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Electromyographic and mechanomyographic responses across repeated maximal isometric and concentric muscle actions of the leg extensors
Journal of Electromyography and Kinesiology 23 (2013) 342–348
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Electromyographic and mechanomyographic responses across repeated maximal isometric and concentric muscle actions of the leg extensors Clayton L. Camic a,⇑, Terry J. Housh b, Jorge M. Zuniga c, C. Russell Hendrix b, Haley C. Bergstrom b, Daniel A. Traylor b, Richard J. Schmidt b, Glen O. Johnson b a b c
University of Wisconsin-La Crosse, La Crosse, WI 54601, United States University of Nebraska-Lincoln, Lincoln, NE 68583, United States Creighton University, Omaha, NE 68178, United States
a r t i c l e
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Article history: Received 4 February 2012 Received in revised form 24 July 2012 Accepted 27 September 2012
Keywords: EMG MMG Amplitude Frequency Fatigue
a b s t r a c t The purpose of the present study was to examine the patterns of responses for torque, electromyographic (EMG) amplitude, EMG mean power frequency (MPF), mechanomyographic (MMG) amplitude, and MMG MPF across 30 repeated maximal isometric (ISO) and concentric (CON) muscle actions of the leg extensors. Twelve female subjects (21.1 ± 1.4 yrs; 63.3 ± 7.4 kg) performed ISO and CON fatigue protocols with EMG and MMG signals recorded from the vastus lateralis. The relationships for torque, EMG amplitude, EMG MPF, MMG amplitude, and MMG MPF versus repetition number were examined using polynomial regression. The results indicated there were decreases (p < 0.05) across the ISO muscle actions for torque (r2 = 0.95), EMG amplitude (R2 = 0.44), EMG MPF (r2 = 0.62), and MMG MPF (r2 = 0.48), but no change in MMG amplitude (r2 = 0.07). In addition, there were decreases across the CON muscle actions for torque (R2 = 0.97), EMG amplitude (R2 = 0.46), EMG MPF (R2 = 0.86), MMG amplitude (R2 = 0.44), and MMG MPF (R2 = 0.80). Thus, the current findings suggested that the mechanisms of fatigue and motor control strategies used to modulate torque production were similar between maximal ISO and CON muscle actions. Ó 2012 Elsevier Ltd. All rights reserved.
1. Introduction Electromyography (EMG) and mechanomyography (MMG) have commonly been used to evaluate muscular function through analysis of the electrical activity of activated skeletal muscle fibers and the low-frequency lateral oscillations as a result of their contraction, respectively. In particular, the surface EMG is a global signal that is composed of information related to the action potentials from all of the motor units within the pick-up range of the recording electrodes (Lynn, 1979). It has been suggested that the MMG signal, however, reflects the mechanical counterpart of the motor unit action potentials as measured by EMG (Gordon and Holbourn, 1948) and is a function of the gross lateral movement at the initiation of contraction, the smaller subsequent lateral oscillations generated at the resonant frequency of the muscle, and the dimensional changes of the active fibers (Orizio, 1993). Previous studies have utilized simultaneous measurements of EMG and MMG to
⇑ Corresponding author. Address: Exercise and Sport Science Department, 142 Mitchell Hall, University of Wisconsin-La Crosse, La Crosse, WI 54601, United States. Tel.: +1 608 785 6524. E-mail address: [email protected] (C.L. Camic). 1050-6411/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.jelekin.2012.09.010
investigate the dissociation between the electrical and mechanical processes of muscle contraction (Stokes and Dalton, 1991), the muscle contractile properties across different physiological conditions (Kimura et al., 2003) as well as to determine the factors responsible for electromechanical delay (Petitjean et al., 1992) and post-exercise muscle soreness (Bajaj et al., 2002). One of the most interesting applications of simultaneous EMG and MMG recording, however, is the evaluation of neuromuscular fatigue associated with exercise performance. For example, fatigue that occurs during submaximal muscle actions is characterized by increases in EMG amplitude that has been attributed to increases in motor unit recruitment, firing rates, or synchronization (Basmajian and DeLuca, 1985). During muscle actions that require maximal effort (i.e. maximal voluntary contractions), however, all motor units are theoretically activated and fatigueinduced de-recruitment is reflected by decreases in EMG amplitude with repeated repetitions. In the frequency domain of the EMG signal, fatigue is associated with a compression of the power density spectrum and decreases in EMG center frequency that are determined primarily by decreases in muscle fiber conduction velocity (Broman et al., 1985) and changes in the shape of the action potential waveform (Mills, 1982). Furthermore, it has been
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suggested that the amplitude content of the MMG signal is related to motor unit recruitment, whereas MMG frequency is associated with the global firing rate of unfused, activated motor units (Orizio, 1993; Orizio et al., 2003). Thus, the amplitude and frequency components of the EMG and MMG signals each provide unique information related to changes in neuromuscular function that occur with fatigue. Recent investigations have examined EMG and MMG responses during sustained isometric (ISO) (Hendrix et al., 2009a,b, 2010) as well as repeated concentric (CON) (Ebersole et al., 2006; PerryRana et al., 2002) or eccentric (Perry-Rana et al., 2003), isokinetic muscle actions. For example, Hendrix et al. (2009a,b), (2010) developed fatigue-thresholds derived from the frequency domains of the EMG and MMG signals during sustained ISO muscle actions of the forearm flexors at submaximal levels of torque. Theoretically, the fatigue-thresholds of Hendrix et al. (2009a,b), (2010) identified the mean ISO torque levels during sustained contractions that could be maintained for an extended period of time without significant decreases in muscle fiber conduction velocity and global motor unit firing rates. In addition, Ebersole et al. (2006) examined the linear, quadratic, or cubic changes in torque, EMG amplitude, EMG MPF, MMG amplitude, and MMG MPF across 50 repeated maximal CON muscle actions of the leg extensors and reported decreases in CON torque that were attributed to progressive decreases in muscular compliance, motor unit discharge rates, muscle fiber conduction velocity, and activated type II muscle fibers. Thus, the findings of these studies (Ebersole et al., 2006; Hendrix et al., 2009a,b, 2010; Perry-Rana et al., 2002, 2003) indicated that analysis of the amplitude and frequency contents of the EMG and MMG signals provide information related to the different motor control strategies used to modulate torque production during various types of fatiguing muscle actions. There are limited data regarding the motor control strategies utilized during repeated intermittent maximal ISO muscle actions. Kouzaki et al. (1999) examined PRE versus POST changes in the EMG and MMG signals following 50 repeated maximal ISO muscle actions of the leg extensors. No previous studies, however, have investigated the fatigue-induced patterns of responses for the EMG and MMG signals across repeated maximal ISO muscle actions. Therefore, the purpose of the present study was to examine the patterns of responses for torque, EMG amplitude, EMG MPF, MMG amplitude, and MMG MPF across 30 repeated maximal ISO and CON muscle actions of the leg extensors. 2. Methods 2.1. Subjects Twelve female subjects (mean age ± SD = 21.1 ± 1.4 yrs; body weight = 63.3 ± 7.4 kg; height = 166.8 ± 2.3 cm) volunteered to participate in this investigation. The subjects were moderately-trained (2.7 ± 1.7 resistance training hours per week, 4.8 ± 2.1 aerobic training hours per week) and instructed to avoid exercise for 48 h prior to each visit. The study was approved by the University Institutional Review Board for Human Subjects and all subjects completed a health history questionnaire and signed a written informed consent prior to any testing. 2.2. Orientation session (Visit 1) During the first laboratory visit, each subject practiced five, 3-s, submaximal and three, 3-s maximal ISO muscle actions as well as five submaximal and three maximal CON isokinetic muscle actions of the leg extensors at 30° s 1 on a calibrated Cybex 6000 isokinetic dynamometer.
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2.3. Determination of the long axis of the muscle fibers (Visit 2) During the second visit, surface EMG signals were measured from the vastus lateralis of the dominant thigh with a 16-channel linear electrode array and surface EMG16 data acquisition system (LISiN-Prima Biomedical and Sport, Treviso, Italy). The linear electrode array was placed over the vastus lateralis according to the procedures described in the EMG16 User’s Manual (2006). The subject was then asked to contract the dominant leg extensors, and the EMG signals from the probe were differentially amplified (gain 2000), analog filtered (fourth-order Bessel, bandwidth = 10– 500 Hz), and displayed on a computer screen. To align the electrode array with the long axis of the muscle fibers, the probe was rotated around the innervation zone until the slopes of the two lines connecting the EMG waveforms from channels above and below the innervation zone were approximately equal (EMG16 User’s Manual, 2006, p. 26). 2.4. Warm-up Prior to the ISO and CON fatigue sessions (Visits 3 and 4), the subjects performed a warm-up of five, 3-s ISO muscle actions or five CON isokinetic muscle actions at 30° s 1 corresponding to approximately 50% of their maximum. 2.5. Fatigue sessions (Visits 3 and 4) The subjects performed randomly ordered intermittent ISO and CON isokinetic fatigue protocols separated by 72 h. The ISO protocol involved 30 repeated maximal ISO leg extension muscle actions that were sustained for 3 s followed by 3 s of rest. The joint angle at the knee was 120° between the thigh and the leg. The CON protocol involved 30 consecutive maximal CON leg extension muscle actions at 30° s 1 followed by passive leg flexion movements. The range of motion was standardized from 90° to 180° of flexion at the knee. During each maximal muscle action, the subjects were encouraged to produce as much torque as possible. 2.6. EMG and MMG measurements During Visits 3 and 4, a bipolar (30 mm center-to-center) surface electrode (circular 4 mm diameter silver/silver chloride, BIOPAC Systems, Inc., Santa Barbara, CA) arrangement was placed over the vastus lateralis of the dominant thigh parallel to the long axis of the muscle fibers (Hermens et al., 1999). The reference electrode was placed over the iliac crest. The EMG signals were amplified (gain: 1000) using differential amplifiers (EMG 100, Biopac Systems, Inc., Santa Barbara, CA, bandwidth = 10–500 Hz) and digitally bandpass filtered (fourth-order Butterworth) at 10–500 Hz. The MMG signals from the vastus lateralis were detected using an accelerometer (Entran EGAS FT 10, bandwidth 0–200 Hz, dimensions: 1.0 1.0 0.5 cm, mass 1.0 g sensitivity 10 mV/g) placed between the proximal and distal EMG electrodes of the bipolar arrangement using double-sided adhesive tape. 2.7. Signal processing The raw EMG and MMG signals were digitized at 1000 Hz with a 12-bit analog-to-digital converter (Model MP100, Biopac Systems, Inc.) and stored in a personal computer (Inspiron 1501 Dell Inc., Round Rock, TX) for subsequent analysis. All signal processing was performed using custom programs written with LabVIEW programming software (version 7.1, National Instruments, Austin, TX). For each of the ISO muscle actions, the EMG amplitude (lVrms) and MPF (Hz) values were calculated for a 1-s epoch corresponding
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to seconds 1.0–2.0 of the 3-s muscle action. The EMG amplitude and MPF values for each of the CON muscle actions were calculated for a 1-s time period that corresponds to a 30° range of motion from approximately 120–150° of flexion at the knee. For the MPF analyses, each data segment was processed with a Hamming window and the discrete Fourier transform algorithm. The MPF was selected to represent the power spectrum in accordance with the recommendations of Hermens et al. (1999). 2.8. Statistical analyses The relationships for torque, EMG amplitude, EMG MPF, MMG amplitude, and MMG MPF versus repetition number for each type of muscle action were examined using polynomial regression analysis (SPSS software program). An alpha of p < 0.05 was considered statistically significant for all comparisons. 3. Results The results indicated there were significant decreases across the 30 repeated maximal ISO muscle actions for torque (linear, r2 = 0.95), EMG amplitude (quadratic, R2 = 0.44), EMG MPF (linear, r2 = 0.62), and MMG MPF (linear, r2 = 0.48), but no change in MMG amplitude (r2 = 0.07) (Figs. 1–5). In addition, there were significant decreases across the 30 repeated maximal CON muscle actions for torque (quadratic, R2 = 0.97), EMG amplitude (quadratic, R2 = 0.46), EMG MPF (quadratic, R2 = 0.86), MMG amplitude (quadratic, R2 = 0.44), and MMG MPF (quadratic, R2 = 0.80) (Figs. 1–5).
Fig. 2. The patterns of responses for electromyographic (EMG) amplitude versus repetition number during the repeated maximal isometric (d) and concentric (N) muscle actions. Values expressed as mean (± SE).
4. Discussion Edwards (1981, p. 1) defined fatigue as ‘‘. . .an inability to maintain the required or expected force.’’ In the present investigation,
Fig. 3. The patterns of responses for electromyographic (EMG) mean power frequency (MPF) versus repetition number during the repeated maximal isometric (d) and concentric (N) muscle actions. Values expressed as mean (±SE).
Fig. 1. The patterns of responses for torque versus repetition number during the repeated maximal isometric (d) and concentric (N) muscle actions. Values expressed as mean (±SE).
there were significant negative torque versus repetition number relationships for the 30 repeated ISO (r2 = 0.95) and CON
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Fig. 4. The patterns of responses for mechanomyographic (MMG) amplitude versus repetition number during the repeated maximal isometric (d) and concentric (N) muscle actions. Values expressed as mean (± SE).
Fig. 5. The patterns of responses for mechanomyographic (MMG) mean power frequency (MPF) versus repetition number during the repeated maximal isometric (d) and concentric (N) muscle actions. Values expressed as mean (±SE).
(R2 = 0.97) (Fig. 1) muscle actions that were associated with percent declines of 22.7% and 24.4%, respectively. These findings indicated that the 30 repeated ISO and CON muscle actions utilized
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in the current study resulted in effects on torque that were consistent with muscular fatigue. No previous studies have defined the torque-related patterns of responses for intermittent ISO muscle actions of the leg extensors. Kouzaki et al. (1999), however, assessed PRE to POST changes in torque of the leg extensors for 50 maximal, intermittent (3-s contraction, 3-s rest) ISO muscle actions and reported a mean (±SEM) decrease of 49.5 (±2.0)%. The greater decline in ISO torque (49.5 ± 2.0%) demonstrated by Kouzaki et al. (1999) compared to the present study (22.7%) may have been due to differences in the number of repetitions performed (50 vs. 30) or the knee joint angle (90° vs. 120°) used to assess ISO torque. For example, Hisaeda et al. (2001) examined muscular endurance of the leg extensors at 50% MVC and reported that submaximal ISO contractions could be maintained longer at a knee joint angle of 130° (mean ± SD = 115 ± 29.5 s) than 90° (71.1 ± 10.2 s). These findings were attributed, in part, to the degree of myofilament overlap which is dependent on the length of the contracting muscle (Edman, 1992). Furthermore, Kulig et al. (1984) reported that force production across joint angles of the knee ranging from 90° to 180° was maximum at 120°. Therefore, any variation from a knee joint angle of 120° would result in a less than optimal crossbridge formation. Thus, it is likely that the mean difference in percent decline during ISO muscle actions between the current study and Kouzaki et al. (1999) was partially due to the relationships among knee joint angle, muscle length, myofilament overlap, and fatigue. Recent investigations that have examined the patterns of responses for CON torque of the leg extensors have reported quadratic (R2 = 0.98) (Ebersole et al., 2006) and cubic (R2 = 0.97) (Perry-Rana et al., 2002) decreases across 50 repeated maximal muscle actions at 60° s 1 that were associated with percent declines of 59 ± 24% and 44 ± 18%, respectively. In addition, previous studies have demonstrated percent declines in torque of 35.9 ± 12.1% (Babault et al., 2006) and 47.7 ± 5.2% (Gray and Chandler, 1989) across 30 and 40 repeated maximal CON muscle actions at 60° s 1 and 180° s 1, respectively. It is possible that the percent decline (24.4%) in the present study was less than those of others (35.9–59.0%) due to differences in the velocity used to measure CON torque. Theoretically, the contribution of fatigue-resistant type I muscle fibers to maximal torque production decreases as velocity increases. Therefore, the percent declines found in previous studies (Babault et al., 2006; Ebersole et al., 2006; Gray and Chandler, 1989; Perry-Rana et al., 2002), compared to the current study, may have been due to a greater reliance on the more fatigable type II muscle fibers which resulted in greater decreases in torque. The physiological mechanisms responsible for decreases in torque during ISO muscle actions have been attributed to increased intramuscular pressure and occlusion of the vascular beds during contraction, leading to a restriction of muscle blood flow (Edwards et al., 1975). These impairments result in lower oxygen availability and an accumulation of metabolic byproducts of muscular contraction (i.e. ammonia, hydrogen ions, potassium, inorganic phosphate) (Edwards, 1981). In particular, these metabolites have been linked to the loss of membrane excitability, impaired excitation–contraction coupling involving calcium release and uptake from the sarcoplasmic reticulum, myofibrillar calcium sensitivity for binding with troponin, and actin–myosin binding, as well as reduced ATP production and breakdown (Gladden, 2004; MacLaren et al., 1989; Robergs et al., 2004). Furthermore, Crenshaw et al. (2000) demonstrated that 40 repeated maximal CON muscle actions of the leg extensors were associated with increased intramuscular fluid content and pressure of the vastus lateralis. Crenshaw et al. (2000) suggested these changes would lead to compression of the vascular beds and a greater diffusion distance between capillaries and muscle fibers, thereby initiating the onset of fatigue. In
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the current investigation, the ISO and CON muscle actions resulted in comparable percent declines (22.7% and 24.4%) across the 30 repetitions. Thus, the findings of the present study were in agreement with those of Crenshaw et al. (2000) and suggested that the mechanisms of fatigue were similar between the ISO and CON muscle actions. In the current investigation, the patterns of EMG and MMG responses were examined to assess the motor control strategies utilized during fatiguing ISO and CON muscle actions. The polynomial regression analyses for EMG amplitude indicated there were similar patterns of muscle activation across the repeated ISO (quadratic, R2 = 0.44) and CON (quadratic, R2 = 0.46) muscle actions (Fig. 2). Specifically, the quadratic relationships for EMG amplitude versus repetitions consisted of an increase during the first 10–15 muscle actions, followed by a decrease until the end of the test. No previous studies have reported the relationship for EMG amplitude across repetitions for repeated maximal intermittent ISO muscle actions. A number of investigations (Ebersole et al., 2006; Nilsson et al., 1977; Perry-Rana et al., 2002; Wretling and Larsén, 1998), however, have defined the EMG amplitude versus repetition number relationships for repeated maximal CON muscle actions. For example, EMG amplitude has been reported to exhibit quadratic (R2 = 0.41; Ebersole et al., 2006) or cubic (R2 = 0.35; Perry-Rana et al., 2002) increases across 50 repeated maximal CON muscle actions or no change across 100 to 150 repetitions (Nilsson et al., 1977; Wretling and Larsén, 1998). Variations in EMG amplitude across repeated maximal muscle actions would suggest changes in the number of activated motor units, firing rates, or synchronization. Theoretically, all available muscle fibers are activated during maximal muscle actions. Babault et al. (2006), however, reported pre-fatigued maximal ISO and CON muscle actions that were associated with activation levels of only 89.4 ± 3.1% and 88.3 ± 3.0%, respectively. Therefore, the findings of the current study and those of others (Babault et al., 2006; Ebersole et al., 2006; Perry-Rana et al., 2002) suggested that complete activation of all available motor units during ISO and CON muscle actions requires multiple repeated maximal repetitions and may not be attained with a single repetition. Furthermore, the decreases in EMG amplitude during the ISO and CON muscle actions in the present study indicated there was de-recruitment of activated motor units or a reduction in the global firing rate as a result of fatigue following 10–15 maximal repetitions. Recent investigations (Kouzaki et al., 1999; Orizio, 1993, Orizio et al., 2003) have utilized the time and frequency domains of the MMG signal to further examine the components of muscle activation. In this regard, Kouzaki et al. (1999) reported decreases in MMG amplitude during intermittent ISO muscle actions that were attributed to fatigue-induced impaired contractility and the subsequent de-recruitment of motor units. It is possible, however, that the amplitude of the MMG signal may also be affected by global firing rate, synchronization, and increased intramuscular pressure that restricts the dimensional changes of the active motor units (Orizio et al., 2003). Therefore, based on these findings (Kouzaki et al., 1999; Orizio et al., 2003), we hypothesized that MMG amplitude would decrease across the repeated ISO muscle actions. Our results, however, indicated there was no change in MMG amplitude during the ISO repetitions (r2 = 0.07) (Fig. 4). The reason for this finding is unclear, but previous studies (Barry et al. 1985; Dalton et al. 1992) have reported decreases followed by increases in MMG amplitude across multiple intermittent ISO muscle actions. Dalton et al. (1992) suggested that the greater amount of work a muscle could accomplish with intermittent rest would allow for ‘‘. . .metabolic processes to continue for longer’’ (p. 59) thereby, leading to greater peripheral fatigue as well as fatigue tremor that is common with ISO muscle actions and known to influence the MMG signal. Therefore, it is possible that the
expected decrease in MMG amplitude (as the result of de-recruitment) during the ISO muscle actions was counteracted by a fatigue tremor occurring simultaneously that increased MMG amplitude. During the CON muscle actions, there were decreases in MMG amplitude (quadratic, R2 = 0.44) (Fig. 4) that were likely the result of a fatigue-induced loss of activated motor units or increased intramuscular pressure (Crenshaw et al., 2000). Ebersole et al. (2006) also found decreases (R2 = 0.43) in MMG amplitude across repeated maximal CON muscle actions of the leg extensors. Thus, the current findings as well as those of Ebersole et al. (2006) and Dalton et al. (1992) suggested that MMG amplitude may be a useful indicator of fatigue during CON, but not intermittent ISO muscle actions. In the present investigation, there were decreases in MMG MPF during the ISO (linear, r2 = 0.48) and CON (quadratic, R2 = 0.80) muscle actions (Fig. 5). These findings were consistent with others (Ebersole et al., 2006; Kouzaki et al., 1999) that have investigated the effects of ISO and CON fatigue on MMG MPF. For example, Kouzaki et al. (1999) reported decreases in MMG MPF from PRE to POST during repeated maximal ISO muscle actions. In addition, Ebersole et al. (2006) found quadratic decreases (R2 = 0.56) in MMG MPF across repeated maximal CON muscle actions. It has been suggested (Orizio et al., 2003) that decreases in MMG MPF are related to factors that reduce the global firing rate, such as fatigue-induced de-recruitment of type II motor units and synchronization (Orizio et al., 2003). In the present investigation, the linear decrease (r2 = 0.48) in MMG MPF across the ISO muscle actions was consistent with the patterns of responses for torque (r2 = 0.95), EMG amplitude (R2 = 0.44), and EMG MPF (r2 = 0.62). Furthermore, during the repeated CON muscle actions, there were quadratic decreases in torque (R2 = 0.97), EMG amplitude (R2 = 0.46), EMG MPF (R2 = 0.86), MMG amplitude (R2 = 0.44), and MMG MPF (R2 = 0.80). Collectively, these findings indicated that across the repeated ISO and CON muscle actions, there were fatigue-induced de-recruitment of type II motor units, resulting in decreased torque, global firing rates, and conduction velocity. In addition, unlike MMG amplitude, MMG MPF may serve as a useful indicator of fatigue during both repeated maximal ISO and CON muscle actions. The present findings also indicated there were significant decreases in EMG MPF during the ISO (linear, r2 = 0.62) and CON (quadratic, R2 = 0.86) muscle actions (Fig. 3). Kouzaki et al. (1999) reported mean decreases in EMG MPF values following 50 maximal ISO muscle actions that paralleled decreases in torque during the first 30 repetitions. Our results were consistent with those of Kouzaki et al. (1999) that indicated EMG MPF (r2 = 0.62) and torque (r2 = 0.95) exhibited similar linear decreases across the fatiguing ISO muscle actions. Ebersole et al. (2006) also found that EMG MPF (quadratic, R2 = 0.85) tracked decreases in torque (quadratic, R2 = 0.97) across repeated maximal CON muscle actions. In addition, Crenshaw et al. (2000) reported decreases in EMG MPF (r = 0.49 to 0.82) across 100 maximal CON repetitions that were ‘‘nearly identical’’ (p. 125) to the decreases in torque. Our findings were in agreement with those of Ebersole et al. (2006) and Crenshaw et al. (2000) that showed EMG MPF (R2 = 0.86) and torque (R2 = 0.97) exhibited similar quadratic decreases during the CON fatigue protocol. Therefore, the present results and those of others (Crenshaw et al., 2000; Ebersole et al., 2006; Kouzaki et al., 1999) indicated that changes in EMG MPF during repeated maximal ISO and CON muscle actions tracked fatigue-related decreases in torque. Previous studies (Broman et al., 1985) have shown that fatigue is reflected in the frequency domain of the EMG signal by decreases in EMG MPF that are due to decreases in muscle fiber conduction velocity. The underlying mechanism responsible for decreases in muscle fiber conduction velocity and EMG MPF is likely a
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fatigue-induced increase in interstitial potassium that leads to a progressive loss of membrane excitability (Fortune and Lowery, 2007; vanDieën et al., 2009). Theoretically, during repeated maximal muscle actions, the loss of membrane excitability would result in the inactivation and de-recruitment of the fatigued motor units. Therefore, due to the accumulation of metabolic byproducts such as potassium that are associated with fatigue, concurrent decreases in EMG MPF and torque across multiple ISO and CON repetitions would be expected. In summary, the findings of the present investigation suggested that the mechanisms of fatigue were similar between the repeated maximal ISO and CON muscle actions. In addition, the decreases in EMG amplitude following 10–15 repetitions during both the ISO and CON muscle actions indicated there was de-recruitment of activated motor units or a reduction in their firing rates. Our findings also suggested that MMG amplitude may be a useful indicator of fatigue during CON, but not intermittent ISO muscle actions. In contrast, the EMG and MMG frequency responses paralleled the decreases in torque during both the ISO and CON muscle actions. Conflict of interest statement The authors have no conflicts of interest. Acknowledgements There were no funding sources. References Babault N, Desbrosses K, Fabre MS, Michaut A, Pousson M. Neuromuscular fatigue development during maximal concentric and isometric knee extensions. J Appl Physiol 2006;100:780–5. Bajaj C, Madeleine P, Sjøgaard G, Arendt-Nielsen L. Assessment of postexercise soreness by electromyography and mechanomyography. J Pain 2002;3(2):126–36. Barry DT, Geiringer SR, Ball RD. Acoustic myography: a non-invasive monitor of motor fatigue. Muscle Nerve 1985;8:189–94. Basmajian JV, DeLuca CJ. Muscles alive: their functions revealed by electromyography. Baltimore: Williams & Wilkins; 1985. Broman H, Bilotto G, De Luca CJ. A note on the noninvasive estimation of muscle fiber conduction velocity. IEEE Trans Biomed Eng 1985;BME-32(5):341–4. Crenshaw AG, Gerdle B, Heiden M, Karlsson S, Fridén J. Intramuscular pressure and electromyographic responses of the vastus lateralis muscle during repeated maximal isokinetic knee extensions. Acta Physiol Scand 2000;170:119–26. Dalton PA, Comerford MJ, Stokes MJ. Acoustic myography of the human quadriceps muscle during intermittent fatiguing activity. J Neurol Sci 1992;109:56–60. Ebersole KT, O’Connor KM, Wier AP. Mechanomyographic and electromyographic responses to repeated concentric muscle actions of the quadriceps femoris. J Electromyogr Kinesiol 2006;16:149–57. Edman KA. Mechanism underlying double-hyperbolic force-velocity relation in vertebrate skeletal muscle. Adv Exp Med Biol 1992;332:667–76. Edwards RH. Human muscle function and fatigue. Ciba Found Symp 1981;82:1–18. Edwards RH, Hill DK, Jones DA. Heat production and chemical changes during isometric contractions of the human quadriceps muscle. J Physiol 1975;251(2):303–15. EMG 16. 16 channels surface electromyographic signal amplifier (user’s manual). Turin (Italy): LISiN Bioengineering Center Polytechnic of Turin – Department of Electronics; 2006. Fortune E, Lowery MM. The effect of extracellular potassium concentration on muscle fiber conduction velocity examined using model simulation. Conf Proc IEEE Eng Med Biol Soc 2007:2726–9. Gladden LB. Lactate metabolism: a new paradigm for the third millennium. J Physiol. 2004;558:5–30. Gordon G, Holbourn AHS. The sounds from single motor units in a contracting muscle. J Physiol 1948;107:456–64. Gray JC, Chandler JM. Percent decline in peak torque production during repeated concentric and eccentric contractions of the quadriceps femoris muscle. J Ortho Sports Phys Ther 1989;2:309–14. Hermens HJ, Freriks B, Merletti R, Stegeman D, Blok J, Rau G, et al. SENIAM European recommendations for surface electromyography: results of the SENIAM project. Enschede, The Netherlands: Roessingh Research and Development; 1999. 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 2009a;181:45–51.
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Hendrix CR, Housh TJ, Zuniga JM, Camic CL, Mielke M, Johnson GO, et al. A mechanomyographic frequency-based fatigue threshold test. J Neurosci Methods 2009b;187(1):1–7. Hisaeda HO, Shinohara M, Kouzaki M, Fukunaga T. Effect of local blood circulation and absolute torque on muscle endurance at two different knee-joint angles in humans. Eur J Appl Physiol 2001;86:17–23. Kimura T, Hamada T, Massako Ueno L, Moritani T. Changes in contractile properties and neuromuscular propagation evaluated by simultaneous mechanomyogram and electromyogram during experimentally induced hypothermia. J Electromyogr Kinesiol 2003;13(5):433–40. 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 1999;80:9–15. Kulig K, Andrews JG, Hay JG. Human strength curves. Exer Sport Sci Rev 1984;12:417–66. Lynn PA. Direct on-line estimation of muscle fiber conduction velocity by surface electromyography. IEEE Trans Biomed Eng 1979;BME-26(10): 564–71. MacLaren DP, Gibson H, Parry-Billings M, Edwards RH. A review of metabolic and physiological factors in fatigue. Exer Sports Sci Rev 1989(1):29–66. Mills KR. Power spectral analysis of electromyogram and compound muscle action potential during muscle fatigue and recovery. J Physiol 1982;326:401–9. Nilsson J, Tesch P, Thorstensson A. Fatigue and EMG of repeated fast voluntary contractions in man. Acta Physiol Scand 1977;101:194–8. 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, 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. Perry-Rana SR, Housh TJ, Johnson GO, Bull AJ, Berning JM, Cramer JT. MMG and EMG responses during fatiguing isokinetic muscle contractions at different velocities. Muscle Nerve 2002;26:367–73. Perry-Rana SR, Housh TJ, Johnson GO, Bull AJ, Cramer JT. MMG and EMG responses during 25 maximal, eccentric, isokinetic muscle actions. Med Sci Sports Exerc 2003;35(12):2048–54. Petitjean M, Maton B, Cnockaert JC. Evaluation of human dynamic contraction by phonomyography. J Appl Physiol 1992;73:2567–73. Robergs RA, Ghiasvand F, Parker D. Biochemistry of exercise-induced metabolic acidosis. Am J Physiol Regul Integr Comp Physiol 2004;287:R502–16. Stokes MJ, Dalton PA. Acoustic myography for investigating human skeletal muscle fatigue. J Appl Physiol 1991;71(4):1422–6. vanDieën JH, Westebring-van der Putten EP, Kingma I, de Looze MP. Low-level activity of the trunk extensor muscles causes electromyographic manifestations of fatigue in absence of decreased oxygenation. J Electromyogr Kinesiol 2009;19:398–406. Wretling ML, Larsén KH. Mechanical output and electromyographic parameters in males and females during fatiguing knee-extensions. Int J Sports Med 1998;19:401–7.
Clayton L. Camic received a BS (2001) degree in Exercise Science from Morehead State University, MS (2003) degree in Exercise Physiology from the University of Wyoming, and PhD (2011) degree from the University of Nebraska-Lincoln. He is currently an Assistant Professor in the Exercise and Sport Science Department at the University of Wisconsin-La Crosse and his main research interests include evaluation of muscle function and fatigue using electromyography as well as sports nutrition.
Terry J. Housh received a BA (1977) degree in Physical Education from Doane College, Crete, NE, and MPE (1979) and Ph.D. (1984) degrees from the University of Nebraska-Lincoln. He is a Fellow of the American College of Sports Medicine, Fellow in the research Consortium of AAHPERD, and received the 1998 Outstanding Sport Scientist Award from the National Strength and Conditioning Association. Presently, he is a Professor in the Department of Nutrition and Health Sciences, Director of the Exercise Physiology Laboratory, and CoDirector of the Center for Youth Fitness and Sports Research at the University of Nebraska-Lincoln. His main areas of research are muscle function, fatigue, and growth and development in young athletes.
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C.L. Camic et al. / Journal of Electromyography and Kinesiology 23 (2013) 342–348 Jorge M. Zuniga received a BS (2003) degree in Physical Education from ‘‘Cardenal R. Silva Henrriquez’’ Catholic University; Santiago, Chile, MS in Exercise Sciences (2007) from the University of Nebraska at Omaha, and Ph.D. in Exercise Physiology from the University of Nebraska-Lincoln. He is a member of the American College of Sports Medicine and the National Strength and Conditioning Association. He is currently an assistant professor at Creighton University and his main research interests include evaluation of muscle function and fatigue using electromyography and mechanomyography during dynamic muscle actions (i.e., cycling and running). It is expected that this work will lead to the development and application of neuromuscular fatigue thresholds for the assessment and improvement of athletic performance.
C. Russell Hendrix received his B.S.E. (1992) in Biology from Emporia State University, an M.S.E. (2002) in Physical Education from Northwest Missouri State University. He is currently a doctoral student in exercise physiology at the University of Nebraska–Lincoln and his main research interests include evaluation of muscle function using electromyography and mechanomyography, especially as they relate to fatigue thresholds. He is a member of the American College of Sports Medicine, an ACSM–certified Health Fitness Specialist, and a member of the National Strength and Conditioning Association.
Haley C. Bergstrom received a BS (2009) degree in Exercise Science from Doane College, Crete, Nebraska and MS (2011) degree in Exercise Physiology from the University of Nebraska-Lincoln. She is a member of the American College of Sports Medicine and the National Strength and Conditioning Association. She is currently a doctoral student in Exercise Physiology at the University of Nebraska-Lincoln and her main research interests include the evaluation of cardiovascular, metabolic, neuromuscular, and perceptual responses during dynamic fatiguing exercise.
Daniel A. Traylor received a BS (2004) degree in Health Promotion from Appalachian State University and MS (2008) degree in Sports Medicine from Armstrong Atlantic State University. He is currently a doctoral student in Exercise Physiology at the University of Nebraska-Lincoln and his main research interests include short-term resistance training and the assessment of muscle fatigue using electromyography.
Richard J. Schmidt received a BS (1969), M.Ed. in Physical Education (1964) and a Ph.D. (1972) in Education (Psychological and Cultural Studies) from the University Nebraska–Lincoln. He is a Fellow in the research Consortium of AAHPERD. He is currently an Associate Professor of Nutrition and Health Sciences at the University of Nebraska-Lincoln. His main areas of research are Exercise testing, clinical exercise physiology, occupational physiology, military & law enforcement sports medicine.
Glen O. Johnson received a BS (1960) and MS (1964) degrees from Winona State University, Winona, MN, and a Ph.D. (1972) from the University of Iowa. He is a Fellow of the American College of Sports Medicine and a Fellow in the research Consortium of AAHPERD. He is currently a Professor of Nutrition and Health Sciences at the University of Nebraska-Lincoln.
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Journal of Electromyography and Kinesiology journal homepage: www.elsevier.com/locate/jelekin
Electromyographic and mechanomyographic responses across repeated maximal isometric and concentric muscle actions of the leg extensors Clayton L. Camic a,⇑, Terry J. Housh b, Jorge M. Zuniga c, C. Russell Hendrix b, Haley C. Bergstrom b, Daniel A. Traylor b, Richard J. Schmidt b, Glen O. Johnson b a b c
University of Wisconsin-La Crosse, La Crosse, WI 54601, United States University of Nebraska-Lincoln, Lincoln, NE 68583, United States Creighton University, Omaha, NE 68178, United States
a r t i c l e
i n f o
Article history: Received 4 February 2012 Received in revised form 24 July 2012 Accepted 27 September 2012
Keywords: EMG MMG Amplitude Frequency Fatigue
a b s t r a c t The purpose of the present study was to examine the patterns of responses for torque, electromyographic (EMG) amplitude, EMG mean power frequency (MPF), mechanomyographic (MMG) amplitude, and MMG MPF across 30 repeated maximal isometric (ISO) and concentric (CON) muscle actions of the leg extensors. Twelve female subjects (21.1 ± 1.4 yrs; 63.3 ± 7.4 kg) performed ISO and CON fatigue protocols with EMG and MMG signals recorded from the vastus lateralis. The relationships for torque, EMG amplitude, EMG MPF, MMG amplitude, and MMG MPF versus repetition number were examined using polynomial regression. The results indicated there were decreases (p < 0.05) across the ISO muscle actions for torque (r2 = 0.95), EMG amplitude (R2 = 0.44), EMG MPF (r2 = 0.62), and MMG MPF (r2 = 0.48), but no change in MMG amplitude (r2 = 0.07). In addition, there were decreases across the CON muscle actions for torque (R2 = 0.97), EMG amplitude (R2 = 0.46), EMG MPF (R2 = 0.86), MMG amplitude (R2 = 0.44), and MMG MPF (R2 = 0.80). Thus, the current findings suggested that the mechanisms of fatigue and motor control strategies used to modulate torque production were similar between maximal ISO and CON muscle actions. Ó 2012 Elsevier Ltd. All rights reserved.
1. Introduction Electromyography (EMG) and mechanomyography (MMG) have commonly been used to evaluate muscular function through analysis of the electrical activity of activated skeletal muscle fibers and the low-frequency lateral oscillations as a result of their contraction, respectively. In particular, the surface EMG is a global signal that is composed of information related to the action potentials from all of the motor units within the pick-up range of the recording electrodes (Lynn, 1979). It has been suggested that the MMG signal, however, reflects the mechanical counterpart of the motor unit action potentials as measured by EMG (Gordon and Holbourn, 1948) and is a function of the gross lateral movement at the initiation of contraction, the smaller subsequent lateral oscillations generated at the resonant frequency of the muscle, and the dimensional changes of the active fibers (Orizio, 1993). Previous studies have utilized simultaneous measurements of EMG and MMG to
⇑ Corresponding author. Address: Exercise and Sport Science Department, 142 Mitchell Hall, University of Wisconsin-La Crosse, La Crosse, WI 54601, United States. Tel.: +1 608 785 6524. E-mail address: [email protected] (C.L. Camic). 1050-6411/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.jelekin.2012.09.010
investigate the dissociation between the electrical and mechanical processes of muscle contraction (Stokes and Dalton, 1991), the muscle contractile properties across different physiological conditions (Kimura et al., 2003) as well as to determine the factors responsible for electromechanical delay (Petitjean et al., 1992) and post-exercise muscle soreness (Bajaj et al., 2002). One of the most interesting applications of simultaneous EMG and MMG recording, however, is the evaluation of neuromuscular fatigue associated with exercise performance. For example, fatigue that occurs during submaximal muscle actions is characterized by increases in EMG amplitude that has been attributed to increases in motor unit recruitment, firing rates, or synchronization (Basmajian and DeLuca, 1985). During muscle actions that require maximal effort (i.e. maximal voluntary contractions), however, all motor units are theoretically activated and fatigueinduced de-recruitment is reflected by decreases in EMG amplitude with repeated repetitions. In the frequency domain of the EMG signal, fatigue is associated with a compression of the power density spectrum and decreases in EMG center frequency that are determined primarily by decreases in muscle fiber conduction velocity (Broman et al., 1985) and changes in the shape of the action potential waveform (Mills, 1982). Furthermore, it has been
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suggested that the amplitude content of the MMG signal is related to motor unit recruitment, whereas MMG frequency is associated with the global firing rate of unfused, activated motor units (Orizio, 1993; Orizio et al., 2003). Thus, the amplitude and frequency components of the EMG and MMG signals each provide unique information related to changes in neuromuscular function that occur with fatigue. Recent investigations have examined EMG and MMG responses during sustained isometric (ISO) (Hendrix et al., 2009a,b, 2010) as well as repeated concentric (CON) (Ebersole et al., 2006; PerryRana et al., 2002) or eccentric (Perry-Rana et al., 2003), isokinetic muscle actions. For example, Hendrix et al. (2009a,b), (2010) developed fatigue-thresholds derived from the frequency domains of the EMG and MMG signals during sustained ISO muscle actions of the forearm flexors at submaximal levels of torque. Theoretically, the fatigue-thresholds of Hendrix et al. (2009a,b), (2010) identified the mean ISO torque levels during sustained contractions that could be maintained for an extended period of time without significant decreases in muscle fiber conduction velocity and global motor unit firing rates. In addition, Ebersole et al. (2006) examined the linear, quadratic, or cubic changes in torque, EMG amplitude, EMG MPF, MMG amplitude, and MMG MPF across 50 repeated maximal CON muscle actions of the leg extensors and reported decreases in CON torque that were attributed to progressive decreases in muscular compliance, motor unit discharge rates, muscle fiber conduction velocity, and activated type II muscle fibers. Thus, the findings of these studies (Ebersole et al., 2006; Hendrix et al., 2009a,b, 2010; Perry-Rana et al., 2002, 2003) indicated that analysis of the amplitude and frequency contents of the EMG and MMG signals provide information related to the different motor control strategies used to modulate torque production during various types of fatiguing muscle actions. There are limited data regarding the motor control strategies utilized during repeated intermittent maximal ISO muscle actions. Kouzaki et al. (1999) examined PRE versus POST changes in the EMG and MMG signals following 50 repeated maximal ISO muscle actions of the leg extensors. No previous studies, however, have investigated the fatigue-induced patterns of responses for the EMG and MMG signals across repeated maximal ISO muscle actions. Therefore, the purpose of the present study was to examine the patterns of responses for torque, EMG amplitude, EMG MPF, MMG amplitude, and MMG MPF across 30 repeated maximal ISO and CON muscle actions of the leg extensors. 2. Methods 2.1. Subjects Twelve female subjects (mean age ± SD = 21.1 ± 1.4 yrs; body weight = 63.3 ± 7.4 kg; height = 166.8 ± 2.3 cm) volunteered to participate in this investigation. The subjects were moderately-trained (2.7 ± 1.7 resistance training hours per week, 4.8 ± 2.1 aerobic training hours per week) and instructed to avoid exercise for 48 h prior to each visit. The study was approved by the University Institutional Review Board for Human Subjects and all subjects completed a health history questionnaire and signed a written informed consent prior to any testing. 2.2. Orientation session (Visit 1) During the first laboratory visit, each subject practiced five, 3-s, submaximal and three, 3-s maximal ISO muscle actions as well as five submaximal and three maximal CON isokinetic muscle actions of the leg extensors at 30° s 1 on a calibrated Cybex 6000 isokinetic dynamometer.
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2.3. Determination of the long axis of the muscle fibers (Visit 2) During the second visit, surface EMG signals were measured from the vastus lateralis of the dominant thigh with a 16-channel linear electrode array and surface EMG16 data acquisition system (LISiN-Prima Biomedical and Sport, Treviso, Italy). The linear electrode array was placed over the vastus lateralis according to the procedures described in the EMG16 User’s Manual (2006). The subject was then asked to contract the dominant leg extensors, and the EMG signals from the probe were differentially amplified (gain 2000), analog filtered (fourth-order Bessel, bandwidth = 10– 500 Hz), and displayed on a computer screen. To align the electrode array with the long axis of the muscle fibers, the probe was rotated around the innervation zone until the slopes of the two lines connecting the EMG waveforms from channels above and below the innervation zone were approximately equal (EMG16 User’s Manual, 2006, p. 26). 2.4. Warm-up Prior to the ISO and CON fatigue sessions (Visits 3 and 4), the subjects performed a warm-up of five, 3-s ISO muscle actions or five CON isokinetic muscle actions at 30° s 1 corresponding to approximately 50% of their maximum. 2.5. Fatigue sessions (Visits 3 and 4) The subjects performed randomly ordered intermittent ISO and CON isokinetic fatigue protocols separated by 72 h. The ISO protocol involved 30 repeated maximal ISO leg extension muscle actions that were sustained for 3 s followed by 3 s of rest. The joint angle at the knee was 120° between the thigh and the leg. The CON protocol involved 30 consecutive maximal CON leg extension muscle actions at 30° s 1 followed by passive leg flexion movements. The range of motion was standardized from 90° to 180° of flexion at the knee. During each maximal muscle action, the subjects were encouraged to produce as much torque as possible. 2.6. EMG and MMG measurements During Visits 3 and 4, a bipolar (30 mm center-to-center) surface electrode (circular 4 mm diameter silver/silver chloride, BIOPAC Systems, Inc., Santa Barbara, CA) arrangement was placed over the vastus lateralis of the dominant thigh parallel to the long axis of the muscle fibers (Hermens et al., 1999). The reference electrode was placed over the iliac crest. The EMG signals were amplified (gain: 1000) using differential amplifiers (EMG 100, Biopac Systems, Inc., Santa Barbara, CA, bandwidth = 10–500 Hz) and digitally bandpass filtered (fourth-order Butterworth) at 10–500 Hz. The MMG signals from the vastus lateralis were detected using an accelerometer (Entran EGAS FT 10, bandwidth 0–200 Hz, dimensions: 1.0 1.0 0.5 cm, mass 1.0 g sensitivity 10 mV/g) placed between the proximal and distal EMG electrodes of the bipolar arrangement using double-sided adhesive tape. 2.7. Signal processing The raw EMG and MMG signals were digitized at 1000 Hz with a 12-bit analog-to-digital converter (Model MP100, Biopac Systems, Inc.) and stored in a personal computer (Inspiron 1501 Dell Inc., Round Rock, TX) for subsequent analysis. All signal processing was performed using custom programs written with LabVIEW programming software (version 7.1, National Instruments, Austin, TX). For each of the ISO muscle actions, the EMG amplitude (lVrms) and MPF (Hz) values were calculated for a 1-s epoch corresponding
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to seconds 1.0–2.0 of the 3-s muscle action. The EMG amplitude and MPF values for each of the CON muscle actions were calculated for a 1-s time period that corresponds to a 30° range of motion from approximately 120–150° of flexion at the knee. For the MPF analyses, each data segment was processed with a Hamming window and the discrete Fourier transform algorithm. The MPF was selected to represent the power spectrum in accordance with the recommendations of Hermens et al. (1999). 2.8. Statistical analyses The relationships for torque, EMG amplitude, EMG MPF, MMG amplitude, and MMG MPF versus repetition number for each type of muscle action were examined using polynomial regression analysis (SPSS software program). An alpha of p < 0.05 was considered statistically significant for all comparisons. 3. Results The results indicated there were significant decreases across the 30 repeated maximal ISO muscle actions for torque (linear, r2 = 0.95), EMG amplitude (quadratic, R2 = 0.44), EMG MPF (linear, r2 = 0.62), and MMG MPF (linear, r2 = 0.48), but no change in MMG amplitude (r2 = 0.07) (Figs. 1–5). In addition, there were significant decreases across the 30 repeated maximal CON muscle actions for torque (quadratic, R2 = 0.97), EMG amplitude (quadratic, R2 = 0.46), EMG MPF (quadratic, R2 = 0.86), MMG amplitude (quadratic, R2 = 0.44), and MMG MPF (quadratic, R2 = 0.80) (Figs. 1–5).
Fig. 2. The patterns of responses for electromyographic (EMG) amplitude versus repetition number during the repeated maximal isometric (d) and concentric (N) muscle actions. Values expressed as mean (± SE).
4. Discussion Edwards (1981, p. 1) defined fatigue as ‘‘. . .an inability to maintain the required or expected force.’’ In the present investigation,
Fig. 3. The patterns of responses for electromyographic (EMG) mean power frequency (MPF) versus repetition number during the repeated maximal isometric (d) and concentric (N) muscle actions. Values expressed as mean (±SE).
Fig. 1. The patterns of responses for torque versus repetition number during the repeated maximal isometric (d) and concentric (N) muscle actions. Values expressed as mean (±SE).
there were significant negative torque versus repetition number relationships for the 30 repeated ISO (r2 = 0.95) and CON
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Fig. 4. The patterns of responses for mechanomyographic (MMG) amplitude versus repetition number during the repeated maximal isometric (d) and concentric (N) muscle actions. Values expressed as mean (± SE).
Fig. 5. The patterns of responses for mechanomyographic (MMG) mean power frequency (MPF) versus repetition number during the repeated maximal isometric (d) and concentric (N) muscle actions. Values expressed as mean (±SE).
(R2 = 0.97) (Fig. 1) muscle actions that were associated with percent declines of 22.7% and 24.4%, respectively. These findings indicated that the 30 repeated ISO and CON muscle actions utilized
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in the current study resulted in effects on torque that were consistent with muscular fatigue. No previous studies have defined the torque-related patterns of responses for intermittent ISO muscle actions of the leg extensors. Kouzaki et al. (1999), however, assessed PRE to POST changes in torque of the leg extensors for 50 maximal, intermittent (3-s contraction, 3-s rest) ISO muscle actions and reported a mean (±SEM) decrease of 49.5 (±2.0)%. The greater decline in ISO torque (49.5 ± 2.0%) demonstrated by Kouzaki et al. (1999) compared to the present study (22.7%) may have been due to differences in the number of repetitions performed (50 vs. 30) or the knee joint angle (90° vs. 120°) used to assess ISO torque. For example, Hisaeda et al. (2001) examined muscular endurance of the leg extensors at 50% MVC and reported that submaximal ISO contractions could be maintained longer at a knee joint angle of 130° (mean ± SD = 115 ± 29.5 s) than 90° (71.1 ± 10.2 s). These findings were attributed, in part, to the degree of myofilament overlap which is dependent on the length of the contracting muscle (Edman, 1992). Furthermore, Kulig et al. (1984) reported that force production across joint angles of the knee ranging from 90° to 180° was maximum at 120°. Therefore, any variation from a knee joint angle of 120° would result in a less than optimal crossbridge formation. Thus, it is likely that the mean difference in percent decline during ISO muscle actions between the current study and Kouzaki et al. (1999) was partially due to the relationships among knee joint angle, muscle length, myofilament overlap, and fatigue. Recent investigations that have examined the patterns of responses for CON torque of the leg extensors have reported quadratic (R2 = 0.98) (Ebersole et al., 2006) and cubic (R2 = 0.97) (Perry-Rana et al., 2002) decreases across 50 repeated maximal muscle actions at 60° s 1 that were associated with percent declines of 59 ± 24% and 44 ± 18%, respectively. In addition, previous studies have demonstrated percent declines in torque of 35.9 ± 12.1% (Babault et al., 2006) and 47.7 ± 5.2% (Gray and Chandler, 1989) across 30 and 40 repeated maximal CON muscle actions at 60° s 1 and 180° s 1, respectively. It is possible that the percent decline (24.4%) in the present study was less than those of others (35.9–59.0%) due to differences in the velocity used to measure CON torque. Theoretically, the contribution of fatigue-resistant type I muscle fibers to maximal torque production decreases as velocity increases. Therefore, the percent declines found in previous studies (Babault et al., 2006; Ebersole et al., 2006; Gray and Chandler, 1989; Perry-Rana et al., 2002), compared to the current study, may have been due to a greater reliance on the more fatigable type II muscle fibers which resulted in greater decreases in torque. The physiological mechanisms responsible for decreases in torque during ISO muscle actions have been attributed to increased intramuscular pressure and occlusion of the vascular beds during contraction, leading to a restriction of muscle blood flow (Edwards et al., 1975). These impairments result in lower oxygen availability and an accumulation of metabolic byproducts of muscular contraction (i.e. ammonia, hydrogen ions, potassium, inorganic phosphate) (Edwards, 1981). In particular, these metabolites have been linked to the loss of membrane excitability, impaired excitation–contraction coupling involving calcium release and uptake from the sarcoplasmic reticulum, myofibrillar calcium sensitivity for binding with troponin, and actin–myosin binding, as well as reduced ATP production and breakdown (Gladden, 2004; MacLaren et al., 1989; Robergs et al., 2004). Furthermore, Crenshaw et al. (2000) demonstrated that 40 repeated maximal CON muscle actions of the leg extensors were associated with increased intramuscular fluid content and pressure of the vastus lateralis. Crenshaw et al. (2000) suggested these changes would lead to compression of the vascular beds and a greater diffusion distance between capillaries and muscle fibers, thereby initiating the onset of fatigue. In
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the current investigation, the ISO and CON muscle actions resulted in comparable percent declines (22.7% and 24.4%) across the 30 repetitions. Thus, the findings of the present study were in agreement with those of Crenshaw et al. (2000) and suggested that the mechanisms of fatigue were similar between the ISO and CON muscle actions. In the current investigation, the patterns of EMG and MMG responses were examined to assess the motor control strategies utilized during fatiguing ISO and CON muscle actions. The polynomial regression analyses for EMG amplitude indicated there were similar patterns of muscle activation across the repeated ISO (quadratic, R2 = 0.44) and CON (quadratic, R2 = 0.46) muscle actions (Fig. 2). Specifically, the quadratic relationships for EMG amplitude versus repetitions consisted of an increase during the first 10–15 muscle actions, followed by a decrease until the end of the test. No previous studies have reported the relationship for EMG amplitude across repetitions for repeated maximal intermittent ISO muscle actions. A number of investigations (Ebersole et al., 2006; Nilsson et al., 1977; Perry-Rana et al., 2002; Wretling and Larsén, 1998), however, have defined the EMG amplitude versus repetition number relationships for repeated maximal CON muscle actions. For example, EMG amplitude has been reported to exhibit quadratic (R2 = 0.41; Ebersole et al., 2006) or cubic (R2 = 0.35; Perry-Rana et al., 2002) increases across 50 repeated maximal CON muscle actions or no change across 100 to 150 repetitions (Nilsson et al., 1977; Wretling and Larsén, 1998). Variations in EMG amplitude across repeated maximal muscle actions would suggest changes in the number of activated motor units, firing rates, or synchronization. Theoretically, all available muscle fibers are activated during maximal muscle actions. Babault et al. (2006), however, reported pre-fatigued maximal ISO and CON muscle actions that were associated with activation levels of only 89.4 ± 3.1% and 88.3 ± 3.0%, respectively. Therefore, the findings of the current study and those of others (Babault et al., 2006; Ebersole et al., 2006; Perry-Rana et al., 2002) suggested that complete activation of all available motor units during ISO and CON muscle actions requires multiple repeated maximal repetitions and may not be attained with a single repetition. Furthermore, the decreases in EMG amplitude during the ISO and CON muscle actions in the present study indicated there was de-recruitment of activated motor units or a reduction in the global firing rate as a result of fatigue following 10–15 maximal repetitions. Recent investigations (Kouzaki et al., 1999; Orizio, 1993, Orizio et al., 2003) have utilized the time and frequency domains of the MMG signal to further examine the components of muscle activation. In this regard, Kouzaki et al. (1999) reported decreases in MMG amplitude during intermittent ISO muscle actions that were attributed to fatigue-induced impaired contractility and the subsequent de-recruitment of motor units. It is possible, however, that the amplitude of the MMG signal may also be affected by global firing rate, synchronization, and increased intramuscular pressure that restricts the dimensional changes of the active motor units (Orizio et al., 2003). Therefore, based on these findings (Kouzaki et al., 1999; Orizio et al., 2003), we hypothesized that MMG amplitude would decrease across the repeated ISO muscle actions. Our results, however, indicated there was no change in MMG amplitude during the ISO repetitions (r2 = 0.07) (Fig. 4). The reason for this finding is unclear, but previous studies (Barry et al. 1985; Dalton et al. 1992) have reported decreases followed by increases in MMG amplitude across multiple intermittent ISO muscle actions. Dalton et al. (1992) suggested that the greater amount of work a muscle could accomplish with intermittent rest would allow for ‘‘. . .metabolic processes to continue for longer’’ (p. 59) thereby, leading to greater peripheral fatigue as well as fatigue tremor that is common with ISO muscle actions and known to influence the MMG signal. Therefore, it is possible that the
expected decrease in MMG amplitude (as the result of de-recruitment) during the ISO muscle actions was counteracted by a fatigue tremor occurring simultaneously that increased MMG amplitude. During the CON muscle actions, there were decreases in MMG amplitude (quadratic, R2 = 0.44) (Fig. 4) that were likely the result of a fatigue-induced loss of activated motor units or increased intramuscular pressure (Crenshaw et al., 2000). Ebersole et al. (2006) also found decreases (R2 = 0.43) in MMG amplitude across repeated maximal CON muscle actions of the leg extensors. Thus, the current findings as well as those of Ebersole et al. (2006) and Dalton et al. (1992) suggested that MMG amplitude may be a useful indicator of fatigue during CON, but not intermittent ISO muscle actions. In the present investigation, there were decreases in MMG MPF during the ISO (linear, r2 = 0.48) and CON (quadratic, R2 = 0.80) muscle actions (Fig. 5). These findings were consistent with others (Ebersole et al., 2006; Kouzaki et al., 1999) that have investigated the effects of ISO and CON fatigue on MMG MPF. For example, Kouzaki et al. (1999) reported decreases in MMG MPF from PRE to POST during repeated maximal ISO muscle actions. In addition, Ebersole et al. (2006) found quadratic decreases (R2 = 0.56) in MMG MPF across repeated maximal CON muscle actions. It has been suggested (Orizio et al., 2003) that decreases in MMG MPF are related to factors that reduce the global firing rate, such as fatigue-induced de-recruitment of type II motor units and synchronization (Orizio et al., 2003). In the present investigation, the linear decrease (r2 = 0.48) in MMG MPF across the ISO muscle actions was consistent with the patterns of responses for torque (r2 = 0.95), EMG amplitude (R2 = 0.44), and EMG MPF (r2 = 0.62). Furthermore, during the repeated CON muscle actions, there were quadratic decreases in torque (R2 = 0.97), EMG amplitude (R2 = 0.46), EMG MPF (R2 = 0.86), MMG amplitude (R2 = 0.44), and MMG MPF (R2 = 0.80). Collectively, these findings indicated that across the repeated ISO and CON muscle actions, there were fatigue-induced de-recruitment of type II motor units, resulting in decreased torque, global firing rates, and conduction velocity. In addition, unlike MMG amplitude, MMG MPF may serve as a useful indicator of fatigue during both repeated maximal ISO and CON muscle actions. The present findings also indicated there were significant decreases in EMG MPF during the ISO (linear, r2 = 0.62) and CON (quadratic, R2 = 0.86) muscle actions (Fig. 3). Kouzaki et al. (1999) reported mean decreases in EMG MPF values following 50 maximal ISO muscle actions that paralleled decreases in torque during the first 30 repetitions. Our results were consistent with those of Kouzaki et al. (1999) that indicated EMG MPF (r2 = 0.62) and torque (r2 = 0.95) exhibited similar linear decreases across the fatiguing ISO muscle actions. Ebersole et al. (2006) also found that EMG MPF (quadratic, R2 = 0.85) tracked decreases in torque (quadratic, R2 = 0.97) across repeated maximal CON muscle actions. In addition, Crenshaw et al. (2000) reported decreases in EMG MPF (r = 0.49 to 0.82) across 100 maximal CON repetitions that were ‘‘nearly identical’’ (p. 125) to the decreases in torque. Our findings were in agreement with those of Ebersole et al. (2006) and Crenshaw et al. (2000) that showed EMG MPF (R2 = 0.86) and torque (R2 = 0.97) exhibited similar quadratic decreases during the CON fatigue protocol. Therefore, the present results and those of others (Crenshaw et al., 2000; Ebersole et al., 2006; Kouzaki et al., 1999) indicated that changes in EMG MPF during repeated maximal ISO and CON muscle actions tracked fatigue-related decreases in torque. Previous studies (Broman et al., 1985) have shown that fatigue is reflected in the frequency domain of the EMG signal by decreases in EMG MPF that are due to decreases in muscle fiber conduction velocity. The underlying mechanism responsible for decreases in muscle fiber conduction velocity and EMG MPF is likely a
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fatigue-induced increase in interstitial potassium that leads to a progressive loss of membrane excitability (Fortune and Lowery, 2007; vanDieën et al., 2009). Theoretically, during repeated maximal muscle actions, the loss of membrane excitability would result in the inactivation and de-recruitment of the fatigued motor units. Therefore, due to the accumulation of metabolic byproducts such as potassium that are associated with fatigue, concurrent decreases in EMG MPF and torque across multiple ISO and CON repetitions would be expected. In summary, the findings of the present investigation suggested that the mechanisms of fatigue were similar between the repeated maximal ISO and CON muscle actions. In addition, the decreases in EMG amplitude following 10–15 repetitions during both the ISO and CON muscle actions indicated there was de-recruitment of activated motor units or a reduction in their firing rates. Our findings also suggested that MMG amplitude may be a useful indicator of fatigue during CON, but not intermittent ISO muscle actions. In contrast, the EMG and MMG frequency responses paralleled the decreases in torque during both the ISO and CON muscle actions. Conflict of interest statement The authors have no conflicts of interest. Acknowledgements There were no funding sources. References Babault N, Desbrosses K, Fabre MS, Michaut A, Pousson M. Neuromuscular fatigue development during maximal concentric and isometric knee extensions. J Appl Physiol 2006;100:780–5. Bajaj C, Madeleine P, Sjøgaard G, Arendt-Nielsen L. Assessment of postexercise soreness by electromyography and mechanomyography. J Pain 2002;3(2):126–36. Barry DT, Geiringer SR, Ball RD. Acoustic myography: a non-invasive monitor of motor fatigue. Muscle Nerve 1985;8:189–94. Basmajian JV, DeLuca CJ. Muscles alive: their functions revealed by electromyography. Baltimore: Williams & Wilkins; 1985. Broman H, Bilotto G, De Luca CJ. A note on the noninvasive estimation of muscle fiber conduction velocity. IEEE Trans Biomed Eng 1985;BME-32(5):341–4. Crenshaw AG, Gerdle B, Heiden M, Karlsson S, Fridén J. Intramuscular pressure and electromyographic responses of the vastus lateralis muscle during repeated maximal isokinetic knee extensions. Acta Physiol Scand 2000;170:119–26. Dalton PA, Comerford MJ, Stokes MJ. Acoustic myography of the human quadriceps muscle during intermittent fatiguing activity. J Neurol Sci 1992;109:56–60. Ebersole KT, O’Connor KM, Wier AP. Mechanomyographic and electromyographic responses to repeated concentric muscle actions of the quadriceps femoris. J Electromyogr Kinesiol 2006;16:149–57. Edman KA. Mechanism underlying double-hyperbolic force-velocity relation in vertebrate skeletal muscle. Adv Exp Med Biol 1992;332:667–76. Edwards RH. Human muscle function and fatigue. Ciba Found Symp 1981;82:1–18. Edwards RH, Hill DK, Jones DA. Heat production and chemical changes during isometric contractions of the human quadriceps muscle. J Physiol 1975;251(2):303–15. EMG 16. 16 channels surface electromyographic signal amplifier (user’s manual). Turin (Italy): LISiN Bioengineering Center Polytechnic of Turin – Department of Electronics; 2006. Fortune E, Lowery MM. The effect of extracellular potassium concentration on muscle fiber conduction velocity examined using model simulation. Conf Proc IEEE Eng Med Biol Soc 2007:2726–9. Gladden LB. Lactate metabolism: a new paradigm for the third millennium. J Physiol. 2004;558:5–30. Gordon G, Holbourn AHS. The sounds from single motor units in a contracting muscle. J Physiol 1948;107:456–64. Gray JC, Chandler JM. Percent decline in peak torque production during repeated concentric and eccentric contractions of the quadriceps femoris muscle. J Ortho Sports Phys Ther 1989;2:309–14. Hermens HJ, Freriks B, Merletti R, Stegeman D, Blok J, Rau G, et al. SENIAM European recommendations for surface electromyography: results of the SENIAM project. Enschede, The Netherlands: Roessingh Research and Development; 1999. 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 2009a;181:45–51.
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Hendrix CR, Housh TJ, Zuniga JM, Camic CL, Mielke M, Johnson GO, et al. A mechanomyographic frequency-based fatigue threshold test. J Neurosci Methods 2009b;187(1):1–7. Hisaeda HO, Shinohara M, Kouzaki M, Fukunaga T. Effect of local blood circulation and absolute torque on muscle endurance at two different knee-joint angles in humans. Eur J Appl Physiol 2001;86:17–23. Kimura T, Hamada T, Massako Ueno L, Moritani T. Changes in contractile properties and neuromuscular propagation evaluated by simultaneous mechanomyogram and electromyogram during experimentally induced hypothermia. J Electromyogr Kinesiol 2003;13(5):433–40. 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 1999;80:9–15. Kulig K, Andrews JG, Hay JG. Human strength curves. Exer Sport Sci Rev 1984;12:417–66. Lynn PA. Direct on-line estimation of muscle fiber conduction velocity by surface electromyography. IEEE Trans Biomed Eng 1979;BME-26(10): 564–71. MacLaren DP, Gibson H, Parry-Billings M, Edwards RH. A review of metabolic and physiological factors in fatigue. Exer Sports Sci Rev 1989(1):29–66. Mills KR. Power spectral analysis of electromyogram and compound muscle action potential during muscle fatigue and recovery. J Physiol 1982;326:401–9. Nilsson J, Tesch P, Thorstensson A. Fatigue and EMG of repeated fast voluntary contractions in man. Acta Physiol Scand 1977;101:194–8. 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, 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. Perry-Rana SR, Housh TJ, Johnson GO, Bull AJ, Berning JM, Cramer JT. MMG and EMG responses during fatiguing isokinetic muscle contractions at different velocities. Muscle Nerve 2002;26:367–73. Perry-Rana SR, Housh TJ, Johnson GO, Bull AJ, Cramer JT. MMG and EMG responses during 25 maximal, eccentric, isokinetic muscle actions. Med Sci Sports Exerc 2003;35(12):2048–54. Petitjean M, Maton B, Cnockaert JC. Evaluation of human dynamic contraction by phonomyography. J Appl Physiol 1992;73:2567–73. Robergs RA, Ghiasvand F, Parker D. Biochemistry of exercise-induced metabolic acidosis. Am J Physiol Regul Integr Comp Physiol 2004;287:R502–16. Stokes MJ, Dalton PA. Acoustic myography for investigating human skeletal muscle fatigue. J Appl Physiol 1991;71(4):1422–6. vanDieën JH, Westebring-van der Putten EP, Kingma I, de Looze MP. Low-level activity of the trunk extensor muscles causes electromyographic manifestations of fatigue in absence of decreased oxygenation. J Electromyogr Kinesiol 2009;19:398–406. Wretling ML, Larsén KH. Mechanical output and electromyographic parameters in males and females during fatiguing knee-extensions. Int J Sports Med 1998;19:401–7.
Clayton L. Camic received a BS (2001) degree in Exercise Science from Morehead State University, MS (2003) degree in Exercise Physiology from the University of Wyoming, and PhD (2011) degree from the University of Nebraska-Lincoln. He is currently an Assistant Professor in the Exercise and Sport Science Department at the University of Wisconsin-La Crosse and his main research interests include evaluation of muscle function and fatigue using electromyography as well as sports nutrition.
Terry J. Housh received a BA (1977) degree in Physical Education from Doane College, Crete, NE, and MPE (1979) and Ph.D. (1984) degrees from the University of Nebraska-Lincoln. He is a Fellow of the American College of Sports Medicine, Fellow in the research Consortium of AAHPERD, and received the 1998 Outstanding Sport Scientist Award from the National Strength and Conditioning Association. Presently, he is a Professor in the Department of Nutrition and Health Sciences, Director of the Exercise Physiology Laboratory, and CoDirector of the Center for Youth Fitness and Sports Research at the University of Nebraska-Lincoln. His main areas of research are muscle function, fatigue, and growth and development in young athletes.
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C.L. Camic et al. / Journal of Electromyography and Kinesiology 23 (2013) 342–348 Jorge M. Zuniga received a BS (2003) degree in Physical Education from ‘‘Cardenal R. Silva Henrriquez’’ Catholic University; Santiago, Chile, MS in Exercise Sciences (2007) from the University of Nebraska at Omaha, and Ph.D. in Exercise Physiology from the University of Nebraska-Lincoln. He is a member of the American College of Sports Medicine and the National Strength and Conditioning Association. He is currently an assistant professor at Creighton University and his main research interests include evaluation of muscle function and fatigue using electromyography and mechanomyography during dynamic muscle actions (i.e., cycling and running). It is expected that this work will lead to the development and application of neuromuscular fatigue thresholds for the assessment and improvement of athletic performance.
C. Russell Hendrix received his B.S.E. (1992) in Biology from Emporia State University, an M.S.E. (2002) in Physical Education from Northwest Missouri State University. He is currently a doctoral student in exercise physiology at the University of Nebraska–Lincoln and his main research interests include evaluation of muscle function using electromyography and mechanomyography, especially as they relate to fatigue thresholds. He is a member of the American College of Sports Medicine, an ACSM–certified Health Fitness Specialist, and a member of the National Strength and Conditioning Association.
Haley C. Bergstrom received a BS (2009) degree in Exercise Science from Doane College, Crete, Nebraska and MS (2011) degree in Exercise Physiology from the University of Nebraska-Lincoln. She is a member of the American College of Sports Medicine and the National Strength and Conditioning Association. She is currently a doctoral student in Exercise Physiology at the University of Nebraska-Lincoln and her main research interests include the evaluation of cardiovascular, metabolic, neuromuscular, and perceptual responses during dynamic fatiguing exercise.
Daniel A. Traylor received a BS (2004) degree in Health Promotion from Appalachian State University and MS (2008) degree in Sports Medicine from Armstrong Atlantic State University. He is currently a doctoral student in Exercise Physiology at the University of Nebraska-Lincoln and his main research interests include short-term resistance training and the assessment of muscle fatigue using electromyography.
Richard J. Schmidt received a BS (1969), M.Ed. in Physical Education (1964) and a Ph.D. (1972) in Education (Psychological and Cultural Studies) from the University Nebraska–Lincoln. He is a Fellow in the research Consortium of AAHPERD. He is currently an Associate Professor of Nutrition and Health Sciences at the University of Nebraska-Lincoln. His main areas of research are Exercise testing, clinical exercise physiology, occupational physiology, military & law enforcement sports medicine.
Glen O. Johnson received a BS (1960) and MS (1964) degrees from Winona State University, Winona, MN, and a Ph.D. (1972) from the University of Iowa. He is a Fellow of the American College of Sports Medicine and a Fellow in the research Consortium of AAHPERD. He is currently a Professor of Nutrition and Health Sciences at the University of Nebraska-Lincoln.