Decoding of facial muscle-brain relation by information-based analysis of electromyogram (EMG) and electroencephalogram (EEG) signals

Decoding of the coupling among the brain and heart activations is an important research area in network physiology. We studied the coupling of brain and heart activations for 48 subjects who performed the NASA Revised Multi-Attribute Task Battery II under three different activity level conditions. During the experiment, the physical activity of subjects was manipulated by changing the speed of a stationary bike (including no movement, 50[Formula: see text]rpm, and 70[Formula: see text]rpm) or a treadmill (including no movement, 3[Formula: see text]km/h, and 5[Formula: see text]km/h), while their physiological signals were recorded. We analyzed the complex structure of electroencephalogram (EEG) and R-R signals using fractal theory and sample entropy. The results demonstrated that the alterations of the complex structures of EEG and R-R signals are strongly correlated, which indicates the coupling between brain and heart activations. This method of analysis can be applied to evaluate the coupling between different organs.

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Decoding of facial muscle-brain relation by information-based analysis of electromyogram (EMG) and electroencephalogram (EEG) signals

Abstract: Namazi (2021): Decoding of facial muscle-brain relation by information-based analysis of electromyogram (EMG) and electroencephalogram (EEG) signals, Waves in Random and Complex Media,

Cited by 8 publications

References 37 publications

Analysis of EEG and ECG time series in response to olfactory and Cognitive tasks

Analysis of EEG and ECG time series in response to olfactory and Cognitive tasks

A Simulated Intelligent Pixelated Electrode Array for Surface Electromyography Sensors

Decoding the Correlation Between Brain and Heart Activations in the Combination of Mental Workload and Physical Activity

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