52

Japanese Journal of Comprehensive Rehabilitation Science (2020)

Original Article

Evaluation of the myoelectric potential of the infrahyoid muscles asa means of detecting muscle activity of the suprahyoid muscles
Hitoshi Mori, PhD,1,2,3 Shin-Ichi Izumi, MD, PhD,4 Hitoshi Kagaya, MD, DMSc,5 Hideki Oyama,
PhD,4 Genji Abe, PhD,6,7 Kenji Yashima, PhD,1 Toshiyuki Takagi, PhD2,8
IFG Corporation, Sendai, Miyagi, Japan
Institute of Fluid Science, Tohoku University, Sendai, Miyagi, Japan
3
Graduate School of Engineering, Tohoku University, Sendai, Miyagi, Japan
4
Department of Physical Medicine and Rehabilitation, Graduate School of Biomedical Engineering, Tohoku
University, Sendai, Miyagi, Japan
5
Department of Rehabilitation Medicine I, School of Medicine, Fujita Health University, Toyoake, Aichi, Japan
6
Faculty of Medical Science and Welfare, Tohoku Bunka Gakuen University, Sendai, Miyagi, Japan7
Department of Physical Medicine and Rehabilitation, Tohoku University Graduate School of Medicine, Sendai,
Miyagi, Japan
8
ELyTMaX UMI 3757, CNRS - Université de Lyon - Tohoku University, International Joint Unit, Sendai, Miyagi,
Japan
1
2

ABSTRACT
Mori H, Izumi S, Kagaya H, Oyama H, Abe G,
Yashima K, Takagi T. Evaluation of the myoelectric
potential of the infrahyoid muscles as a means ofdetecting muscle activity of the suprahyoid muscles.
Jpn J Compr Rehabil Sci 2020; 11: 52‐58.
Objective: To investigate the use of the myoelectric
potential of the infrahyoid muscles as a synchronizing
signal for the contraction of the suprahyoid muscles
during swallowing.
Methods: The myoelectric potentials of the anterior
belly of the digastric muscle and the sternohyoidmuscle of 10 healthy adults during swallowing were
measured, and the activity of each muscle wasanalyzed. Additionally, the real-time process of muscle
activity detection was simulated using the measured
waveform of the myoelectric potentials.
Results: The ratio of the “elapsed time from theactivity of the anterior belly of the digastric muscle tothe activity of the sternohyoid muscle” to the “time ofactivity of the anterior belly of the digastric muscle”
was 22.5 ± 19.6%. The sternohyoid muscle activity
started in the early period of activity of the digastricmuscle. In the simulation, differential processing
Correspondence: Hitoshi Mori, PhD
IFG Corporation, 1‐14‐9, Oritate, Aoba-ku, Sendai, Miyagi
982‐0261, Japan.
E-mail: h.mori@ifg.jp
Accepted: March 9, 2020
Conflict of Interest: The authors declare that there are no
conflicts of interest.
©Kaifukuki Rehabilitation Ward Association 2020
doi.org/10.11336/jjcrs.11.52

enabled detection of the activity of the sternohyoidmuscle in 49 of 50 trials within the activation time of
the anterior belly of the digastric muscle.
Conclusion: The myoelectric potential of thesternohyoid muscle can be used as a synchronization
signal for the contraction of the anterior belly of thedigastric muscle during swallowing.
Key words: dysphagia, magnetic stimulation, anterior
belly of digastric muscle, sternohyoid muscle,
myoelectric potential
Introduction
Japan has become a super-aged society ahead of therest of the world. As the population ages, the incidenceof cerebrovascular disorders, and the number ofpatients with dysphagia due to sequelae of
cerebrovascular disorders, is increasing year by year[1]. If food enters the trachea due to abnormal
swallowing, aspiration pneumonia or suffocation may
result [1‐3]. More than 70% of cases of pneumonia inolder adults are associated with aspiration [4], andtherefore more effective rehabilitation methods fordysphagia need to be developed.
Our research group is studying a new method of
rehabilitation for dysphagia that uses magnetic
stimulation for dysphagia training. Magnetic stimulation
generates a varying magnetic flux from a magnetic
stimulation coil, excites the motor nerve by the change
in the magnetic flux, and induces contraction of thetarget muscle. Magnetic stimulation is minimallyinvasive, less painful than other stimulation methods,
Jpn J Compr Rehabil Sci Vol 11, 2020

Mori H et al.: Myoelectric potential of infrahyoid muscles to detect activity of suprahyoid muscles 53

Figure 1. Stimulation coil for the suprahyoidmuscles.
An eddy current is induced in the submental region
by a magnetic pulse to contract the suprahyoidmuscles.
and does not require the attachment of electrodes [5].
Our previous studies have shown that applying magnetic
stimulation to the suprahyoid muscles results in a
substantial elevation of the hyoid bone without pain [6].
Figure 1 shows the coil for stimulating the suprahyoidmuscles and its arrangement during stimulation.
Recent research has shown that in physical therapy
using electrical stimulation, more effective rehabilitation
can be provided by using the myoelectric potential of
the target muscle as a trigger than by simply inducing
muscle contraction [7]. Similarly, in training using
magnetic stimulation, magnetic stimulation of thesuprahyoid muscles triggered by the myoelectric
potentials of the swallowing-related muscles is expected
to provide more effective rehabilitation.
However, when magnetic stimulation is performed
from above the electrode attached to the suprahyoidmuscles, there is a problem that the metal inside theelectrode changes the distribution of the magnetic pulse.
Additionally, the unnecessary potential generated on
the electrodes due to magnetic induction is greatly
amplified by the high-gain amplifier inside theelectromyography (EMG) machine, and the internal
circuit of the EMG machine may be destroyed. For
males, the surface of the lower jaw where the electrodeis attached may be covered with a beard, causing poor
contact of the electrode. Therefore, it is difficult to use
the myoelectric potential of the suprahyoid muscles as a
trigger for the magnetic stimulation of the suprahyoidmuscles.
During the swallowing reflex, the infrahyoidmuscles contract after the suprahyoid muscles. The
muscle activity of the infrahyoid muscles starts during
the contraction of the suprahyoid muscles [8, 9].
Therefore, it is possible that stimulation synchronizedwith contraction of the suprahyoid muscles can be
performed by using the myoelectric potential of theinfrahyoid muscles as a trigger. When the electrode is

attached to the infrahyoid muscles and magnetic
stimulation is applied to the suprahyoid muscles, themagnetic flux density near the electrodes is small.
Therefore, the electrodes do not change the magnetic
field distribution of the magnetic stimulation and, in
addition, the risk of malfunction of the EMG machineis small.
The purpose of this study was to evaluate thepossibility of using the myoelectric potential of theinfrahyoid muscles, rather than the suprahyoidmuscles, as a trigger signal synchronized with thecontraction of the suprahyoid muscles. The myoelectric
potentials of the suprahyoid and infrahyoid muscles
were measured, and the time series of the activity ofthese muscles was examined. Additionally, asimulation using the measured myoelectric potential
was performed to estimate the timing of the detectionof the myoelectric potential of the infrahyoid muscles
including the delay due to detection processing in realtime. Using these results, we evaluated the validity of
substituting the myoelectric potential of the infrahyoidmuscles as a trigger signal synchronized with thecontraction of the suprahyoid muscles.
Methods
This study was approved by the Ethics Committeeof Tohoku University School of Medicine (accession
number: 2019-1-252).
1. Measurement of myoelectric potential
Measurements of myoelectric potential were
performed on 10 healthy adults (8 males, 2 females,age 21‐67 years, average age 41.7 ± 18.1 years).
Written consent for the measurements was obtained
from all subjects. The myoelectric potential wasmeasured using an active electrode (Biometrics Ltd.,SX230) with a distance of 20 mm between theelectrodes. The gain of this active electrode was 60 dB,
and the bandwidth was 20‐460 Hz. In this study, theamplified signal output from the electrode was treatedas a signal of myoelectric potential. The subject’s
lower jaw and neck were wiped with an alcohol swab,
and electrodes were applied to the epidermis along thedirection of the muscle fibers corresponding to theanterior belly of the digastric muscle to detect theaction potential of the suprahyoid muscles. Similarly,
an electrode was attached to the epidermis
corresponding to the sternohyoid muscle on the rightside of the neck to detect the action potential of theinfrahyoid muscle. Figure 2 shows the electrodeattachment position and the electrode mounting state.
A band with electrodes was attached as a referenceelectrode so that it touched the head of the subject’s
right elbow. The subject was seated in a chair in ashielded room in a state of rest with the electrodes
attached, and was instructed to perform saliva
swallowing five times. The start of swallowing, theJpn J Compr Rehabil Sci Vol 11, 2020

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Mori H et al.: Myoelectric potential of infrahyoid muscles to detect activity of suprahyoid muscles

Figure 2. Position of the electromyography electrode.
Electrodes are placed on the epidermis above the anterior belly of the digastric muscle and thesternohyoid muscle.
completion of swallowing, and the timing of theswallowing instruction were recorded. No specificinstructions were given about the speed of swallowing
or the amount of saliva swallowed. The measurements
were recorded with an AD converter (ADInstruments,
PowerLab) and recording software (ADInstruments,
LabChart 7). Recording was performed at a sampling
rate of 1 kHz. The recorded myoelectric potential
waveforms of each subject were cut out for eachswallowing instruction, with the myoelectric potential
waveforms at rest included for at least 2 s before andafter the swallow, and saved in such a way that theorder of the trials could be identified.
2. Activity time analysis of each muscle
In analyzing the activity time, band-stop filter

processing of 48‐52 Hz to remove hum noise and timedifferential processing were performed in advance oneach myoelectric waveform by digital signal
processing using a personal computer. Digital signal
processing was performed with analysis software(National Instrument, Labview). All digital signal
processing and analyses in this study were performedin Labview. Figure 3 shows an example of the
myoelectric waveforms before digital processing of
the anterior belly of the digastric muscle and thesternohyoid muscle during swallowing and the resultof a fast Fourier transform (FFT) with a width of 0.2 s
for these waveforms. Figure 4 shows the waveforms
after filtering and differentiation processing and its
FFT waveform. In the waveforms after digitalprocessing, the period below 3 SD of the baseline

Figure 3. Example of a measured myoelectric waveform (left) and its frequency characteristic analysis
result (right).
The upper graph shows measurements for the anterior belly of the digastric muscle, and the lower graphshows measurements for the sternohyoid muscle.
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Mori H et al.: Myoelectric potential of infrahyoid muscles to detect activity of suprahyoid muscles 55

Figure 4. Myoelectric waveform after hum noise filter processing and differentiation processing (left) and
its frequency characteristic analysis (right).
The upper graph shows measurements for the anterior belly of the digastric muscle, and the lower graphshows measurements for the sternohyoid muscle. The start and end times of muscle activity can be
determined from the period that the myoelectric waveform was less than ± 3 SD of the baseline activity
before and after the signal peak.
activity for 0.1 s or more was detected in a negative
direction on the time axis from the signal peak, and theend of that period was defined as the muscle activity
start time. Similarly, the period below 3 SD of thebaseline activity for 0.1 s or more was detected in apositive direction on the time axis from the signal
peak, and the beginning of that period was defined as
the muscle activity end time. In this analysis, theresting myoelectric waveform for 1 s before
swallowing is defined as the baseline activity. This
analysis was performed on myoelectric waveforms
from a total of 50 trials (five trials on 10 subjects each).
Mean, standard deviation, and maximum andminimum values for the muscle activity time of theanterior belly of the digastric muscle (A), the muscle
activity time of the sternohyoid muscle (B), the elapsed
time from the start of activity of the anterior belly of

Figure 5. Definitions of the evaluated time parameters.


the digastric muscle to the start of activity of thesternohyoid muscle (C), and the ratio of C to A (C/A)
were recorded. Figure 5 shows the definitions of theevaluated time parameters. The value of C/A is aparameter that indicated when the sternohyoid muscle
activity started during the entire muscle activity of theanterior belly of the digastric muscle. Because it was
confirmed that single-shot muscle activity occurred
about once every 0.08 s in the myoelectric waveformof the anterior belly of the digastric muscle of one
subject, the muscle activity time for this one subject
was determined by detecting the period below 3 SD of
the baseline activity for 0.05 s or more.
3. Simulation of real-time processing for detectionof the start of muscle activity
Before digital processing, bandstop filter processingof 48–52 Hz was applied to the myoelectric waveformof the sternohyoid muscle of all subjects. Additionally,a differentiated waveform and a non-differentiatedwaveform were prepared, and root mean square(RMS) processing with a width of 10 ms was
performed on each waveform. In the following
description, the RMS processed waveform without
differential processing is called the RMS waveform,
and the RMS processed waveform after differential
processing is called the differentiated root mean square(DRMS) waveform. Figure 6 shows an example of the
RMS and DRMS waveforms. The waveforms in
Figure 6 are the RMS and DRMS waveforms of the
myoelectric potential of the sternohyoid muscle shown
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Mori H et al.: Myoelectric potential of infrahyoid muscles to detect activity of suprahyoid muscles

Figure 6. Root mean square (RMS) waveform (left) and differentiated root mean square (DRMS)
waveform (right).
The rising of the myoelectric waveform is detected when the waveform exceeds the mean + 3 SD of thebaseline activity for a specified time t.
in Figure 3. Next, for each of the obtained RMS
waveforms and DRMS waveforms, the period that the
waveform exceeded mean + 3 SD of the baseline
activity for a specified time t was detected from thestart of the waveform data toward the positive side.
The end of the period was defined as the detection
time of the start of muscle activity of the sternohyoidmuscle. This series of signal processing is possible inreal time using an analog circuit. Here, the signal
processing by the analog circuit was simulated by apersonal computer.
The simulation of the above-mentioned muscle
activity detection was performed for a total of 50 trials(five trials on 10 subjects each) while changing thevalue of t from 20 ms to 100 ms. If sternohyoid muscle
activity was detected between the start and end ofactivity of the anterior belly of the digastric muscle,
the detection was regarded as successful. If the activity
was outside this range, or if muscle activity was notdetected, the detection was regarded as failed. In thesimulation of the myoelectric waveform for the five
trials for each subject, the smallest value of t with thehighest number of successful detections wasdetermined. Then, from the detection time of the startof muscle activity with the optimal t for each subject,
the elapsed time from the start of muscle activity of
the anterior belly of the digastric muscle to thedetection time of the start of muscle activity of thesternohyoid muscle (D) was calculated. Mean,
standard deviation, and maximum and minimum
values for the ratio (D/A) of (D) to the muscle activity
time of the anterior abdominal muscle (A) were
calculated. Figure 5 shows the definitions of thesetime parameters. The value of D/A is a parameter thatindicated when the activity of the sternohyoid muscle
was detected during the entire muscle activity of theanterior belly of the digastric muscle. The number ofsuccessful detections (rate) when the optimal t was set
for each subject was also calculated.

Jpn J Compr Rehabil Sci Vol 11, 2020

Results
Table 1 shows the results of the activity time
analysis for each muscle. The average muscle activity
time of the anterior belly of the digastric muscle (A)and the sternohyoid muscle (B) were both about 1 slong, and the elapsed time from the start of muscle
activity of the anterior belly of the digastric muscle tothe start of muscle activity of the sternohyoid muscle(C) was 0.31 ± 0.29 s. The elapsed time ranged from−0.07 to 1.16 s, and there were cases in which the
myoelectric potential of the sternohyoid muscle
occurred slightly earlier than in the anterior belly ofthe digastric muscle in six trials. The timing of thestart of sternohyoid muscle activity (C/A) was 22.5 ±
19.6%, and sternohyoid muscle activity mainly began
in the early period of activity of the anterior belly ofthe digastric muscle. In the 50 trials in this study, themaximum value of the timing of the start of muscle
activity of the sternohyoid muscle (C/A) was 66.7%,
and the activity of the sternohyoid muscle neverstarted after the end of the activity of the anterior bellyof the digastric muscle.
Table 2 shows the simulation results of the real-time
detection process for the start of muscle activity. The
success rate of detection of the start of muscle activity
using the RMS waveform was 41/50, and the successrate of detection using the DRMS waveform was
Table 1. Muscle activity time of the anterior belly ofthe digastric muscle (A), muscle activity time of thesternohyoid muscle (B), and elapsed time from thestart of activity of the anterior belly of the digastricmuscle to the start of activity of the sternohyoidmuscle (C).
Mean±SD
A[s]
B[s]
C[s]
C/A[%]

1.43±0.64
1.26±0.58
0.31±0.29
22.5±19.6

Maximum Minimum
3.40
2.63
1.16
66.7

0.45
0.26
−0.07
−6.5

Mori H et al.: Myoelectric potential of infrahyoid muscles to detect activity of suprahyoid muscles 57

Table 2. Detection rate of muscle activity and timing of detection (D/A)
of the sternohyoid muscle estimated by simulation of real-time analysis.

RMS
DRMS

Detection rate

D/A [%]
Mean±SD

41/50
49/50

44.9±22.8
41.5±21.7

49/50. These results suggest that the onset of muscle
activity is easier to detect using DRMS waveforms.
Additionally, the timing (D/A) of the detection of thestart of muscle activity of the sternohyoid muscle wasabout 40%, regardless of the waveform used. Thisfinding suggests that actual magnetic stimulation
triggered by the myoelectric potential of thesternohyoid muscle is applied at a timing slightly
earlier than the entire muscle activity of the anterior
belly of the digastric muscle.
Discussion
As shown in the waveform in Figure 3, pulsationsynchronized with the heartbeat was often mixed in
the myoelectric waveform of the sternohyoid muscle,
and there were some subjects in whom this pulsation
could not be eliminated even when the electrodeposition was adjusted. This pulsation was difficult toremove by averaging or RMS processing because of
the wideness of the pulse. Observation of the FFT
waveform of the signal containing this pulsation
revealed that the frequency component of the pulsation
was at a very low level of about a few Hz, and thefrequency component of the myoelectric potential of
the anterior belly of the digastric muscle and thesternohyoid muscle during swallowing existed in thefrequency band higher than 50 Hz. This was a featurecommon to the whole myoelectric waveform of all
subjects in this study. Additionally, peaks around 50
Hz were observed in FFT waveforms from the baseline
activity in many myoelectric waveforms. Therefore, in
the analysis to determine the activity time of themuscle, a band-stop filter near 50 Hz and differentiation
processing were performed as pre-processing.
Differentiation processing was considered to be thebest pre-processing for the myoelectric waveform inthis study because the low-frequency component is
weakened and the high-frequency component isemphasized. As shown in Figures 3 and 4, after preprocessing, the pulsation disappeared, and the highfrequency components and the range of muscle activity
due to swallowing that had been buried in the noise
were emphasized. It is considered that pre-processing
contributed to improving the accuracy of themeasurements in this study.
As a feature common to myoelectric waveforms
measured in this study, the waveform of some subjects
tended to include random, high-amplitude, narrow

D/A [%]
D/A [%]
Maximum Minimum
92.7
92.2

3.4
4.7

pulse noise in the background. If a search is performedin the direction from the signal peak, the influence ofthe pulse noise on the detection accuracy of the muscle
activity is limited, but such processing is not possible
with real-time signal processing. Therefore, it isconsidered that the pulse width trigger, which is a
detection condition in which the threshold value is
exceeded during a certain time width, is effective forreal-time detection of the start of muscle activity. A
small noise can be ignored by the pulse width trigger.
As a result, in the simulation of muscle activity
detection using DRMS waveforms, the start of muscle
activity was detected in almost all trials. We consider
that the method using the DRMS waveform and thepulse width trigger is effective as a means for detecting
the actual start of muscle activity.
In this study, the myoelectric potential of thesternohyoid muscle was measured using a surface
electrode, and there was a possibility of cross-talk
contamination. However, measurement with theimplanted EMG using a hook-type wire electrode also
recorded the contraction of the suprahyoid muscle
following the contraction of the sternohyoid muscle[9], suggesting that the contraction of the sternohyoidmuscle was actually captured by the measurements inthis study. Additionally, the relative position between
the surface electrode and the muscle was expected toshift due to muscle contraction. However, theconduction velocity of the myoelectric potential was
3‐5 m/s [10], and the typical error due to muscle
contraction in the analysis was expected to be about
1/100 s. Therefore, it is assumed that the influence ofthe change of the relative position on the result of the
waveform processing was minor.
In conclusion, our findings confirmed that the
myoelectric potential of the sternohyoid muscle risesin the early phase of the muscle activity of the anterior
belly of the digastric muscle. Additionally, even taking
into account the delay caused in real-time processing,it is highly probable that the activity of the sternohyoidmuscle can be detected in the first half of the activityof the anterior belly of the digastric muscle. Therefore,
it is considered that the myoelectric potential of thesternohyoid muscle can be used as a synchronizing
signal for the contraction of the anterior belly of thedigastric muscle during swallowing.

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Mori H et al.: Myoelectric potential of infrahyoid muscles to detect activity of suprahyoid muscles

Acknowledgement
We thank Helen Jeays, BDSc AE, from Edanz
Group (https://en-author-services.edanzgroup.com/)for editing a draft of this manuscript.

References

1. Sura L, Madhavan A, Carnaby G, Crary MA. Dysphagia
in the elderly: management and nutritional considerations.
Clin Intery Aging 2012; 7: 287－98.
2
. Lieu PK, Chong MS, Seshadri R. The impact ofswallowing disorders in the elderly. Ann Acad Med
Singapore 2001; 30: 148－54.
3. Remesso GC, Fukujima MM, Chiappetta AL, Oda AL,
Aguiar AS, Oliveira AS, et al. Swallowing disorders after
ischemic stroke. Arq Neuropsiquiatr 2011; 69: 785－9.
4. Michiwaki Y, Sumi Y. Estimated national health carecosts for aspiration pneumonia over 70 years old
inpatients. Rounenshigaku 2014; 28: 366－8. Japanese.
5. Szecsi J, Schiller M, Straube A, Gerling D. A comparisonof functional electrical and magnetic stimulation forpropelled cycling of paretic patients. Arch Phys Med
Rehabil 2009; 90: 564－70.

Jpn J Compr Rehabil Sci Vol 11, 2020

6. Kagaya H, Ogawa S, Mori S, Aoyagi Y, Shibata S,
Inamoto Y, et al. Hyoid bone movement at rest by
peripheral magnetic stimulation of suprahyoid muscles innormal individuals. Neuromodulation 2019; 22: 593－6.
7. Francisco G, Chae J, Chawla H, Kirshblum S, Zorowitz
R, Lewis G, et al. Electromyogram-triggered neuromuscular
stimulation for improving the arm function of acute stroke
survivors: a randomized pilot study. Arch Phys Med
Rehabil 1998; 79: 570－5.
8. Ding R, Larson CR, Logemann JA, Rademaker AW.
Surface electromyographic and electroglottographic
studies in normal subjects under two swallow conditions:normal and during the Mendelsohn maneuver. Dysphagia
2002; 17: 1－12.
9. Inokuchi H, González-Fernández M, Matsuo K, Brodsky
MB, Yoda M, Taniguchi H, et al. Electromyography ofswallowing with fine wire intramuscular electrodes inhealthy human: activation sequence of selected hyoidmuscles. Dysphagia 2014; 29: 713－21.
10. Oh SJ. Clinical Electromyography: Nerve Conduction
Studies. 3rd ed. Philadelphia: Lippincott Williams andWilkins; 2002. p. 473－4.