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.

中文翻译：

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使用高密度表面肌电图比较健康和贝尔麻痹受试者的面部肌肉激活模式

面部肌肉活动对于人类的外观和交流至关重要。因此，探索面部肌肉的激活模式有助于了解贝尔麻痹等面部神经肌肉疾病。鉴于面部肌肉的不规则形状以及它们的不同位置，使用几个电极应该很难检测到整个面部肌肉的活动。在这项研究中，使用具有 90 个电极的高密度表面肌电图 (HD sEMG) 系统来记录健康和贝尔麻痹受试者在进行不同面部运动时面部肌肉的 EMG 信号。电极以矩形阵列排列，覆盖面部的前额和脸颊区域。肌肉激活模式显示在地图上，由所有 90 通道 EMG 记录的均方根 (RMS) 值构建而成。实验结果表明，在做不同的面部动作时，面部肌肉的激活模式是不同的，可以清楚地观察到被激活的肌肉区域。此外，提取激活模式的两个特征，二维相关系数 (corr2) 和重心 (CG)，分别量化空间对称性和激活肌肉区域的位置。此外，通过计算 CG 两侧之间的距离来量化面部瘫痪侧与健康侧相比的激活肌肉区域的偏差。结果显示，贝尔麻痹受试者面部肌肉激活区（分为前额区和脸颊区）的 corr2 显着低于健康受试者（p < 0.05），而贝尔瘫痪受试者面部激活区的 CG 距离为显着（p < 0.05）高于健康受试者。这些区域的 corr2 与贝尔麻痹 [由面部神经分级量表 (FNGS) 2.0 评估] 之间的相关性在贝尔麻痹受试者中也很显着 (p < 0.05)。激活肌肉区域的空间信息可能对未来贝尔麻痹的诊断和治疗有用。这些区域的 corr2 与贝尔麻痹 [由面部神经分级量表 (FNGS) 2.0 评估] 之间的相关性在贝尔麻痹受试者中也很显着 (p < 0.05)。激活肌肉区域的空间信息可能对未来贝尔麻痹的诊断和治疗有用。这些区域的 corr2 与贝尔麻痹 [由面部神经分级量表 (FNGS) 2.0 评估] 之间的相关性在贝尔麻痹受试者中也很显着 (p < 0.05)。激活肌肉区域的空间信息可能对未来贝尔麻痹的诊断和治疗有用。