- Email: [email protected]
A preliminary investigation of reproducibility of EMG signals during daytime masticatory muscle activity using a portable EMG logging device
Accepted Manuscript A preliminary investigation of reproducibility of EMG signals during daytime masticatory muscle activity using a portable EMG logging device Katsuhiro Omoto, Shuji Shigemoto, Yoshitaka Suzuki, Mayumi Nakamura, Kazuo Okura, Keisuke Nishigawa, Nami Goto, Omar Marianito Maningo Rodis, Yoshizo Matsuka PII: DOI: Reference:
S1050-6411(15)00080-2 http://dx.doi.org/10.1016/j.jelekin.2015.04.012 JJEK 1853
To appear in:
Journal of Electromyography and Kinesiology
Received Date: Revised Date: Accepted Date:
24 September 2014 21 April 2015 22 April 2015
Please cite this article as: K. Omoto, S. Shigemoto, Y. Suzuki, M. Nakamura, K. Okura, K. Nishigawa, N. Goto, O.M.M. Rodis, Y. Matsuka, A preliminary investigation of reproducibility of EMG signals during daytime masticatory muscle activity using a portable EMG logging device, Journal of Electromyography and Kinesiology (2015), doi: http://dx.doi.org/10.1016/j.jelekin.2015.04.012
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Title:
A preliminary investigation of reproducibility of EMG signals during daytime masticatory muscle activity using a portable EMG logging device
[Original research]
Authors and affiliations: Katsuhiro Omoto, DDS1, Shuji Shigemoto, DDS, PhD1,3, Yoshitaka Suzuki, DDS, PhD1, Mayumi Nakamura, DDS1, Kazuo Okura, DDS, PhD1, Keisuke Nishigawa, DDS, PhD1, Nami Goto, DDS1, Omar Marianito Maningo Rodis, DMD, PhD2, Yoshizo Matsuka, DDS, PhD1 1
Department of Stomatognathic Function and Occlusal Reconstruction, Institute of Health Biosciences,
The University of Tokushima Graduate School, Tokushima, Japan 2
Institute of Health Biosciences, The University of Tokushima Graduate School, Tokushima, Japan
3
Department of Fixed Prosthodontics, School of Dental Medicine, Tsurumi University, Yokohama, Japan
Key words Daytime masseter muscle activity, teeth grinding, clenching
Corresponding author Prof. Yoshizo Matsuka Department of Fixed Prosthodontics, Institute of Health Biosciences, The University of Tokushima Graduate School 3-18-15 Kuramoto-cho, Tokushima, 770-8504, Japan Email: [email protected]
1
Abstract
Continuous parafunctional masseter muscle activities (MMA) that are associated with daytime
bruxism have been suspected to be one of the main pathoetiology for orofacial pain. The purpose of this
study was to examine the long-term stability and reliability of daytime EMG measurement of MMA using
a portable device (Actiwave; CamNtech Ltd). Daytime masseter muscle EMG of five subjects were
recorded for four days in their normal living environment. There was no significant time dependent effect
on EMG amplitude during recording period. A total of 4923 MMA events were detected in all analysis
periods (129.4 hours) and classified into phasic type (1209 events, 24.6 %), tonic type (1759 events,
37.0 %), and mixed type (1377 events, 28.0 %). There was no significant difference in the number of
occurrence among three MMA types. With respect to the duration and peak MMA, there were significant
differences among three MMA types. The result of this study indicated that Actiwave can be used to
measure MMA events during daytime with high stability and reliability under the normal living
environment and it was suspected that parafunctional habits may be associated with the occurrence
patterns of MMA during daytime.
1
1.
Introduction
According to the guidelines of the American Academy of Orofacial Pain, bruxism is defined as
a repetitive jaw-muscle activity characterized by clenching or grinding of the teeth and/or by bracing or
thrusting of the mandible; and can occur during sleep or during wakefulness (De Leeuw et al., 2013).
From the physical statements during the activity, bruxism can be divided into sleep bruxism and daytime
bruxism. Since sleep bruxism may be associated with excessive occlusal force (Nishigawa et al., 2001),
this parafunction causes tooth attrition, abfraction, destruction and/or desorption of dental restoration, and
become an advance factor for periodontal disease and orofacial pain (Kato et al., 2013; Rompré et al.,
2007; Rugh etal., 1988; Kato et al., 2001; Lavigne et al., 2005). On the other hand, daytime bruxism is
typically characterized as parafunctional continuous muscle contraction, and it is reported that this diurnal
oral habit is one of the main pathogenesis of orofacial pain (Sato et al., 2006). EMG recording of
masticatory muscle activity is indispensable for detecting daytime bruxism but it is difficult to recognize
daytime bruxism because of the methodological limitations (Piquero et al., 2000). Thus, diagnosis of
daytime bruxism is generally done with the patient’s declaration and intraoral examination (Tsuggos et al.,
2008; Watanabe et al., 2011; Fujisawa et al., 2013). Self-report to assess bruxism presence and absence is
convenient, but bruxism patients are sometimes unaware of their oral habits (Shetty et al., 2010;
Manfredini et al., 2012). Tooth attrition, scalloped tongue and linea alba on buccal mucosa are frequently
1
found as a sign of bruxism. However, these intraoral findings are not necessarily associated with bruxism
and cannot be a reliable evidence of this parafunction (Piquero et al., 2000; Fujisawa et al., 2013).
Lately, some studies reported about the use of portable EMG recorder for the detection of
daytime masticatory muscle activity (Watanabe et al., 2011; Fujisawa et al., 2013; Endo et al., 2011).
Actiwave (CamNtech Ltd, Cambridge, UK) range of miniature biomedical logging devices are designed
to capture EMG, EEG and ECG signals in daily living. Actiwave EMG is small (25 × 27 × 8.5 mm) and
lightweight (5.6 g) as shown in Figure 1. However, its validity of EMG recording of masticatory muscle
activity under daytime free-living situations has not been examined. We conducted the feasibility study
with a small number of subjects before a large scale study to check the long-term stability and reliability
of daytime EMG recording of masseter muscle activity (MMA) using Actiwave. The occurrence patterns
and characteristics of daytime nonfunctional MMA were also examined.
2.
Methods
2.1. Participants
Participants of this research were recruited from the University of Tokushima, School of
Dentistry. Inclusion criteria for this study were: the subject (1) agreed to participate in this study for 4
days, (2) agreed to use the surface electrodes to measure their MMA during daytime, (3) presented fully
erupted permanent teeth except for third molars, (5) signed informed consent. Participants were excluded
2
if they: (1) had impaired jaw functions (e.g. temporomandibular disorders, orofacial pain, and eating
difficulties), (2) were on medications and had health problems. Five adult male volunteers (mean age 28.1
± 2.6 years old) who matched the above criteria were selected (Sub1 - 5). The subjects consisted of one
dental laboratory technician (Sub1) and one dental student (sub2), and three dentists (Sub3, Sub4, and
Sub5). The experiment procedures were explained to all participants before obtaining informed consent.
This research was approved by the Research Ethics Committee of Tokushima University Hospital (No.
1274).
2.2. EMG recording experimental procedure
Surface EMG of the masseter muscle was recorded with Actiwave EMG that has a set of
configuration options, including software selectable resolutions (8, 9 or 10 bit), sampling rates (128, 256,
512 or 1024 Hz), and input signal ranges (800 μV or 8 mV peak-to-peak). In this study, to perform
continuous recording of EMG activity for up to 12 hours, 512 Hz sampling rate and 9-bit resolution were
selected. In the morning of each measurement day, the subjects came to our laboratory, where the device
was set up to record EMG. After scrubbing and cleaning the area of interest of the subject’s skin with
alcohol, one disposable self-adhesive pregeled surface Ag/AgCl electrode with 10 mm circle conductive
area (Inspad 1090K, Japan Medicalnext Co., Ltd, Osaka, JP) was applied over the thickest portion of the
masseter muscle belly at the habitual chewing side in the unipolar configuration. The thickest portion is
3
usually the mid portion of the muscle, which becomes also more convex during dental clenching. The
device can simply be taped to the ipsilateral shoulder. The reference electrode was placed on the center of
the forehead (Fig. 1). Prior to each full EMG recording, participants were carefully instructed to perform
maximal isometric voluntary clenching in the intercuspal position (>2 seconds) as fast and hard as
possible, and performed short test EMG recordings during maximal clenching to train for eliciting true
maximal clenching and also to verify the suitability of the input signal range. The full EMG recording
includes the calibration periods at its beginning part (BP) and ending part (EP). After setting up, they
were asked to record EMG activities during maximal clenching at the BP and EP calibration periods,
respectively, and to continue EMG recording as long as possible and report their own daytime behavior,
including eating, working, studying and resting using paper-and-pencil format. They then went about their
daily life. EMG signals were amplified (impedance 10 MΩ) and band-pass filtered (50 – 500 Hz) and
then stored within an internal non-volatile memory. After data collection in each measurement day, the
subjects returned to the laboratory where the electrodes were removed and the stored data and
self-reported data were collected and transferred to a personal computer for off-line analysis. This EMG
recording was performed on four separate days (D1, D2, D3, and D4).
2.3. Data analysis
2.3.1. Stability and reliability of EMG recording during daytime
4
Collected EMG data was rectified (full-wave rectification) with root mean square (RMS)
conversion with an integration time of 60 msec. The RMS EMG data (µV) every hour were then sorted in
ascending order of amplitude value. The average of RMS EMG values of the first 600 × 512 data points
(equal to 10-minutes recording at 512 Hz) for every sorted data set was calculated as a baseline of MMA
(during rest) (Fig. 2). Additionally, each 15-sec RMS EMG data (µV) set, including maximum voluntary
clenching, was selected respectively at the BP and EP of EMG recording (Fig. 3). We sorted and arranged
the selected data in ascending order of amplitude value. The averages of RMS EMG values of the first
and last 512 data points (equal to 1-second recording at 512 Hz) were calculated as MMA during rest
(baseline MMA) and maximum clenching, respectively. Finally, MMA during maximum voluntary
contraction (MVC) was obtained by subtracting the baseline MMA from that during maximum clenching
respectively at the BP and EP.
2.3.2. Nonfunctional masseter muscle activity (MMA) during daytime
The amplitude of EMG was normalized in terms of the subject’s 100% MVC level at the BP.
The normalized % MVC data during the recording period, except the calibration and functional period,
was analyzed with a custom-made computer program that was created in Microsoft Visual C++ 2008 ®.
Figure 4 shows MMA detection and classification flowchart. First, the following EMG criteria for the
detection of sleep bruxism event by Okura (Okura et al., 1999) was used to detect a daytime MMA
5
events: (a) Elevations of EMG signal above 5% MVC were selected; (b) The exclusion of EMG events
with a duration of less than 0.25 seconds; (c) Combination of EMG events with intervals of less than or
equal to 2 seconds; (d) EMG events with a duration of longer than 2 seconds; and (e) with peak MMA
greater than 10% MVC detected as a daytime MMA event. The detected MMA not relating to functional
behaviors such as eating was termed a nonfunctional MMA. Second, according to Lavigne’s criteria
(Lavigne et al., 1996), the detected nonfunctional MMA event was classified as phasic, tonic, and mixed
type. The phasic type corresponds to at least three EMG bursts of 0.25 to 2.0 seconds duration, separated
by two interburst intervals; the tonic type corresponds to an EMG burst lasting more than 2.0 second; and
the mixed type is a combination of phasic and tonic events. The frequency of occurrence and duration
time (second), and peak MMA (%MVC) of each MMA event type were calculated.
2.4. Statistical analysis
Friedman’s test was used to evaluate the significance of change over time in the baseline MMA.
The MMAs during MVC at the BP and EP for individual subjects were compared using Wilcoxon singed
rank tests. Linear regression analysis was used to determine the relationship between the baseline MMA
for the first 1-hour period and those for the other 1-hour periods, and between the MMA during MVC at
the BP and EP. Friedman’s test was also conducted to evaluate the difference of the frequency of
occurrence among the former three MMA types. Steel-Dwass test was used for comparison of the
6
duration and peak MMA among the three MMA types. Statistical significance was set at α=0.05.
3. Results
3.1. Stability and reliability of EMG recording during daytime
Four days daytime EMG data were obtained from 5 subjects with 2.5 ± 3.1 days recording
interval. Mean duration of time for recording was 7.4 ± 1.0 hours per day (6.1 – 9.5 hours). According to
subject’s self-report, main activities of the participants during recording period were clinical work,
laboratory work, deskwork or receiving lectures, and no excessive exercise-induced sweating. Figure 5
exhibits examples of EMG data through one day recording period. The different characteristics of
daytime MMA pattern were shown in these example graphs. Table 1 shows the baseline MMA hourly
obtained for each subject from each measurement day. The recording periods not exceeding 6 hours were
used for statistical analysis. No significant time effect on the baseline of MMA was seen for individual
subjects (Friedman test P>0.05). Table 2 shows MMA during MVC at the BP and EP calculated for each
subjects from each measurement day. There were no significant time-dependent effects on the value of
MMA during MVC (Wilcoxon singed rank test P>0.05). Figures 6 and 7 show the linear relationship
between the baseline MMAs for first 1-hour period and those for the other 1-hour periods, and between
MMAs during MVC at the BP and EP, respectively. The slope of the regression line for the baseline MMA was 0.96 (R2 = 0.67 ), and for the MMA during MVC was 0.92 (R2 = 0.95).
7
3.2. Nonfunctional masseter muscle activity (MMA) during daytime
The analysis on nonfunctional of MMA during daytime was performed during all recording
periods except for the calibration periods and the functional activity period including eating and napping
period defined by subject’s self-report (Fig. 5). Additionally, data from the second day (D2) of the second
subject (Sub2) was excluded from data analysis because they consisted of noise for several hours during
EMG recording. Because of this data loss due to noise contamination, 19 measurement days was
considered for analysis. Table 3 shows the frequency of occurrence of each MMA event type. Total
duration of analysis period was 129.4 hour (mean 6.8 ± 1.0 hours per day). A total of 4923 MMA events
were detected. The number of the MMA event was 1209 events (24.6 %) for phasic type, 1759 events
(37.0 %) for tonic type, 1377 events (28.0 %) for mixed type, and 578 events (11.7 %) for other type,
respectively. There was no significant difference in the number of occurrence among phasic, tonic, and
mixed types (Friedman’s test P = 0.165). Figure 8 shows the duration and peak MMA of each MMA type.
Median (25th - 75th percentile) of the duration was 4.0 sec (2.9 - 6.1 sec) for phasic type, 4.0 sec (2.7 -
6.7 sec) for tonic type, 7.4 sec (5.0 – 12.6 sec) for mixed type, respectively. The duration of mixed type
was significantly longer than that of the other two types (Steel-Dwass test P<0.05). Median (25th – 75th
percentile) of the peak MMA was 45.1 %MVC (25.0 – 70.3 %MVC) for phasic type, 32.8 %MVC (22.1 –
49.9 %MVC) for tonic type, 41.6 %MVC (27.6 – 67.6 %MVC) for mixed type, respectively. The peak
8
MMA of tonic type was significantly lower than that of the other two types (Steel-Dwass test P<0.05).
4. Discussion
Our main interest in this small scale study was to examine the long-term stability and reliability
of daytime EMG measurement using the portable device. In selection of participants, their ability to
participate the daytime study for four days was the most important criterion, and this study did not
consider their daytime oral habits such as grinding, clenching, and teeth contacting habit (Sato et al.,
2006).
There are some problems include artifacts and noise in long-term EMG measurement using the
portable device. The current study explored the stability and reliability of surface EMG measurement of
MMA using Actiwave for 6.1 to 9.5-hour recording periods (mean 7.4). There were no significant time
dependent effects on the value of the baseline MMA and the MMA during MVC (p>0.05), as seen by the
regression slopes (0.96 for baseline MMA, and 0.92 for MMA during MVC). The MMAs during rest
(baseline) and during MVC were consistent at least 6 hours and the slopes of regression line were close to
unity. These results indicate that there were no statistically significant time-dependent effects on the
measurement of MMA using Actiwave during daytime.
The data from one day in all of 20 measurement days was excluded from analysis of
nonfunctional MMA because of data loss due to big noise contamination. The most significant noise
9
sources in surface EMG include electromagnetic source and motion artifact. The unwanted signals were
observed in some parts of the analysis period and had amplitudes that were larger than the EMG signal.
Since changes in the skin-electrode impedance can produce large amplitude artifacts (Rosell et al., 1995),
the noise signals may be attributed to the poor skin-electrode interface because of subject movements. We
think this level of data loss is acceptable and not excessive when the portable device is used under
daytime free-living situation.
Gallo et al. (1998) studied about masseter muscle EMG activity pattern during intentional
functional activities (during rest, chewing, swallowing, laughing, and speaking) and parafunctional
activities (during grinding and clenching). In that study, they concluded that the functional and
parafunctional activities were recognized correctly with EMG analysis. On the other hand, Kato et al.
(2006) studied orofacial activities during the 30-minute silent reading in 16 healthy subjects and reported
that functional and parafunctional orofacial activities that occur in the natural living environment could be
specifically distinguished by EMG recording with audio video recording. Miyamoto et al. (1996) studied
MMAs during the whole day in 30 healthy young adult with a portable device and found that most of the
strong MMAs appeared only during eating and the frequency of occurrence of MMA increased during
daytime without eating from that during sleep. Accordingly, in our research, we excluded EMG activity
during eating and napping periods from analysis on MMAs, according to subject’s self-reported data and
observation of EMG data in order to more exactly detect nonfunctional MMA events not associated with
10
functional behaviors during daytime wakefulness. The paper-and-pencil self-report diaries could be
inaccurate because of recall biases, hence the detected MMA events may contain the some data during
functional activities.
Many criteria have been reported to detect sleep bruxism from EMG data (Okura et al., 1999;
Lavigne et al., 1996; Ikeda et al., 1996). But so far, no study has reported about algorithm with numerical
standard for detection of daytime bruxism (Piquero et al., 2000). We detected and classified daytime
nonfunctional MMA event with Okura’s and Lavigne’s criteria that were originally applied for the
definition of sleep bruxism (Okura et al., 1999; Lavigne et al., 1996). Since Okura’s criteria uses low
threshold level of EMG elevation of 5% MVC, onset of MMA events can be accurately detected. The
MMA levels during swallowing and speech are much lower than those during teeth grinding and
clenching (Gallo et al., 1998). Accordingly, to select MMA event with peak MMA greater than 10%MVC
was supposedly effective to reject swallowing and speech period. By using the MMA detection and
classification criteria that were the same as those for sleep bruxism , it may be possible to directory
compare MMA events during both sleep and daytime.
We detected 38.1 (range, 24.5 – 59.1) nonfuncional MMA events per hour during daytime among
all subjects. Nonfunctional MMAs not relating to chewing behavior were observed in all five participants.
In the previous studies (Miyamoto et al., 1996; Kato et al., 2006), the masseter EMG bursts were
observed at 15.5 to 30.3 events per hour during daytime without eating. Therefore, our results may be
11
reasonable and not excessive. Furthermore, tonic type MMA event (13.6 event/hour, 37.0 %) was more
frequently observed than the other two types (9.3 event/hour, 24.6 % for phasic type; 10.6 event/hour,
28.5% for mixed type) (Table 3). Since about 90% of sleep bruxism events are classified as phasic or
mixed type (Kato et al., 2003; Lavigne et al., 2008), daytime bruxism seems to have a different kinematic
property from that of sleep bruxism. Lavigne et al. (2008) reported that most of daytime bruxism is teeth
clenching. The results of this study agreed with their reports. However, phasic type events that correspond
with teeth grinding was also found in 24.6 % of the total MMA event. There were the significant
differences among the three MMA types with respect to the duration and peak MMA, and the frequency
of occurrence of each MMA type did not show the significant difference. The visual and occurrence
pattern of MMA was different among subjects (Fig. 5, Table 3). Consequently, we suspected that
parafunctional habit may be associated with the occurrence patterns of MMA during daytime.
In summary, the result of this study indicated that Actiwave can be used to measure MMA
events during daytime with high stability and reliability. Further studies with a large sample size are
necessary to better understand if MMA patterns during daytime reflects individual disposition of daytime
orofacial nonfunctional activities.
12
Acknowledgements
This study was supported by grants from the Ministry of Education, Culture, Sports, Science and
Technology of Japan (No. 25861848).
13
References
De Leeuw R, Klasser GD eds. Glossary. In Orofacial pain: Guidelines for Assessment, Diagnosis and
Management. 5th edition. Illinois (IL): American Academy of Orofacial Pain. Quintessence
Publishing, 2013, 254.
Endo H, Kanemura K, Tanabe N, Takebe J. Clenching occurring during the day is influenced by
psychological factors. J Prosthodont Res 2011;55:159-164.
Fujisawa M, Kanemura K, Tanabe N, Gohdo Y, Watanabe A, Iizuka T, Sato M, Ishibashi K.
Determination of daytime clenching events in subjects with and without self-reported clenching.
J Oral Rehabil 2013;40:731-736.
Gallo LM, Guerra PO, Palla S. Automatic on-line onechannel recognition of masseter activity. J Dent Res
1998;77:1539-1546.
Ikeda T, Nishigawa K, Kondo K, Takeuchi H, Clark GT. Criteria for the detection of sleep-associated
bruxism in humans. J Orofac Pain 1996;10:270-282.
Kato T, Yamaguchi T, Okura K, Abe S, Lavigne GJ, Sleep less and bite more: Sleep disorders associated
with occlusal loads during sleep. J Proth Res 2003;57:69-81.
Kato T, Akiyama S, Kato Y, Yamashita S, Masuda Y, Morimoto T. The occurrence of spontaneous
functional and nonfunctional orofacial activities in subjects without pain under laboratory
conditions: a descriptive study. J Orofac Pain 2006;20:317-324.
14
Kato T, Thie NM, Huynh N, Miyawaki S, Lavigne GJ. Topical review: sleep bruxism and the role of
peripheral sensory influences. J Orofac Pain 2003;17:191-213.
Kato T, Thie NMR, Montplaisir JY, Lavigne GJ. Bruxism and orofacial movements during sleep. Dent
Clin North Am 2001;45:657-684.
Lavigne GJ, Khoury S, Abe S, Yamaguchi T, Raphael K. Bruxism physiology and pathology: an overview
for clinicians. J Oral Rehabil 2008;35:476–494.
Lavigne GJ, Manzini C, Huynh NT. Sleep bruxism. In: Kryger MH, Roth T, Dement WC editors.
Principles and Practice of Sleep Medicine. 5the ed. Philadelphia: Elsevier, 2005:946-959.
Lavigne GJ, Rompré PH, Montplaisir JY. Sleep bruxism: validity of clinical research diagnostic criteria in
a controlled polysomnographic study. J Dent Res 1996;75:546-552.
Manfredini D, Winocur E, Guarda-Nardini L, Lobbezoo F. Self-reported bruxism and temporomandibular
disorders: findings from two specialised centres. J Oral Rehabil 2012;39:319-325.
Miyamoto K, Yamada K, Ishizuka Y, Morimoto N, Tanne K. Masseter muscle activity during the whole
day in young adult. Am J Orthod Dentfacial Orthop 1996;110:394-398.
Nishigawa K, Bando E, Nakano M. Quantitative study of bite force during sleep associated bruxism. J
Oral Rehabil 2001;28:485-491.
Okura K, Nishigawa K, Bando E, Nakano M, Ikeda T, Suzuki A. The relationship between jaw movement
and masseter muscle EMG during sleep associated bruxism. Dent Jpn 1999;35:53-56.
15
Piquero K, Sakurai K. A clinical diagnosis of diurnal (non-sleep) bruxism in denture wearers. J Oral
Rehabil 2000;27;473-482.
Rompré PH, Daigle-Landry D, Guitard F, Montplaisir JY, Lavigne GJ. Identification of a sleep bruxism
subgroup with a higher risk of pain. J Dent Res 2007;6:837-842.
Rosell J, Cohen KP, Webster JG. Reduction of motion artifacts using a two-frequency impedance
plethysmograph and adaptive filtering. IEEE Trans Biomed Eng. 1995;42(10):1044-8.
Rugh JD, Harlan J. Nocturnal bruxism and temporomandibular disorders．Adv Neurol 1988;49:329-341.
Sato F, Kino K, Sugisaki M, Haketa T, Amemori Y, Ishikawa T, Shibuya T, Amagasa T, Shibuya T, Tanabe
H, Yoda T, Sakamoto I, Omura K, Miyaoka H. Teeth contacting habit as a contributing factor to
chronic pain in patients with temporomandibular disorders. J Med Dent Sci 2006;53:103-109.
Shetty S, Pitti V, Babu CLS, Kumar GPS, Deepthi BC. Bruxism: A Literature Review. J Indian
Prosthodont Soc 2010;10:141-148.
Tsiggos N, Tortopidis D, Hatzikyriakos A, Menexes G. Association between self-reported bruxism
activity and occurrence of dental attrition, abfraction, and occlusal pits on natural teeth. J
Prosthet Dent 2008;100:41-46.
Watanabe A, Kanemura K, Tanabe N, Fujisawa M. Effect of electromyogram biofeedback on daytime
clenching behavior in subjects with masticatory muscle pain. J Prosthodont Res 2011;55:75-81.
16
Figure and Table Legends
Fig. 1
Experimental set-up to record surface EMG activity of the masseter muscle. This portable device
(Actiwave CamNtech) performs continuous recording of EMG activity for up to 12 hours with 512 Hz
sampling rate and 9-bit resolution. Disposable self-adhesive pregeled surface electrode (Ag/AgCl) was
applied over the thickest portion of the masseter muscle belly at the habitual chewing side in the unipolar
configuration. The device can simply be taped to the ipsilateral shoulder. Reference electrode was placed
on the center of the forehead.
Fig. 2
Calculation of the baseline MMA. The RMS EMG data (µV) every 1 hour were sorted in ascending order
of amplitude value. The average of RMS EMG values of the first 600×512 data points for every 1-hour
recording period was calculated as a baseline of MMA (during rest).
Fig. 3
Calculation of the MMA during MVC. Each 15 sec RMS EMG data (µV) set including maximum
voluntary clenching was selected respectively at the BP and EP of EMG recording. The selected data
17
were sorted and arranged in ascending order of amplitude value. The average of RMS EMG values of
the first 512 data points and of the last 512 data points were calculated as the MMA during rest (baseline
MMA) and maximum clenching, respectively. MMA during maximum voluntary contraction (MVC) was
obtained by subtracting the baseline MMA from that during maximum clenching at the BP and EP
respectively.
Fig. 4
Nonfunctional MMA during daytime detection and classification flowchart
Fig. 5
Examples of EMG data through one day recording period.
Fig. 6
The linear relationship between the baseline MMAs for first 1-hour period and those for the other 1-hour
periods
Fig. 7
The linear relationship between the MMA during MVC at the BP and EP
18
Fig. 8
Box chart of the duration and peak MMA of each MMA type. Box-whisker charts represent boxes for
medians with the first and third quartiles and whiskers for the most extreme values within 1.5 × the
interquartile range from the first and third quartiles, respectively. The duration of mixed type was
significantly longer than that of the other two types (Steel-Dwass test P<0.05). The peak MMA of tonic
type was significantly lower than that of the other two types (Steel-Dwass test P<0.05).
Table 1.
The baseline MMA obtained hourly for each subject from each measurement day. The recording periods
not exceeding 6 hours (surrounded with the bold line) were used for statistical analysis. No significant
time effect on the baseline of MMA was seen for each subject (Friedman test P>0.05).
Table 2
The MMA during MVC at the BP and EP calculated for each subject from each measurement day. There
were no significant time dependent effects on the value of MMA during MVC (Wilcoxon singed rank test
P>0.05).
19
Table 3
The frequency of occurrence of each MMA event type.
There was no significant difference in the number of occurrence among three MMA event types
(Friedman’s test
P=0.165).
20
Figure1
Figure2
Figure3
Figure4
Figure5
Figure6
Figure7
Figure8
Author Bio Photo Dr Omoto
Author Bio Photo Dr Shigemoto
Author Bio Photo Dr Suzuki
Author Bio Photo Dr Nakamura
Author Bio Photo Dr Okura
Author Bio Photo Dr Nishigawa
Author Bio Photo Dr Goto
Author Bio Photo Dr Omar
Author Bio Photo Dr Matsuka
Katsuhiro Omoto completed his D.D.S. at the University of Tokushima, School of Dentistry, Japan in 2012. He worked as Dental Resident at the Post-graduate Education Center, Tokushima University Hospital from 2012 to 2013. Now he is a Ph.D. student in The University of Tokushima Graduate School. Dr. Omoto’s research is focused on oral function, basic mechanisms of neural transmission of tooth sensation and fixed prosthodontics. Shuji Shigemoto received his Ph.D. in Dentistry from The University of Tokushima, Japan in 1996. He worked at Zurich University, Switzerland as a visiting fellow from 1999 to 2001. He is currently an Assistant Professor in the Department of Stomatognathic Function and Occlusal Reconstruction at the University of Tokushima, and a Clinical Professor in the Department of Fixed Prosthodontics at Turumi University. His research interests focus on stomatognathic function; in particular, development of jaw tracking device and kinematic dental bite registration method, and jaw movement status during sleep bruxism, and EMG activity during daytime clenching. Yoshitaka Suzuki graduated from the University of Tokushima, School of Dentistry, Japan in 2008. After a dental resident in Tokushima University Hospital in a year, He entered the University of Tokushima Graduate School and was award the Ph.D. in 2012. Now he works at Department of Stomatognathic Function and Occlusal Reconstraction, the University of Tokushima Graduate School as an assistant professor. He studies about bruxism, jaw movement, occlusion, sports dentistry and swallowing. Mayumi Nakamura graduated from the University of Tokushima, School of Dentistry, Japan in 2009. She worked as Dental Resident at the Post-graduate Education Center, Tokushima University Hospital from 2010 to 2011. Now she is a Ph.D. student in The University of Tokushima Graduate School and works as a staff in Fukui Dental Clinic. Dr. Nakamura’s studies about jaw function and prosthodontics. Kazuo Okura completed his DDS and PhD at the University of Tokushima, Japan. He worked at University de Montreal, Canada as a visiting professor from 2003 to 2005. He is currently an associate professor at the University of Tokushima, Japan. Dr. Okura’s research is focused on stomatognathic function, sleep bruxism and fixed prothodontics. Nami Goto graduated from the Fukuoka Dental College, Japan in 2010.
She worked as Dental Resident at the Post-graduate Education Center, Tokushima University Hospital from 2010 to 2011. And she is currently a Dental Staff in General Dentistry, Tokushima University Hospital. Dr. Takata’s research interests include oral function, oral implantology and fixed prosthodontics. Omar Marianito Maningo Rodis earned his Doctor of Dental Medicine degree from Southwestern University, Philippines; Ph.D. degree from Okayama University, Japan; and training in Clinical Dental Research Methods from the University of Washington, USA. He worked as an Assistant Professor in the Department of Behavioral Pediatric Dentistry of Okayama University and is currently an Assistant Professor in the Institute of Health Biosciences of the University of Tokushima, Japan. His research interests include public health, pediatric dentistry, geriatric dentistry, curriculum development, international exchange and collaboration. Yoshizo Matsuka completed his D.D.S. and Ph.D. at Okayama University in Japan. He finished hospital residency program and was an Assistant Professor at School of Dentistry, University of California Los Angeles. He was also Associate Professor at Oral Rehabilitation and Regenerative Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences. He is currently a Professor and chair at Department of Stomatognathic Function and Occlusal Reconstruction, Institute of Health Biosciences, Tokushima University. Dr. Matsuka’s research is focused on oral function, neurotransmitter release from sensory ganglia and clinical epidemiology of prosthodontics.
Fig. 5
subject
sub1
sub2
sub3
sub4
sub5
Table. 1
measurement day D1 D2 D3 D4 D1 D2 D3 D4 D1 D2 D3 D4 D1 D2 D3 D4 D1 D2 D3 D4
baseline MMA (µV) Friedman test 0-1 h
1-2 h
2-3 h
3-4 h
4-5 h
5-6 h
6-7 h
7-8 h
8-9 h
2.41 3.06 2.85 2.66 2.09 2.47 2.10 2.26 1.84 2.53 1.76 1.87 2.59 2.23 2.61 2.79 1.69 1.47 1.60 1.36
2.66 2.71 2.61 2.96 2.33 2.69 1.76 1.72 1.83 2.05 1.69 1.69 2.66 2.81 2.54 2.91 1.60 1.46 1.48 1.33
2.76 2.82 3.22 2.83 1.71 2.59 1.73 2.15 1.77 2.33 1.73 1.64 2.80 2.15 2.22 3.07 1.64 1.46 1.51 1.33
3.07 3.05 2.94 2.97 2.17 2.87 2.03 1.94 1.69 1.96 2.07 1.77 2.27 1.80 2.59 2.35 1.71 1.54 1.72 1.37
2.65 2.89 3.17 2.50 1.78 2.55 2.23 1.61 2.33 1.68 1.44 2.20 1.59 1.52 2.22 2.61 1.72 1.53 1.35 1.44
2.79 2.79 3.26 2.80 1.74 2.66 2.37 1.54 1.83 1.47 1.62 1.71 2.86 2.11 2.49 2.19 1.60 1.51 1.36 1.38
2.54 2.96 3.17 2.83 1.87 2.58 2.32
2.81 2.82 3.26 2.48 1.86
2.98 2.83 4.29 3.04 2.83
2.10 2.13 2.12
1.85 1.69 1.52 1.48 1.57
p = 0.35 df = 5
p = 0.70 df = 5
p = 0.34 df = 5
p = 0.11 df = 5
p = 0.10 df = 5
subject
sub1
sub2
sub3
sub4
sub5
Table. 2
MMA during MVC measurment Wilcoxon test day BP vs EP at BP (µV) at EP (µV) D1 D2 D3 D4 D1 D2 D3 D4 D1 D2 D3 D4 D1 D2 D3 D4 D1 D2 D3 D4
112.36 115.44 123.92 102.72 91.69 85.66 67.96 64.06 69.43 44.86 58.85 49.55 71.37 64.88 70.90 110.98 72.43 28.50 82.24 28.68
109.88 114.39 117.00 84.76 82.00 85.36 77.93 64.10 64.89 46.33 60.11 52.94 68.73 58.08 66.72 101.75 59.99 27.95 87.37 22.39
p = 0.125
p = 1.000
p = 0.875
p = 0.125
p = 0.375
recording day
analysis period (hour)
phasic
tonic
mixed
other
total / per hour
Sub1
4
34.0
192
255
200
186
833 / 24.5
Sub2
3
17.8
106
357
243
94
800 / 44.8
Sub3
4
27.6
690
315
458
167
1630 / 59.1
Sub4
4
23.5
170
436
293
104
1003 / 42.7
Sub5
4
26.5
51
396
183
27
657 / 24.8
total / per hour
19
129.4
1209 / 9.3
1759 / 13.6
1377 / 10.6
578 / 4.5
4923 / 38.1
-
24.6
37.0
28.0
11.7
100.0
subject
frequency (%)
Table.3
-
number of MMA event
S1050-6411(15)00080-2 http://dx.doi.org/10.1016/j.jelekin.2015.04.012 JJEK 1853
To appear in:
Journal of Electromyography and Kinesiology
Received Date: Revised Date: Accepted Date:
24 September 2014 21 April 2015 22 April 2015
Please cite this article as: K. Omoto, S. Shigemoto, Y. Suzuki, M. Nakamura, K. Okura, K. Nishigawa, N. Goto, O.M.M. Rodis, Y. Matsuka, A preliminary investigation of reproducibility of EMG signals during daytime masticatory muscle activity using a portable EMG logging device, Journal of Electromyography and Kinesiology (2015), doi: http://dx.doi.org/10.1016/j.jelekin.2015.04.012
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Title:
A preliminary investigation of reproducibility of EMG signals during daytime masticatory muscle activity using a portable EMG logging device
[Original research]
Authors and affiliations: Katsuhiro Omoto, DDS1, Shuji Shigemoto, DDS, PhD1,3, Yoshitaka Suzuki, DDS, PhD1, Mayumi Nakamura, DDS1, Kazuo Okura, DDS, PhD1, Keisuke Nishigawa, DDS, PhD1, Nami Goto, DDS1, Omar Marianito Maningo Rodis, DMD, PhD2, Yoshizo Matsuka, DDS, PhD1 1
Department of Stomatognathic Function and Occlusal Reconstruction, Institute of Health Biosciences,
The University of Tokushima Graduate School, Tokushima, Japan 2
Institute of Health Biosciences, The University of Tokushima Graduate School, Tokushima, Japan
3
Department of Fixed Prosthodontics, School of Dental Medicine, Tsurumi University, Yokohama, Japan
Key words Daytime masseter muscle activity, teeth grinding, clenching
Corresponding author Prof. Yoshizo Matsuka Department of Fixed Prosthodontics, Institute of Health Biosciences, The University of Tokushima Graduate School 3-18-15 Kuramoto-cho, Tokushima, 770-8504, Japan Email: [email protected]
1
Abstract
Continuous parafunctional masseter muscle activities (MMA) that are associated with daytime
bruxism have been suspected to be one of the main pathoetiology for orofacial pain. The purpose of this
study was to examine the long-term stability and reliability of daytime EMG measurement of MMA using
a portable device (Actiwave; CamNtech Ltd). Daytime masseter muscle EMG of five subjects were
recorded for four days in their normal living environment. There was no significant time dependent effect
on EMG amplitude during recording period. A total of 4923 MMA events were detected in all analysis
periods (129.4 hours) and classified into phasic type (1209 events, 24.6 %), tonic type (1759 events,
37.0 %), and mixed type (1377 events, 28.0 %). There was no significant difference in the number of
occurrence among three MMA types. With respect to the duration and peak MMA, there were significant
differences among three MMA types. The result of this study indicated that Actiwave can be used to
measure MMA events during daytime with high stability and reliability under the normal living
environment and it was suspected that parafunctional habits may be associated with the occurrence
patterns of MMA during daytime.
1
1.
Introduction
According to the guidelines of the American Academy of Orofacial Pain, bruxism is defined as
a repetitive jaw-muscle activity characterized by clenching or grinding of the teeth and/or by bracing or
thrusting of the mandible; and can occur during sleep or during wakefulness (De Leeuw et al., 2013).
From the physical statements during the activity, bruxism can be divided into sleep bruxism and daytime
bruxism. Since sleep bruxism may be associated with excessive occlusal force (Nishigawa et al., 2001),
this parafunction causes tooth attrition, abfraction, destruction and/or desorption of dental restoration, and
become an advance factor for periodontal disease and orofacial pain (Kato et al., 2013; Rompré et al.,
2007; Rugh etal., 1988; Kato et al., 2001; Lavigne et al., 2005). On the other hand, daytime bruxism is
typically characterized as parafunctional continuous muscle contraction, and it is reported that this diurnal
oral habit is one of the main pathogenesis of orofacial pain (Sato et al., 2006). EMG recording of
masticatory muscle activity is indispensable for detecting daytime bruxism but it is difficult to recognize
daytime bruxism because of the methodological limitations (Piquero et al., 2000). Thus, diagnosis of
daytime bruxism is generally done with the patient’s declaration and intraoral examination (Tsuggos et al.,
2008; Watanabe et al., 2011; Fujisawa et al., 2013). Self-report to assess bruxism presence and absence is
convenient, but bruxism patients are sometimes unaware of their oral habits (Shetty et al., 2010;
Manfredini et al., 2012). Tooth attrition, scalloped tongue and linea alba on buccal mucosa are frequently
1
found as a sign of bruxism. However, these intraoral findings are not necessarily associated with bruxism
and cannot be a reliable evidence of this parafunction (Piquero et al., 2000; Fujisawa et al., 2013).
Lately, some studies reported about the use of portable EMG recorder for the detection of
daytime masticatory muscle activity (Watanabe et al., 2011; Fujisawa et al., 2013; Endo et al., 2011).
Actiwave (CamNtech Ltd, Cambridge, UK) range of miniature biomedical logging devices are designed
to capture EMG, EEG and ECG signals in daily living. Actiwave EMG is small (25 × 27 × 8.5 mm) and
lightweight (5.6 g) as shown in Figure 1. However, its validity of EMG recording of masticatory muscle
activity under daytime free-living situations has not been examined. We conducted the feasibility study
with a small number of subjects before a large scale study to check the long-term stability and reliability
of daytime EMG recording of masseter muscle activity (MMA) using Actiwave. The occurrence patterns
and characteristics of daytime nonfunctional MMA were also examined.
2.
Methods
2.1. Participants
Participants of this research were recruited from the University of Tokushima, School of
Dentistry. Inclusion criteria for this study were: the subject (1) agreed to participate in this study for 4
days, (2) agreed to use the surface electrodes to measure their MMA during daytime, (3) presented fully
erupted permanent teeth except for third molars, (5) signed informed consent. Participants were excluded
2
if they: (1) had impaired jaw functions (e.g. temporomandibular disorders, orofacial pain, and eating
difficulties), (2) were on medications and had health problems. Five adult male volunteers (mean age 28.1
± 2.6 years old) who matched the above criteria were selected (Sub1 - 5). The subjects consisted of one
dental laboratory technician (Sub1) and one dental student (sub2), and three dentists (Sub3, Sub4, and
Sub5). The experiment procedures were explained to all participants before obtaining informed consent.
This research was approved by the Research Ethics Committee of Tokushima University Hospital (No.
1274).
2.2. EMG recording experimental procedure
Surface EMG of the masseter muscle was recorded with Actiwave EMG that has a set of
configuration options, including software selectable resolutions (8, 9 or 10 bit), sampling rates (128, 256,
512 or 1024 Hz), and input signal ranges (800 μV or 8 mV peak-to-peak). In this study, to perform
continuous recording of EMG activity for up to 12 hours, 512 Hz sampling rate and 9-bit resolution were
selected. In the morning of each measurement day, the subjects came to our laboratory, where the device
was set up to record EMG. After scrubbing and cleaning the area of interest of the subject’s skin with
alcohol, one disposable self-adhesive pregeled surface Ag/AgCl electrode with 10 mm circle conductive
area (Inspad 1090K, Japan Medicalnext Co., Ltd, Osaka, JP) was applied over the thickest portion of the
masseter muscle belly at the habitual chewing side in the unipolar configuration. The thickest portion is
3
usually the mid portion of the muscle, which becomes also more convex during dental clenching. The
device can simply be taped to the ipsilateral shoulder. The reference electrode was placed on the center of
the forehead (Fig. 1). Prior to each full EMG recording, participants were carefully instructed to perform
maximal isometric voluntary clenching in the intercuspal position (>2 seconds) as fast and hard as
possible, and performed short test EMG recordings during maximal clenching to train for eliciting true
maximal clenching and also to verify the suitability of the input signal range. The full EMG recording
includes the calibration periods at its beginning part (BP) and ending part (EP). After setting up, they
were asked to record EMG activities during maximal clenching at the BP and EP calibration periods,
respectively, and to continue EMG recording as long as possible and report their own daytime behavior,
including eating, working, studying and resting using paper-and-pencil format. They then went about their
daily life. EMG signals were amplified (impedance 10 MΩ) and band-pass filtered (50 – 500 Hz) and
then stored within an internal non-volatile memory. After data collection in each measurement day, the
subjects returned to the laboratory where the electrodes were removed and the stored data and
self-reported data were collected and transferred to a personal computer for off-line analysis. This EMG
recording was performed on four separate days (D1, D2, D3, and D4).
2.3. Data analysis
2.3.1. Stability and reliability of EMG recording during daytime
4
Collected EMG data was rectified (full-wave rectification) with root mean square (RMS)
conversion with an integration time of 60 msec. The RMS EMG data (µV) every hour were then sorted in
ascending order of amplitude value. The average of RMS EMG values of the first 600 × 512 data points
(equal to 10-minutes recording at 512 Hz) for every sorted data set was calculated as a baseline of MMA
(during rest) (Fig. 2). Additionally, each 15-sec RMS EMG data (µV) set, including maximum voluntary
clenching, was selected respectively at the BP and EP of EMG recording (Fig. 3). We sorted and arranged
the selected data in ascending order of amplitude value. The averages of RMS EMG values of the first
and last 512 data points (equal to 1-second recording at 512 Hz) were calculated as MMA during rest
(baseline MMA) and maximum clenching, respectively. Finally, MMA during maximum voluntary
contraction (MVC) was obtained by subtracting the baseline MMA from that during maximum clenching
respectively at the BP and EP.
2.3.2. Nonfunctional masseter muscle activity (MMA) during daytime
The amplitude of EMG was normalized in terms of the subject’s 100% MVC level at the BP.
The normalized % MVC data during the recording period, except the calibration and functional period,
was analyzed with a custom-made computer program that was created in Microsoft Visual C++ 2008 ®.
Figure 4 shows MMA detection and classification flowchart. First, the following EMG criteria for the
detection of sleep bruxism event by Okura (Okura et al., 1999) was used to detect a daytime MMA
5
events: (a) Elevations of EMG signal above 5% MVC were selected; (b) The exclusion of EMG events
with a duration of less than 0.25 seconds; (c) Combination of EMG events with intervals of less than or
equal to 2 seconds; (d) EMG events with a duration of longer than 2 seconds; and (e) with peak MMA
greater than 10% MVC detected as a daytime MMA event. The detected MMA not relating to functional
behaviors such as eating was termed a nonfunctional MMA. Second, according to Lavigne’s criteria
(Lavigne et al., 1996), the detected nonfunctional MMA event was classified as phasic, tonic, and mixed
type. The phasic type corresponds to at least three EMG bursts of 0.25 to 2.0 seconds duration, separated
by two interburst intervals; the tonic type corresponds to an EMG burst lasting more than 2.0 second; and
the mixed type is a combination of phasic and tonic events. The frequency of occurrence and duration
time (second), and peak MMA (%MVC) of each MMA event type were calculated.
2.4. Statistical analysis
Friedman’s test was used to evaluate the significance of change over time in the baseline MMA.
The MMAs during MVC at the BP and EP for individual subjects were compared using Wilcoxon singed
rank tests. Linear regression analysis was used to determine the relationship between the baseline MMA
for the first 1-hour period and those for the other 1-hour periods, and between the MMA during MVC at
the BP and EP. Friedman’s test was also conducted to evaluate the difference of the frequency of
occurrence among the former three MMA types. Steel-Dwass test was used for comparison of the
6
duration and peak MMA among the three MMA types. Statistical significance was set at α=0.05.
3. Results
3.1. Stability and reliability of EMG recording during daytime
Four days daytime EMG data were obtained from 5 subjects with 2.5 ± 3.1 days recording
interval. Mean duration of time for recording was 7.4 ± 1.0 hours per day (6.1 – 9.5 hours). According to
subject’s self-report, main activities of the participants during recording period were clinical work,
laboratory work, deskwork or receiving lectures, and no excessive exercise-induced sweating. Figure 5
exhibits examples of EMG data through one day recording period. The different characteristics of
daytime MMA pattern were shown in these example graphs. Table 1 shows the baseline MMA hourly
obtained for each subject from each measurement day. The recording periods not exceeding 6 hours were
used for statistical analysis. No significant time effect on the baseline of MMA was seen for individual
subjects (Friedman test P>0.05). Table 2 shows MMA during MVC at the BP and EP calculated for each
subjects from each measurement day. There were no significant time-dependent effects on the value of
MMA during MVC (Wilcoxon singed rank test P>0.05). Figures 6 and 7 show the linear relationship
between the baseline MMAs for first 1-hour period and those for the other 1-hour periods, and between
MMAs during MVC at the BP and EP, respectively. The slope of the regression line for the baseline MMA was 0.96 (R2 = 0.67 ), and for the MMA during MVC was 0.92 (R2 = 0.95).
7
3.2. Nonfunctional masseter muscle activity (MMA) during daytime
The analysis on nonfunctional of MMA during daytime was performed during all recording
periods except for the calibration periods and the functional activity period including eating and napping
period defined by subject’s self-report (Fig. 5). Additionally, data from the second day (D2) of the second
subject (Sub2) was excluded from data analysis because they consisted of noise for several hours during
EMG recording. Because of this data loss due to noise contamination, 19 measurement days was
considered for analysis. Table 3 shows the frequency of occurrence of each MMA event type. Total
duration of analysis period was 129.4 hour (mean 6.8 ± 1.0 hours per day). A total of 4923 MMA events
were detected. The number of the MMA event was 1209 events (24.6 %) for phasic type, 1759 events
(37.0 %) for tonic type, 1377 events (28.0 %) for mixed type, and 578 events (11.7 %) for other type,
respectively. There was no significant difference in the number of occurrence among phasic, tonic, and
mixed types (Friedman’s test P = 0.165). Figure 8 shows the duration and peak MMA of each MMA type.
Median (25th - 75th percentile) of the duration was 4.0 sec (2.9 - 6.1 sec) for phasic type, 4.0 sec (2.7 -
6.7 sec) for tonic type, 7.4 sec (5.0 – 12.6 sec) for mixed type, respectively. The duration of mixed type
was significantly longer than that of the other two types (Steel-Dwass test P<0.05). Median (25th – 75th
percentile) of the peak MMA was 45.1 %MVC (25.0 – 70.3 %MVC) for phasic type, 32.8 %MVC (22.1 –
49.9 %MVC) for tonic type, 41.6 %MVC (27.6 – 67.6 %MVC) for mixed type, respectively. The peak
8
MMA of tonic type was significantly lower than that of the other two types (Steel-Dwass test P<0.05).
4. Discussion
Our main interest in this small scale study was to examine the long-term stability and reliability
of daytime EMG measurement using the portable device. In selection of participants, their ability to
participate the daytime study for four days was the most important criterion, and this study did not
consider their daytime oral habits such as grinding, clenching, and teeth contacting habit (Sato et al.,
2006).
There are some problems include artifacts and noise in long-term EMG measurement using the
portable device. The current study explored the stability and reliability of surface EMG measurement of
MMA using Actiwave for 6.1 to 9.5-hour recording periods (mean 7.4). There were no significant time
dependent effects on the value of the baseline MMA and the MMA during MVC (p>0.05), as seen by the
regression slopes (0.96 for baseline MMA, and 0.92 for MMA during MVC). The MMAs during rest
(baseline) and during MVC were consistent at least 6 hours and the slopes of regression line were close to
unity. These results indicate that there were no statistically significant time-dependent effects on the
measurement of MMA using Actiwave during daytime.
The data from one day in all of 20 measurement days was excluded from analysis of
nonfunctional MMA because of data loss due to big noise contamination. The most significant noise
9
sources in surface EMG include electromagnetic source and motion artifact. The unwanted signals were
observed in some parts of the analysis period and had amplitudes that were larger than the EMG signal.
Since changes in the skin-electrode impedance can produce large amplitude artifacts (Rosell et al., 1995),
the noise signals may be attributed to the poor skin-electrode interface because of subject movements. We
think this level of data loss is acceptable and not excessive when the portable device is used under
daytime free-living situation.
Gallo et al. (1998) studied about masseter muscle EMG activity pattern during intentional
functional activities (during rest, chewing, swallowing, laughing, and speaking) and parafunctional
activities (during grinding and clenching). In that study, they concluded that the functional and
parafunctional activities were recognized correctly with EMG analysis. On the other hand, Kato et al.
(2006) studied orofacial activities during the 30-minute silent reading in 16 healthy subjects and reported
that functional and parafunctional orofacial activities that occur in the natural living environment could be
specifically distinguished by EMG recording with audio video recording. Miyamoto et al. (1996) studied
MMAs during the whole day in 30 healthy young adult with a portable device and found that most of the
strong MMAs appeared only during eating and the frequency of occurrence of MMA increased during
daytime without eating from that during sleep. Accordingly, in our research, we excluded EMG activity
during eating and napping periods from analysis on MMAs, according to subject’s self-reported data and
observation of EMG data in order to more exactly detect nonfunctional MMA events not associated with
10
functional behaviors during daytime wakefulness. The paper-and-pencil self-report diaries could be
inaccurate because of recall biases, hence the detected MMA events may contain the some data during
functional activities.
Many criteria have been reported to detect sleep bruxism from EMG data (Okura et al., 1999;
Lavigne et al., 1996; Ikeda et al., 1996). But so far, no study has reported about algorithm with numerical
standard for detection of daytime bruxism (Piquero et al., 2000). We detected and classified daytime
nonfunctional MMA event with Okura’s and Lavigne’s criteria that were originally applied for the
definition of sleep bruxism (Okura et al., 1999; Lavigne et al., 1996). Since Okura’s criteria uses low
threshold level of EMG elevation of 5% MVC, onset of MMA events can be accurately detected. The
MMA levels during swallowing and speech are much lower than those during teeth grinding and
clenching (Gallo et al., 1998). Accordingly, to select MMA event with peak MMA greater than 10%MVC
was supposedly effective to reject swallowing and speech period. By using the MMA detection and
classification criteria that were the same as those for sleep bruxism , it may be possible to directory
compare MMA events during both sleep and daytime.
We detected 38.1 (range, 24.5 – 59.1) nonfuncional MMA events per hour during daytime among
all subjects. Nonfunctional MMAs not relating to chewing behavior were observed in all five participants.
In the previous studies (Miyamoto et al., 1996; Kato et al., 2006), the masseter EMG bursts were
observed at 15.5 to 30.3 events per hour during daytime without eating. Therefore, our results may be
11
reasonable and not excessive. Furthermore, tonic type MMA event (13.6 event/hour, 37.0 %) was more
frequently observed than the other two types (9.3 event/hour, 24.6 % for phasic type; 10.6 event/hour,
28.5% for mixed type) (Table 3). Since about 90% of sleep bruxism events are classified as phasic or
mixed type (Kato et al., 2003; Lavigne et al., 2008), daytime bruxism seems to have a different kinematic
property from that of sleep bruxism. Lavigne et al. (2008) reported that most of daytime bruxism is teeth
clenching. The results of this study agreed with their reports. However, phasic type events that correspond
with teeth grinding was also found in 24.6 % of the total MMA event. There were the significant
differences among the three MMA types with respect to the duration and peak MMA, and the frequency
of occurrence of each MMA type did not show the significant difference. The visual and occurrence
pattern of MMA was different among subjects (Fig. 5, Table 3). Consequently, we suspected that
parafunctional habit may be associated with the occurrence patterns of MMA during daytime.
In summary, the result of this study indicated that Actiwave can be used to measure MMA
events during daytime with high stability and reliability. Further studies with a large sample size are
necessary to better understand if MMA patterns during daytime reflects individual disposition of daytime
orofacial nonfunctional activities.
12
Acknowledgements
This study was supported by grants from the Ministry of Education, Culture, Sports, Science and
Technology of Japan (No. 25861848).
13
References
De Leeuw R, Klasser GD eds. Glossary. In Orofacial pain: Guidelines for Assessment, Diagnosis and
Management. 5th edition. Illinois (IL): American Academy of Orofacial Pain. Quintessence
Publishing, 2013, 254.
Endo H, Kanemura K, Tanabe N, Takebe J. Clenching occurring during the day is influenced by
psychological factors. J Prosthodont Res 2011;55:159-164.
Fujisawa M, Kanemura K, Tanabe N, Gohdo Y, Watanabe A, Iizuka T, Sato M, Ishibashi K.
Determination of daytime clenching events in subjects with and without self-reported clenching.
J Oral Rehabil 2013;40:731-736.
Gallo LM, Guerra PO, Palla S. Automatic on-line onechannel recognition of masseter activity. J Dent Res
1998;77:1539-1546.
Ikeda T, Nishigawa K, Kondo K, Takeuchi H, Clark GT. Criteria for the detection of sleep-associated
bruxism in humans. J Orofac Pain 1996;10:270-282.
Kato T, Yamaguchi T, Okura K, Abe S, Lavigne GJ, Sleep less and bite more: Sleep disorders associated
with occlusal loads during sleep. J Proth Res 2003;57:69-81.
Kato T, Akiyama S, Kato Y, Yamashita S, Masuda Y, Morimoto T. The occurrence of spontaneous
functional and nonfunctional orofacial activities in subjects without pain under laboratory
conditions: a descriptive study. J Orofac Pain 2006;20:317-324.
14
Kato T, Thie NM, Huynh N, Miyawaki S, Lavigne GJ. Topical review: sleep bruxism and the role of
peripheral sensory influences. J Orofac Pain 2003;17:191-213.
Kato T, Thie NMR, Montplaisir JY, Lavigne GJ. Bruxism and orofacial movements during sleep. Dent
Clin North Am 2001;45:657-684.
Lavigne GJ, Khoury S, Abe S, Yamaguchi T, Raphael K. Bruxism physiology and pathology: an overview
for clinicians. J Oral Rehabil 2008;35:476–494.
Lavigne GJ, Manzini C, Huynh NT. Sleep bruxism. In: Kryger MH, Roth T, Dement WC editors.
Principles and Practice of Sleep Medicine. 5the ed. Philadelphia: Elsevier, 2005:946-959.
Lavigne GJ, Rompré PH, Montplaisir JY. Sleep bruxism: validity of clinical research diagnostic criteria in
a controlled polysomnographic study. J Dent Res 1996;75:546-552.
Manfredini D, Winocur E, Guarda-Nardini L, Lobbezoo F. Self-reported bruxism and temporomandibular
disorders: findings from two specialised centres. J Oral Rehabil 2012;39:319-325.
Miyamoto K, Yamada K, Ishizuka Y, Morimoto N, Tanne K. Masseter muscle activity during the whole
day in young adult. Am J Orthod Dentfacial Orthop 1996;110:394-398.
Nishigawa K, Bando E, Nakano M. Quantitative study of bite force during sleep associated bruxism. J
Oral Rehabil 2001;28:485-491.
Okura K, Nishigawa K, Bando E, Nakano M, Ikeda T, Suzuki A. The relationship between jaw movement
and masseter muscle EMG during sleep associated bruxism. Dent Jpn 1999;35:53-56.
15
Piquero K, Sakurai K. A clinical diagnosis of diurnal (non-sleep) bruxism in denture wearers. J Oral
Rehabil 2000;27;473-482.
Rompré PH, Daigle-Landry D, Guitard F, Montplaisir JY, Lavigne GJ. Identification of a sleep bruxism
subgroup with a higher risk of pain. J Dent Res 2007;6:837-842.
Rosell J, Cohen KP, Webster JG. Reduction of motion artifacts using a two-frequency impedance
plethysmograph and adaptive filtering. IEEE Trans Biomed Eng. 1995;42(10):1044-8.
Rugh JD, Harlan J. Nocturnal bruxism and temporomandibular disorders．Adv Neurol 1988;49:329-341.
Sato F, Kino K, Sugisaki M, Haketa T, Amemori Y, Ishikawa T, Shibuya T, Amagasa T, Shibuya T, Tanabe
H, Yoda T, Sakamoto I, Omura K, Miyaoka H. Teeth contacting habit as a contributing factor to
chronic pain in patients with temporomandibular disorders. J Med Dent Sci 2006;53:103-109.
Shetty S, Pitti V, Babu CLS, Kumar GPS, Deepthi BC. Bruxism: A Literature Review. J Indian
Prosthodont Soc 2010;10:141-148.
Tsiggos N, Tortopidis D, Hatzikyriakos A, Menexes G. Association between self-reported bruxism
activity and occurrence of dental attrition, abfraction, and occlusal pits on natural teeth. J
Prosthet Dent 2008;100:41-46.
Watanabe A, Kanemura K, Tanabe N, Fujisawa M. Effect of electromyogram biofeedback on daytime
clenching behavior in subjects with masticatory muscle pain. J Prosthodont Res 2011;55:75-81.
16
Figure and Table Legends
Fig. 1
Experimental set-up to record surface EMG activity of the masseter muscle. This portable device
(Actiwave CamNtech) performs continuous recording of EMG activity for up to 12 hours with 512 Hz
sampling rate and 9-bit resolution. Disposable self-adhesive pregeled surface electrode (Ag/AgCl) was
applied over the thickest portion of the masseter muscle belly at the habitual chewing side in the unipolar
configuration. The device can simply be taped to the ipsilateral shoulder. Reference electrode was placed
on the center of the forehead.
Fig. 2
Calculation of the baseline MMA. The RMS EMG data (µV) every 1 hour were sorted in ascending order
of amplitude value. The average of RMS EMG values of the first 600×512 data points for every 1-hour
recording period was calculated as a baseline of MMA (during rest).
Fig. 3
Calculation of the MMA during MVC. Each 15 sec RMS EMG data (µV) set including maximum
voluntary clenching was selected respectively at the BP and EP of EMG recording. The selected data
17
were sorted and arranged in ascending order of amplitude value. The average of RMS EMG values of
the first 512 data points and of the last 512 data points were calculated as the MMA during rest (baseline
MMA) and maximum clenching, respectively. MMA during maximum voluntary contraction (MVC) was
obtained by subtracting the baseline MMA from that during maximum clenching at the BP and EP
respectively.
Fig. 4
Nonfunctional MMA during daytime detection and classification flowchart
Fig. 5
Examples of EMG data through one day recording period.
Fig. 6
The linear relationship between the baseline MMAs for first 1-hour period and those for the other 1-hour
periods
Fig. 7
The linear relationship between the MMA during MVC at the BP and EP
18
Fig. 8
Box chart of the duration and peak MMA of each MMA type. Box-whisker charts represent boxes for
medians with the first and third quartiles and whiskers for the most extreme values within 1.5 × the
interquartile range from the first and third quartiles, respectively. The duration of mixed type was
significantly longer than that of the other two types (Steel-Dwass test P<0.05). The peak MMA of tonic
type was significantly lower than that of the other two types (Steel-Dwass test P<0.05).
Table 1.
The baseline MMA obtained hourly for each subject from each measurement day. The recording periods
not exceeding 6 hours (surrounded with the bold line) were used for statistical analysis. No significant
time effect on the baseline of MMA was seen for each subject (Friedman test P>0.05).
Table 2
The MMA during MVC at the BP and EP calculated for each subject from each measurement day. There
were no significant time dependent effects on the value of MMA during MVC (Wilcoxon singed rank test
P>0.05).
19
Table 3
The frequency of occurrence of each MMA event type.
There was no significant difference in the number of occurrence among three MMA event types
(Friedman’s test
P=0.165).
20
Figure1
Figure2
Figure3
Figure4
Figure5
Figure6
Figure7
Figure8
Author Bio Photo Dr Omoto
Author Bio Photo Dr Shigemoto
Author Bio Photo Dr Suzuki
Author Bio Photo Dr Nakamura
Author Bio Photo Dr Okura
Author Bio Photo Dr Nishigawa
Author Bio Photo Dr Goto
Author Bio Photo Dr Omar
Author Bio Photo Dr Matsuka
Katsuhiro Omoto completed his D.D.S. at the University of Tokushima, School of Dentistry, Japan in 2012. He worked as Dental Resident at the Post-graduate Education Center, Tokushima University Hospital from 2012 to 2013. Now he is a Ph.D. student in The University of Tokushima Graduate School. Dr. Omoto’s research is focused on oral function, basic mechanisms of neural transmission of tooth sensation and fixed prosthodontics. Shuji Shigemoto received his Ph.D. in Dentistry from The University of Tokushima, Japan in 1996. He worked at Zurich University, Switzerland as a visiting fellow from 1999 to 2001. He is currently an Assistant Professor in the Department of Stomatognathic Function and Occlusal Reconstruction at the University of Tokushima, and a Clinical Professor in the Department of Fixed Prosthodontics at Turumi University. His research interests focus on stomatognathic function; in particular, development of jaw tracking device and kinematic dental bite registration method, and jaw movement status during sleep bruxism, and EMG activity during daytime clenching. Yoshitaka Suzuki graduated from the University of Tokushima, School of Dentistry, Japan in 2008. After a dental resident in Tokushima University Hospital in a year, He entered the University of Tokushima Graduate School and was award the Ph.D. in 2012. Now he works at Department of Stomatognathic Function and Occlusal Reconstraction, the University of Tokushima Graduate School as an assistant professor. He studies about bruxism, jaw movement, occlusion, sports dentistry and swallowing. Mayumi Nakamura graduated from the University of Tokushima, School of Dentistry, Japan in 2009. She worked as Dental Resident at the Post-graduate Education Center, Tokushima University Hospital from 2010 to 2011. Now she is a Ph.D. student in The University of Tokushima Graduate School and works as a staff in Fukui Dental Clinic. Dr. Nakamura’s studies about jaw function and prosthodontics. Kazuo Okura completed his DDS and PhD at the University of Tokushima, Japan. He worked at University de Montreal, Canada as a visiting professor from 2003 to 2005. He is currently an associate professor at the University of Tokushima, Japan. Dr. Okura’s research is focused on stomatognathic function, sleep bruxism and fixed prothodontics. Nami Goto graduated from the Fukuoka Dental College, Japan in 2010.
She worked as Dental Resident at the Post-graduate Education Center, Tokushima University Hospital from 2010 to 2011. And she is currently a Dental Staff in General Dentistry, Tokushima University Hospital. Dr. Takata’s research interests include oral function, oral implantology and fixed prosthodontics. Omar Marianito Maningo Rodis earned his Doctor of Dental Medicine degree from Southwestern University, Philippines; Ph.D. degree from Okayama University, Japan; and training in Clinical Dental Research Methods from the University of Washington, USA. He worked as an Assistant Professor in the Department of Behavioral Pediatric Dentistry of Okayama University and is currently an Assistant Professor in the Institute of Health Biosciences of the University of Tokushima, Japan. His research interests include public health, pediatric dentistry, geriatric dentistry, curriculum development, international exchange and collaboration. Yoshizo Matsuka completed his D.D.S. and Ph.D. at Okayama University in Japan. He finished hospital residency program and was an Assistant Professor at School of Dentistry, University of California Los Angeles. He was also Associate Professor at Oral Rehabilitation and Regenerative Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences. He is currently a Professor and chair at Department of Stomatognathic Function and Occlusal Reconstruction, Institute of Health Biosciences, Tokushima University. Dr. Matsuka’s research is focused on oral function, neurotransmitter release from sensory ganglia and clinical epidemiology of prosthodontics.
Fig. 5
subject
sub1
sub2
sub3
sub4
sub5
Table. 1
measurement day D1 D2 D3 D4 D1 D2 D3 D4 D1 D2 D3 D4 D1 D2 D3 D4 D1 D2 D3 D4
baseline MMA (µV) Friedman test 0-1 h
1-2 h
2-3 h
3-4 h
4-5 h
5-6 h
6-7 h
7-8 h
8-9 h
2.41 3.06 2.85 2.66 2.09 2.47 2.10 2.26 1.84 2.53 1.76 1.87 2.59 2.23 2.61 2.79 1.69 1.47 1.60 1.36
2.66 2.71 2.61 2.96 2.33 2.69 1.76 1.72 1.83 2.05 1.69 1.69 2.66 2.81 2.54 2.91 1.60 1.46 1.48 1.33
2.76 2.82 3.22 2.83 1.71 2.59 1.73 2.15 1.77 2.33 1.73 1.64 2.80 2.15 2.22 3.07 1.64 1.46 1.51 1.33
3.07 3.05 2.94 2.97 2.17 2.87 2.03 1.94 1.69 1.96 2.07 1.77 2.27 1.80 2.59 2.35 1.71 1.54 1.72 1.37
2.65 2.89 3.17 2.50 1.78 2.55 2.23 1.61 2.33 1.68 1.44 2.20 1.59 1.52 2.22 2.61 1.72 1.53 1.35 1.44
2.79 2.79 3.26 2.80 1.74 2.66 2.37 1.54 1.83 1.47 1.62 1.71 2.86 2.11 2.49 2.19 1.60 1.51 1.36 1.38
2.54 2.96 3.17 2.83 1.87 2.58 2.32
2.81 2.82 3.26 2.48 1.86
2.98 2.83 4.29 3.04 2.83
2.10 2.13 2.12
1.85 1.69 1.52 1.48 1.57
p = 0.35 df = 5
p = 0.70 df = 5
p = 0.34 df = 5
p = 0.11 df = 5
p = 0.10 df = 5
subject
sub1
sub2
sub3
sub4
sub5
Table. 2
MMA during MVC measurment Wilcoxon test day BP vs EP at BP (µV) at EP (µV) D1 D2 D3 D4 D1 D2 D3 D4 D1 D2 D3 D4 D1 D2 D3 D4 D1 D2 D3 D4
112.36 115.44 123.92 102.72 91.69 85.66 67.96 64.06 69.43 44.86 58.85 49.55 71.37 64.88 70.90 110.98 72.43 28.50 82.24 28.68
109.88 114.39 117.00 84.76 82.00 85.36 77.93 64.10 64.89 46.33 60.11 52.94 68.73 58.08 66.72 101.75 59.99 27.95 87.37 22.39
p = 0.125
p = 1.000
p = 0.875
p = 0.125
p = 0.375
recording day
analysis period (hour)
phasic
tonic
mixed
other
total / per hour
Sub1
4
34.0
192
255
200
186
833 / 24.5
Sub2
3
17.8
106
357
243
94
800 / 44.8
Sub3
4
27.6
690
315
458
167
1630 / 59.1
Sub4
4
23.5
170
436
293
104
1003 / 42.7
Sub5
4
26.5
51
396
183
27
657 / 24.8
total / per hour
19
129.4
1209 / 9.3
1759 / 13.6
1377 / 10.6
578 / 4.5
4923 / 38.1
-
24.6
37.0
28.0
11.7
100.0
subject
frequency (%)
Table.3
-
number of MMA event