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

Pakniyat, Najmeh; Namazi, Hamidreza

doi:10.3389/fnhum.2021.749082

Cited by 12 publications

(7 citation statements)

References 41 publications

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“…However, our present results showed that practice under incongruent condition decreased the left TA muscles activity but increased the complexity of left TA sEMG data with higher FD values. This results are consistent with previous studies, where showed that when balance task difficulty increased, the calf muscle activity increased (Gebel et al, 2019) and the complexity of sEMG data decreased (Murillo et al, 2012;Pakniyat and Namazi, 2021). Besides, we also observed that practice under incongruent condition reduced the left MG muscle activity without any significant changes of fractal exponent of left MG muscle (Figure 3).…”

Section: Interpretation Of Complexitysupporting

confidence: 93%

“…Accordingly, we hypothesized that the complexity of EEG data would decrease after repeated balance practice. Previous studies found that when the difficulty in balance tasks increased, the lower limb muscle activity increased (Gebel et al, 2019) and the complexity of sEMG data from calf muscles decreased (Murillo et al, 2012;Pakniyat and Namazi, 2021). Since these results suggested that higher sEMG complexity probably reflect an effective strategy in postural muscles when facing perturbations, we hypothesized that the complexity of sEMG data of calf muscles would increase after repeated balance practice.…”

Section: Introductionmentioning

confidence: 85%

“…Furthermore, Gupta et al (2021) found that the meditation reduced the complexity of EEG (i.e., lower FD value), suggesting the brain improved the ability for effectively handling cognitive load. When there was a pull perturbation, the complexity of EEG signals was higher (i.e., higher FD value and higher entropy value) in walking than standing (Pakniyat and Namazi, 2021). Accordingly, lower complexity of EEG signal might suggest that the brain is more likely to effectively handle cognitive load or to deal with complex environments.…”

Section: Eeg Datamentioning

confidence: 99%

“…Therefore, our first aim was to investigate the dynamic characteristics of subsystems of postural control system during (Pakniyat and Namazi, 2021), which suggested that the lower EEG complexity in the frontal lobe may indicate a lower cognitive load or a lower attention level (Ke et al, 2014;Gupta et al, 2021). Accordingly, we hypothesized that the complexity of EEG data would decrease after repeated balance practice.…”

Section: Introductionmentioning

confidence: 99%

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Nonlinear dynamics of postural control system under visual-vestibular habituation balance practice: evidence from EEG, EMG and center of pressure signals

Hua,

Wang,

Bai

et al. 2024

Front. Hum. Neurosci.

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Human postural control system is inherently complex with nonlinear interaction among multiple subsystems. Accordingly, such postural control system has the flexibility in adaptation to complex environments. Previous studies applied complexity-based methods to analyze center of pressure (COP) to explore nonlinear dynamics of postural sway under changing environments, but direct evidence from central nervous system or muscular system is limited in the existing literature. Therefore, we assessed the fractal dimension of COP, surface electromyographic (sEMG) and electroencephalogram (EEG) signals under visual-vestibular habituation balance practice. We combined a rotating platform and a virtual reality headset to present visual-vestibular congruent or incongruent conditions. We asked participants to undergo repeated exposure to either congruent (n = 14) or incongruent condition (n = 13) five times while maintaining balance. We found repeated practice under both congruent and incongruent conditions increased the complexity of high-frequency (0.5–20 Hz) component of COP data and the complexity of sEMG data from tibialis anterior muscle. In contrast, repeated practice under conflicts decreased the complexity of low-frequency (<0.5 Hz) component of COP data and the complexity of EEG data of parietal and occipital lobes, while repeated practice under congruent environment decreased the complexity of EEG data of parietal and temporal lobes. These results suggested nonlinear dynamics of cortical activity differed after balance practice under congruent and incongruent environments. Also, we found a positive correlation (1) between the complexity of high-frequency component of COP and the complexity of sEMG signals from calf muscles, and (2) between the complexity of low-frequency component of COP and the complexity of EEG signals. These results suggested the low- or high-component of COP might be related to central or muscular adjustment of postural control, respectively.

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Section: Interpretation Of Complexitysupporting

confidence: 93%

Section: Introductionmentioning

confidence: 85%

Section: Eeg Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Nonlinear dynamics of postural control system under visual-vestibular habituation balance practice: evidence from EEG, EMG and center of pressure signals

Hua,

Wang,

Bai

et al. 2024

Front. Hum. Neurosci.

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show abstract

“…For this reason, SampEn has been calculated with a smaller number of data points or with using a continuous signal [ 13 ]. Various forms of continuous data [ 2 , 8 , 10 ] have been used in complexity analysis, however, the usage of center of pressure (COP) signal during a steady-state, where many consecutive steps can be captured, is becoming more popular [ 9 , 14 – 16 ]. The COP at a given moment in time is the location of resultant vertical ground reaction force vector.…”

Section: Introductionmentioning

confidence: 99%

The influence of walking speed and effects of signal processing methods on the level of human gait regularity during treadmill walking

Brachman

Sobota

Bacik

2022

BMC Sports Sci Med Rehabil

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Background In recent years the use of sample entropy (SampEn) to evaluate the complexity of the locomotor system in human gait data has gained in popularity. However, it has been suggested that SampEn is sensitive to various input parameters and signal preprocessing methods. This study quantified the effects of different temporal and spatial normalization approaches and various lengths of the template vector (m) on SampEn calculations. The discriminatory ability of SampEn was studied by comparing two walking conditions. Methods Twenty-three participants (seven males, 55.7 ± 8.5 years, 165.7 ± 7.9 cm, 80.5 ± 16.7 kg) walked on a treadmill with preferred (Vpref) and maximum (Vmax) speed. Data were segmented and resampled (SEGM), resampled and spatially normalized (NORM), resampled and detrended (ZERO). Results For vertical ground reaction force (vGRF) and center of pressure in anterio-posterior direction (COPap), in both walking conditions, SampEn was generally sensitive to the vector length and not to the data processing, except for COPap in ZERO, m = 2, 4. For the COPml SampEn behaved oppositely, it was sensitive to preprocessing method and not to the m length. The regularity of COPap and vGRF in all processed signals increased in Vmax condition. For the COPml only two signals, WHOLE and ZERO, revealed increased complexity caused by more demanding walking conditions. Conclusions SampEn was able to discriminate between different walking conditions in all analyzed variables, but not in all signals. Depending on evaluated variable, SampEn was susceptible in different way for the m level and processing method. Hence, these should be checked and selected for each variable independently. For future studies evaluating influence of walking velocity on COP and vGRF regularity during treadmill walking it is advised to use raw time series. Furthermore, to maintain template vector which represents biological relevance it is advised to detect highest frequencies present in analyzed signals and evaluate minimal time interval which can reflect change caused by response of a neuromuscular system. During evaluating treadmill walking measured with 100 Hz sampling frequency it is recommended to adopt m from 6 to 10, when average stride time is up to about 1 s.

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Complexity and Information-Based Analysis of the Electroencephalogram (Eeg) Signals in Standing, Walking, and Walking With a Brain–computer Interface

Ramadoss¹,

Dawi²,

Rajagopal³

et al. 2021

Fractals

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In this paper, we analyzed the variations in brain activation between different activities. Since Electroencephalogram (EEG) signals as an indicator of brain activation contain information and have complex structures, we employed complexity and information-based analysis. Specifically, we used fractal theory and Shannon entropy for our analysis. Eight subjects performed three different activities (standing, walking, and walking with a brain–computer interface) while their EEG signals were recorded. Based on the results, the complexity and information content of EEG signals have the greatest and smallest values in walking and standing, respectively. Complexity and information-based analysis can be applied to analyze the activations of other organs in different conditions.

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

Cited by 12 publications

References 41 publications

Nonlinear dynamics of postural control system under visual-vestibular habituation balance practice: evidence from EEG, EMG and center of pressure signals

Nonlinear dynamics of postural control system under visual-vestibular habituation balance practice: evidence from EEG, EMG and center of pressure signals

The influence of walking speed and effects of signal processing methods on the level of human gait regularity during treadmill walking

Complexity and Information-Based Analysis of the Electroencephalogram (Eeg) Signals in Standing, Walking, and Walking With a Brain–computer Interface

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