The Relation between Chaotic Feature of Surface EEG and Muscle Force: Case Study Report

Fereidoun Nowshiravan Rahatabad, Parisa Rangraz, Masood Dalir, Ali Motie Nasrabadi

DOI: 10.4103/jmss.JMSS_47_20

Abstract


Background: Nonlinear dynamics, especially the chaos characteristics, are useful in analyzing bio-potentials with many complexities. In this study, the evaluation of arm-tip force estimation method from the electroencephalography (EEG) signal in the vertical plane has been studied and chaos characteristics, including fractal dimension, Lyapunov exponent, entropy, and correlation dimension characteristics of EEG signals have been measured and analyzed at different levels of forces. Method: Electromyography signal was recorded with the help of the BIOPEC device (the Mp-100 model) and from the forearm muscle with surface electrodes, and the EEG signals were recorded from five major motor-related cortical areas according to 10-20 standard three times in a normal healthy 33-year-old male, athlete and right handed simultaneously with importing a force to 10 sinkers weighing from 10 to 100 Newton with step 10 Newton. Results: The findings confirm that force estimation through EEG signals is feasible, especially using fractal dimension feature. The R-squared values for Fractal dimension, Lyapunov exponent, and entropy and correlation dimension features for linear trend line were 0.93, 0.7, 0.86, and 0.41, respectively. Conclusion: The linear increase of characteristics especially fractal dimension and entropy, together with the results from other EEG and neuroimaging studies, suggests that under normal conditions, brain recruits motor neurons at a linear progress when increasing the force.


Keywords


Brain, dynamic, electroencephalography, force estimation, motor control, signal complexity

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References


Liu JZ, Yang Q, Yao B, Brown RW, Yue GH. Linear correlation between fractal dimension of EEG signal and handgrip force. Biol Cybern 2005;93:131-40.

Liang H, Zhu C, Yoshikawa Y, Yoshioka M, Uemoto K, Yu H, et al. EMG estimation from EEG for constructing a power assist system. IEEE Int Conf Robotics Biomim 2014;419-24.

Siemionow V, Yue GH, Ranganathan VK, Liu JZ, Sahgal V. Relationship between motor activity-related cortical potential and voluntary muscle activation. Exp Brain Res 2000;133:303-11.

Mihajlovic V, Li H, Grundlehner B, Penders J, Schouten AC. Investigating the impact of force and movements on impedance magnitude and EEG. Annu Int Conf IEEE Eng Med Biol Soc 2013;2013:1466-9.

Yao B, Liu JZ, Brown RW, Sahgal V, Yue GH. Nonlinear features of surface EEG showing systematic brain signal adaptations with muscle force and fatigue. Brain Res 2009;1272:89-98.

Yang Q, Jing Zhi L, Sahgal V, Yue GH. Time-dependent association between source strength of scalp EEG and level of voluntary muscle activation. J Biomech 2007;40:S302.

Fernandez-Vargas J, Tarvainen TV, Kita K, Yu W. Hand motion reconstruction using EEG and EMG. 2016 4th International Winter Conference on Brain-Computer Interface; 2016.

Kristeva-Feige R, Fritsch C, Timmer J, Lücking CH. Effects of attention and precision of exerted force on beta range EEG-EMG synchronization during a maintained motor contraction task. Clin Neurophysiol 2002;113:124-31.

Shibata T, Suhara Y, Oga T, Ueki Y, Mima T, Ishii S. Application of multivariate autoregressive modeling for analyzing the interaction between EEG and EMG in humans. International Congress Series 2004;1270:249-53.

Kiguchi K, Hayashi Y. Task estimation of upper-limb using EEG and EMG signals. IEEE ASME Int Conf Adv Intell Mechatron 2016;1229-32.

Nowshirvan Rahatabad F, Jafari AH, Fallah A. A study of chaotic phenomena in human-like reaching movements. Int J Bifurcat Chaos 2012;21:3293-303.

Sepanta S, Nowshiravan Rahatabad F, Einalou Z. Detection of different levels of multiple sclerosis by assessing nonlinear characteristics of posture. Int Clin Neurosci J 2018;5:115-20.

Available from: http://home.iitk.ac.in/~shalab/regression/Chapter12-Regression-PolynomialRegression.pdf. [Last accessed 2020 Sep 20].


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