Difference between Right and Left Facial Surface Electromyography in Healthy People

Kim, Bo‐Hyun; Kim, Kyeong Han; Kim, Lakhyung; Kim, Jong-Uk; Yook, Tae-Han

doi:10.1155/2018/4069530

Cited by 6 publications

(6 citation statements)

References 7 publications

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“…Knowledge of facial muscles is vital in understanding the physiological process of diverse facial movements. Except for a few studies focusing on the anatomy of facial muscles (Odwyer et al, 1981 ; D’Andrea and Barbaix, 2006 ; D’Antoni, 2016 ), the electrophysiological method are frequently used in the study of these muscles (Grosheva et al, 2008 ; Lapatki et al, 2010 ; Han et al, 2015 ; Kim et al, 2018 ). However, too few electrodes are used in a majority of these electrophysiological studies therefore the activation of multiple facial muscles cannot be detected simultaneously.…”

Section: Discussionmentioning

confidence: 99%

“…Compared to previous studies utilizing surface EMG techniques in recording facial muscle activities (Schumann et al, 2010;Kim et al, 2018), this study is the first one to report the activation patterns of facial muscles in Bell's palsy subjects using the HD sEMG method. The activation patterns in Bell's palsy displayed two characteristics: (i) the amplitude of the EMG signals on the affected side of the face was decreased; and (ii) there was an asymmetric distribution of the activated regions of facial muscles during facial movements.…”

Section: Distinct Facial Muscle Activation Patterns During Different Tasksmentioning

confidence: 99%

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Comparison of Facial Muscle Activation Patterns Between Healthy and Bell’s Palsy Subjects Using High-Density Surface Electromyography

Cui

Zhong

Yang

et al. 2021

Front. Hum. Neurosci.

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Facial muscle activities are essential for the appearance and communication of human beings. Therefore, exploring the activation patterns of facial muscles can help understand facial neuromuscular disorders such as Bell’s palsy. Given the irregular shape of the facial muscles as well as their different locations, it should be difficult to detect the activities of whole facial muscles with a few electrodes. In this study, a high-density surface electromyogram (HD sEMG) system with 90 electrodes was used to record EMG signals of facial muscles in both healthy and Bell’s palsy subjects when they did different facial movements. The electrodes were arranged in rectangular arrays covering the forehead and cheek regions of the face. The muscle activation patterns were shown on maps, which were constructed from the Root Mean Square (RMS) values of all the 90-channel EMG recordings. The experimental results showed that the activation patterns of facial muscles were distinct during doing different facial movements and the activated muscle regions could be clearly observed. Moreover, two features of the activation patterns, 2D correlation coefficient (corr2) and Centre of Gravity (CG) were extracted to quantify the spatial symmetry and the location of activated muscle regions respectively. Furthermore, the deviation of activated muscle regions on the paralyzed side of a face compared to the healthy side was quantified by calculating the distance between two sides of CGs. The results revealed that corr2 of the activated facial muscle region (classified into forehead region and cheek region) in Bell’s palsy subjects was significantly (p < 0.05) lower than that in healthy subjects, while CG distance of activated facial region in Bell’s palsy subjects was significantly (p < 0.05) higher than that in healthy subjects. The correlation between corr2 of these regions and Bell’s palsy [assessed by the Facial Nerve Grading Scale (FNGS) 2.0] was also significant (p < 0.05) in Bell’s palsy subjects. The spatial information on activated muscle regions may be useful in the diagnosis and treatment of Bell’s palsy in the future.

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Section: Discussionmentioning

confidence: 99%

Section: Distinct Facial Muscle Activation Patterns During Different Tasksmentioning

confidence: 99%

Comparison of Facial Muscle Activation Patterns Between Healthy and Bell’s Palsy Subjects Using High-Density Surface Electromyography

Cui

Zhong

Yang

et al. 2021

Front. Hum. Neurosci.

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“…The conducted analysis of decoding the relationship among facial muscles and brain is one step forward compared to the studies 1‐10 that only investigated the variations of facial muscles without considering the brain activity.…”

Section: Discussionmentioning

confidence: 99%

“…For this purpose, scientists evaluate the reaction of facial muscles through electromyography (EMG) signals analysis in different conditions. The reported investigations that decoded mental simulation and moral evaluation by analysis of facial EMG signals, 1 found out the relationship between facial EMG response and the ability of emotion perception, 2 analyzed EMG signals to find out the difference in facial muscle reaction in case of different muscles (right and left), age and sex, 3 investigated the changes in facial EMG signals in human face to face interactions, 4 controlled mobile robot by analysis of frontalis and zygomaticus major muscles, 5 analyzed the relation between EMG signals and quantitative ultrasonography of facial muscles in case of patients with facial palsy, 6 used EMG biofeedback in order to treat periorbital facial muscle tension, 7 analyzed facial muscles reaction to odors in solitude and with an audience, 8 evaluated facial EMG signals in order to recognize hedonic sensation, 9 and investigated facial expression to emotions by EMG signals analysis in patients with schizophrenia, 10 can to be mentioned.…”

Section: Introductionmentioning

confidence: 99%

Analysis of brain‐facial muscle connection in the static fractal visual stimulation

Soundirarajan

Babini

Sim

et al. 2020

Int J Imaging Syst Tech

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Analysis of the coupling among the brain and various organs activities is an exciting and new research area of biomedical signal analysis. We decode the correlation among the brain and facial muscle activities during rest and visual stimulation. Fractal analysis is utilized to evaluate the alterations of complexity. In this study, we present different images with different complexities to participants and evaluate how complex structures of electromyography (EMG) signals and electroencephalography (EEG) signals are related. The findings indicate that the alteration of EMG signals' complexity was significant (P value = .0001). Besides, more significant alterations in the EMG and EEG signals' complexities in response to the stimuli with higher complexities were observed. We conclude that the brain and facial muscles activities are related. We can analyze other physiological signals using this method to investigate their relationship with the brain.

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“…The asymmetry index (AI) was obtained using the following equation to represent the left-right asymmetry in the CMAP amplitude 7–10 …”

Section: Methodsmentioning

confidence: 99%

Broad and Asymmetric Lower Extremity Myotomes

Hashimoto,

Murohashi,

Yamada

et al. 2023

Spine

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Study Design. Retrospective review of prospectively collected data.Objective. This study aimed to accurately map the lower extremity muscles innervated by the lumbar spinal roots by directly stimulating the spinal roots during surgery. Summary of Background Data. Innervation of the spinal roots in the lower extremities has been estimated by clinical studies, anatomic studies, and animal experiments. However, there have been discrepancies between studies. Moreover, there are no studies that have studied the laterality of lower limb innervation. Materials and Methods. In 73 patients with lumbar degenerative disease, a total of 147 spinal roots were electrically stimulated and the electromyographic response was recorded at the vastus medialis (VM), gluteus medius (GM), tibialis anterior (TA), biceps femoris (BF), and gastrocnemius (GC). The asymmetry index (AI) was obtained using the following equation to represent the leftright asymmetry in the compound muscle action potential (CMAP) amplitude. Paired t tests were used to compare CMAP amplitudes on the right and left sides. Differences in the AI among the same spinal root groups were determined using one-way analysis of variance.

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Difference between Right and Left Facial Surface Electromyography in Healthy People

Cited by 6 publications

References 7 publications

Comparison of Facial Muscle Activation Patterns Between Healthy and Bell’s Palsy Subjects Using High-Density Surface Electromyography

Comparison of Facial Muscle Activation Patterns Between Healthy and Bell’s Palsy Subjects Using High-Density Surface Electromyography

Analysis of brain‐facial muscle connection in the static fractal visual stimulation

Broad and Asymmetric Lower Extremity Myotomes

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