Decoding of the Relationship between Brain and Facial Muscle Activities in Response to Dynamic Visual Stimuli

Soundirarajan, Mirra; Babini, Mohammad Hossein; Sim, Sue; Nathan, Visvamba; Namazi, Hamidreza

doi:10.1142/s0219477520500418

Cited by 17 publications

(2 citation statements)

References 36 publications

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“…The subjects’ EEG data was collected using the Emotiv Epoc, wireless 14-channel EEG acquisition equipment. 23 The signals were acquired using the widely established 10–20 electrode arrangement. The Emotiv system was chosen for its ease of use on children and the versatile architecture that allowed for full brain measurement.…”

Section: Methodsmentioning

confidence: 99%

Quantitative assessment of cognitive profile and brain asymmetry in the characterization of autism spectrum in children: A task-based EEG study

Balathay¹,

Narasimhan

Belo

et al. 2023

Proc Inst Mech Eng H

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Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by learning, attention, social, communication, and behavioral impairments. Each person with Autism has a different severity and level of brain functioning, ranging from high functioning (HF) to low functioning (LF), depending on their intellectual/developmental abilities. Identifying the level of functionality remains crucial in understanding the cognitive abilities of Autistic children. Assessment of EEG signals acquired during specific cognitive tasks is more appropriate in identifying brain functional and cognitive load variations. The spectral power of EEG sub-band frequency and parameters related to brain asymmetry has the potential to be employed as indices to characterize brain functioning. Thus, the objective of this work is to analyze the cognitive task-based electrophysiological variations in autistic and control groups, using EEG acquired during two well-defined protocols. Theta to Alpha ratio (TAR) and Theta to Beta ratio (TBR) of absolute powers of the respective sub-band frequencies have been estimated to quantify the cognitive load. The variations in interhemispheric cortical power measured by EEG were studied using the brain asymmetry index. For the arithmetic task, the TBR of the LF group was found to be considerably higher than the HF group. The findings reveal that the spectral powers of EEG sub-bands can be a key indicator in the assessment of high and low-functioning ASD to facilitate appropriate training strategies. Instead of depending solely on behavioral tests to diagnose autism, it could be a beneficial approach to use task-based EEG characteristics to differentiate between the LF and HF groups.

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Section: Methodsmentioning

confidence: 99%

Quantitative assessment of cognitive profile and brain asymmetry in the characterization of autism spectrum in children: A task-based EEG study

Balathay¹,

Narasimhan

Belo

et al. 2023

Proc Inst Mech Eng H

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“…Thus, the processed information in the brain and organs should be related. Considering the brain-facial muscles connection through the physiological system of the human body [9], we hypothesize that the information of facial EMG and EEG signals should be correlated. Thus, we evaluated the correlation of facial muscles and brain activities by quantifying their signals' information.…”

Section: Introductionmentioning

confidence: 99%

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

Pakniyat¹,

Soundirarajan

Gohari

et al. 2021

Waves in Random and Complex Media

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Complexity and Memory-Based Comparison of the Brain Activity Between Adhd and Healthy Subjects While Playing a Serious Game

et al. 2021

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Attention deficit hyperactivity disorder (ADHD) is a mental health disorder that is very common among children and may last into their adulthood. It is known that ADHD affects the attention of patients due to problems with short-term memory. Therefore, analysis of attention and memory of these patients should come into consideration. In this study, the complexity and memory of Electroencephalogram (EEG) signals are analyzed to investigate the reduction in attention and memory of patients with ADHD compared to normal subjects while playing a serious game. To achieve this, the fractal dimension and sample entropy of EEG signals are analyzed to evaluate the alterations in the complexity of EEG signals. Moreover, the Hurst exponent of EEG signals for ADHD and non-ADHD subjects is calculated to discuss the memory of EEG signals. The results showed a smaller fractal dimension and sample entropy of EEG signals for patients with ADHD that reflects their lower attention. Besides, the Hurst exponent of EEG signals for these patients reflects their lower memory than normal subjects. Therefore, it can be concluded that the reductions of attention and memory in ADHD subjects are mapped on the reduction of complexity and memory of their EEG signals.

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Decoding of the Relationship between Brain and Facial Muscle Activities in Response to Dynamic Visual Stimuli

Cited by 17 publications

References 36 publications

Quantitative assessment of cognitive profile and brain asymmetry in the characterization of autism spectrum in children: A task-based EEG study

Quantitative assessment of cognitive profile and brain asymmetry in the characterization of autism spectrum in children: A task-based EEG study

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

Complexity and Memory-Based Comparison of the Brain Activity Between Adhd and Healthy Subjects While Playing a Serious Game

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