Information-based analysis of the relationship between brain and facial muscle activities in response to static visual stimuli.

Facial muscle brain electroencephalography (EEG) signal electromyography (EMG) signal information shannon entropy static visual stimuli

Journal

Technology and health care : official journal of the European Society for Engineering and Medicine
ISSN: 1878-7401
Titre abrégé: Technol Health Care
Pays: Netherlands
ID NLM: 9314590

Informations de publication

Date de publication:
2021
Historique:
pubmed: 23 6 2020
medline: 1 9 2021
entrez: 23 6 2020
Statut: ppublish

Résumé

Human facial muscles react differently to different visual stimuli. It is known that the human brain controls and regulates the activity of the muscles. In this research, for the first time, we investigate how facial muscle reaction is related to the reaction of the human brain. Since both electromyography (EMG) and electroencephalography (EEG) signals, as the features of muscle and brain activities, contain information, we benefited from the information theory and computed the Shannon entropy of EMG and EEG signals when subjects were exposed to different static visual stimuli with different Shannon entropies (information content). Based on the obtained results, the variations of the information content of the EMG signal are related to the variations of the information content of the EEG signal and the visual stimuli. Statistical analysis also supported the results indicating that the visual stimuli with greater information content have a greater effect on the variation of the information content of both EEG and EMG signals. This investigation can be further continued to analyze the relationship between facial muscle and brain reactions in case of other types of stimuli.

Sections du résumé

BACKGROUND BACKGROUND
Human facial muscles react differently to different visual stimuli. It is known that the human brain controls and regulates the activity of the muscles.
OBJECTIVE OBJECTIVE
In this research, for the first time, we investigate how facial muscle reaction is related to the reaction of the human brain.
METHODS METHODS
Since both electromyography (EMG) and electroencephalography (EEG) signals, as the features of muscle and brain activities, contain information, we benefited from the information theory and computed the Shannon entropy of EMG and EEG signals when subjects were exposed to different static visual stimuli with different Shannon entropies (information content).
RESULTS RESULTS
Based on the obtained results, the variations of the information content of the EMG signal are related to the variations of the information content of the EEG signal and the visual stimuli. Statistical analysis also supported the results indicating that the visual stimuli with greater information content have a greater effect on the variation of the information content of both EEG and EMG signals.
CONCLUSION CONCLUSIONS
This investigation can be further continued to analyze the relationship between facial muscle and brain reactions in case of other types of stimuli.

Identifiants

pubmed: 32568131
pii: THC192085
doi: 10.3233/THC-192085
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

99-109

Auteurs

Mirra Soundirarajan (M)

School of Engineering, Monash University, Selangor, Malaysia.

Najmeh Pakniyat (N)

Shiraz University of Medical Sciences, Shiraz, Iran.

Sue Sim (S)

School of Engineering, Monash University, Selangor, Malaysia.

Visvamba Nathan (V)

School of Engineering, Monash University, Selangor, Malaysia.

Hamidreza Namazi (H)

School of Engineering, Monash University, Selangor, Malaysia.

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Classifications MeSH