Analysis of the correlation between the human voice and brain activity

Namazi, Hamidreza; Ahamed, Mohamed Rasmi Ashfaq; Babini, Mohammad Hossein; Krejcar, Ondřej

doi:10.1080/17455030.2021.1921313

Cited by 12 publications

(1 citation statement)

References 34 publications

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“…Although many reported works analyzed the complex structure of EEG signals in different conditions [e.g., response to different stimuli (Namazi et al, 2021a), classifying brain disorders (Simons et al, 2015)] using sample entropy, however, no reported work evaluated the complexity of EEG signals during walking or running using sample entropy.…”

Section: Introductionmentioning

confidence: 99%

Complexity-Based Analysis of the Variations of Brain and Muscle Reactions in Walking and Standing Balance While Receiving Different Perturbations

Pakniyat¹,

Namazi

2021

Front. Hum. Neurosci.

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In this article, we evaluated the variations of the brain and muscle activations while subjects are exposed to different perturbations to walking and standing balance. Since EEG and EMG signals have complex structures, we utilized the complexity-based analysis. Specifically, we analyzed the fractal dimension and sample entropy of Electroencephalogram (EEG) and Electromyogram (EMG) signals while subjects walked and stood, and received different perturbations in the form of pulling and rotation (via virtual reality). The results showed that the complexity of EEG signals was higher in walking than standing as the result of different perturbations. However, the complexity of EMG signals was higher in standing than walking as the result of different perturbations. Therefore, the alterations in the complexity of EEG and EMG signals are inversely correlated. This analysis could be extended to investigate simultaneous variations of rhythmic patterns of other physiological signals while subjects perform different activities.

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Section: Introductionmentioning

confidence: 99%

Complexity-Based Analysis of the Variations of Brain and Muscle Reactions in Walking and Standing Balance While Receiving Different Perturbations

Pakniyat¹,

Namazi

2021

Front. Hum. Neurosci.

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Complexity and Information-Based Analysis of the Heart Rate Variability (Hrv) While Sitting, Hand Biking, Walking, and Running

Namazi

2021

Fractals

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Analysis of the variations of heart activity during different human activities is an important area of research in sport sciences. Therefore, in this paper, we evaluated the variations of heart activity for 23 subjects while sitting, hand biking, walking, and running. Since the obtained R-R time series (as the indicator of heart rate variability (HRV)) has a complex structure that contains information, we employed fractal dimension, sample entropy, and Shannon entropy for our analysis. According to the results, doing a harder activity causes a more significant alteration in the complexity and information content of HRV. The results of statistical analyses also verified the obtained results. Similar investigations can be conducted in case of other activities to evaluate the variations in heart activity in different conditions.

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Complexity-Based Evaluation of the Correlation Between Heart and Brain Responses to Music

et al. 2021

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The evaluation of the correlation between the activations of various organs has great importance. This work investigated the synchronization of the brain and heart responses to different auditory stimuli using complexity-based analysis. We selected three pieces of music based on the difference in the complexity of embedded noise (including white noise, brown noise, and pink noise) in them. We played these pieces of music for 11 subjects (7 M and 4 F) and computed the fractal dimension and sample entropy of EEG signals and R–R time series [as heart rate variability (HRV)]. We found strong correlations ([Formula: see text] in the case of fractal dimension and [Formula: see text] in the case of sample entropy) among the complexities of EEG signals and HRV. This finding demonstrates the synchronization of the brain and heart responses and auditory stimuli from the complexity perspective.

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Analysis of the correlation between the human voice and brain activity

Cited by 12 publications

References 34 publications

Complexity-Based Analysis of the Variations of Brain and Muscle Reactions in Walking and Standing Balance While Receiving Different Perturbations

Complexity-Based Analysis of the Variations of Brain and Muscle Reactions in Walking and Standing Balance While Receiving Different Perturbations

Complexity and Information-Based Analysis of the Heart Rate Variability (Hrv) While Sitting, Hand Biking, Walking, and Running

Complexity-Based Evaluation of the Correlation Between Heart and Brain Responses to Music

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