Facial Plast Surg
DOI: 10.1055/s-0041-1725168
Original Research

Signal-To-Noise Ratio Calculations to Validate Sensor Positioning for Facial Muscle Assessment Using Noninvasive Facial Electromyography

Konstantin Frank
1  Department for Hand, Plastic and Aesthetic Surgery, Ludwig—Maximilian University, Munich, Germany
,
Nicholas Moellhoff
1  Department for Hand, Plastic and Aesthetic Surgery, Ludwig—Maximilian University, Munich, Germany
,
Antonia Kaiser
1  Department for Hand, Plastic and Aesthetic Surgery, Ludwig—Maximilian University, Munich, Germany
,
Michael Alfertshofer
1  Department for Hand, Plastic and Aesthetic Surgery, Ludwig—Maximilian University, Munich, Germany
,
Robert H. Gotkin
2  Private Practice, New York City, New York
3  Private Practice, Greenvale, New York
,
Ashit Patel
4  Division of Plastic Surgery, Department of Surgery, Albany Medical Center, Albany, New York
,
Michael P. Smith
4  Division of Plastic Surgery, Department of Surgery, Albany Medical Center, Albany, New York
,
Samir Mardini
5  Division of Plastic and Reconstructive Surgery, Mayo Clinic, Rochester, Minnesota
,
Diana Gavril
6  Private Practice, Napoca, Cluj, Romania
,
Sebastian Cotofana
7  Department of Clinical Anatomy, Mayo Clinic College of Medicine and Science, Rochester, Minnesota
› Author Affiliations
Funding The study was funded by Merz North America Inc., with funding number 2262019.

Abstract

The evaluation of neuromodulator treatment outcomes can be performed by noninvasive surface-derived facial electromyography (fEMG) which can detect cumulative muscle fiber activity deep to the skin. The objective of the present study is to identify the most reliable facial locations where the motor unit action potentials (MUAPs) of various facial muscles can be quantified during fEMG measurements. The study population consisted of five males and seven females (31.0 [12.9] years, body mass index of 22.15 [1.6] kg/m2). Facial muscle activity was assessed in several facial regions in each patient for their respective muscle activity utilizing noninvasive surface-derived fEMG. Variables of interest were the average root mean square of three performed muscle contractions (= signal) (µV), mean root mean square between those contraction with the face in a relaxed facial expression (= baseline noise) (µV), and the signal to noise ratio (SNR). A total of 1,709 processed fEMG signals revealed one specific reliable location in each investigated region based on each muscle's anatomy, on the highest value of the SNR, on the lowest value for the baseline noise, and on the practicability to position the sensor while performing a facial expression. The results of this exploratory study may help guiding future researchers and practitioners in designing study protocols and measuring individual facial MUAP when utilizing fEMG. The locations presented herein were selected based on the measured parameters (SNR, signal, baseline noise) and on the practicability and reproducibility of sensor placement.



Publication History

Publication Date:
05 March 2021 (online)

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