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Applying support vector regression analysis on grip force level-related corticomuscular coherence

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机构: [1]College of Life Science and Bioengineering, Beijing University of Technology, Beijing, People’s Republic of China 100124 [2]Medical Engineering Division, Xuanwu Hospital, Capital Medical University, Beijing, China 100053 [3]Department of Informatics and Mathematical Modeling, Technical University of Denmark, Kgs. Lyngby, Denmark 2800 [4]Institute of Medical Information, School of Biomedical Engineering, Southern Medical University, Guangzhou, China 510515
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关键词: Corticomuscular coherence Support vector regression EEG EMG

摘要:
Voluntary motor performance is the result of cortical commands driving muscle actions. Corticomuscular coherence can be used to examine the functional coupling or communication between human brain and muscles. To investigate the effects of grip force level on corticomuscular coherence in an accessory muscle, this study proposed an expanded support vector regression (ESVR) algorithm to quantify the coherence between electroencephalogram (EEG) from sensorimotor cortex and surface electromyogram (EMG) from brachioradialis in upper limb. A measure called coherence proportion was introduced to compare the corticomuscular coherence in the alpha (7-15Hz), beta (15-30Hz) and gamma (30-45Hz) band at 25 % maximum grip force (MGF) and 75 % MGF. Results show that ESVR could reduce the influence of deflected signals and summarize the overall behavior of multiple coherence curves. Coherence proportion is more sensitive to grip force level than coherence area. The significantly higher corticomuscular coherence occurred in the alpha (p < 0.01) and beta band (p < 0.01) during 75 % MGF, but in the gamma band (p < 0.01) during 25 % MGF. The results suggest that sensorimotor cortex might control the activity of an accessory muscle for hand grip with increased grip intensity by changing functional corticomuscular coupling at certain frequency bands (alpha, beta and gamma bands).

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出版当年[2013]版:
大类 | 3 区 生物
小类 | 2 区 数学与计算生物学 4 区 神经科学
最新[2023]版:
大类 | 4 区 医学
小类 | 4 区 数学与计算生物学 4 区 神经科学
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出版当年[2012]版:
Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY Q3 NEUROSCIENCES
最新[2023]版:
Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY Q4 NEUROSCIENCES

影响因子: 最新[2023版] 最新五年平均 出版当年[2012版] 出版当年五年平均 出版前一年[2011版] 出版后一年[2013版]

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第一作者机构: [1]College of Life Science and Bioengineering, Beijing University of Technology, Beijing, People’s Republic of China 100124 [2]Medical Engineering Division, Xuanwu Hospital, Capital Medical University, Beijing, China 100053
通讯作者:
通讯机构: [1]College of Life Science and Bioengineering, Beijing University of Technology, Beijing, People’s Republic of China 100124
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