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A mechanomyographic frequency-based fatigue threshold test
Journal of Neuroscience Methods 187 (2010) 1–7
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A mechanomyographic frequency-based fatigue threshold test C. Russell Hendrix a,∗ , Terry J. Housh a , Jorge M. Zuniga a , Clayton L. Camic a , Michelle Mielke b , Glen O. Johnson a , Richard J. Schmidt a a Department of Nutrition and Health Sciences, Human Performance Laboratory, 110 Ruth Leverton Hall, University of Nebraska-Lincoln, Lincoln, NE 68583-0806, United States b Department of Sport Sciences, University of the Pacific, Stockton, CA 95211, United States
a r t i c l e
i n f o
Article history: Received 13 October 2009 Received in revised form 18 November 2009 Accepted 23 November 2009 Keywords: Mechanomyographic mean power frequency (MMG MPF) MMG MPF fatigue threshold (MMG MPFFT ) Isometric leg extension
a b s t r a c t Theoretically, the mechanomyographic (MMG) mean power frequency fatigue threshold (MMG MPFFT ) describes the maximal isometric torque that can be maintained for an extended period of time with no change in the global firing rate of the unfused, activated motor units. Purpose: The purposes of this study were twofold: (1) to determine if the mathematical model for estimating the electromyographic (EMG) MPFFT from the frequency of the EMG signal was applicable to the frequency domain of the MMG signal to estimate a new fatigue threshold called the MMG MPFFT ; and (2) to compare the mean torque levels derived from the MMG MPFFT test for the vastus lateralis (VL), vastus medialis (VM), and rectus femoris (RF) muscles during isometric leg extension muscle actions. Methods: Nine adults (4 men and 5 women; mean ± S.D. age = 21.6 ± 1.2 years) performed three or four continuous, fatiguing, isometric muscle actions of the leg extensors at 30, 45, 60, and 75% of maximum voluntary isometric contraction (MVIC) to exhaustion. Surface MMG signals were recorded from the VL, VM, and RF muscles during each fatiguing isometric muscle action. The MMG MPFFT was defined as the y-intercept of the isometric torque versus slope coefficient (MMG MPF versus time) plot. Results: There were no significant differences among the MMG MPFFT values for the VL, VM, and RF (34.8 ± 23.4, 32.1 ± 16.1, and 31.6 ± 15.2 N m, respectively) muscles. Conclusion: The MMG MPFFT test may provide a non-invasive method to examine the effects of various interventions on the global motor unit firing rate during isometric muscle actions. © 2009 Elsevier B.V. All rights reserved.
1. Introduction Theoretically, the electromyographic fatigue threshold (EMGFT ) (Hendrix et al., 2009a), critical torque (CT) (Hendrix et al., 2009a,b,c), and EMG mean power frequency fatigue threshold (EMG MPFFT ) tests (Hendrix et al., 2009b) demarcate fatiguing from non-fatiguing isometric torque levels. These tests, however, often result in thresholds that are characterized by different torque levels (Hendrix et al., 2009a,c). Specifically, a recent study by Hendrix et al. (2009c) reported that, for the forearm flexors, the CT was less than the EMGFT (mean ± S.D. = 6.6 ± 3.2 and 10.9 ± 4.7 N m, respectively). In addition, it has been reported that the CT for the leg extensors was less than the EMGFT from the rectus femoris muscle (25.9 ± 12.1 and 41.1 ± 20.7 N m, respectively) (Hendrix et al., 2009a). A recent study by Hendrix et al. (2009b), however, reported that there was no significant (p > 0.05) difference between the CT (25.2 ± 11.4 N m) for the leg extensors and EMG MPFFT (29.8 ± 22.9 N m) from the vastus lateralis muscle. The mean dif-
∗ Corresponding author. Tel.: +1 402 472 2690; fax: +1 402 472 0522. E-mail address: [email protected] (C.R. Hendrix). 0165-0270/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.jneumeth.2009.11.019
ferences in torque levels found in previous studies (Hendrix et al., 2009a,c) may be attributed to the methodology used to estimate the various fatigue thresholds. That is, the EMGFT and EMG MPFFT tests measure neuromuscular activity, while the CT test describes the torque versus duration relationship. Therefore, the torque level associated with the onset of fatigue is dependent upon which specific fatigue threshold is identified. The selection of the most appropriate fatigue threshold test to use depends on factors such as the muscles involved, the purpose of testing, and the availability of testing equipment. The EMGFT test (Hendrix et al., 2009a,c) for isometric muscle actions is an adaptation of the original EMGFT test for cycle ergometry (deVries et al., 1982) and involves the determination of the rate of rise in EMG amplitude as a function of time (slope coefficient) at three or four fatiguing torque levels (Fig. 1A). The amplitude of the EMG signal reflects muscular activation and is determined by both the number of active motor units and their respective firing rates (Basmajian and DeLuca, 1985). The torque levels are then plotted as a function of their corresponding slope coefficients for the EMG amplitude versus time relationships and the EMGFT is defined as the y-intercept (Fig. 1B) (deVries et al., 1982). Therefore, the EMGFT test for isometric muscle actions (Hendrix et al., 2009a,c) estimates
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C.R. Hendrix et al. / Journal of Neuroscience Methods 187 (2010) 1–7
Fig. 2. Model for estimating the EMG MPFFT from isometric data. (A) Each subject’s EMG MPF data were plotted as a function of time (s) for three or four percentages of MVIC (approximately 30, 45, 60, and 75%MVIC). (B) The EMG MPF slope coefficients from (A) were plotted versus torque for each of the three or four percentages of MVIC and the EMG MPFFT was estimated as the y-intercept (slope coefficient of zero) value (20.7 N m).
Fig. 1. Model for estimating the EMGFT from isometric data. (A) The EMG amplitude (Vrms) data were plotted as a function of time (s) for the four continuous, fatiguing isometric workbouts at 30, 45, 60, and 75%MVIC. (B) The slope coefficients from (A) were plotted versus torque for each of the four percentages of MVIC and the EMGFT was estimated as the y-intercept (slope coefficient of zero) value (23.1 N m).
the highest level of isometric torque that can be sustained without neuromuscular evidence of fatigue (i.e., a slope coefficient for the EMG amplitude versus time relationship of zero) (Matsumoto et al., 1991; Moritani et al., 1993). That is, theoretically, the EMGFT test estimates the highest non-fatiguing torque level at which motor unit activation does not increase over time. Recently, the mathematical model used for the determination of EMGFT (deVries et al., 1982) was applied to the frequency domain of the EMG signal to estimate a new fatigue threshold called the EMG MPFFT (Hendrix et al., 2009b). The estimation of EMG MPFFT , however, involves the determination of the rate of decrease in EMG MPF as a function of time (negative slope coefficient) for each of three or four continuous, fatiguing isometric muscle actions (Fig. 2A) (Hendrix et al., 2009b). The shift in the EMG power spectrum toward lower frequencies during fatiguing isometric muscle actions, which results in a reduction in EMG MPF over time, has been attributed to a decrease in the action potential conduction velocity and changes in the shape of the muscle fiber action potential waveform (Basmajian and DeLuca, 1985; Kranz et al., 1983). The torque levels are then plotted as a function of the negative slope coefficients for the EMG MPF versus time relationships and the EMG MPFFT is defined as the y-intercept (Fig. 2B) (Hendrix et al., 2009b). Theoretically, the EMG MPFFT represents the highest torque output that can be maintained for an extended period of time with no change in the conduction velocity and shape of the action potential waveforms. Thus, the EMGFT and EMG MPFFT tests
for isometric muscle actions utilize different domains of the EMG signal and provide fatigue thresholds that are based on different aspects of neuromuscular fatigue. That is, the EMGFT test is based on the rate of rise in EMG amplitude, while the EMG MPFFT test utilizes the rate of decrease in EMG MPF. Mechanomyography (MMG) records and quantifies the lowfrequency lateral oscillations of the unfused, active muscle fibers (Barry and Cole, 1990; Orizio, 1993; Stokes, 1993). Gordon and Holbourn (1948) indicated that these oscillations reflect the “mechanical counterpart” of the motor unit action potential activity measured by EMG. The MMG signal is a non-linear summation of the activity from individual motor units and it has been suggested that the time and frequency domains of the MMG signal may provide information regarding motor unit recruitment and firing rate during isometric muscle actions (Akataki et al., 2001; Orizio, 1993; Orizio et al., 2003). Beck et al. (2007) suggested that the compression of the MMG power density spectrum and associated decrease in MMG MPF are a result of fatigue-induced decreases in global firing rate of the unfused, activated motor units. Previous studies (Itoh et al., 2004; Madeleine et al., 2002; Mamaghani et al., 2002; Weir et al., 2000) have reported that the center frequency (MPF and median frequency) of the MMG signal decreases as a function of time during sustained isometric muscle actions. Furthermore, the negative slope coefficient for the MMG MPF versus time relationship is inversely proportional to the torque level. Thus, the mathematical model that has previously been used to determine EMG MPFFT (Hendrix et al., 2009b) may be applicable to MMG MPF responses. Therefore, the purposes of this study were twofold: (1) to determine if the mathematical model for estimating the EMG MPFFT from the frequency of the EMG signal was applicable to the frequency domain of the MMG signal to estimate a new fatigue threshold called the mechanomyographic mean power frequency fatigue threshold (MMG MPFFT ); and (2) to compare the
C.R. Hendrix et al. / Journal of Neuroscience Methods 187 (2010) 1–7
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mean torque levels derived from the MMG MPFFT test for the vastus lateralis (VL), vastus medialis (VM), and rectus femoris (RF) muscles during isometric leg extension muscle actions. Previous studies have reported differences in fiber type (Edgerton et al., 1975; Johnson et al., 1973) or fatigue threshold values (Housh et al., 1995) among the superficial muscles of the quadriceps femoris. On the basis of previous studies, we hypothesized that: (1) the mathematical model used for the determination of EMG MPFFT (Hendrix et al., 2009b) would be applicable to MMG MPF responses to estimate the MMG MPFFT (Itoh et al., 2004; Madeleine et al., 2002; Mamaghani et al., 2002; Weir et al., 2000); and (2) there would be differences among the mean torque levels associated with the MMG MPFFT for the VL, VM, and RF muscles (Edgerton et al., 1975; Housh et al., 1995; Johnson et al., 1973). 2. Methods 2.1. Subjects Nine adults (4 men and 5 women, mean ± S.D. Age = 21.6 ± 1.2 year; Height = 169.3 ± 15.3 cm; Weight = 67.9 ± 19.2 kg) volunteered for this study. None of the subjects were competitive athletes, but they participated regularly in walking (n = 2), bicycling (n = 3), jogging or running (n = 9), weight training (n = 5), and/or various sports (n = 1: basketball, soccer, or boxing). All procedures were approved by the University Institutional Review Board for human subjects, and each subject completed a health history questionnaire and gave their written informed consent to participate prior to testing. The subjects visited the laboratory on five occasions. The first visit served as an orientation to familiarize the subject with the testing protocols and equipment used during the study. During the second visit, maximum voluntary isometric contraction (MVIC) was determined and one continuous, fatiguing muscle action was performed at a randomly ordered percentage of MVIC (approximately 30, 45, 60, or 75%MVIC). The subsequent three visits were to perform the continuous, fatiguing muscle actions at the remaining percentages of MVIC. These %MVIC values were selected to be consistent with those used in previous studies that examined endurance times during isometric muscle actions (Carlson and McCraw, 1971; Heyward, 1975). Each laboratory visit was separated by 24 h and was performed at the same time of day. 2.2. Determination of MVIC All isometric leg extension testing, performed by the dominant leg (based on kicking preference), began with a warm-up of five, 6 s submaximal isometric muscle actions. The subjects were instructed to provide an effort corresponding to approximately 50% of their MVIC. Following the warm-up and 2 min rest, two MVIC trials were performed. Each MVIC trial consisted of a 6 s maximal isometric muscle action at a joint angle of 120◦ between the thigh and the leg. Peak torque was recorded by a calibrated Cybex II isokinetic dynamometer. The subject rested 2 min between MVIC trials. The highest measured peak torque level was used as the individual’s MVIC. Following the second MVIC trial, each subject rested 5 min, then performed the first continuous, isometric muscle action at a randomly determined percentage of MVIC. 2.3. MMG measurements The MMG signal was recorded during each of the fatiguing, isometric muscle actions (visits 2–5). Three separate accelerometers (Entran EGAS FT 10, bandwidth 0–200 Hz, dimensions: 1.0 × 1.0 × 0.5 cm, mass 1.0 g, sensitivity 10 mV/g) were placed over the superficial muscles of the quadriceps femoris of the dominant leg (Fig. 3). With the subject in the standing position and
Fig. 3. Example of MMG accelerometer placement.
the dominant leg fully extended, a reference line was drawn from the anterior superior iliac spine (ASIS) to the superior lateral border of the patella to identify the VL accelerometer-placement site. The accelerometer was located over the lateral portion of the VL muscle, approximately 33% of the distance between the superior, lateral border of the patella to the ASIS, and was placed 4–5 cm lateral to the reference line to place it over the belly of the VL. The accelerometer placement for the VM was approximately 20% of the distance between the joint space anterior to the medial ligament of the knee joint and the ASIS of the pelvis, starting at the knee joint. The accelerometer placement for the RF was approximately 50% of the distance between the patella and the ASIS of the pelvis along the longitudinal axis of the thigh (Rana, 2006). Six, 5-s epochs (1–5, 11–15, 21–25, 31–35, 41–45, and 51–55 s) of the MMG signal were collected during each minute of each muscle action. An inline amplifier (gain: 200×) was used to amplify the MMG signal before digitization. The raw MMG signals were digitized at 1000 Hz and stored in a personal computer (Macintosh 7100/80 AV Power PC, Apple Computer, Inc., Cupertino, CA) for subsequent analyses. All signal processing was performed using custom programs written with LabVIEW programming software (version 7.1, National Instruments, Austin, TX). The MMG signals were digitally bandpass filtered (fourth-order Butterworth) at 5–100 Hz. The filtered signal was then processed with a Hamming window and the discrete Fourier transform (DFT) algorithm. The mean power frequency (MPF, Hz) was selected to represent the MMG power density spectrum based on the recommendations of Diemont et al. (1988) and was calculated as described by Kwatny et al. (1970). 2.4. Determination of MMG MPFFT The determination of MMG MPFFT was based on an adaptation of the mathematical model of deVries et al. (1982) and involved the measurement of MMG MPF for each continuous, fatiguing, isometric muscle action at approximately 30, 45, 60 and 75%MVIC during visits 2–5. The rate of decrease in MMG MPF as a function of time (negative slope coefficient) was calculated for each of the continuous isometric muscle actions for each subject (Fig. 4A). Based on the recommendation of deVries et al. (1982) for the EMGFT test, only those workbouts that resulted in r2 values ≥0.60 for the MMG MPF versus time relationship were included in the analyses (Table 1). The torque levels were then plotted as a function of the slope coefficients for the MMG MPF versus time relationships (Fig. 4B). The MMG MPFFT was defined as the y-intercept of the torque level versus slope coefficient (MMG MPF versus time) plot. For nine of the twenty-seven estimations of MMG MPFFT , three workbouts were used (subject 3 for the VL; subjects 1, 3, 4, 7 and 8 for the VM; sub-
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Table 1 Data for the vastus lateralis (VL), vastus medialis (VM), and rectus femoris (RF) muscles for each subject from the mechanomyographic mean power frequency fatigue threshold (MMG MPFFT ) tests. Subject
Gender
Torque (N m)
VL MMG MPF slope (Hz s−1 )
VM r2 (MMG MPF vs. time)
r2
(Torque vs. MMG MPF slope)
MMG MPFFT (N m)
F
29.0 37.3 45.6 53.9
−0.029 −0.061 −0.074 −0.094
0.89 0.89 0.97 0.95
0.97
16.5
2
F
23.8 29.7 35.6 41.6
−0.016 −0.030 −0.056 −0.074
0.71 0.90 0.93 0.97
0.99
19.7
3
M
45.9 57.4 68.8 80.3
−0.079 −0.104 – −0.153
0.69 0.88 – 0.86
0.99
9.1
4
F
34.2 51.2 68.3 79.7
−0.021 −0.026 −0.094 −0.123
0.73 0.84 0.93 0.90
0.91
5
F
24.7 30.9 37.1 43.3
−0.042 −0.050 −0.086 −0.099
0.73 0.68 0.88 0.83
6
M
82.6 106.2 141.5 176.9
−0.048 −0.059 −0.150 −0.212
7
M
70.8 106.2 141.5 165.1
8
M
9
F
Mean S.D.
MMG MPF slope (Hz s−1 )
(MMG MPF vs. time)
r2
(Torque vs. MMG MPF slope)
MMG MPFFT (N m)
MMG MPFFT (%MVIC)
MMG MPF slope (Hz s−1 )
r2 (MMG MPF vs. time)
r2 (Torque vs. MMG MPF slope)
MMG MPFFT (N m)
MMG MPFFT (%MVIC)
−0.041 −0.066 – −0.133
0.65 0.68 – 0.85
0.99
18.9
22.8
−0.016 −0.042 −0.042 −0.068
0.77 0.82 0.83 0.80
0.91
21.3
25.7
−0.021 −0.035 −0.033 −0.058
0.79 0.93 0.95 0.94
0.83
16.0
26.9
−0.012 −0.026 −0.038 –
0.86 0.92 0.79 –
0.99
18.1
30.5
7.9
−0.059 −0.081 – −0.156
0.76 0.91 – 0.89
0.99
27.6
24.1
−0.067 −0.096 −0.127 –
0.78 0.84 0.97 –
0.99
20.4
17.8
33.7
29.6
−0.017 −0.047 −0.076 –
0.69 0.82 0.97 –
0.99
24.6
21.6
−0.013 −0.015 −0.053 −0.063
0.70 0.86 0.97 0.84
0.89
31.8
27.9
0.94
14.6
23.6
−0.053 −0.043 −0.103 −0.138
0.64 0.85 0.91 0.94
0.84
20.2
32.7
−0.027 −0.057 −0.059 −0.076
0.67 0.91 0.95 0.88
0.90
13.8
22.3
0.76 0.88 0.78 0.95
0.97
65.6
27.8
−0.027 −0.037 −0.052 −0.108
0.82 0.85 0.86 0.86
0.89
66.5
28.2
−0.025 −0.022 −0.035 −0.054
0.78 0.95 0.98 0.91
0.86
36.9
15.6
−0.031 −0.082 −0.123 −0.128
0.84 0.81 0.85 0.93
0.95
39.4
16.7
– −0.065 −0.099 −0.115
– 0.98 0.96 0.97
0.99
29.3
12.4
−0.021 −0.054 −0.069 −0.086
0.67 0.91 0.86 0.95
0.98
35.4
15.0
83.0 124.5 166.0 193.6
−0.030 −0.108 −0.120 −0.239
0.77 0.94 0.78 0.97
0.87
76.8
27.8
−0.046 −0.095 −0.141 –
0.77 0.94 0.91 –
0.99
42.8
15.5
−0.023 −0.087 – −0.163
0.71 0.92 – 0.98
0.99
61.5
22.2
41.5 62.2 83.0 103.7
−0.023 −0.127 −0.187 −0.321
0.62 0.76 0.60 0.84
0.98
37.5
27.1
−0.046 −0.079 −0.184 −0.370
0.77 0.88 0.98 0.93
0.91
42.9
31.0
−0.022 −0.056 −0.111 −0.256
0.75 0.86 0.95 0.98
0.90
45.2
32.7
34.8 23.4
23.7 7.8
32.1 16.1
21.9 6.8
31.6 15.2
21.6 6.4
19.9
33 2
Note: Three workbouts were used for nine of the twenty-seven estimations of MMG MPFFT (VL: subject 3; VM: subjects 1, 3, 4, 7 and 8; RF: subjects 2, 3 and 8). Only those workbouts that resulted in r2 values ≥0.60 for the MMG MPF versus time relationship were included in the analyses. The MMG MPF slope values represented by – had r2 values that were <0.60 and, therefore, were not used in the estimation of MMG MPFFT .
C.R. Hendrix et al. / Journal of Neuroscience Methods 187 (2010) 1–7
1
MMG MPFFT (%MVIC)
RF r2
C.R. Hendrix et al. / Journal of Neuroscience Methods 187 (2010) 1–7
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Table 2 Correlations among the torque levels (N m) for the mechanomyographic mean power frequency fatigue thresholds (MMG MPFFT ) of the vastus lateralis (VL), vastus medialis (VM), and rectus femoris (RF) muscles.
MMG MPFFT VL MMG MPFFT RF MMG MPFFT VM *
MMG MPFFT VL
MMG MPFFT RF
MMG MPFFT VM
1.00 0.88* 0.79*
1.00 0.64
1.00
Significant at p < 0.05.
These MMG MPFFT values represented 23.7 ± 7.8, 21.9 ± 6.8 and 21.6 ± 6.4% of MVIC, respectively. The results indicated that there were no significant mean differences among the absolute or %MVIC MMG MPFFT values for the three superficial muscles of the quadriceps femoris. In addition, Pearson’s correlation coefficients indicated significant relationships between MMG MPFFT values for the VL and VM, VL and RF, but not VM and RF (Table 2). 4. Discussion
Fig. 4. Method for estimating MMG MPFFT from data for subject 2. (A) Each subject’s MMG MPF data were plotted as a function of time (s) for three or four percentages of MVIC (approximately 30, 45, 60, and 75%MVIC). (B) The MMG MPF slope coefficients from (A) were plotted versus torque for each of the three or four percentages of MVIC and the MMG MPFFT was estimated as the y-intercept (slope coefficient of zero) value (19.7 N m).
jects 2, 3 and 8 for the RF; Table 1), because the MMG MPF slope values for those nine workbouts had r2 values that were <0.60 and, therefore, were not used in the estimation of MMG MPFFT . 2.5. Statistical analyses Linear regression was used to estimate the MMG MPFFT values for the VL, VM, and RF muscles (Table 1). Two separate one-way repeated measures ANOVAs were used to compare the mean absolute and %MVIC values for MMG MPFFT for the VL, VM, and RF muscles. In addition, Pearson correlations were used to determine the relationships among the absolute MMG MPFFT values for each of the muscles of the quadriceps femoris (VL, VM, and RF). An alpha of p ≤ 0.05 was considered statistically significant. The data were analyzed using the Statistical Package for the Social Sciences software (v. 17.0, SPSS Inc., Chicago, IL). 3. Results Table 1 includes the data for each subject for the MMG MPFFT tests. The r2 of all three muscles (VL, VM and RF) for the MMG MPF versus time, and torque versus MMG MPF slope coefficient relationships for the determination of MMG MPFFT ranged from 0.60 to 0.99 and 0.83 to 0.99, respectively. Furthermore, all of the torque versus MMG MPF slope coefficient relationships in the present study were statistically significant (r2 ≥ 0.81 and ≥0.98 for four and three workbouts, respectively; Table 1). The mean (±S.D.) value for MVIC was 146.6 ± 82.0. The mean (±S.D.) values for MMG MPFFT for the VL, VM and RF were 34.8 ± 23.4, 32.1 ± 16.1, and 31.6 ± 15.2 N m, respectively.
One purpose of this study was to determine if the mathematical model that has been used to estimate the EMGFT from amplitude data (deVries et al., 1982) and the EMG MPFFT from the frequency domain (Hendrix et al., 2009b) could be applied to the frequency domain of the MMG signal to derive a new fatigue threshold called the MMG MPFFT . In the present study, the MMG MPF values decreased linearly (negative slope) with time (Fig. 4A) during the continuous, fatiguing, isometric muscle actions (r2 = 0.60–0.99), and there were negative, linear relationships (r2 = 0.83–0.99) for the torque versus slope coefficient plots (Fig. 4B). These ranges of r2 values were consistent with those previously reported (Hendrix et al., 2009a,c) for the EMGFT test during isometric muscle actions (r2 = 0.01–0.99 and 0.62–0.99, respectively), and cycle ergometry (r2 = 0.01–0.99 and 0.03–0.99, respectively) (deVries et al., 1982; Housh et al., 1995; Pavlat et al., 1995). In addition, these ranges of r2 values were consistent with those previously reported (Hendrix et al., 2009b) for the EMG MPFFT test during isometric muscle actions (r2 = 0.60–0.94 and 0.88–0.99, respectively). These findings indicated that the mathematical model used for the determination of EMGFT from amplitude data (deVries et al., 1982) and EMG MPFFT from frequency data (Hendrix et al., 2009b) could be applied to the frequency domain of the MMG signal to estimate the MMG MPFFT . Thus, theoretically, the MMG MPFFT represents the highest level of isometric torque that can be sustained for an extended period of time without mechanomyographic evidence of fatigue (i.e., slope coefficient of zero for the MMG MPF versus time relationship). Previous studies (Esposito et al., 1998; Itoh et al., 2004; Madeleine et al., 2002; Mamaghani et al., 2002; Orizio, 1992; Orizio et al., 1992; Wee and Ashley, 1989; Weir et al., 2000) have examined the patterns of responses for MMG MPF or median frequency during sustained isometric muscle actions. It has been suggested that changes in the shape of the power density spectrum of the MMG signal provide qualitative information regarding the global firing rate of the activated motor units (Barry et al., 1985; Beck et al., 2007; Cescon et al., 2004; Orizio, 1992; Orizio et al., 1996). That is, a change (increase or decrease) in global firing rate is associated with a concomitant change in MMG MPF (Beck et al., 2007). Thus, the decreases in MMG MPF that were used to estimate the MMG MPFFT in the present study may be attributable to fatigue-induced decreases in motor unit firing rates (Esposito et al., 1998; Marsden et al., 1983; Orizio, 1992) and/or de-recruitment of fast-twitch muscle fibers (Beck et al., 2007; Kouzaki et al., 1999; Peters and Fuglevand, 1999). Specifically, during fatiguing activities, muscle spindles and Golgi tendon organs provide proprioceptive feedback to the central nervous system which decreases motor unit firing
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rates to allow for optimal fusion of motor unit twitches (Marsden et al., 1983). This concept has been termed “muscular wisdom” and is a motor control strategy that “minimizes fatigue during prolonged effort” (Marsden et al., 1983, p. 169). There is conflicting evidence, however, concerning the application of the muscular wisdom hypothesis to fatiguing, submaximal isometric muscle actions (Enoka and Stuart, 1992; Esposito et al., 1998; Garland and Gossen, 2002; Kuchinad et al., 2004). For example, Garland and Gossen (2002) concluded that the muscular wisdom hypothesis may not apply to prolonged, submaximal isometric contractions. Kuchinad et al. (2004), however, reported that decreases in motor unit firing rate paralleled changes in contractile properties of the muscle during fatiguing isometric muscle actions at 42–66%MVIC. In addition, it has been suggested (Peters and Fuglevand, 1999) that some motor units may stop firing (i.e., be de-recruited) prior to the end of the task during sustained MVICs of the finger extensors. Therefore, it is possible that muscular wisdom and/or motor unit de-recruitment reduced the global motor unit firing rate and resulted in the fatigueinduced decreases in MMG MPF that served as the foundation for estimating the MMG MPFFT in the present study. Based on previous studies (Edgerton et al., 1975; Hendrix et al., 2009a; Housh et al., 1995; Johnson et al., 1973), we hypothesized that, in the present study, there would be differences among the MMG MPFFT values for the VL, VM, and RF muscles. The results of the present study, however, indicated that there were no mean differences in the torque (mean ± S.D. for VL = 34.8 ± 23.4, VM = 32.1 ± 16.1, and RF = 31.6 ± 15.2 N m) or %MVIC (VL = 23.7 ± 7.8, VM = 21.9 ± 6.8 and RF = 21.6 ± 6.4%MVIC) for the MMG MPFFT values (Table 1). These findings were consistent with previous studies (Hendrix et al., 2009a,b; Monod and Scherrer, 1965) which have reported fatigue threshold values for CT and EMG MPFFT during isometric muscle actions of the leg extensors that ranged from 15 to 21%MVIC. Furthermore, these findings were consistent with previous studies (Hendrix et al., 2009a; Housh et al., 1996) that reported no significant mean differences (p > 0.05) among the fatigue threshold values (EMGFT and PWCFT ) for the three superficial muscles of the quadriceps femoris group. These findings, however, were not consistent with those of Housh et al. (1995) who reported that during cycle ergometry, the mean EMGFT for the RF (220 ± 30 W) was 11.3% less (p < 0.05) than that of the VL (248 ± 31 W). It is possible that the difference between the findings of Housh et al. (1995) for cycle ergometry and those of the current study of continuous, isometric muscle actions were due to mode-specific differences in muscle blood flow. Future studies should compare the effects of continuous isometric, intermittent isometric, and dynamic muscle actions on differences in the MMG MPFFT of the VL, VM, and RF muscles. Previous studies (Edwards et al., 1975, 1972) found that the onset of a reduction in muscle blood flow due to an increase in intramuscular pressure and occlusion of the vascular beds occurred at forces greater than 20%MVIC for isometric muscle actions of the leg extensors. Thus, the current findings (Table 1), in conjunction with those of Edwards et al. (1975, 1972), suggest that a forcerelated restriction of muscle blood flow would not limit the times to exhaustion during continuous isometric leg extension muscle actions at the MMG MPFFT for the VL, VM, and RF muscles. Future studies are needed to validate the MMG MPFFT test by determining the times to exhaustion values during continuous isometric muscle actions of the leg extensors at torque levels equal to, as well as greater than and less than, those associated with the MMG MPFFT . Theoretically, the MMG MPFFT represents the highest torque output that can be maintained for an extended period of time with no change in the global firing rate of the unfused, activated motor units and, therefore, no change in MMG MPF. At torque levels greater than the MMG MPFFT , however, the global firing rate of unfused, activated motor units should decrease, resulting in a
concomitant decrease in MMG MPF. Previous studies (Itoh et al., 2004; Orizio et al., 1992) have reported that MMG MPF remained unchanged during continuous isometric muscle actions of the forearm flexors at 20%MVIC. Thus, the current findings (MMG MPFFT ranged from 21.6 to 23.7%MVIC), in conjunction with those of Itoh et al. (2004) and Orizio et al. (1992), suggest that continuous isometric muscle actions at the torque level corresponding to the MMG MPFFT would not affect the global firing rate of the unfused, activated motor units. In summary, the mathematical model used for the determination of EMG MPFFT (Hendrix et al., 2009b) can be applied to the frequency domain of the MMG signal to estimate the MMG MPFFT . The MMG MPFFT , theoretically, represents the highest torque that can be maintained for an extended period of time with no change in the global firing rate of the unfused, activated motor units, and therefore, no change in MMG MPF. The results of the present study indicated that there were no differences in the isometric torque levels associated with the MMG MPFFT for the three superficial muscles of the quadriceps (VL, VM, and RF). In addition, the mean MMG MPFFT values (23.7 ± 7.8, 21.9 ± 6.8 and 21.6 ± 6.4%MVIC, respectively) occurred at torque levels that are typically not affected by muscular occlusion, and therefore, are not likely to be limited by restricted blood flow to the working muscles. Therefore, the MMG MPFFT test may provide a non-invasive method to examine the effects of interventions such as caffeine, strength training, stretching, and fatigue on the global motor unit firing rate during isometric muscle actions. References Akataki K, Mita K, Watakabe M, Itoh K. Mechanomyogram and force relationship during voluntary isometric ramp contractions of the biceps brachii muscle. Eur J Appl Physiol 2001;84:19–25. Barry DT, Cole NM. Muscle sounds are emitted at the resonant frequencies of skeletal muscle. IEEE Trans Biomed Eng 1990;37:525–31. Barry DT, Geiringer SR, Ball RD. Acoustic myography: a noninvasive monitor of motor unit fatigue. Muscle Nerve 1985;8:189–94. Basmajian JV, DeLuca CJ. Muscles alive: their functions revealed by electromyography. 5th ed. Baltimore: Williams & Wilkins; 1985. Beck TW, Housh TJ, Johnson GO, Cramer JT, Weir JP, Coburn JW, et al. Does the frequency content of the surface mechanomyographic signal reflect motor unit firing rates? A brief review. J Electromyogr Kinesiol 2007;17:1–13. Carlson BR, McCraw LW. Isometric strength and relative isometric endurance. Res Q 1971;42:244–50. Cescon C, Gazzoni M, Gobbo M, Orizio C, Farina D. Non-invasive assessment of single motor unit mechanomyographic response and twitch force by spike-triggered averaging. Med Biol Eng Comput 2004;42:496–501. deVries HA, Moritani T, Nagata A, Magnussen K. The relation between critical power and neuromuscular fatigue as estimated from electromyographic data. Ergonomics 1982;25:783–91. Diemont B, Figini MM, Orizio C, Perini R, Veicsteinas A. Spectral analysis of muscular sound at low and high contraction level. Int J Biomed Comput 1988;23:161–75. Edgerton VR, Smith JL, Simpson DR. Muscle fibre type populations of human leg muscles. Histochem J 1975;7:259–66. Edwards RH, Hill DK, Jones DA. Heat production and chemical changes during isometric contractions of the human quadriceps muscle. J Physiol 1975;251:303–15. Edwards RH, Hill DK, McDonnell M. Myothermal and intramuscular pressure measurements during isometric contractions of the human quadriceps muscle. J Physiol 1972;224:58P–9P. Enoka RM, Stuart DG. Neurobiology of muscle fatigue. J Appl Physiol 1992;72:1631–48. Esposito F, Orizio C, Veicsteinas A. Electromyogram and mechanomyogram changes in fresh and fatigued muscle during sustained contraction in men. Eur J Appl Physiol Occup Physiol 1998;78:494–501. Garland SJ, Gossen ER. The muscular wisdom hypothesis in human muscle fatigue. Exerc Sport Sci Rev 2002;30:45–9. Gordon G, Holbourn AH. The sounds from single motor units in a contracting muscle. J Physiol 1948;107:456–64. Hendrix CR, Housh TJ, Johnson GO, Mielke M, Camic CL, Zuniga JM, et al. Comparison of critical force to EMG fatigue thresholds during isometric leg extension. Med Sci Sports Exerc 2009a;41:956–65. Hendrix CR, Housh TJ, Johnson GO, Mielke M, Camic CL, Zuniga JM, et al. A new EMG frequency-based fatigue threshold test. J Neurosci Methods 2009b;181:45–51. Hendrix CR, Housh TJ, Johnson GO, Weir JP, Beck TW, Malek MH, et al. A comparison of critical force and electromyographic fatigue threshold for isometric muscle actions of the forearm flexors. Eur J Appl Physiol 2009c;105:333–42.
C.R. Hendrix et al. / Journal of Neuroscience Methods 187 (2010) 1–7 Heyward VH. Influence of static strength and intramuscular occlusion on submaximal static muscle endurance. Res Q 1975;46:393–402. Housh TJ, deVries HA, Johnson GO, Evans SA, Housh DJ, Stout JR, et al. Neuromuscular fatigue thresholds of the vastus lateralis, vastus medialis and rectus femoris muscles. Electromyogr Clin Neurophysiol 1996;36:247–55. Housh TJ, deVries HA, Johnson GO, Housh DJ, Evans SA, Stout JR, et al. Electromyographic fatigue thresholds of the superficial muscles of the quadriceps femoris. Eur J Appl Physiol Occup Physiol 1995;71:131–6. Itoh Y, Akataki K, Mita K, Watakabe M, Itoh K. Time-frequency analysis of mechanomyogram during sustained contractions with muscle fatigue. Syst Comput Japan 2004;35:26–36. Johnson MA, Polgar J, Weightman D, Appleton D. Data on the distribution of fibre types in thirty-six human muscles. An autopsy study. J Neurol Sci 1973;18:111–29. Kouzaki M, Shinohara M, Fukunaga T. Non-uniform mechanical activity of quadriceps muscle during fatigue by repeated maximal voluntary contraction in humans. Eur J Appl Physiol Occup Physiol 1999;80:9–15. Kranz H, Williams AM, Cassell J, Caddy DJ, Silberstein RB. Factors determining the frequency content of the electromyogram. J Appl Physiol 1983;55:392–9. Kuchinad RA, Ivanova TD, Garland SJ. Modulation of motor unit discharge rate and H-reflex amplitude during submaximal fatigue of the human soleus muscle. Exp Brain Res 2004;158:345–55. Kwatny E, Thomas DH, Kwatny HG. An application of signal processing techniques to the study of myoelectric signals. IEEE Trans Biomed Eng 1970;17:303– 13. Madeleine P, Jorgensen LV, Sogaard K, Arendt-Nielsen L, Sjogaard G. Development of muscle fatigue as assessed by electromyography and mechanomyography during continuous and intermittent low-force contractions: effects of the feedback mode. Eur J Appl Physiol 2002;87:28–37. Mamaghani NK, Shimomura Y, Iwanaga K, Katsuura T. Mechanomyogram and electromyogram responses of upper limb during sustained isometric fatigue with varying shoulder and elbow postures. J Physiol Anthropol Appl Human Sci 2002;21:29–43. Marsden C, Meadows J, Merton P. “Muscular wisdom” that minimizes fatigue during prolonged effort in man: peak rates of motoneuron discharge and slowing of
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discharge during fatigue. In: Desmedt J, editor. Motor control mechanisms in health and disease. New York: Raven Press; 1983. p. 169–211. Matsumoto T, Ito K, Moritani T. The relationship between anaerobic threshold and electromyographic fatigue threshold in college women. Eur J Appl Physiol Occup Physiol 1991;63:1–5. Monod H, Scherrer J. The work capacity of a synergic muscular group. Ergonomics 1965;8:329–38. Moritani T, Takaishi T, Matsumoto T. Determination of maximal power output at neuromuscular fatigue threshold. J Appl Physiol 1993;74:1729–34. Orizio C. Muscle sound: bases for the introduction of a mechanomyographic signal in muscle studies. Crit Rev Biomed Eng 1993;21:201–43. Orizio C. Soundmyogram and EMG cross-spectrum during exhausting isometric contractions in humans. J Electromyogr Kinesiol 1992;2:141–9. Orizio C, Gobbo M, Diemont B, Esposito F, Veicsteinas A. The surface mechanomyogram as a tool to describe the influence of fatigue on biceps brachii motor unit activation strategy. Historical basis and novel evidence. Eur J Appl Physiol 2003;90:326–36. Orizio C, Liberati D, Locatelli C, De Grandis D, Veicsteinas A. Surface mechanomyogram reflects muscle fibres twitches summation. J Biomech 1996;29:475–81. Orizio C, Perini R, Diemont B, Veicsteinas A. Muscle sound and electromyogram spectrum analysis during exhausting contractions in man. Eur J Appl Physiol Occup Physiol 1992;65:1–7. Pavlat DJ, Housh TJ, Johnson GO, Eckerson JM. Electromyographic responses at the neuromuscular fatigue threshold. J Sports Med Phys Fitness 1995;35:31–7. Peters EJ, Fuglevand AJ. Cessation of human motor unit discharge during sustained maximal voluntary contraction. Neurosci Lett 1999;274:66–70. Rana SR. Effect of the Wingate test on mechanomyography and electromyography. J Strength Cond Res 2006;20:292–7. Stokes M. Acoustic myography: applications and considerations in measuring muscle performance. Isokinet Exerc Sci 1993;3:4–15. Wee AS, Ashley RA. Vibrations and sounds produced during sustained voluntary muscle contraction. Electromyogr Clin Neurophysiol 1989;29:333–7. Weir JP, Ayers KM, Lacefield JF, Walsh KL. Mechanomyographic and electromyographic responses during fatigue in humans: influence of muscle length. Eur J Appl Physiol 2000;81:352–9.
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Journal of Neuroscience Methods journal homepage: www.elsevier.com/locate/jneumeth
A mechanomyographic frequency-based fatigue threshold test C. Russell Hendrix a,∗ , Terry J. Housh a , Jorge M. Zuniga a , Clayton L. Camic a , Michelle Mielke b , Glen O. Johnson a , Richard J. Schmidt a a Department of Nutrition and Health Sciences, Human Performance Laboratory, 110 Ruth Leverton Hall, University of Nebraska-Lincoln, Lincoln, NE 68583-0806, United States b Department of Sport Sciences, University of the Pacific, Stockton, CA 95211, United States
a r t i c l e
i n f o
Article history: Received 13 October 2009 Received in revised form 18 November 2009 Accepted 23 November 2009 Keywords: Mechanomyographic mean power frequency (MMG MPF) MMG MPF fatigue threshold (MMG MPFFT ) Isometric leg extension
a b s t r a c t Theoretically, the mechanomyographic (MMG) mean power frequency fatigue threshold (MMG MPFFT ) describes the maximal isometric torque that can be maintained for an extended period of time with no change in the global firing rate of the unfused, activated motor units. Purpose: The purposes of this study were twofold: (1) to determine if the mathematical model for estimating the electromyographic (EMG) MPFFT from the frequency of the EMG signal was applicable to the frequency domain of the MMG signal to estimate a new fatigue threshold called the MMG MPFFT ; and (2) to compare the mean torque levels derived from the MMG MPFFT test for the vastus lateralis (VL), vastus medialis (VM), and rectus femoris (RF) muscles during isometric leg extension muscle actions. Methods: Nine adults (4 men and 5 women; mean ± S.D. age = 21.6 ± 1.2 years) performed three or four continuous, fatiguing, isometric muscle actions of the leg extensors at 30, 45, 60, and 75% of maximum voluntary isometric contraction (MVIC) to exhaustion. Surface MMG signals were recorded from the VL, VM, and RF muscles during each fatiguing isometric muscle action. The MMG MPFFT was defined as the y-intercept of the isometric torque versus slope coefficient (MMG MPF versus time) plot. Results: There were no significant differences among the MMG MPFFT values for the VL, VM, and RF (34.8 ± 23.4, 32.1 ± 16.1, and 31.6 ± 15.2 N m, respectively) muscles. Conclusion: The MMG MPFFT test may provide a non-invasive method to examine the effects of various interventions on the global motor unit firing rate during isometric muscle actions. © 2009 Elsevier B.V. All rights reserved.
1. Introduction Theoretically, the electromyographic fatigue threshold (EMGFT ) (Hendrix et al., 2009a), critical torque (CT) (Hendrix et al., 2009a,b,c), and EMG mean power frequency fatigue threshold (EMG MPFFT ) tests (Hendrix et al., 2009b) demarcate fatiguing from non-fatiguing isometric torque levels. These tests, however, often result in thresholds that are characterized by different torque levels (Hendrix et al., 2009a,c). Specifically, a recent study by Hendrix et al. (2009c) reported that, for the forearm flexors, the CT was less than the EMGFT (mean ± S.D. = 6.6 ± 3.2 and 10.9 ± 4.7 N m, respectively). In addition, it has been reported that the CT for the leg extensors was less than the EMGFT from the rectus femoris muscle (25.9 ± 12.1 and 41.1 ± 20.7 N m, respectively) (Hendrix et al., 2009a). A recent study by Hendrix et al. (2009b), however, reported that there was no significant (p > 0.05) difference between the CT (25.2 ± 11.4 N m) for the leg extensors and EMG MPFFT (29.8 ± 22.9 N m) from the vastus lateralis muscle. The mean dif-
∗ Corresponding author. Tel.: +1 402 472 2690; fax: +1 402 472 0522. E-mail address: [email protected] (C.R. Hendrix). 0165-0270/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.jneumeth.2009.11.019
ferences in torque levels found in previous studies (Hendrix et al., 2009a,c) may be attributed to the methodology used to estimate the various fatigue thresholds. That is, the EMGFT and EMG MPFFT tests measure neuromuscular activity, while the CT test describes the torque versus duration relationship. Therefore, the torque level associated with the onset of fatigue is dependent upon which specific fatigue threshold is identified. The selection of the most appropriate fatigue threshold test to use depends on factors such as the muscles involved, the purpose of testing, and the availability of testing equipment. The EMGFT test (Hendrix et al., 2009a,c) for isometric muscle actions is an adaptation of the original EMGFT test for cycle ergometry (deVries et al., 1982) and involves the determination of the rate of rise in EMG amplitude as a function of time (slope coefficient) at three or four fatiguing torque levels (Fig. 1A). The amplitude of the EMG signal reflects muscular activation and is determined by both the number of active motor units and their respective firing rates (Basmajian and DeLuca, 1985). The torque levels are then plotted as a function of their corresponding slope coefficients for the EMG amplitude versus time relationships and the EMGFT is defined as the y-intercept (Fig. 1B) (deVries et al., 1982). Therefore, the EMGFT test for isometric muscle actions (Hendrix et al., 2009a,c) estimates
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C.R. Hendrix et al. / Journal of Neuroscience Methods 187 (2010) 1–7
Fig. 2. Model for estimating the EMG MPFFT from isometric data. (A) Each subject’s EMG MPF data were plotted as a function of time (s) for three or four percentages of MVIC (approximately 30, 45, 60, and 75%MVIC). (B) The EMG MPF slope coefficients from (A) were plotted versus torque for each of the three or four percentages of MVIC and the EMG MPFFT was estimated as the y-intercept (slope coefficient of zero) value (20.7 N m).
Fig. 1. Model for estimating the EMGFT from isometric data. (A) The EMG amplitude (Vrms) data were plotted as a function of time (s) for the four continuous, fatiguing isometric workbouts at 30, 45, 60, and 75%MVIC. (B) The slope coefficients from (A) were plotted versus torque for each of the four percentages of MVIC and the EMGFT was estimated as the y-intercept (slope coefficient of zero) value (23.1 N m).
the highest level of isometric torque that can be sustained without neuromuscular evidence of fatigue (i.e., a slope coefficient for the EMG amplitude versus time relationship of zero) (Matsumoto et al., 1991; Moritani et al., 1993). That is, theoretically, the EMGFT test estimates the highest non-fatiguing torque level at which motor unit activation does not increase over time. Recently, the mathematical model used for the determination of EMGFT (deVries et al., 1982) was applied to the frequency domain of the EMG signal to estimate a new fatigue threshold called the EMG MPFFT (Hendrix et al., 2009b). The estimation of EMG MPFFT , however, involves the determination of the rate of decrease in EMG MPF as a function of time (negative slope coefficient) for each of three or four continuous, fatiguing isometric muscle actions (Fig. 2A) (Hendrix et al., 2009b). The shift in the EMG power spectrum toward lower frequencies during fatiguing isometric muscle actions, which results in a reduction in EMG MPF over time, has been attributed to a decrease in the action potential conduction velocity and changes in the shape of the muscle fiber action potential waveform (Basmajian and DeLuca, 1985; Kranz et al., 1983). The torque levels are then plotted as a function of the negative slope coefficients for the EMG MPF versus time relationships and the EMG MPFFT is defined as the y-intercept (Fig. 2B) (Hendrix et al., 2009b). Theoretically, the EMG MPFFT represents the highest torque output that can be maintained for an extended period of time with no change in the conduction velocity and shape of the action potential waveforms. Thus, the EMGFT and EMG MPFFT tests
for isometric muscle actions utilize different domains of the EMG signal and provide fatigue thresholds that are based on different aspects of neuromuscular fatigue. That is, the EMGFT test is based on the rate of rise in EMG amplitude, while the EMG MPFFT test utilizes the rate of decrease in EMG MPF. Mechanomyography (MMG) records and quantifies the lowfrequency lateral oscillations of the unfused, active muscle fibers (Barry and Cole, 1990; Orizio, 1993; Stokes, 1993). Gordon and Holbourn (1948) indicated that these oscillations reflect the “mechanical counterpart” of the motor unit action potential activity measured by EMG. The MMG signal is a non-linear summation of the activity from individual motor units and it has been suggested that the time and frequency domains of the MMG signal may provide information regarding motor unit recruitment and firing rate during isometric muscle actions (Akataki et al., 2001; Orizio, 1993; Orizio et al., 2003). Beck et al. (2007) suggested that the compression of the MMG power density spectrum and associated decrease in MMG MPF are a result of fatigue-induced decreases in global firing rate of the unfused, activated motor units. Previous studies (Itoh et al., 2004; Madeleine et al., 2002; Mamaghani et al., 2002; Weir et al., 2000) have reported that the center frequency (MPF and median frequency) of the MMG signal decreases as a function of time during sustained isometric muscle actions. Furthermore, the negative slope coefficient for the MMG MPF versus time relationship is inversely proportional to the torque level. Thus, the mathematical model that has previously been used to determine EMG MPFFT (Hendrix et al., 2009b) may be applicable to MMG MPF responses. Therefore, the purposes of this study were twofold: (1) to determine if the mathematical model for estimating the EMG MPFFT from the frequency of the EMG signal was applicable to the frequency domain of the MMG signal to estimate a new fatigue threshold called the mechanomyographic mean power frequency fatigue threshold (MMG MPFFT ); and (2) to compare the
C.R. Hendrix et al. / Journal of Neuroscience Methods 187 (2010) 1–7
3
mean torque levels derived from the MMG MPFFT test for the vastus lateralis (VL), vastus medialis (VM), and rectus femoris (RF) muscles during isometric leg extension muscle actions. Previous studies have reported differences in fiber type (Edgerton et al., 1975; Johnson et al., 1973) or fatigue threshold values (Housh et al., 1995) among the superficial muscles of the quadriceps femoris. On the basis of previous studies, we hypothesized that: (1) the mathematical model used for the determination of EMG MPFFT (Hendrix et al., 2009b) would be applicable to MMG MPF responses to estimate the MMG MPFFT (Itoh et al., 2004; Madeleine et al., 2002; Mamaghani et al., 2002; Weir et al., 2000); and (2) there would be differences among the mean torque levels associated with the MMG MPFFT for the VL, VM, and RF muscles (Edgerton et al., 1975; Housh et al., 1995; Johnson et al., 1973). 2. Methods 2.1. Subjects Nine adults (4 men and 5 women, mean ± S.D. Age = 21.6 ± 1.2 year; Height = 169.3 ± 15.3 cm; Weight = 67.9 ± 19.2 kg) volunteered for this study. None of the subjects were competitive athletes, but they participated regularly in walking (n = 2), bicycling (n = 3), jogging or running (n = 9), weight training (n = 5), and/or various sports (n = 1: basketball, soccer, or boxing). All procedures were approved by the University Institutional Review Board for human subjects, and each subject completed a health history questionnaire and gave their written informed consent to participate prior to testing. The subjects visited the laboratory on five occasions. The first visit served as an orientation to familiarize the subject with the testing protocols and equipment used during the study. During the second visit, maximum voluntary isometric contraction (MVIC) was determined and one continuous, fatiguing muscle action was performed at a randomly ordered percentage of MVIC (approximately 30, 45, 60, or 75%MVIC). The subsequent three visits were to perform the continuous, fatiguing muscle actions at the remaining percentages of MVIC. These %MVIC values were selected to be consistent with those used in previous studies that examined endurance times during isometric muscle actions (Carlson and McCraw, 1971; Heyward, 1975). Each laboratory visit was separated by 24 h and was performed at the same time of day. 2.2. Determination of MVIC All isometric leg extension testing, performed by the dominant leg (based on kicking preference), began with a warm-up of five, 6 s submaximal isometric muscle actions. The subjects were instructed to provide an effort corresponding to approximately 50% of their MVIC. Following the warm-up and 2 min rest, two MVIC trials were performed. Each MVIC trial consisted of a 6 s maximal isometric muscle action at a joint angle of 120◦ between the thigh and the leg. Peak torque was recorded by a calibrated Cybex II isokinetic dynamometer. The subject rested 2 min between MVIC trials. The highest measured peak torque level was used as the individual’s MVIC. Following the second MVIC trial, each subject rested 5 min, then performed the first continuous, isometric muscle action at a randomly determined percentage of MVIC. 2.3. MMG measurements The MMG signal was recorded during each of the fatiguing, isometric muscle actions (visits 2–5). Three separate accelerometers (Entran EGAS FT 10, bandwidth 0–200 Hz, dimensions: 1.0 × 1.0 × 0.5 cm, mass 1.0 g, sensitivity 10 mV/g) were placed over the superficial muscles of the quadriceps femoris of the dominant leg (Fig. 3). With the subject in the standing position and
Fig. 3. Example of MMG accelerometer placement.
the dominant leg fully extended, a reference line was drawn from the anterior superior iliac spine (ASIS) to the superior lateral border of the patella to identify the VL accelerometer-placement site. The accelerometer was located over the lateral portion of the VL muscle, approximately 33% of the distance between the superior, lateral border of the patella to the ASIS, and was placed 4–5 cm lateral to the reference line to place it over the belly of the VL. The accelerometer placement for the VM was approximately 20% of the distance between the joint space anterior to the medial ligament of the knee joint and the ASIS of the pelvis, starting at the knee joint. The accelerometer placement for the RF was approximately 50% of the distance between the patella and the ASIS of the pelvis along the longitudinal axis of the thigh (Rana, 2006). Six, 5-s epochs (1–5, 11–15, 21–25, 31–35, 41–45, and 51–55 s) of the MMG signal were collected during each minute of each muscle action. An inline amplifier (gain: 200×) was used to amplify the MMG signal before digitization. The raw MMG signals were digitized at 1000 Hz and stored in a personal computer (Macintosh 7100/80 AV Power PC, Apple Computer, Inc., Cupertino, CA) for subsequent analyses. All signal processing was performed using custom programs written with LabVIEW programming software (version 7.1, National Instruments, Austin, TX). The MMG signals were digitally bandpass filtered (fourth-order Butterworth) at 5–100 Hz. The filtered signal was then processed with a Hamming window and the discrete Fourier transform (DFT) algorithm. The mean power frequency (MPF, Hz) was selected to represent the MMG power density spectrum based on the recommendations of Diemont et al. (1988) and was calculated as described by Kwatny et al. (1970). 2.4. Determination of MMG MPFFT The determination of MMG MPFFT was based on an adaptation of the mathematical model of deVries et al. (1982) and involved the measurement of MMG MPF for each continuous, fatiguing, isometric muscle action at approximately 30, 45, 60 and 75%MVIC during visits 2–5. The rate of decrease in MMG MPF as a function of time (negative slope coefficient) was calculated for each of the continuous isometric muscle actions for each subject (Fig. 4A). Based on the recommendation of deVries et al. (1982) for the EMGFT test, only those workbouts that resulted in r2 values ≥0.60 for the MMG MPF versus time relationship were included in the analyses (Table 1). The torque levels were then plotted as a function of the slope coefficients for the MMG MPF versus time relationships (Fig. 4B). The MMG MPFFT was defined as the y-intercept of the torque level versus slope coefficient (MMG MPF versus time) plot. For nine of the twenty-seven estimations of MMG MPFFT , three workbouts were used (subject 3 for the VL; subjects 1, 3, 4, 7 and 8 for the VM; sub-
4
Table 1 Data for the vastus lateralis (VL), vastus medialis (VM), and rectus femoris (RF) muscles for each subject from the mechanomyographic mean power frequency fatigue threshold (MMG MPFFT ) tests. Subject
Gender
Torque (N m)
VL MMG MPF slope (Hz s−1 )
VM r2 (MMG MPF vs. time)
r2
(Torque vs. MMG MPF slope)
MMG MPFFT (N m)
F
29.0 37.3 45.6 53.9
−0.029 −0.061 −0.074 −0.094
0.89 0.89 0.97 0.95
0.97
16.5
2
F
23.8 29.7 35.6 41.6
−0.016 −0.030 −0.056 −0.074
0.71 0.90 0.93 0.97
0.99
19.7
3
M
45.9 57.4 68.8 80.3
−0.079 −0.104 – −0.153
0.69 0.88 – 0.86
0.99
9.1
4
F
34.2 51.2 68.3 79.7
−0.021 −0.026 −0.094 −0.123
0.73 0.84 0.93 0.90
0.91
5
F
24.7 30.9 37.1 43.3
−0.042 −0.050 −0.086 −0.099
0.73 0.68 0.88 0.83
6
M
82.6 106.2 141.5 176.9
−0.048 −0.059 −0.150 −0.212
7
M
70.8 106.2 141.5 165.1
8
M
9
F
Mean S.D.
MMG MPF slope (Hz s−1 )
(MMG MPF vs. time)
r2
(Torque vs. MMG MPF slope)
MMG MPFFT (N m)
MMG MPFFT (%MVIC)
MMG MPF slope (Hz s−1 )
r2 (MMG MPF vs. time)
r2 (Torque vs. MMG MPF slope)
MMG MPFFT (N m)
MMG MPFFT (%MVIC)
−0.041 −0.066 – −0.133
0.65 0.68 – 0.85
0.99
18.9
22.8
−0.016 −0.042 −0.042 −0.068
0.77 0.82 0.83 0.80
0.91
21.3
25.7
−0.021 −0.035 −0.033 −0.058
0.79 0.93 0.95 0.94
0.83
16.0
26.9
−0.012 −0.026 −0.038 –
0.86 0.92 0.79 –
0.99
18.1
30.5
7.9
−0.059 −0.081 – −0.156
0.76 0.91 – 0.89
0.99
27.6
24.1
−0.067 −0.096 −0.127 –
0.78 0.84 0.97 –
0.99
20.4
17.8
33.7
29.6
−0.017 −0.047 −0.076 –
0.69 0.82 0.97 –
0.99
24.6
21.6
−0.013 −0.015 −0.053 −0.063
0.70 0.86 0.97 0.84
0.89
31.8
27.9
0.94
14.6
23.6
−0.053 −0.043 −0.103 −0.138
0.64 0.85 0.91 0.94
0.84
20.2
32.7
−0.027 −0.057 −0.059 −0.076
0.67 0.91 0.95 0.88
0.90
13.8
22.3
0.76 0.88 0.78 0.95
0.97
65.6
27.8
−0.027 −0.037 −0.052 −0.108
0.82 0.85 0.86 0.86
0.89
66.5
28.2
−0.025 −0.022 −0.035 −0.054
0.78 0.95 0.98 0.91
0.86
36.9
15.6
−0.031 −0.082 −0.123 −0.128
0.84 0.81 0.85 0.93
0.95
39.4
16.7
– −0.065 −0.099 −0.115
– 0.98 0.96 0.97
0.99
29.3
12.4
−0.021 −0.054 −0.069 −0.086
0.67 0.91 0.86 0.95
0.98
35.4
15.0
83.0 124.5 166.0 193.6
−0.030 −0.108 −0.120 −0.239
0.77 0.94 0.78 0.97
0.87
76.8
27.8
−0.046 −0.095 −0.141 –
0.77 0.94 0.91 –
0.99
42.8
15.5
−0.023 −0.087 – −0.163
0.71 0.92 – 0.98
0.99
61.5
22.2
41.5 62.2 83.0 103.7
−0.023 −0.127 −0.187 −0.321
0.62 0.76 0.60 0.84
0.98
37.5
27.1
−0.046 −0.079 −0.184 −0.370
0.77 0.88 0.98 0.93
0.91
42.9
31.0
−0.022 −0.056 −0.111 −0.256
0.75 0.86 0.95 0.98
0.90
45.2
32.7
34.8 23.4
23.7 7.8
32.1 16.1
21.9 6.8
31.6 15.2
21.6 6.4
19.9
33 2
Note: Three workbouts were used for nine of the twenty-seven estimations of MMG MPFFT (VL: subject 3; VM: subjects 1, 3, 4, 7 and 8; RF: subjects 2, 3 and 8). Only those workbouts that resulted in r2 values ≥0.60 for the MMG MPF versus time relationship were included in the analyses. The MMG MPF slope values represented by – had r2 values that were <0.60 and, therefore, were not used in the estimation of MMG MPFFT .
C.R. Hendrix et al. / Journal of Neuroscience Methods 187 (2010) 1–7
1
MMG MPFFT (%MVIC)
RF r2
C.R. Hendrix et al. / Journal of Neuroscience Methods 187 (2010) 1–7
5
Table 2 Correlations among the torque levels (N m) for the mechanomyographic mean power frequency fatigue thresholds (MMG MPFFT ) of the vastus lateralis (VL), vastus medialis (VM), and rectus femoris (RF) muscles.
MMG MPFFT VL MMG MPFFT RF MMG MPFFT VM *
MMG MPFFT VL
MMG MPFFT RF
MMG MPFFT VM
1.00 0.88* 0.79*
1.00 0.64
1.00
Significant at p < 0.05.
These MMG MPFFT values represented 23.7 ± 7.8, 21.9 ± 6.8 and 21.6 ± 6.4% of MVIC, respectively. The results indicated that there were no significant mean differences among the absolute or %MVIC MMG MPFFT values for the three superficial muscles of the quadriceps femoris. In addition, Pearson’s correlation coefficients indicated significant relationships between MMG MPFFT values for the VL and VM, VL and RF, but not VM and RF (Table 2). 4. Discussion
Fig. 4. Method for estimating MMG MPFFT from data for subject 2. (A) Each subject’s MMG MPF data were plotted as a function of time (s) for three or four percentages of MVIC (approximately 30, 45, 60, and 75%MVIC). (B) The MMG MPF slope coefficients from (A) were plotted versus torque for each of the three or four percentages of MVIC and the MMG MPFFT was estimated as the y-intercept (slope coefficient of zero) value (19.7 N m).
jects 2, 3 and 8 for the RF; Table 1), because the MMG MPF slope values for those nine workbouts had r2 values that were <0.60 and, therefore, were not used in the estimation of MMG MPFFT . 2.5. Statistical analyses Linear regression was used to estimate the MMG MPFFT values for the VL, VM, and RF muscles (Table 1). Two separate one-way repeated measures ANOVAs were used to compare the mean absolute and %MVIC values for MMG MPFFT for the VL, VM, and RF muscles. In addition, Pearson correlations were used to determine the relationships among the absolute MMG MPFFT values for each of the muscles of the quadriceps femoris (VL, VM, and RF). An alpha of p ≤ 0.05 was considered statistically significant. The data were analyzed using the Statistical Package for the Social Sciences software (v. 17.0, SPSS Inc., Chicago, IL). 3. Results Table 1 includes the data for each subject for the MMG MPFFT tests. The r2 of all three muscles (VL, VM and RF) for the MMG MPF versus time, and torque versus MMG MPF slope coefficient relationships for the determination of MMG MPFFT ranged from 0.60 to 0.99 and 0.83 to 0.99, respectively. Furthermore, all of the torque versus MMG MPF slope coefficient relationships in the present study were statistically significant (r2 ≥ 0.81 and ≥0.98 for four and three workbouts, respectively; Table 1). The mean (±S.D.) value for MVIC was 146.6 ± 82.0. The mean (±S.D.) values for MMG MPFFT for the VL, VM and RF were 34.8 ± 23.4, 32.1 ± 16.1, and 31.6 ± 15.2 N m, respectively.
One purpose of this study was to determine if the mathematical model that has been used to estimate the EMGFT from amplitude data (deVries et al., 1982) and the EMG MPFFT from the frequency domain (Hendrix et al., 2009b) could be applied to the frequency domain of the MMG signal to derive a new fatigue threshold called the MMG MPFFT . In the present study, the MMG MPF values decreased linearly (negative slope) with time (Fig. 4A) during the continuous, fatiguing, isometric muscle actions (r2 = 0.60–0.99), and there were negative, linear relationships (r2 = 0.83–0.99) for the torque versus slope coefficient plots (Fig. 4B). These ranges of r2 values were consistent with those previously reported (Hendrix et al., 2009a,c) for the EMGFT test during isometric muscle actions (r2 = 0.01–0.99 and 0.62–0.99, respectively), and cycle ergometry (r2 = 0.01–0.99 and 0.03–0.99, respectively) (deVries et al., 1982; Housh et al., 1995; Pavlat et al., 1995). In addition, these ranges of r2 values were consistent with those previously reported (Hendrix et al., 2009b) for the EMG MPFFT test during isometric muscle actions (r2 = 0.60–0.94 and 0.88–0.99, respectively). These findings indicated that the mathematical model used for the determination of EMGFT from amplitude data (deVries et al., 1982) and EMG MPFFT from frequency data (Hendrix et al., 2009b) could be applied to the frequency domain of the MMG signal to estimate the MMG MPFFT . Thus, theoretically, the MMG MPFFT represents the highest level of isometric torque that can be sustained for an extended period of time without mechanomyographic evidence of fatigue (i.e., slope coefficient of zero for the MMG MPF versus time relationship). Previous studies (Esposito et al., 1998; Itoh et al., 2004; Madeleine et al., 2002; Mamaghani et al., 2002; Orizio, 1992; Orizio et al., 1992; Wee and Ashley, 1989; Weir et al., 2000) have examined the patterns of responses for MMG MPF or median frequency during sustained isometric muscle actions. It has been suggested that changes in the shape of the power density spectrum of the MMG signal provide qualitative information regarding the global firing rate of the activated motor units (Barry et al., 1985; Beck et al., 2007; Cescon et al., 2004; Orizio, 1992; Orizio et al., 1996). That is, a change (increase or decrease) in global firing rate is associated with a concomitant change in MMG MPF (Beck et al., 2007). Thus, the decreases in MMG MPF that were used to estimate the MMG MPFFT in the present study may be attributable to fatigue-induced decreases in motor unit firing rates (Esposito et al., 1998; Marsden et al., 1983; Orizio, 1992) and/or de-recruitment of fast-twitch muscle fibers (Beck et al., 2007; Kouzaki et al., 1999; Peters and Fuglevand, 1999). Specifically, during fatiguing activities, muscle spindles and Golgi tendon organs provide proprioceptive feedback to the central nervous system which decreases motor unit firing
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C.R. Hendrix et al. / Journal of Neuroscience Methods 187 (2010) 1–7
rates to allow for optimal fusion of motor unit twitches (Marsden et al., 1983). This concept has been termed “muscular wisdom” and is a motor control strategy that “minimizes fatigue during prolonged effort” (Marsden et al., 1983, p. 169). There is conflicting evidence, however, concerning the application of the muscular wisdom hypothesis to fatiguing, submaximal isometric muscle actions (Enoka and Stuart, 1992; Esposito et al., 1998; Garland and Gossen, 2002; Kuchinad et al., 2004). For example, Garland and Gossen (2002) concluded that the muscular wisdom hypothesis may not apply to prolonged, submaximal isometric contractions. Kuchinad et al. (2004), however, reported that decreases in motor unit firing rate paralleled changes in contractile properties of the muscle during fatiguing isometric muscle actions at 42–66%MVIC. In addition, it has been suggested (Peters and Fuglevand, 1999) that some motor units may stop firing (i.e., be de-recruited) prior to the end of the task during sustained MVICs of the finger extensors. Therefore, it is possible that muscular wisdom and/or motor unit de-recruitment reduced the global motor unit firing rate and resulted in the fatigueinduced decreases in MMG MPF that served as the foundation for estimating the MMG MPFFT in the present study. Based on previous studies (Edgerton et al., 1975; Hendrix et al., 2009a; Housh et al., 1995; Johnson et al., 1973), we hypothesized that, in the present study, there would be differences among the MMG MPFFT values for the VL, VM, and RF muscles. The results of the present study, however, indicated that there were no mean differences in the torque (mean ± S.D. for VL = 34.8 ± 23.4, VM = 32.1 ± 16.1, and RF = 31.6 ± 15.2 N m) or %MVIC (VL = 23.7 ± 7.8, VM = 21.9 ± 6.8 and RF = 21.6 ± 6.4%MVIC) for the MMG MPFFT values (Table 1). These findings were consistent with previous studies (Hendrix et al., 2009a,b; Monod and Scherrer, 1965) which have reported fatigue threshold values for CT and EMG MPFFT during isometric muscle actions of the leg extensors that ranged from 15 to 21%MVIC. Furthermore, these findings were consistent with previous studies (Hendrix et al., 2009a; Housh et al., 1996) that reported no significant mean differences (p > 0.05) among the fatigue threshold values (EMGFT and PWCFT ) for the three superficial muscles of the quadriceps femoris group. These findings, however, were not consistent with those of Housh et al. (1995) who reported that during cycle ergometry, the mean EMGFT for the RF (220 ± 30 W) was 11.3% less (p < 0.05) than that of the VL (248 ± 31 W). It is possible that the difference between the findings of Housh et al. (1995) for cycle ergometry and those of the current study of continuous, isometric muscle actions were due to mode-specific differences in muscle blood flow. Future studies should compare the effects of continuous isometric, intermittent isometric, and dynamic muscle actions on differences in the MMG MPFFT of the VL, VM, and RF muscles. Previous studies (Edwards et al., 1975, 1972) found that the onset of a reduction in muscle blood flow due to an increase in intramuscular pressure and occlusion of the vascular beds occurred at forces greater than 20%MVIC for isometric muscle actions of the leg extensors. Thus, the current findings (Table 1), in conjunction with those of Edwards et al. (1975, 1972), suggest that a forcerelated restriction of muscle blood flow would not limit the times to exhaustion during continuous isometric leg extension muscle actions at the MMG MPFFT for the VL, VM, and RF muscles. Future studies are needed to validate the MMG MPFFT test by determining the times to exhaustion values during continuous isometric muscle actions of the leg extensors at torque levels equal to, as well as greater than and less than, those associated with the MMG MPFFT . Theoretically, the MMG MPFFT represents the highest torque output that can be maintained for an extended period of time with no change in the global firing rate of the unfused, activated motor units and, therefore, no change in MMG MPF. At torque levels greater than the MMG MPFFT , however, the global firing rate of unfused, activated motor units should decrease, resulting in a
concomitant decrease in MMG MPF. Previous studies (Itoh et al., 2004; Orizio et al., 1992) have reported that MMG MPF remained unchanged during continuous isometric muscle actions of the forearm flexors at 20%MVIC. Thus, the current findings (MMG MPFFT ranged from 21.6 to 23.7%MVIC), in conjunction with those of Itoh et al. (2004) and Orizio et al. (1992), suggest that continuous isometric muscle actions at the torque level corresponding to the MMG MPFFT would not affect the global firing rate of the unfused, activated motor units. In summary, the mathematical model used for the determination of EMG MPFFT (Hendrix et al., 2009b) can be applied to the frequency domain of the MMG signal to estimate the MMG MPFFT . The MMG MPFFT , theoretically, represents the highest torque that can be maintained for an extended period of time with no change in the global firing rate of the unfused, activated motor units, and therefore, no change in MMG MPF. The results of the present study indicated that there were no differences in the isometric torque levels associated with the MMG MPFFT for the three superficial muscles of the quadriceps (VL, VM, and RF). In addition, the mean MMG MPFFT values (23.7 ± 7.8, 21.9 ± 6.8 and 21.6 ± 6.4%MVIC, respectively) occurred at torque levels that are typically not affected by muscular occlusion, and therefore, are not likely to be limited by restricted blood flow to the working muscles. Therefore, the MMG MPFFT test may provide a non-invasive method to examine the effects of interventions such as caffeine, strength training, stretching, and fatigue on the global motor unit firing rate during isometric muscle actions. References Akataki K, Mita K, Watakabe M, Itoh K. Mechanomyogram and force relationship during voluntary isometric ramp contractions of the biceps brachii muscle. Eur J Appl Physiol 2001;84:19–25. Barry DT, Cole NM. Muscle sounds are emitted at the resonant frequencies of skeletal muscle. IEEE Trans Biomed Eng 1990;37:525–31. Barry DT, Geiringer SR, Ball RD. Acoustic myography: a noninvasive monitor of motor unit fatigue. Muscle Nerve 1985;8:189–94. Basmajian JV, DeLuca CJ. Muscles alive: their functions revealed by electromyography. 5th ed. Baltimore: Williams & Wilkins; 1985. Beck TW, Housh TJ, Johnson GO, Cramer JT, Weir JP, Coburn JW, et al. Does the frequency content of the surface mechanomyographic signal reflect motor unit firing rates? A brief review. J Electromyogr Kinesiol 2007;17:1–13. Carlson BR, McCraw LW. Isometric strength and relative isometric endurance. Res Q 1971;42:244–50. Cescon C, Gazzoni M, Gobbo M, Orizio C, Farina D. Non-invasive assessment of single motor unit mechanomyographic response and twitch force by spike-triggered averaging. Med Biol Eng Comput 2004;42:496–501. deVries HA, Moritani T, Nagata A, Magnussen K. The relation between critical power and neuromuscular fatigue as estimated from electromyographic data. Ergonomics 1982;25:783–91. Diemont B, Figini MM, Orizio C, Perini R, Veicsteinas A. Spectral analysis of muscular sound at low and high contraction level. Int J Biomed Comput 1988;23:161–75. Edgerton VR, Smith JL, Simpson DR. Muscle fibre type populations of human leg muscles. Histochem J 1975;7:259–66. Edwards RH, Hill DK, Jones DA. Heat production and chemical changes during isometric contractions of the human quadriceps muscle. J Physiol 1975;251:303–15. Edwards RH, Hill DK, McDonnell M. Myothermal and intramuscular pressure measurements during isometric contractions of the human quadriceps muscle. J Physiol 1972;224:58P–9P. Enoka RM, Stuart DG. Neurobiology of muscle fatigue. J Appl Physiol 1992;72:1631–48. Esposito F, Orizio C, Veicsteinas A. Electromyogram and mechanomyogram changes in fresh and fatigued muscle during sustained contraction in men. Eur J Appl Physiol Occup Physiol 1998;78:494–501. Garland SJ, Gossen ER. The muscular wisdom hypothesis in human muscle fatigue. Exerc Sport Sci Rev 2002;30:45–9. Gordon G, Holbourn AH. The sounds from single motor units in a contracting muscle. J Physiol 1948;107:456–64. Hendrix CR, Housh TJ, Johnson GO, Mielke M, Camic CL, Zuniga JM, et al. Comparison of critical force to EMG fatigue thresholds during isometric leg extension. Med Sci Sports Exerc 2009a;41:956–65. Hendrix CR, Housh TJ, Johnson GO, Mielke M, Camic CL, Zuniga JM, et al. A new EMG frequency-based fatigue threshold test. J Neurosci Methods 2009b;181:45–51. Hendrix CR, Housh TJ, Johnson GO, Weir JP, Beck TW, Malek MH, et al. A comparison of critical force and electromyographic fatigue threshold for isometric muscle actions of the forearm flexors. Eur J Appl Physiol 2009c;105:333–42.
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