Rantanen Ville, Ilves Mirja, Vehkaoja Antti, Kontunen Anton, Lylykangas Jani, Makela Eeva, Rautiainen Markus, Surakka Veikko, Lekkala Jukka
Annu Int Conf IEEE Eng Med Biol Soc. 2016 Aug;2016:1688-1691. doi: 10.1109/EMBC.2016.7591040.
A survey on the feasibility of surface electromyography (EMG) measurements in facial pacing is presented. Pacing for unilateral facial paralysis consists of the measurement of activity from the healthy side of the face and functional electrical stimulation to reanimate the paralyzed one. The goal of this study is to evaluate the feasibility of surface EMG as a measurement method to detect muscle activations and to determine their intensities. Prior work is discussed, and results from experiments where 12 participants carried out a set of facial movements are presented. EMG was registered from zygomaticus major (smile), orbicularis oris (lip pucker), orbicularis oculi (eye blink), corrugator supercilii (frown), and masseter (chew). Most important facial functions that are limited due to the paralysis are blinking, smiling, and puckering. With majority of the participants, crosstalk between the measured EMG channels was found to be acceptably small to be able to pace smiling and puckering based on detecting their contraction intensities from the healthy side. However, pacing blinking based on orbicularis oculi EMG measurement does not seem possible due to crosstalk from other muscles, but the electro-oculographic (EOG) signals that couple to the same measurement channel could help to detect eye blinks and trigger stimuli. Futhermore, masseter greatly disturbs EMG measurement of most facial muscles, which needs to be addressed in the pacing system to avoid falsely interpreting its activity as the activity of another muscle.
本文介绍了一项关于面部起搏中表面肌电图（EMG）测量可行性的调查。单侧面瘫的起搏包括测量面部健康侧的活动以及进行功能性电刺激以使瘫痪侧恢复活动。本研究的目的是评估表面肌电图作为一种检测肌肉激活并确定其强度的测量方法的可行性。文中讨论了先前的工作，并展示了12名参与者进行一系列面部动作的实验结果。从颧大肌（微笑）、口轮匝肌（噘嘴）、眼轮匝肌（眨眼）、皱眉肌（皱眉）和咬肌（咀嚼）记录了肌电图。由于面瘫而受限的最重要的面部功能是眨眼、微笑和噘嘴。对于大多数参与者，发现测量的肌电图通道之间的串扰小到可以接受，从而能够根据从健康侧检测到的收缩强度对面部的微笑和噘嘴动作进行起搏。然而，由于来自其他肌肉的串扰，基于眼轮匝肌肌电图测量对面部眨眼动作进行起搏似乎不太可能，但耦合到同一测量通道的眼电图（EOG）信号可能有助于检测眨眼并触发刺激。此外，咬肌极大地干扰了大多数面部肌肉的肌电图测量，这在起搏系统中需要加以解决，以避免将其活动错误地解释为另一块肌肉的活动。
