WAVELET ANALYSIS OF QUADRICEPS POWER SPECTRA AND AMPLITUDE UNDER VARYING LEVELS OF CONTRACTION INTENSITY AND VELOCITY RONALD CROCE, PhD,1 JOHN MILLER, PhD,1 KENT CHAMBERLIN, PhD,2 DAVID FILIPOVIC, MS,2 and WAYNE SMITH, PhD2 1

Motor Control and Biomechanics Laboratory, Department of Kinesiology, University of New Hampshire, Durham, New Hampshire 03824, USA 2 Department of Electrical and Computer Engineering, University of New Hampshire, Durham, New Hampshire, USA Accepted 26 February 2014 ABSTRACT: Introduction: We investigated the effect of contraction intensity [100%, 75%, 50%, and 25% maximum voluntary contraction (MVC)] and movement velocity (50 , 100 , 200 , and 400 /s) on surface electromyography root mean square amplitude (SEMGRMS) and median frequency (SEMGMDF) of rectus femoris (RF), vastus lateralis (VL), and vastus medialis (VM). Methods: SEMGs during knee extension were resolved into their respective frequencies using wavelet transformations. Results: RF, VL, and VM muscles displayed increased SEMGMDF as contraction intensity increased from 25% to 50% MVC and from 75% to 100% MVC, and each muscle displayed its own unique frequency shifting patterns. The SEMGMDF was not influenced by movement velocity. SEMGRMS increased in all 3 muscles as contraction intensity increased and was influenced by movement velocity, with the highest values observed at 400 and 200 /s. Conclusions: We infer that increasing contraction intensity facilitates greater recruitment of fast-twitch muscle fibers, but there are differing responses in RF, VL, and VM muscles. Muscle Nerve 50: 844–853, 2014

During voluntary muscular contractions, several mechanisms are utilized by which a muscle increases contraction force. This is accomplished by increasing motor unit firing rate or firing frequency (often referred to as rate coding), by increasing the number of motor units recruited, and by a combination of these. Moreover, as more motor units are recruited, more of them are engaged that can innervate muscle fiber types more acclimated to producing force and power (type II motor units). Taken as a whole, these mechanisms are also involved in how a muscle increases velocity of movement and how a given muscle responds to fatiguing contractions. Abbreviations: ANOVA, analysis of variance; CWT, continuous wavelet transform; DFT, discrete Fourier transform; FFT, fast Fourier transform; FT, fast-twitch; QF, quadriceps femoris muscle; RF, rectus femoris muscle; SEMG, surface electromyography; SEMGAMP, surface electromyography signal amplitude; SEMGINT, integration of surface electromyography signal; SEMGRMS, root mean square of surface electromyography signal; SEMGPSD, power spectra density of surface electromyography signal; SEMGMDF, median frequency of surface electromyography power spectra; SEMGMNF, mean frequency of surface electromyography power spectra; ST, type I slow-twitch muscle fibers; STFT, short-time Fourier transform; VL, vastus lateralis muscle; VM, vastus medialis muscle; WT, wavelet transform Key words: electromyography; isokinetic; power spectrum; quadriceps; wavelet transform Correspondence to: R. Croce; e-mail: [email protected] C 2014 Wiley Periodicals, Inc. V

Published online 2 March 2014 in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/mus.24230

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SEMG Quadriceps Wavelet Analysis

Surface electromyography (SEMG) is a noninvasive procedure for investigating the degree to which these 2 mechanisms are involved in controlling voluntary muscular contractions. SEMG produces a time waveform with an amplitude and frequency content that provides information about muscle functioning.1 Myoelectric signal amplitude (SEMGAMP) is used as an indirect measure of overall muscle activity and of muscle contraction force. It is usually reported as either the time integral (SEMGINT) or root mean square (SEMGRMS) of the signal. Frequency distribution, sometimes referred to as power spectral density (SEMGPSD), consists of a series of action potentials firing at specific frequencies and is usually reported as either the median (SEMGMDF) or mean (SEMGMNF) frequency. Frequency analysis decomposes the SEMG signal into its constituent frequency components, which, either individually or in combination, can be associated with conduction velocity of the respective motor units.2–4 According to current theory, a shift in the power spectrum toward higher frequencies is indicative of an increase in average conduction velocity of active muscle fibers, indicating recruitment of larger, type II fast-twitch (FT) motor units, whereas a shift toward lower frequencies indicates a decrease in average conduction velocity and recruitment of smaller, type I slow-twitch (ST) motor units.5–8 Wakeling and Rozitis8 demonstrated significant correlations between intensity of contraction and SEMG frequency in all 3 of the superficial quadriceps muscles. Both Wakeling9 and von Tscharner and Goepfert10 speculated that frequency analysis is applicable for identification of recruitment patterns of different muscle fiber types and as a tracking mechanism for motor unit recruitment strategies, but this viewpoint is not shared universally.11,12 Nonetheless, although still controversial and unsettled, there is reasonable support to suggest that faster type II motor units generate higher SEMG frequencies than do slower type I motor units. The interactive effect of force and velocity on quadriceps femoris (QF) muscle SEMG parameters has yielded inconsistent and equivocal results. MUSCLE & NERVE

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Based on the literature, both force and velocity impact on knee extensor muscle SEMG in the following ways: (1) as muscle force increases, SEMG frequency increases,13–15 decreases,16 does not show any particular association with knee extensor force,16,17 or is primarily dependent on fiber-type distribution within a particular muscle14,18; (2) as velocity of a muscular contraction increases, SEMG frequency shows a tendency to decrease,17,19 remain constant,20,21 or slightly increase at low velocities1; (3) as muscle force increases, SEMG amplitude increases, showing a curvilinear or linear relationship13,15; and (4) as velocity of muscular contraction increases, SEMG amplitude either increases (often plateauing between 180 /s and 300 /s)22–25 or decreases.19,20 Croce et al.1 concluded that the degree to which the central nervous system activates muscle is based on the interplay of both contraction intensity and velocity needed to complete the required motor task. The discrepancies found in the literature can be attributed mostly to differences in the particular QF muscle investigated, electrode placement, velocities tested, and the range of motion over which muscles were tested.1 Moreover, studies of SEMG waveforms in the frequency domain have been performed primarily through spectral analysis using mathematical algorithms such as Fast Fourier Transform (FFT) or Discrete Fourier Transform (DFT). These and all Fourier techniques provide frequency-domain (spectral) information about signals and correlate them with constant-frequency sinusoids. Consequently, Fourier analysis is not well suited for processing signals that are not inherently periodic and time-stationary. Changes in muscle force, length, and contraction speed over time introduce variations in SEMG spectral components that render it non-stationary, thereby creating difficulties when using Fourier analysis to determine frequency content that changes over time. To alleviate this problem researchers identify time windows in which the signal is relatively time-invariant (i.e., the signal is stationary) and then process the signal inside of these short time windows. This technique, known as Short-Time Fourier Transform (STFT), allows researchers to determine spectral content of small or localized portions of a signal over time. One limitation of STFT analysis is that, although it minimizes the non-stationarity of the waveform, it also distorts and limits the range and resolution of observable waveform frequency content. Another, perhaps more significant, limitation of any Fourier analysis is that it assumes the signal being analyzed is comprised of the sum of sinusoids of harmonically related frequencies. Although any waveform, including SEMG waveforms, can be decomposed mathematically into the SEMG Quadriceps Wavelet Analysis

sum of sinusoids, such decomposition (i.e., frequency spectrum) is most meaningful if the waveform in question is inherently comprised of sinusoids. Because SEMG waveforms are comprised of the sum of action potentials occurring at different times with differing amplitudes and durations, a Fourier analysis is lacking in terms of meaningful information it can provide. Given the limitations imposed by using FFT, DFT, or STFT in SEMG spectral analysis, the use of another technique developed for signal decomposition, called wavelet transformation (WT), was employed in the present analysis. Wavelet transforms are similar to Fourier transforms; however, instead of projecting a signal into space of sinusoids, WTs project a signal into space comprised of functions limited in duration. This technique consists of mapping the signal in frequency and time from a series of base functions, which produces a family of ordered decompositions located in different frequency bands. From a single basic wavelet, a so-called mother wavelet, stretching and shifting (dilating and translating) the wavelet allows for discovery of the frequency content and location in time of the signal. Thus, FFT analysis describes a signal in terms of sinusoids of different frequencies (or stretched sinusoids in wavelet terms) compared with describing a signal in terms of stretched and shifted wavelets. In other words, instead of correlating with various stretched, constant-frequency sinusoidal waves, WTs use waveforms limited in duration (wavelets).26 Furthermore, whereas FFT techniques are timeinvariant, WTs are time-variant (i.e., localized in time), with location and scale adjustable by the researcher. Thus, wavelets can analyze waveforms in a very short duration so that change in timing and frequency content can be evaluated simultaneously.27 Wavelet transforms are also effective in removing undesired artifacts from data, such as those caused by subject movement or other noise sources.28 There are 2 variations of the wavelet transform: discrete (DWT) and continuous (CWT). The main difference between them rests in what values the wavelet parameters are allowed to take when forming daughter wavelets from the mother wavelet. With DWT, these parameters are usually taken in powers of 2, allowing for the wavelets to form an orthogonal basis and making the DWT itself invertible. This can be useful when the analyzed signal is meant to be coded or transformed using the calculated wavelet coefficients and later reconstructed; however, for SEMG signal analysis, choosing coefficients in such a manner would severely limit the frequency resolution of the calculated spectra. On the other hand, CWTs enable these parameters to MUSCLE & NERVE

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FIGURE 1. Screen display depicting, from top to bottom: limb position, torque output, and vastus medialis (VM), vastus lateralis (VL), and rectus femoris (RF) filtered SEMG signals at isovelocites of 50 /s (A) and 200 /s (B).

take on any value, thus permitting the researcher to freely select the wavelet scale and shift parameters, which results in fine control over the frequency resolution. This makes CWTs, rather than DWTs, more suitable for analysis of SEMG signals.26 This investigation was undertaken because of the inconsistent and equivocal results of previous research, and the lack of SEMG signal analysis using WTs. Accordingly, we examined the effects of muscle contraction intensity [100%, 75%, 50%, and 25% maximum voluntary contraction (MVC)] and movement velocity [50 /s, 100 /s, 200 /s, and 400 /s (isovelocities)] on SEMGMDF and SEMGRMS of the rectus femoris (RF), vastus lateralis (VL), and vastus medialis (VM) muscles. These muscles were chosen because they are an inclusive representation of the superficial knee-extensor musculature during varying levels of force and velocity, and they display differing muscle-fiber profiles (e.g., RF have a greater percentage of type II FT fibers than VL and VM muscles).29 We investigated women only because gender differences have been shown to exist for SEMG profiles.30 METHODS

Ten healthy, recreationally active, women university students (mean 6 standard deviation: age 22.6 6 2.1 years; height

Subjects.

846

SEMG Quadriceps Wavelet Analysis

162.8 6 6.2 cm; weight 62.4 6 5.1 kg) with no known knee pathology (as stated on a pretest health questionnaire) participated in the investigation. Subjects were informed verbally of the procedures and potential risks, and they read and signed an informed consent document prior to participation. The institutional review board of the University of New Hampshire approved this study. Dynamometer Set-Up. Subjects were tested on an isokinetic dynamometer (HUMAC-NORM; Computer Sports Medicine, Inc., Stoughton, Massachusetts) using the dominant limb. Limb dominance was defined as the leg with which the subject would kick a ball.20 Full extension was measured as 0 and was determined manually by an examiner using a goniometer and anatomical landmarks (the greater trochanter and lateral epicondyle of the femur, and the anterior border of the tibia). Moment values were recorded in newton-meters (Nm), with real-time moment and position (ROM) data downloaded from the dynamometer into a data acquisition and analysis system (MP 100; BIOPAC Systems, Inc., Santa Barbara, California) by way of external output channels, thus allowing for simultaneous recording and display of moment, position, and SEMG data (Fig. 1). MUSCLE & NERVE

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Experimental Protocol. Subjects were familiarized with testing procedures and equipment prior to testing by attending a pretesting session. Output signals were analog-to-digitally converted (MP 150; BIOPAC Systems) online at a sampling frequency of 500 HZ. Subjects warmed up for 10 minutes by pedaling on a cycle ergometer and performing quadriceps stretching exercises. Subjects were then tested at 4 angular isovelocities (50 /s, 100 /s, 200 /s, and 400 /s) and 4 contraction intensities (100%, 75%, 50%, and 25% MVC), through kneejoint angles of 0 (straight leg) and 100 . Before testing at each velocity, subjects performed 6 submaximal warm-up repetitions to become familiar with testing velocities. Isometric MVCs were obtained over a 5-s contraction with the knee flexed at 60 .20 At each isovelocity tested, subjects performed quadriceps contractions (extension) at the desired intensity followed by passive flexion of the hamstrings. Peak moment values for each test velocity were determined by the repetition at which maximum moment was achieved at 60 knee flexion (point at which isometric MVCs were measured) during a 6repetition trial. A 3-minute rest period was given between each test trial to minimize fatigue on moment production and SEMG activity.31 Testing order of submaximal contraction intensities and movement velocities was counterbalanced over subjects through a sampling without replacement procedure. During MVC tests, subjects were instructed to push into extension as hard as possible using strong verbal encouragement (“push, push, push, hard”). For this study, an MVC was defined operationally as a maximal contraction that a subject accepts as maximal and that is produced with appropriate continuous feedback of achievement. All other muscle contractions were submaximal, and subjects were instructed to produce a moment that, to the best of their ability, corresponded to a specific percentage of their maximum moment output at the corresponding velocity. During submaximal tests, subjects viewed a moment–time curve of their moment output and were given verbal feedback to reach, but not exceed, the percent of maximum being tested. A submaximal test trial was repeated if the moment value produced was not within 65% of desired moment value and not reached within 6 repetitions.1 Recording and Processing of SEMG. Bipolar SEMG was used to determine the electrical activity of VM and RF muscles. Silver/silver chloride pre-gelled surface electrodes (Moore Medical Corp., Farmington, Connecticut) were placed 2.5 cm apart and parallel to the muscle fibers over the longitudinal SEMG Quadriceps Wavelet Analysis

midline between the motor point and the tendon according to points recommended by Criswell,32 and further modified according the recommendations of Ebersole et al.33 to minimize cross-talk from superficial components of the QF due to common neural drive and anatomical location. This essentially involved increasing the distance between electrodes of adjacent muscles such that this distance was approximately 10 cm. Therefore, it was not likely that cross-talk between muscles influenced the SEMG signals to a significant extent. A common reference electrode was placed over the head of the fibula. The skin was cleaned and abraded with preparation gel (Nuprep; D.O. Weaver Co., Aurora, Colorado) to achieve skin impedance of 5 kX. Skin impedance was tested using a 15-range digital multimeter (RadioShack, Fort Worth, Texas). The SEMG signal was amplified, filtered, and analog-todigitally converted (MP 150; BIOPAC Systems) online at a sampling frequency of 2 kHZ. Raw SEMG signals were monitored online, stored, and processed through a Dell Optiplex computer with high- and low-pass filters of 20 and 500 HZ, respectively. The gain was set at 1000 with a common mode rejection ratio of 100 dB. In total, skin preparation, sampling rate, and filtering frequencies were designed to achieve minimal cross-talk between electrodes, minimize signal attenuation, and remove potential movement artifacts and high-frequency noise.34 The SEMG signal was filtered (AcqKnowledge 4.2 software; BIOPAC, Inc.), and SEMGMDF and SEMGRMS were calculated for the repetition at which peak moment occurred and the repetition at which desired percent MVCs occurred. The SEMGRMS data were normalized against SEMGRMS obtained for each muscle during isometric MVCs and were used as a measure of overall muscle activity.32 The SEMGs were resolved into their respective intensities in time-frequency space using a CWT. Specifically, the Daubechies family of wavelets (in particular the db8 wavelet) was selected for CWT decomposition, because they best resemble the waveforms of motor unit action potentials. Performing a CWT on a time waveform results in a matrix of normalized coefficients calculated over scale and time. Scales are responsible for stretching and shrinking the original wavelet and provide an indication of the frequency content within a time interval. Because frequency content is estimated over a narrower time-frame, it can be defined most accurately as a form of pseudofrequency, determined from the predominate frequency of the original wavelet. SEMGMDF was processed by way of a CWT using the toolbox function in MATLAB, version 7.1 (MathWorks, Natick, MUSCLE & NERVE

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Table 1. Rectus femoris (RF), vastus medialis (VM), and vastus lateralis (VL) surface electromyography median frequency power spectra (SEMGMDF) as a function of contraction intensity. Contraction intensity

100%

75%

50%

25%

Rectus femoris (RF) Vastus medialis (VM) Vastus lateralis (VL)

72.33 (6.89) 61.79 (6.77) 64.12 (5.51)

68.63 (7.01) 60.46 (6.51) 62.50 (6.24)

65.85 (6.70) 60.79 (6.79) 61.23 (6.22)

61.07 (7.42) 57.53 (9.06) 57.40 (7.90)

Data expressed as mean (standard deviation).

Massachusetts), and was used to determine potential changes in motor unit recruitment strategies.9,12 For each repetition over which data were analyzed, isovelocity SEMG recordings were calculated between 40 and 80 knee flexion. This portion of the range of motion was selected for 3 reasons. First, it avoided the impact of acceleration and deceleration phases of the extension movement on SEMG data, although this was mitigated somewhat by not utilizing predetermined stops at the endpoints of the testing ranges and the fact that isokinetic dynamometers on the market today generally control for these types of movements.35 Second, as frequencies at the extremes of muscle length (i.e., closer to full knee flexion and extension) are less representative of actual spectral frequencies represented in the muscle, waveforms from a more midmuscle length were sought. According to Kaman and Caldwell,36 overall spectral frequencies tend to shift toward lower frequencies with increasing muscle length. Last, analyzing data from points adjacent to 60 knee flexion (the point at which normalization measurements were obtained) minimized, as much as possible, muscle length discrepancies during movement, reducing the impact of muscle-fiber length on SEMG values. Data were analyzed using statistical software (StatView; SAS Institute, Cary, North Carolina). Isovelocity (50 /s, 100 /s, 200 /s, and 400 /s) values were compared using repeatedmeasures analysis of variance (ANOVA); interaction of movement velocity and contraction intensity on RF, VL, and VM SEMGMDF and SEMGRMS were analyzed by separate 4 (velocity) 3 4 (intensity) 3 3 (muscles) repeated-measures ANOVA. The conservative Greenhouse–Geisser adjustment was used to evaluate observed within-group F ratios. Post hoc comparisons consisted of planned orthogonal contrasts. The criterion level for significant difference was set at P  0.05. Statistical Analysis.

RESULTS Surface

Electromyography

Median

Frequency.

Spectral frequency values (SEMGMDF) of RF, VL, and VM for contraction intensity and movement velocity are shown in Tables 1 and 2, respectively, 848

SEMG Quadriceps Wavelet Analysis

and normalized amplitude (SEMGRMS) values of RF, VL, and VM for contraction intensity and movement are shown in Tables 3 and 4, respectively. The SEMGMDF data show significant main effects for intensity (F3, 27 5 19.14, P  0.001) and muscle (F2, 18 5 13.45, P  0.01) and a significant intensity 3 muscle interaction effect (F6, 54 5 8.11, P  0.001) (Tables 1 and 2). Analyses indicated: (1) as a group, RF, VL, and VM displayed increased median frequencies as contraction intensity increased from 25% to 50% MVC, stabilized from 50% to 75% MVC, then increased again from 75% to 100% MVC; (2) RF median frequencies were significantly higher than those of VL and VM across all contraction intensities and increased significantly across all contraction intensities, such that 100% > 75% > 50% > 25% MVC; (3) although showing increased values with increasing contraction intensities, VM median frequencies were significantly greater only at 50%, 75%, and 100% MVC compared with 25% MVC, and VL median frequencies were significantly greater at 100% MVC and greater at 50% and 75% MVC compared with 25% MVC, with no significant difference between 50% and 75% MVC; and (4) velocity had no significant effect on median frequency. Surface Electromyography Amplitude. Normalized SEMGRMS (muscle amplitude) data showed significant main effects for velocity (F3, 27 5 5.25, P  0.05) and intensity (F3, 27 5 132.42, P  0.0001) (Tables 3 and 4). Post hoc analyses indicated: (1) significantly greater amplitude in all 3 muscles at 400 /s and 200 /s than at 50 /s and a significantly greater amplitude at 400 /s than at 100 /s; and (2) amplitude increased significantly in all 3 muscles as force levels increased from 25% MVC to 100% MVC. Overall, the highest SEMGRMS values occurred at 400 /s and 200 /s, and the lowest occurred at 50 /s. DISCUSSION

This study was undertaken to investigate the effects of contraction intensity and movement velocity on SEMG parameters of 1- (VM and VL) and 2-joint (RF) knee-extensor muscles using both muscle spectral frequency and amplitude to determine motor unit recruitment strategies and muscle MUSCLE & NERVE

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Table 2. Rectus femoris (RF), vastus medialis (VM), and vastus lateralis (VL) surface electromyography median frequency power spectra (SEMGMDF) as a function of movement velocity. 50 /s

100 /s

200 /s

400 /s

66.44 (7.11) 60.98 (7.71) 61.45 (6.43)

66.68 (8.24) 60.30 (7.84) 61.56 (6.26)

67.25 (8.18) 59.60 (6.87) 61.11 (6.32)

67.51 (8.92) 59.69 (7.57) 61.24 (8.71)

Movement velocity Rectus femoris (RF) Vastus medialis (VM) Vastus lateralis (VL)

Data expressed as mean (standard deviation).

activation, respectively. Moreover, this investigation was directed toward a comprehensive analysis using a spectrum of velocities and contraction intensities incorporating CWT. The association between frequency spectrum and motor unit recruitment is based primarily on conduction velocity of the respective motor units, which is a function of muscle-fiber diameter and twitch characteristics.2–4 Consequently, type II FT motor units have faster conduction velocities and, when recruited, the frequency spectrum increases.9 In this investigation, median frequency was compared across contraction velocities and intensities to present a noninvasive indicator of motor unit recruitment strategies.9,12 The median frequency response patterns to increasing contraction intensities we found can be summarized as follows: RF showed a stepwise increase in frequency response to increasing contraction intensities and displayed significantly higher median frequencies than VL and VM. Both VM and VL showed increased median frequency responses from 25% to 50% MVC, with the VL additionally showing increased median frequencies at 100% MVC over those found at 50% and 75% MVC (Tables 1 and 2). Based on the available research, the relationship between force and spectral frequency in QF muscles is equivocal. Coburn et al.,22 Ebenbichler et al.,37 and Weir et al.38 all reported no significant relationship between spectral frequencies and torque across RF, VL, and VM muscles; VM and VL muscles; and VM muscle, respectively. On the other hand, Croce et al.,1 Gerdle et al.,13 Karlsson and Gerdle,15 and Gerdle and Karlsson39 all reported positive, torque-dependent associations between frequency content and increasing torque in the superficial QF muscles. Pincivero et al.40

reported highest spectral frequencies in the VL and lowest frequencies in the VM, with RF frequencies between the 2, and Bilodeau et al.18 found spectral frequencies increased only in the VL in men and not in women, and not in RF and VM, which they attributed to the VL in men having greater type II fiber content. The results from our investigation concur most with the results of Croce et al.1 and Gerdle et al.,13 who reported that QF spectral frequencies are positively torquedependent, with the RF displaying highest values. For example, Croce et al.1 investigated the effect of contraction intensity and movement velocity on SEMG median frequency, as measured by STFT, and found a positive relationship between contraction intensity and SEMGMDF, with greater SEMGMDF values for RF than the VM across all contraction intensities. The observed increases in SEMGMDF found here provide some evidence of specific fiber-type activation during increased contraction intensities as described by Wakeling9 and von Tscharner and Nigg.12 It would make intuitive sense that, during higher intensities of QF contraction, there would be greater recruitment of FT fibers than during lower intensities. Henneman41 found that motor unit recruitment follows an orderly sequence based on size, such that smaller, type I motor units are activated before larger, type II motor units. Along with increasing motor unit firing rates, progressive recruitment of motor units within a muscle is the principal way by which a muscle increases contraction force. During increasing intensity levels, faster motor units are recruited, which is manifested by higher frequency components appearing within the myoelectric intensity spectra.8 Moreover, in larger muscles, such as QF, motor unit recruitment

Table 3. Rectus femoris (RF), vastus medialis (VM), and vastus lateralis (VL) surface electromyography root mean square (SEMGRMS) (percent of MVC) as a function of contraction intensity. Contraction intensity

100%

75%

50%

25%

Rectus femoris (RF) Vastus medialis (VM) Vastus lateralis (VL)

1.08 (0.29) 1.07 (0.25) 1.08 (0.23)

0.87 (0.19) 0.85 (0.20) 0.84 (0.21)

0.70 (0.21) 0.68 (0.19) 0.67 (0.21)

0.43 (0.12) 0.46 (0.16) 0.44 (0.19)

Data expressed as mean (standard deviation).

SEMG Quadriceps Wavelet Analysis

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Table 4. Rectus femoris (RF), vastus medialis (VM), and vastus lateralis (VL) surface electromyography root mean square (SEMGRMS) (percent of MVC) as a function of movement velocity. 50 /s

100 /s

200 /s

400 /s

0.69 (0.30) 0.66 (0.25) 0.67 (0.29)

0.75 (0.31) 0.73 (0.30) 0.71 (0.31)

0.81 (0.33) 0.84 (0.33) 0.83 (0.32)

0.82 (0.33) 0.83 (0.31) 0.82 (0.33)

Movement velocity Rectus femoris (RF) Vastus medialis (VM) Vastus lateralis (VL)

Data expressed as mean (standard deviation).

appears to continue over the entire spectrum of forces, whereas rate coding, or firing frequency, tends to play a greater role at higher ends of the force spectrum.42–44 The fact that RF displayed increased frequency content relative to VL and VM, and showed a more linear and consistent shift in median frequency over intensity levels, is also supported by the literature. Researchers noted that there are variations in fiber composition in components of the QF. For example, Edgerton et al.45 found a greater type I fiber distribution in VM compared with VL. Johnson et al.29 reported that RF displayed the highest percentage of type II fibers, followed by VL and VM, and Polgar et al.46 reported greater muscle diameter for type II fibers in the RF compared with VM and VL. Differences in type I and type II fiber distribution of QF muscles are germane to this, as fiber composition and diameter influence SEMG frequency content. Researchers have confirmed that SEMG frequencies for muscles with a higher percentage of type II fibers, as well as those observed changes in SEMG frequencies with increasing force, are influenced by this percentage.13,14,39,47,48 Although our data show increasing levels of SEMGMDF with increasing contraction intensities in all 3 muscles, the pattern of increase was dissimilar across muscles. Whereas there was a sequential increase in RF spectral frequencies as contraction intensity increased (i.e., 100% MVC > 75% MVC > 50% MVC > 25% MVC), VM spectral frequencies were only significantly greater at 50%, 75%, and 100% MVC compared with 25% MVC, and VL spectral frequencies were significantly greater at 100% MVC compared with lower intensities, and greater at 50% and 75% MVC compared to 25% MVC; therefore, the pattern of increase in SEMGMDF with increasing levels of contraction intensity was slightly different in VM and VL compared with that in RF. It would appear that differing SEMGMDF responses observed in RF, VL, and VM to higher contraction intensities provide further evidence of fiber-type differentiation in these muscles.14,29,40 As Pincivero et al. noted,40 muscles that have a greater percentage of type I fibers (VM) may not display shifts in the power spectrum 850

SEMG Quadriceps Wavelet Analysis

to higher values based on increased force levels despite additional recruitment of motor units during maximal contractions. Moreover, the more pronounced increase in SEMGMDF in RF could reflect the higher percentage of type II fibers present in this muscle and progressive recruitment of these fibers as force increased. As type II fibers have a greater conduction velocity compared with type I fibers, and as power spectral properties are in turn influenced by conduction velocity, their recruitment would increase SEMGMDF values.4 Moreover, increases in SEMGMDF values with increasing contraction intensity observed in the RF indicate that the techniques we used (CWT of power spectrum) could detect differences in active type II motor units across intensity levels and is consistent with the notion of progressively greater recruitment of type II motor units with increasing intensity. In contrast, SEMGMDF did not increase as noticeably in the VM with increasing contraction intensity, which would indicate that equal proportions of type II and type I motor units were recruited across all intensities, from low to high. A second finding of this study was a nonsignificant velocity effect for SEMG spectral frequency in all 3 muscles. Similar to the available research regarding the effect of force on SEMG spectral frequency, the effect of velocity on SEMG spectral frequency is likewise mixed. Some researchers have reported spectral shifts that were inversely related to movement velocity and positively related to torque output,17,19 or greater at very low velocities only.1,25 Others reported that velocity had no impact on spectral frequency and remained essentially the same throughout a range of tested velocities.21,49 Still other researchers have reported spectral shifts based on the particular QF muscle investigated.47,50 In concordance with Hutchins et al.21 and Croce et al.,49 it would appear that maximum recruitment of type II, FT motor units, as determined by increased SEMGMDF values, is not impacted appreciably by velocity during dynamic movements. There is a caveat to the aforementioned explanation of differences between our findings and those of other researchers investigating the effects of velocity on spectral frequency. Foremost is that MUSCLE & NERVE

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methodological issues could have influenced SEMG frequency spectrum values in prior investigations and resulted in imperfect interpretation of data. Controlling for interelectrode spacing, configuration, and placement relative to the innervation zone and controlling for changes in muscle length are all essential for proper interpretation of the frequency spectrum.15,36 In our investigation, these methodological issues were controlled to a large extent, as data were collected during a single session. This resulted in consistent electrode spacing, configuration, and placement across all test trials and should not have confounded data collection. Nevertheless, differences in methodological procedures in our study compared with those in previous studies could have led to varying results. A second much greater methodological problem, however, is that, in the preponderance of earlier investigations, FFT or STFT was utilized to analyze SEMG waveforms. This becomes a major concern when analyzing SEMG data during dynamic movements due to the non-stationary nature of SEMG signals. Continuous changes in muscle-fiber length during dynamic contractions have always posed a problem in analyzing the frequency spectrum, because, at shorter muscle lengths, muscle-fiber diameters are greater, resulting in higher frequencies. In isometric measurements, muscle position is fixed and results in a specific muscle fascicle length, whereas muscle fascicle lengths change under differing velocitydependent conditions.1,36 This problem, however, was avoided in our investigation by using CWT to analyze SEMGMDF data, and isovelocity SEMG measurements were taken in a narrow range of motion surrounding 60 knee flexion. Although there is a large amount of experimental evidence supporting the Henneman size principle, there also is a growing body of evidence suggesting that orderly recruitment does not adequately describe motor unit recruitment in all situations and that motor units within individual muscles can form groups that may fulfill specific functions independently.8,51 These “task-related” motoneurons could be recruited selectively for kinematic conditions within a motor task so that it is possible for mechanical factors to influence motor unit recruitment strategies. In some instances, it is logical for type I motor units to not be recruited during movements that require muscle contractions at a fast rate or where rapid force development is required. In these cases, preferential recruitment of type II motor units would be more advantageous due to their faster activation and relaxation rates and their potential to produce maximum power. The presence of these taskrelated motoneurons provides a mechanism by SEMG Quadriceps Wavelet Analysis

which preferential recruitment of faster motor units within a muscle can occur.51 Therefore, the size principle of motor unit recruitment provides a rather “robust” framework upon which motor unit recruitment occurs. It would appear that the neuromuscular system is multifunctional, not only shifting activity between muscles but also allowing discrete populations of motor units to be activated differentially.52 Consequently, another possible cause for the discrepancy between our study and previous studies of the impact of velocity on EMGMDF could be the muscle-fiber characteristics of participants in the study. Purportedly, if individuals have a greater percentage of type II motor units, then the likelihood of detecting spectral shifts occurring with increasing movement velocities would be greater, as muscles with a greater percentage of type II fibers have a greater tendency to display these spectral shifts under appropriate conditions.13,14,40 Moreover, if subjects are more athletic and more involved with ballistic-type movements, there may also be a greater likelihood to detect spectral shifts with increasing movement velocities through preferential recruitment of faster, task-related motor units.51,52 In our study, as well as those performed by others, systematically isolating the impact of subject muscle-fiber characteristics and levels of training on spectral shifts during increasing movement velocities was not presented. Although only conjecture at this point, the individual muscle-fiber phenotype could have had an impact on spectral shifts in the muscle with increasing movement velocities. Future research should address these relationships. The significant increase in SEMGRMS observed in all 3 superficial QF muscles with increasing contraction intensity was consistent with previous investigations involving both isometric15,18,33,53 and dynamic muscular contractions.1,22,25 In our investigation, SEMG amplitude increased significantly across contraction intensities in all 3 muscles in a nearly identical fashion (see Table 4). Previous investigations of force and SEMG amplitude have been characterized by either linear or curvilinear increases in SEMG amplitude due to concurrent increases in motor unit recruitment and firing rates up to about 50–80% MVC and thereafter due to increases in firing rates up to MVC.1,15,22,25,33 Our data confirm this relationship, as steady increases in SEMGRMS were observed with increasing force levels. Previous studies of QF muscle amplitude under varying movement velocities have shown conflicting results. Earlier work showed that QF SEMG amplitude either increases with decreasing velocity19,20,54; decreases with decreasing velocity,1,24,25,55,56 with MUSCLE & NERVE

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the most significant decrease in SEMG amplitude occurring in movements at velocities

Wavelet analysis of quadriceps power spectra and amplitude under varying levels of contraction intensity and velocity.

We investigated the effect of contraction intensity [100%, 75%, 50%, and 25% maximum voluntary contraction (MVC)] and movement velocity (50°, 100°, 20...
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