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Relationships between the mechanomyographic amplitude patterns of response and concentric isokinetic fatiguing tasks of the leg extensors

This content has been downloaded from IOPscience. Please scroll down to see the full text. 2013 Physiol. Meas. 34 1293 (http://iopscience.iop.org/0967-3334/34/10/1293) View the table of contents for this issue, or go to the journal homepage for more

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IOP PUBLISHING

PHYSIOLOGICAL MEASUREMENT

Physiol. Meas. 34 (2013) 1293–1301

doi:10.1088/0967-3334/34/10/1293

Relationships between the mechanomyographic amplitude patterns of response and concentric isokinetic fatiguing tasks of the leg extensors Michael A Cooper 1 , Trent J Herda 1,3 , John P Vardiman 2 , Phillip M Gallagher 2 and Andrew C Fry 1 1

Neuromechanics Laboratory, Department of Health, Sport and Exercise Sciences, University of Kansas, Lawrence, KS, USA 2 Applied Physiology Laboratory, Department of Health, Sport and Exercise Sciences, University of Kansas, Lawrence, KS, USA E-mail: [email protected], [email protected], [email protected], [email protected] and [email protected]

Received 14 June 2013, accepted for publication 20 August 2013 Published 11 September 2013 Online at stacks.iop.org/PM/34/1293 Abstract The purpose of the present study was to examine possible correlations between the b terms (slopes) form the log-transformed mechanomyographic amplitude (MMGRMS)–force relationships and the fatigue index calculated from 50 maximal concentric contractions. Forty healthy subjects (age = 21 ± 2 yr) performed isometric ramp contractions from 5% to 85% of their maximal voluntary contraction followed by a 50-repetition concentric fatigue protocol of the leg extensors, fatigue index (%) was calculated from the 50-repetitions. MMG was recorded during the ramp contractions from the vastus lateralis (VL) and rectus femoris (RF). The b terms (slopes) were calculated from the log-transformed MMGRMS–force relationships. Correlations were performed comparing the b terms from the MMGRMS–force relationships for the VL and RF with the fatigue index. Significant positive correlations were found among the b terms from the MMGRMS–force relationships for the VL (p = 0.007, r = 0.417) and RF (p = 0.014, r = 0.386) with the fatigue index. The b terms from the log-transformed MMGRMS–force relationships for the VL and RF may have reflected muscle fiber type composition and, thus, correlated with the fatigue index. This adds further support that the MMGRMS–force relationships may reflect muscle fiber type composition. Keywords: mechanomyography, muscle fiber type, fatigue, isokinetic

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1. Introduction Surface mechanomyography (MMG) is a noninvasive tool that has been used to study muscle function (Behm et al 2001, Orizio 1993, Orizio et al 1989). MMG, has been defined as the recording of low-frequency lateral oscillations of muscle fibers that occur during a contraction (Barry and Cole 1990, Orizio 1993). Barry and Cole (1990) and Orizio (1993) have suggested that these oscillations are manifested through (a) the gross lateral movement of the muscle at the initiation of the contraction, (b) smaller subsequent lateral oscillations occurring at the resonant frequency of the muscle, and (c) dimensional changes in the active fibers. Previously, there have been numerous studies that examined the force-related amplitude responses of the MMG signal (Akataki et al 2003, Herda et al 2009, Ryan et al 2007, 2008). It has been suggested that the MMG amplitude–force relationships may reflect the motor unit activation strategies of the muscle (Akataki et al 2004, Ryan et al 2008). Specifically, there are rapid rises in the amplitude of the MMG signal when the muscle is primarily using motor unit recruitment to increase force, while there is no change or even slight decreases in the amplitude of the signal when the modulation of firing rates is the primary mechanism to increase force (Orizio et al 2003, Ryan et al 2007). Therefore, it has been suggested that the MMG amplitude–force relationships may be able to distinguish differences between muscles with known motor unit activation strategy differences (Akataki et al 2003, Beck et al 2008, Yoshitake and Moritani 1999). Herda et al (2009) suggested that log-transformed MMG amplitude–force relationships might provide an alternative, quantitative method for describing the force-related patterns of responses for MMG amplitude. The b term (slope) of a linear relationship in which both X and Y variables are log-transformed indicates whether the original, non-transformed relationship is linear or nonlinear (Herda et al 2009). If the b term is equal to 1 (or if the 95% confidence interval (CI) of the slope contains 1), then the rate of change in Y equals the rate of change in X. If the b term is less than 1 and the 95% CI of the slope does not contain 1, the rate of change in Y is less than the rate of change in X and the curve decelerates across the force spectrum. Previous studies have reported the MMG amplitude–force relationships as either linear or nonlinear with a plateau or decrease in MMG amplitude at higher force levels (Beck et al 2004, 2008, Coburn et al 2004, Ryan et al 2007). Therefore, it would be expected that these patterns would have b terms of  1. Indeed, Herda et al (2010) and Cooper and Herda (2013) reported that b terms were  1 and were dependent on the fiber type composition of the muscles. For example, individuals with a greater percentage of type I myosin heavy chain (MHC) had lower b terms than individuals with a greater percentage of type II MHC of the vastus lateralis (VL) (Herda et al 2010). It has been previously reported that there are differences in the fatigability between type I and type II muscle fibers (Burke et al 1973, Hulten et al 1975, Linssen et al 1991). Thorstensson and Karlsson (1976) introduced a fatiguing protocol that included 50 maximal concentric isokinetic contractions at 180◦ s–1 to calculate a fatigue index (FI) for an individual. The authors correlated the FI with the muscle fiber type composition of the individual and reported a positive correlation coefficient of 0.86. Thus, individuals with a greater percentage of fast-twitch fibers had a greater FI than the individuals with a greater percentage of slowtwitch fibers. In theory, since the b term from the MMGRMS–force relationships have been used to distinguish fiber type compositions. Therefore, the purpose of the present study is to examine possible correlations among the b terms from the log-transformed MMGRMS versus force relationships for the VL and rectus femoris (RF) and the FI calculated from 50 maximal concentric isokinetic contractions at 180◦ s–1 of the leg extensors. We hypothesize that the b terms from the log-transformed MMGRMS versus force relationships for the VL and RF will

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have relationships with the FI calculated from the fatiguing protocol utilized in Thorstensson and Karlsson (1976). 2. Methods 2.1. Participants Seventeen male (mean ± SD; age = 21 ± 2 yr, weight = 81.9 ± 13.6 kg, height = 1.8 ± 0.09 m) and 23 female (age = 21 ± 2 yr, weight = 67.3 ± 8.9 kg, height = 1.69 ± 0.07 m) healthy subjects volunteered to participate in this study. All subjects were screened for any current or ongoing neuromuscular diseases or musculoskeletal injuries that involve the ankle, knee or hip joints. This study was approved by the University Institutional Review Board for the protection of human subjects, and all participants were required to complete a health history questionnaire and sign a written informed consent document. 2.2. Research design Isometric maximal voluntary contractions (MVC), isometric ramp contractions, and a concentric isokinetic fatigue protocol of the right leg extensors were performed during one experimental visit. Isometric and isokinetic strength for the right leg extensor muscles were measured using the force signal from a load cell (LC402, Omegadyne, Inc., Sunbury, OH) that was fitted to a Biodex System 3 isokinetic dynamometer (Biodex Medical Systems, Inc., Shirley, NY). The participants sat with restraining straps over the pelvis, trunk, and contralateral thigh, and the lateral condyle of the femur was aligned with the input axis of the dynamometer in accordance with the Biodex User’s Guide (Biodex Pro manual, Applications/Operations. Biodex Medical Systems, Inc., Shirley, NY, 1998). All isometric leg extensor strength assessments were performed at a leg flexion angle of 90◦ (i.e. 90◦ below full leg extension). 2.3. Isometric ramp contraction Participants performed two isometric MVCs with strong verbal encouragement for motivation with 3–5 m rest between trials. The highest force output between the two trials was used to represent the MVC value. After the MVC trials, each participant performed two to four 6 s isometric ramp muscle actions separated by 2–4 min rest. During the ramp muscle actions, participants were required to track their force production on a computer monitor placed in front of them that displayed their real-time, digitized force signal overlaid onto a programmed ramp template. The ramp template consisted of a 5 s horizontal baseline at 5% MVC and a 6 s linearly increasing ramp line from 5% to 100% MVC. For a ramp trial to be used for analysis, the following criteria must have been met: (a) force reaching at least 85% of the MVC and (b) a tracking error less than 3% around the ramp template as visually inspected by an experienced investigator. All software programs were custom-written with LabVIEW v 8.5 (National Instruments, Austin, TX). 2.4. Isokinetic fatigue protocol For the fatiguing protocol, subjects performed 50 consecutive maximal concentric isokinetic leg extension muscle actions at 180◦ s–1 with the right leg as described by Thorstensson and Karlsson (1976). The active range of motion was standardized from 90◦ to 180◦ of knee flexion and extension. Subjects were instructed to perform consecutive leg extensions with

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maximal effort and to resume the starting position passively between each contraction. Every contraction lasted 0.5 s and the passive phase approximately 0.7 s. The FI was calculated with the following equation:   Initial Peak Force – Final Peak Force × 100. FI = Initial Peak Force Peak force (PF) was determined for each of the 50-repetitions during the extension muscle actions as the highest 10 ms average force value that occurred during each force curve. The initial PF was calculated as the average of the three highest PF values that occurred during the first ten repetitions, whereas the final PF will represent the average of the three lowest PF values that occurred during the final ten repetitions. 2.5. Mechanomyography (MMG) An active miniature accelerometer (EGAS-FS-10-/V05, Measurement Specialties, Inc., Hampton, VA) that was preamplified with a gain of 200, frequency response of 20–200 Hz, sensitivity of 68.5 mV/(m s)−2 and range of ± 98.1 ms−2 was used to detect the MMG signal. Accelerometers were placed on the VL and RF on the lateral/anterior portion of the muscle at 50% of the distance between the greater trochanter and lateral condyle of the femur. Double-sided adhesive tape was used to attach the accelerometer to the skin. 2.6. Signal processing The MMG (m s−2) and force (N) signals were simultaneously sampled at 2 kHz with a Biopac data acquisition system (MP150, Biopac systems, Inc., Santa Barbara, CA) during each voluntary muscle action. All subsequent signals were then stored and processed off-line with custom written LabVIEW 8.5 software (National Instruments, Austin, TX). The MMG signals were bandpass filtered (fourth-order Butterworth) at 5–100 Hz, whereas the force signal was lowpass filtered (fourth-order Butterworth) at 20 Hz. During the 6 s isometric ramp contraction consecutive, non-overlapping 0.25 s epochs were analyzed for the force and MMG signal. The amplitude of the MMG (MMGRMS) was quantified by calculating the root-mean-square (RMS) values for each signal epoch. 2.7. Statistical analyses Simple linear regression models were fit to the natural log-transformed MMGRMS–force relationships (10 to 85% of MVC) from the non-fatiguing isometric ramp contractions for the VL and RF. The equation was represented as: ln(Y ) = b(ln[X]) + ln(a),

(1)

where ln(Y) = the natural log of the MMGRMS value, ln(X) = the natural log of the force values, b = slope, and ln(a) = the natural log of the Y-intercept. This can also be expressed as an exponential equation after antilog transformation of both sides of the equation Y = aX b

(2)

where Y = the predicted MMGRMS value, X = force, b = slope of equation (1), and a = the antilog of the Y-intercept from equation (1). Slopes (b) and Y-intercepts (a) were calculated using Microsoft Excel version 2007 (Microsoft, Inc., Redmond, WA). Pearson’s product moment correlations were calculated comparing the b terms from the MMGRMS–force relationships for the VL and RF with the FI (%) calculated from the

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Figure 1. Composite force mean ± SD values for each repetition of the 50-repetition fatigue protocol of the leg extensors. Table 1. Mean ± standard deviation and 95% confidence intervals for the slopes (b term) from the log-transformed mechanomyographic amplitude (MMGRMS)–force relationships for the vastus lateralis (VL) and rectus femoris (RF) along with the correlation (r) and significance values (p) between the b terms and fatigue index for each muscle.

b terms VL RF a

0.55 ± 0.24 0.67 ± 0.21

a

b term 95% CI

r

p-value

0.31–0.79 0.46–0.88

0.417 0.386

0.007 0.014

Indicates that the MMGRMS b terms VL is significantly different than that of the RF.

50 maximal concentric isokinetic leg extension muscle actions. In addition, a paired samples t-test was used to examine possible differences between muscles (VL and RF) for the b terms from the MMGRMS–force relationships. 3. Results Table 1 contains the mean ± standard deviation (SD), Pearson’s product moment correlations (r), and p values for the relationships among the FI and b terms from the MMGRMS– force relationships for the VL and RF. Figure 1 contains the composite mean ± SD force responses of the leg extensors for each repetition of the 50-repetition fatigue protocol of the leg extensors. Correlations among the FI and the b terms from the MMGRMS–force relationships were significant for the RF (p = 0.014, r = 0.386) (figure 2(a)) and VL (p = 0.007, r = 0.417) (figure 2(b)). In addition, the paired samples t-test indicated that the b terms from the MMGRMS–force relationships for the RF (0.66 ± 0.21) were greater than (p < 0.001) the VL (0.53 ± 0.24). 4. Discussion The findings of the present study are the b terms from the VL and RF MMGRMS–force relationship were significantly correlated with the FI calculated from 50 maximal concentric isokinetic contractions at 180◦ s–1 and the b terms were greater for the RF than the VL. Thus, supporting our hypothesis that the FI and the b terms from the MMGRMS–force relationships

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(a)

(b)

Figure 2. The plotted relationships between the fatigue index (%) and the b terms from the mechanomyographic-amplitude patterns of response for the vastus lateralis (a) and rectus femoris (b).

may be correlated on the basis that each measurement has previously distinguished between muscle fiber type compositions. A previous study, Thorstensson and Karlsson (1976), reported a correlation (r = 0.86) between the fatigability of the leg extensors with the relative distribution of muscle fiber type in the VL. Specifically, the authors reported that the relative reduction in force during a concentric isokinetic protocol of 50-repetition at 180◦ s–1 of the leg extensors was related to the relative percentage of type II muscle fibers of the VL. The leg extensors have been generally considered mixed fiber type muscles (Staron et al 2000). Although, variations in fiber type have been reported among individuals, such as, Herda et al (2010) reported differences in myosin chain expression between the aerobically-(type I MHC = 72.6 ± 17.5) and resistance-trained (type I MHC = 40.9 ± 9.7) individuals. Previous research has

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demonstrated that differences in fiber type can influence the fatiguing characteristics of the muscle (Edstrom and Kugelberg 1968, Hulten et al 1975, Thorstensson and Karlsson 1976). For example, Kugelberg and Edstrom (1968) reported differences in glycogen consumption between fast (glycolytic) and slow (oxidative) fibers during electrical stimulation, such as, glycogen consumption was exhausted faster during stimulation of the fast-twitch than the slow twitch fibers of the anterior tibial muscle of rats. Others have demonstrated that skeletal muscle made up of primarily fast-twitch fibers results in a rapid decline in twitch and tetanic tension during repetitive electrical stimulation. Slow-twitch muscle fibers, however, only exhibited minor fatigue during repetitive stimulation (Burke and Nelson 1971). Due to these physiological differences between muscle fiber types, individuals with a greater percentage of fast-twitch fibers display greater fatigue than the individuals with a greater percentage of slow-twitch fibers during an isokinetic fatiguing protocol (Thorstensson and Karlsson 1976, Viitasalo and Komi 1981). The force-related amplitude response of the MMG signal is reported to be influenced by motor unit recruitment and rate coding. Specifically, MMGRMS increases rapidly as additional motor units are being recruited to increase force, whereas slight decreases or plateaus in the signal occur when rate coding is the primary mechanism to increase force. Therefore, the MMG amplitude–force relationships has been able to distinguish differences between muscles with known motor unit activation strategy differences, such as, muscles with fiber type differences (Akataki et al 2003, Beck et al 2008, Yoshitake and Moritani 1999). Previously, Herda et al (2010) reported that the b terms reflected the MHC expression of the VL indicating that individuals with a greater percentage of type I MHC (type I MHC = 72.6 ± 17.5) had lower b terms (b term = 0.325 ± 0.06) than individuals with a greater percentage of type II MHC (type II MHC = 59.0 ± 9.5, b term = 0.856 ± 0.28) of the VL. Furthermore, Cooper and Herda (2013) reported a significant difference between muscles with known fiber type differences, such as, the b terms for the MMGRMS–force relationships were reported to be lower for muscles composed of primarily type I muscle fibers (first dorsal interosseous, b term = 0.17 ± 0.20) than more mixed fiber type muscles (VL and RF, b terms = 0.78 ± 0.16, 0.82 ± 0.28), indicating that the b term may reflect differences between muscles that rely primarily on either motor unit recruitment or rate coding later in the force spectrum. Therefore, the b terms from the MMGRMS–force relationships have detected differences in muscle fiber type on the basis of motor unit activation strategies, unlike, the isokinetic fatigue protocol that relies on the metabolic differences of the muscle to determine fiber type. Although these tests examine different characteristics of muscle to distinguish between muscle fiber types, in the present study, there were significant positive correlations between the FI from the concentric isokinetic fatiguing test and the b terms from the MMGRMS–force relationships for the RF (r = 0.386, p = 0.014) and VL (r = 0.417, p = 0.007). Therefore, a greater MMGRMS b term would coincide with a greater FI calculated from the concentric isokinetic fatiguing task. The correlations were rather small, however, when considering the extraneous factors, such as, subject effort level during the fatiguing and MVCs (i.e., the basis for the ramp contraction) and the measurements were either concentric or isometric contractions that examined different muscle characteristics (metabolic versus activation strategies), the correlation does provide compelling evidence that the MMGRMS–force relationships may reflect muscle fiber type composition. Ryan et al (2007) examined the MMGRMS–torque relationships of the leg extensors (VL and RF) and observed clear differences in the patterns of response for MMGRMS at higher force levels. Differences in muscle fiber type composition have been attributed to the differences between the MMGRMS–force relationships reported between muscles. For example, Yoshitake and Moritani (1999) reported force related increases in MMG amplitude to 80% MVC for

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the gastrocnemius muscle, whereas MMGRMS peaked at 60% MVC for the soleus muscle. In support of these observations, Johnson et al (1973) reported that at the surface (superficial location) of the muscle there was a higher percentage of type II fibers for the RF compared to the VL in five of the six post-mortem individuals (age = 17–30) and Housh et al (1996) indicated that the fatigue responses were greater for the RF than the VL during cycle ergometer. In theory, differences in superficial muscle fiber type composition between the VL and RF certainly could be reflected in the shape of the MMGRMS-relationships. Previously, it has been suggested that muscle architecture and motor unit territorial distribution has influenced the MMGRMS patterns of response (Cescon et al 2004). Similar to the present study, Cescon et al (2004) reported distinctly different MMGRMS–force relationships for the biceps brachii (BB) and tibialis anterior (TA) despite both being mixed fiber type muscles. The authors suggested that the differences in the patterns of response may have been influenced by the deeper location of larger and higher threshold motor units for the TA in comparison to the BB (HenrikssonLarsen et al 1983). In addition, the RF is a biarticular muscle, which may also contribute to differences in the patterns of response in comparison to the VL. Nevertheless, future research is needed to clearly understand the mechanisms that resulted in the differences in b term for the MMGRMS–force relationships between the VL and RF in the present study. In the current, study the b terms from the log-transformed MMGRMS–force relationships for the VL and RF had significant correlations with the FI calculated from a concentric isokinetic fatigue protocol of the leg extensors. Thus, this study adds further support that the b terms from the MMGRMS–force relationships may reflect muscle fiber type composition. References Akataki K, Mita K and Watakabe M 2004 Electromyographic and mechanomyographic estimation of motor unit activation strategy in voluntary force production Electromyogr. Clin. Neurophysiol. 44 489–96 PMID: 15646006 Akataki K, Mita K, Watakabe M and Itoh K 2003 Mechanomyographic responses during voluntary ramp contractions of the human first dorsal interosseous muscle Eur. J. Appl. Physiol. 89 520–5 Barry D T and Cole N M 1990 Muscle sounds are emitted at the resonant frequencies of skeletal muscle IEEE Trans. Biomed. Eng. 37 525–31 Beck T W, Housh T J, Fry A C, Cramer J T, Weir J P, Schilling B K, Falvo M J and Moore C A 2008 The influence of myosin heavy chain isoform composition and training status on the patterns of responses for mechanomyographic amplitude versus isometric torque J. Strength Cond. Res. 22 818–25 Beck T W, Housh T J, Johnson G O, Weir J P, Cramer J T, Coburn J W and Malek M H 2004 Mechanomyographic amplitude and mean power frequency versus torque relationships during isokinetic and isometric muscle actions of the biceps brachii J. Electromyogr. Kinesiol. 14 555–64 Behm D, Power K and Drinkwater E 2001 Comparison of interpolation and central activation ratios as measures of muscle inactivation Muscle Nerve 24 925–34 Burke R E, Levine D N, Tsairis P and Zajac F E 3rd 1973 Physiological types and histochemical profiles in motor units of the cat gastrocnemius J. Physiol. 234 733–48 Burke R E and Nelson P G 1971 Accommodation to current ramps in motoneurons of fast and slow twitch motor units Int. J. Neurosci. 1 347–56 Cescon C, Farina D, Gobbo M, Merletti R and Orizio C 2004 Effect of accelerometer location on mechanomyogram variables during voluntary, constant-force contractions in three human muscles Med. Biol. Eng. Comput. 42 121–7 Coburn J W, Housh T J, Cramer J T, Weir J P, Miller J M, Beck T W, Malek M H and Johnson G O 2004 Mechanomyographic time and frequency domain responses of the vastus medialis muscle during submaximal to maximal isometric and isokinetic muscle actions Electromyogr. Clin. Neurophysiol. 44 247–55 PMID: 15224821 Cooper M A and Herda T J 2013 Muscle related differences in MMG-force relationships are model dependent Muscle Nerve (doi:10.1002/mus.23896) Edstrom L and Kugelberg E 1968 Histochemical composition, distribution of fibres and fatiguability of single motor units. Anterior tibial muscle of the rat J. Neurol. Neurosurg. Psychiatry 31 424–33 Henriksson-Larsen K B, Lexell J and Sjostrom M 1983 Distribution of different fibre types in human skeletal muscles: I. Method for the preparation and analysis of cross-sections of whole tibialis anterior Histochem. J. 15 167–78

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Herda T J, Housh T J, Fry A C, Weir J P, Schilling B K, Ryan E D and Cramer J T 2010 A noninvasive, log-transform method for fiber type discrimination using mechanomyography J. Electromyogr. Kinesiol. 20 787–94 Herda T J, Weir J P, Ryan E D, Walter A A, Costa P B, Hoge K M, Beck T W, Stout J R and Cramer J T 2009 Reliability of absolute versus log-transformed regression models for examining the torque-related patterns of response for mechanomyographic amplitude J. Neurosci. Methods 179 240–6 Housh T J, deVries H A, Johnson G O, Evans S A, Housh D J, Stout J R, Bradway R M and Evetovich T K 1996 Neuromuscular fatigue thresholds of the vastus lateralis, vastus medialis and rectus femoris muscles Electromyogr. Clin. Neurophysiol. 36 247–55 Hulten B, Thorstensson A, Sjodin B and Karlsson J 1975 Relationship between isometric endurance and fibre types in human leg muscles Acta Physiol. Scand. 93 135–8 Johnson M A, Polgar J, Weightman D and Appleton D 1973 Data on the distribution of fibre types in thirty-six human muscles. An autopsy study J. Neurol. Sci. 18 111–29 Kugelberg E and Edstrom L 1968 Differential histochemical effects of muscle contractions on phosphorylase and glycogen in various types of fibres: relation to fatigue J. Neurol. Neurosurg. Psychiatry 31 415–23 Linssen W H, Stegeman D F, Joosten E M, Binkhorst R A, Merks M J, ter Laak H J and Notermans S L 1991 Fatigue in type I fiber predominance: a muscle force and surface EMG study on the relative role of type I and type II muscle fibers Muscle Nerve 14 829–37 Orizio C 1993 Muscle sound: bases for the introduction of a mechanomyographic signal in muscle studies Crit. Rev. Biomed. Eng. 21 201–43 PMID: 8243092 Orizio C, Gobbo M, Veicsteinas A, Baratta R V, Zhou B H and Solomonow M 2003 Transients of the force and surface mechanomyogram during cat gastrocnemius tetanic stimulation Eur. J. Appl. Physiol. 88 601–6 Orizio C, Perini R and Veicsteinas A 1989 Muscular sound and force relationship during isometric contraction in man Eur. J. Appl. Physiol. Occup. Physiol. 58 528–33 Ryan E D, Beck T W, Herda T J, Hartman M J, Stout J R, Housh T J and Cramer J T 2008 Mechanomyographic amplitude and mean power frequency responses during isometric ramp versus step muscle actions J. Neurosci. Methods 168 293–305 Ryan E D, Cramer J T, Housh T J, Beck T W, Herda T J, Hartman M J and Stout J R 2007 Inter-individual variability among the mechanomyographic and electromyographic amplitude and mean power frequency responses during isometric ramp muscle actions Electromyogr. Clin. Neurophysiol. 47 161–73 PMID: 17557649 Staron R S, Hagerman F C, Hikida R S, Murray T F, Hostler D P, Crill M T, Ragg K E and Toma K 2000 Fiber type composition of the vastus lateralis muscle of young men and women J. Histochem. Cytochem. 48 623–9 Thorstensson A and Karlsson J 1976 Fatiguability and fibre composition of human skeletal muscle Acta Physiol. Scand. 98 318–22 Viitasalo J T and Komi P V 1981 Effects of fatigue on isometric force- and relaxation-time characteristics in human muscle Acta Physiol. Scand. 111 87–95 Yoshitake Y and Moritani T 1999 The muscle sound properties of different muscle fiber types during voluntary and electrically induced contractions J. Electromyogr. Kinesiol. 9 209–17