP (ES=-1.16; n=23; CI=-1.88,-0.45), PP had similar results as CP (ES=-0.01; n=16; CI=-0.31,0.28), and CP was more effective than MP (ES=0.61; n=12; CI=0.17,1.04). In the retention phase, it was found that MP was more effective than no practice (ES=1.11; n=5; CI=0.44,1.79), PP was more effective than no practice (ES=1.03; n=4; CI=0.08, 1.99), PP was more effective than MP (ES=-1.29; n=9; CI=-3.12,0.54), PP had similar results as CP (ES=0.16; n=8; CI=-0.29,0.63), CP had similar results as MP (ES=-0.06; n=3; CI=-1.22,1.09). In the transfer phase, it was found that MP was more effective than no practice (ES=1.12; n=5; CI=0.01,1.59), PP had similar results as no practice (ES=0.41; n=5; CI=-0.02,0.85), and PP was more effective than MP (ES=0.50; n=6; CI=0.12,0.87). Age, skill level, type of mental practice, total of sessions, and type of skill were considered as possible moderator variables. Conclusions: Mental practice does not replace physical practice, however, under some conditions, physical practice can be complemented with mental practice.

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“…In this study, we replaced the probability in the time domain by the energy spectrum density in the frequency domain to obtain the expression of the energy spectrum in the frequency domain as follows [ 17 , 21 ]:

…”

Section: Methodsmentioning

confidence: 99%

Motor Imagination of Lower Limb Movements at Different Frequencies

Liu

Chen

Belkacem

et al. 2021

Journal of Healthcare Engineering

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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.

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Analysis of EEG signal by flicker-noise spectroscopy: identification of right-/left-hand movement imagination

Cited by 12 publications

References 60 publications

Improvement of brain–computer interface in motor imagery training through the designing of a dynamic experiment and FBCSP

Improvement of brain–computer interface in motor imagery training through the designing of a dynamic experiment and FBCSP

Physical practice, mental practice or both: a systematic review with meta-analysis

Motor Imagination of Lower Limb Movements at Different Frequencies

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