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Annals of Otology, Rhinology & Laryngology 123(4)

laryngoscopic evaluation of vocal fold mobility to assess a

variety of laryngeal disorders such as dystonia and vocal

fold paresis and paralysis, to differentiate among various

neurological disorders,

and for guiding the placement of

botulinum toxin for the treatment of spasmodic dyspho-

nia.

1,8

Laryngeal electromyography may also be poten-

tially useful as a tool for the prognosis of laryngeal nerve

disorders.

9,10

In general, electromyography (EMG) recordings are

affected by multiple confounding variables including elec-

trode type and placement, level of muscle activation, left

and right side dominance, artifact from electrode move-

ment, and so on, which may all, or in part, compromise the

accuracy of the data necessary for diagnostic evaluation.

11,12

Electromyographic investigations of between-session and

intra-session reliability for some limb muscles have

revealed high reliability for both between- and within-ses-

sion measurements.

13,14

However, similar data for laryn-

geal-based EMG are absent and cannot be directly

interpolated from limb studies due to significant differences

in anatomical structure and the ability to control for muscle

length and loading.

Unlike most limb muscles that have skeletal support and

firm attachment points, the larynx is suspended in the neck,

surrounded by soft muscle tissue, a series of membranes,

and a somewhat yielding cartilaginous framework. Distinct

muscle force and leverage points are difficult to determine

in the laryngeal complex because of these flexible attach-

ment points. Placing a consistent and measureable isotonic

load on laryngeal muscles for accurate and reliable activa-

tion is difficult, complicating replication of motor unit acti-

vation in these muscles.

Another factor to be considered regarding the reliability

of clinical in-office LEMG is that phonation is an emergent

behavior, arising through the complex interaction of respi-

ratory, phonatory, and resonance subsystems of the vocal

tract. These vocal subsystems function synergistically, inte-

grating properties of tissue elasticity, muscle activation, and

aerodynamics toward normal vocal function. A change in

any subsystem’s dimension will potentially alter vocal out-

put. These additional confounding variables have the poten-

tial to further complicate in-office LEMG interpretation.

In general, reliable LEMG measurements are dependent

on consistent muscle activation tasks. These tasks must be

carefully controlled and performed for measurement reli-

ability. For example, to describe relative recruitment of

motor unit potentials for the thyroarytenoid muscle (TA),

maximum voluntary contraction (MVC) strategies have

been used for comparison. Typically, a maximal voluntary

contraction is assigned a 100% possible recruitment value

whereby subsequent muscle contractions during voicing

tasks are given a percentage of decreased recruitment.

Maximum voluntary contraction in the laryngeal system is

typically accomplished through performance of a Valsalva

maneuver (hard breath hold).

However, it has been shown

that vocal fold closure is not consistently accomplished dur-

ing Valsalva maneuvers up to 14% of the time, potentially

leading to significant diagnostic error.

Other qualitative

ratings such as decreased recruitment scales are not compa-

rable across offices due to their highly subjective nature and

lack of standardized between-office collection protocols.

Another commonly used clinical LEMG technique is

comparison of recruitment against the contralateral muscle.

Unfortunately, this technique does not take into account the

notion that the contralateral TA muscle is dependent on the

co-contraction of neighboring intrinsic muscles. Thus, TA

contraction may be altered in the presence of a contralateral

paresis or paralysis. In this scenario, compensatory muscle

activation is a likely confounder.

In addition, a large-scale

retrospective study reported unexpected contralateral neu-

ropathy in 26% of patients with laryngeal movement disor-

ders.

Electromyography studies of limb muscle also

indicate significant contralateral differences in motor unit

recruitment even during simultaneously controlled muscle

contractions.

Because raw EMG signals are quasi-random in nature,

they cannot be directly compared. Thus, a principle goal of

this study was to use quantitative methodology with the

addition of control parameters and measures, to character-

ize the reliability of a primarily qualitative clinical evalua-

tion. One such measure was quantification of the LEMG

signal via calculation of the root mean square (RMS). Root

mean square is considered to be the current “gold standard”

for quantitative electromyographic analysis

11,12

and allows

for rapid quantitative comparisons among groups of sig-

nals. Root mean square was chosen as a measurement met-

ric because it provides an indication of mean muscle activity

and signal power and is the analog to voltage output.

Because RMS is also considered a data smoothing tech-

nique, it is not well suited for visualization of waveform

transients and morphology characteristics such as polypha-

sic or nascent potentials; however, it is useful to quantify

and compare LEMG across samples in terms of signal volt-

age and power. Because EMG is a time-varying signal con-

taining positive and negative values, RMS is an ideal

quantitative measure that can be easily calculated post hoc

or in real time with many commercially available data

acquisition software programs.

Determining LEMG data reliability within the context of

an in-office clinical environment is important to make care-

ful and useful clinical interpretations and to potentially

improve clinical protocols. To our knowledge, in-office

clinical LEMG reliability has not been systematically inves-

tigated in a cohort of vocally healthy adults. As such, the

purpose of this study was to prospectively investigate

LEMG signal reliability recorded from the thyroarytenoid

muscle over multiple testing sessions using a common in-

office clinical routine. We modeled our basic methodology