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Research on Brain Dynamics of Precision Grip Force Control |
Zhang Na1, Li Ke1#*, Hou Ying2, Zhang Dongmei2, Wei Na3,4* |
1(Department of Biomedical Engineering, School of Control Science and Engineering, Shandong University, Jinan 250061, China) 2(Department of Rehabilitation, Suzhou Hospital, Nanjing Medical University, Suzhou 215008, Jiangsu, China) 3(Department of Geriatrics, Qilu Hospital, Shandong University, Jinan 250012, China) 4(Suzhou Institute of Shandong University, Suzhou 215123, Jiangsu, China) |
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Abstract Precision grip is the basis of many delicate and complex operations, it contains complex neural control mechanism. However, less is known about the dynamics of the brain during precision grip force regulation. This study aimed to explore the finger force behaviors and electroencephalogram (EEG) characteristics at different force amplitude during precision grip. Twelve healthy subjects were asked to grasp precisely at 10%, 20% and 30% of maximum voluntary contraction (MVC), during which the force signals, the center of pressure (COP) of thumb and index digits and the EEG signals were recorded and then analyzed by coefficient of variation (CV), the COP velocities and COP areas, recurrence quantification analysis (RQA).Results showed that there was a linear positive correlation between CV and force level (thumb: r=0.624, P<0.001; index: r=0.721, P<0.001). The COP areas of thumb and index fingers at 30% of MVC were (1.94±1.21) and (2.02±1.45) mm2, which were significantly higher than that at 10% ((1.01±0.81), (0.89±1.02) mm2) and 20% of MVC ((1.20±0.62), (1.16±0.63) mm2,P<0.05). For the thumb fingers, the COP velocity values of x-axis and y-axis under 10%, 20% and 30% of MVC were (4.23±1.11), (2.11±0.50), (1.70±0.40) mm/s and (6.22±1.45), (3.39±0.70), (2.90±0.69) mm/s respectively, showing a decreased tendency with the force level increased (P<0.01). For the index fingers, the COP velocity values of x-axis and y-axis at 10% of MVC ((4.95±1.34) and (7.04±1.75) mm/s) were significantly higher than that at 20% ((2.78±0.53) and (3.79±0.63) mm/s) and 30% MVC ((2.95±0.94) and (3.54±0.82) mm/s, P<0.05). The RQA parameters of α-band EEG signals decreased significantly with the force level increased (P < 0.05). These results suggested that the variability of force, the reduction of the digits’ adjustment speed and control instability, the complexity of EEG signals was increased with the force level augmented. Furthermore, α-band of EEG was closely related to the motor control of precision grip. This study revealed the close coupling between finger force control and dynamic behavior of the central nervous system, which provides a new path for the in-depth study of the central peripheral cooperative mechanism and the quantitative evaluation of the neuromuscular system function.
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Received: 12 October 2019
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