When planning a workout session, understanding the causes and mechanisms behind fatigue is imperative to achieve optimal results in any given training session. The traditional recovery strategies aimed at reducing fatigue typically involve active or passive recovery (28,29,35). In active recovery, the athlete will perform an unloaded movement similar to the loaded exercise he/she is performing. In passive recovery, the athlete will not perform any exercise or movement with the limb(s) they are currently loading. These approaches, however, can also be combined with an alternative form of recovery, targeting central nervous system activity, which could be more efficient at reducing peripheral and central muscular fatigue and maintain strength between sets.
Previous studies have been conducted to illustrate the importance of central (44) and peripheral (49) fatigue factors. Peripheral factors, including metabolite build up (8,10,29,49) and central fatigue attributed to neurological impairment in excitability levels (22,32,38,47) have been attributed to strength declines during maximal exercise sessions. In addition, it has been reported (19,49) that each source exerts unique influences on muscle activation levels, fiber recruitment ratios (1), and the binding properties of actin and myosin (8,29). Furthermore, previous studies have indicated that during both dynamic and isometric contractions, components of both peripheral and central fatigue exist, but each has its own proportionate influence on performance based on participant training, motivation level, and difficulty of task (5,6,9,13,15).
The mechanisms of fatigue have typically been examined by using electromyography (EMG) in conjunction with a strength or task to failure exercise (8,19,24,42). Electromyographic measures can assist in determining whether the decrease in central motor drive resulted in a decrease in recruitment and/or firing rate (5,12). For example, a subset of studies using EMG has investigated a “diverting activity” as a means to engage the central nervous system and reduce inhibitory signals sent by the motor cortex to working musculature (3,4,7,10,43). The concept of diverting activity follows the idea that an activity, which engages the mental capacities away from the fatiguing exercise could allow the brain to facilitate neural activation, thereby reducing the inhibitory effects on the reticular formation (1,3,31). Mechanomyography (MMG) is the mechanical counterpart to EMG and records and quantifies the lateral oscillations of activated muscle fibers (42). Previous research suggests that MMG may more closely reflect fatigue-induced decline in torque than EMG (42).
Although active and passive recovery strategies have proven effective at reducing muscular fatigue between maximal work bouts (4,11), other measures are necessary to identify the source of fatigue mechanisms (6,12,42). To the best of our knowledge, there has yet to be a study that combines the current information regarding recovery strategies and the mechanisms of central fatigue, specifically the combined use of active and passive recovery strategies, as well as the use of EMG and MMG during a diverting task. Therefore, the purpose of this study was to investigate the effects of a passive recovery, active recovery, and a combination of passive diverting and active diverting recovery on peak torque, percent torque decline, and muscle activation patterns (EMG and MMG) and determine if one of the 4 interventions was the optimal recovery strategy for recovery after maximal isokinetic muscle actions involving a large muscle group.
Experimental Approach to the Problem
This within-groups study examined the effects of 4 different recovery interventions on percent torque decline, EMG, and MMG. The subjects performed a fatiguing exercise protocol involving 2 bouts of 50 maximal isokinetic leg extensions at 180°·s−1 on each of the 4 experimental visits, which was accompanied by 1 of 4 recovery interventions: passive (P), active (A), passive and diverting (PD), and active and diverting (AD). Torque, EMG, and MMG measures were recorded during preintervention and postintervention exercise tasks. Pretest and posttest torque and muscle activity patterns were statistically compared to determine which, if any, of the recovery interventions was more effective at attenuating fatigue after maximal isokinetic muscle actions.
Ten college-aged men (mean ± SD = 23.4 ± 1.0 years; 178.4 ± 5.0 cm; 84.8 ± 15.9 kg) volunteered to participate in this study and were tested across each of the 4 interventions. Age, height, and body mass measurements were taken on the first visit to the laboratory. No subjects under the age of 18 were tested in this study, and the age range was 22–25 years. All subjects received, read, and signed a University institutional review board–approved informed consent before participation. Subjects were screened for the absence of orthopedic and musculoskeletal injuries before participation. All subjects were recreationally trained, participating in at least 3 days of physical activity per week for the past 6 months and were familiar with maximal exercise effort. Subjects were instructed to refrain from all lower-body resistance training and fatiguing aerobic activities for the duration of the study. In addition, subjects were asked to abstain from the consumption of caffeinated beverages and supplements before experimental sessions and to ensure that they consumed at least 1 half liter of water the night before experimental sessions to ensure proper hydration.
Before maximal isokinetic strength testing, subjects were measured for EMG and MMG sensor placement on the right vastus lateralis. After placement of electrodes, subjects completed a 5 minutes warm-up on a Monark cycle ergometer (Monark 839E; Varburg, Sweden) at 50 W. A HUMAC NORM isokinetic dynamometer (CSMi, Inc., Stoughton, MA, USA) was then used to measure maximal isokinetic leg extension strength of the right limb before and after the interset experimental interventions. Participants were positioned according to the HUMAC NORM testing and rehabilitation system user's guide.
For isokinetic strength testing, participants performed 2 sets of 50 maximal leg extensions at an angular velocity of 180°·s−1. Full extension was determined when the lever arm was 20° below parallel. Subjects were instructed to give 100% maximal effort for each extension and to passively lower the leg before the next maximal leg extension. Between the 2 sets of 50 repetitions, subjects performed one of the 4 interset experimental interventions during a 2-minute time period (A, P, PD, or AD). Peak isokinetic torque was calculated separately for both sets of 50 repetitions as the average of the 3 highest torque values achieved between repetition 1 and 5, whereas minimal torque was calculated separately from each set of 50 maximal repetitions as the average of the 3 lowest torque values achieved between repetition 45 and 50. Percent torque decline was calculated for both the first and second set of 50 repetitions using the following formula:
During the passive intervention (P), subjects remained seated and were instructed to rest quietly with no limb movement or interaction with researcher. The active intervention (A) required subjects to be unstrapped from the isokinetic dynamometer leg adapter and perform unloaded leg extensions of the previously exercised limb set to the beat of a metronome (40 b·min−1) (4). Passive diverting activity involved subjects squeezing a 2 × 2 inch foam sponge between thumb and middle finger at a rate of 40 repetitions per minute set to the beat of a metronome (4). The combined active and passive diverting (AD) intervention consisted of simultaneous unloaded leg extensions and sponge squeezing to the same metronome cadence.
A bipolar (5.6 cm center-to-center) disposable surface electrode arrangement (Ag-AgCl, BIOPAC EL500; BIOPAC Systems Inc., Goleta, CA, USA) was placed on the right limb over the mid-portion of the vastus lateralis muscle. The reference electrode was placed over the anterior distal end of the forearm between the styloid processes of the radius and ulna. Subjects were instructed to shave the involved limb areas before experimental sessions, but shaving of the area was done at the session if necessary. Shaving, light abrasion, and rubbing the area with an alcohol pad was used to reduce interelectrode impedance. Signals were preamplified (gain 1000×) using a differential amplifier (EMG100C; BIOPAC Systems Inc., Goleta, CA, USA; bandwidth = 1–500 Hz).
An accelerometer (EGAS-FT-10/V05; Entran, Fairfield, NJ, USA) was used to detect the MMG signals. The accelerometer was placed between the 2 EMG surface electrodes. Double-sided foam tape was used to affix the accelerometer to the vastus lateralis.
A personal computer and commercially available software (AcqKnowledge v. 3.8.1; BIOPAC Systems Inc., Goleta, CA, USA) were used to store and display the EMG and MMG signals. The signals were collected at a 1,000 Hz sampling frequency. Signal processing was performed with custom programs written with LabVIEW software (Version 7.1; National Instruments, Austin, TX, USA). The EMG and MMG signals were bandpass filtered (fourth-order Butterworth) at 10–500 and 5–100 Hz, respectively. The EMG and MMG amplitude and frequency values were calculated for a time period that corresponded to the middle 30° range of motion (approximately the middle 0.33 seconds). This range of motion was selected to avoid the acceleration and deceleration phases that are typical of isokinetic dynamometers. Amplitudes were calculated as root mean square (RMS) values, whereas the frequencies were calculated as mean power frequency (MPF).
A 2-way (time [preintervention, postintervention] × condition [passive, active, passive diverting, and active diverting]) analysis of variance (ANOVA) was used to analyze percent torque decline. Four separate 3-way (time [preintervention, postintervention] × condition [passive, active, passive diverting, and active diverting] × repetitions [initial, final]) ANOVAs were used to analyze the EMG and MMG amplitude and frequency data. When appropriate, follow-up tests included Tukey post hoc comparisons and t-tests. An alpha of 0.05 was used to determine significance for all comparisons. All statistical analyses were performed using IBM SPSS Statistics 20 (IBM Corporation, Somers, NY, USA).
The results of the current study indicated that there was a significant (p ≤ 0.05) 2-way interaction for % torque decline. There were significant (p ≤ 0.05) declines in torque (% torque decline) from the first to last repetitions across all conditions during both preintervention and postintervention tests. However, follow-up tests revealed that there was a significantly greater % torque decline for the postintervention test (Figure 1) for the P (35.14 ± 9.42%) than for the A, PD, or AD (32.47 ± 11.47; 32.62 ± 13.03; 33.70 ± 11.13%) conditions. There was no 3-way or 2-way interaction for EMG amplitude (RMS); however, there was a significant main effect for time (Figure 2). Electromyographic RMS (Figure 2) decreased on the postintervention test but did not differ between initial and final repetitions or between conditions. There was no significant 3-way interaction for EMG frequency (MPF), but there was a significant 2-way (time × repetitions) interaction. There were significant (p ≤ 0.05) decreases in EMG MPF (Figure 3) from the initial repetitions to the final repetitions for both the preintervention and postintervention tests. The decrease in EMG MPF from the initial to final repetitions was greater for the preintervention test than the postintervention test (Figure 3).
There were no significant 3-way or 2-way interactions for MMG amplitude, but there was a main effect for repetitions. There was a significant (p ≤ 0.05) decrease in MMG RMS (Figure 4) from the initial to the final repetitions, regardless of time (preintervention vs. postintervention) or condition. Mechanomyographic frequency (Figure 5) analysis resulted in no significant 3-way interaction, however, a significant 2-way interaction (time × condition) was found. Follow-up tests, however, indicated there were no significant changes in MMG MPF from preintervention to postintervention for any of the 4 experimental conditions.
It has been suggested that active rest strategies may promote recovery by removing fatiguing metabolites, such as inorganic phosphate (50) and lactate (20,21). Others have suggested that there may be a central origin to fatigue, and that diverting activities may reduce inhibition normally associated with fatiguing exercise (3,4). It would seem then, that both peripheral and central mechanisms of fatigue are plausible, and that both active rest and diverting strategies may be effective at combating fatigue. To the best of our knowledge, no previous study has compared active rest to passive diverting strategies while also looking at the potential additive effects of using both. In addition, although various studies have investigated diverting activities alone or in combination with EMG (3,4,7,44), no previous study has investigated muscular activation patterns associated with these strategies using both EMG and MMG.
The results from the present study indicated that all 3 experimental conditions (A, PD, and AD) were significantly better at reducing fatigue during a second bout of leg extensions when compared to the control condition. Specifically, the percentage of torque decline was nearly identical in all 3 experimental conditions (A = 32.47 ± 11.47%, PD = 32.62 ± 13.03%, and AD = 33.70 ± 11.13%) and less than the torque decline in the passive (P) condition (35.14 ± 9.42%). The results of the current study were similar to those of Rotstein et al. (43), who reported that unloaded knee extensions had similar effects as squeezing a sponge on the maximal force achieved during a second bout of fatiguing leg extensions. Both intervention strategies, active and passive diverting, implemented by Rotstein et al. (43) were reported to be more effective than passive rest. As mentioned previously, the low-intensity activity performed by the previously exercised limb between high-intensity fatiguing work bouts is designed to promote recovery by removing metabolic waste products, such as inorganic phosphate and hydrogen ions associated with lactate accumulation. In contrast, diverting activities, such as mental activity or exercise performed with a nonfatigued muscle group, promote recovery through a central mechanism that is independent of blood flow (3,4). Stock et al. (46) reported that there was improved recovery relative to the passive resting trial when either mental diverting (completion of math problems) or physically diverting (contralateral leg extensions) strategies were performed. Collectively, the current study and previous studies (4,43,46) indicated that both active recovery and active and passive diverting activities are effective at promoting recovery between fatiguing exercise bouts. Practically speaking, these findings suggest that during traditional resistance training, one could use small or uninvolved muscle groups and alternative strategies such as those outlined here or Stock et al. (46) to attenuate fatigue between bouts of maximal exercise.
To the best of our knowledge, the present study is the first that has examined the combined effects of submaximal exercise using the previously exercised limb and passive diverting activities (AD condition) on recovery, compared with either method (A or PD) alone. Although in theory, this might lead to greater recovery because of the combined effects of 2 recovery methods differing in physiological mechanisms, the results of the present study suggested that this was not the case. Although each treatment condition promoted recovery better than complete rest (P condition), there were no differences in percent torque decline during the second bout of 50 repetitions between the A, AD, and PD conditions. One possible explanation for this finding is that the active rest strategy used in the present study may have had effects on the central nervous system similar to the passive diverting strategy, making their effects on recovery redundant, rather than individual. Although Asmussen (4) specifically emphasized that diverting activity should involve muscles other than the fatigued muscles, there are aspects of the active rest protocol in the present study, which are similar to those used with active diverting strategies. For example, during the A and AD recovery protocols, subjects performed unloaded knee extensions to the beat of a metronome (40 b·min−1). It is possible that what was intended to be an active rest strategy leading to clearance of metabolic waste products in fact had a mentally diverting component, as subjects were required to focus on the metronome. Future studies should verify the nature of any active rest or combined strategies by measuring variables such as lactate clearance rates.
To the best of our knowledge, the present study is the first to incorporate EMG and MMG to assist in determining central vs. peripheral mechanisms of fatigue and the effects of diverting activity. Electromyographic amplitude represents motor unit recruitment and firing rate. Changes in EMG amplitude have long been associated with fatigue (7,16,18,26,34,36). The present study found a decrease in EMG amplitude from the preintervention to postintervention exercise bout, but the decrease in amplitude did not differ between experimental conditions. Decreases in EMG amplitude during repetitive fatiguing contractions have been attributed to central fatigue indicating a loss in “central motor drive” (36). It was hypothesized that the decrease in EMG amplitude during maximal voluntary contractions could result from the slowing of muscle contractile speed leading to impaired excitation-contraction coupling (18,36). In addition, Komi and Tesch (26) have attributed declines in EMG amplitude to high proportions of fast-twitch fibers. De Luca et al. (16) reported that large fast-twitch motor units never reached complete fusion during a maximal fatiguing voluntary effort, which could account for the decreases in EMG amplitude. In the present study, EMG recordings were taken from the vastus lateralis of male subjects. Previous studies have reported higher percentages of fast vs. slow twitch fibers within the vastus lateralis (25). It has also been reported that male subjects typically have higher proportions of these fast fibers because of a larger muscle cross-sectional area (45). Therefore, the vastus lateralis' fiber-type composition and the decrease in central drive across all 50 repetitions could explain the decrease in EMG amplitude observed for all 4 conditions. These findings also indicate that the type of recovery used in each trial had no effect on central motor drive as a means of attenuating fatigue.
In addition to the decrease in EMG amplitude, EMG MPF decreased from initial to final repetitions for both preintervention and postintervention exercise bouts. Furthermore, the decrease was greater for the preintervention than the postintervention bout (Figure 3). Decreases in the frequency characteristics of the EMG signal have long been associated with fatigue (2,6,17,26,34,36). Decreased action potential conduction velocities have traditionally explained the fatigue-related decrease in EMG frequency (2,6,17,26,34,36), however, increased extracellular K+ and changes in pH may also be responsible (27,37). Previous research has also attributed the decrease in the EMG frequency power spectrum to an accumulation of metabolic byproducts, for example, lactate or ammonia, which can cause a pronounced decrease in action potential conduction velocity (30,37).
A unique aspect of this study was the incorporation of MMG. Previous research has documented that MMG amplitude represents the number of oscillating motor units within a particular muscle (39,40). It has also been reported that at high levels of maximal voluntary contraction, MMG amplitude exhibits either no change (23) or a decrease (23,41) across repetitions. In the present study, MMG amplitude significantly decreased from initial to final repetitions (Figure 4), regardless of time or recovery intervention. The decrease in MMG amplitude across each bout of 50 maximal leg extensions could be attributed to a derecruitment of fast-twitch motor units (6,14,40), a decrease in muscle compliance because of twitch summation (40), or the effects of “muscle wisdom” (33). Muscle wisdom has been theorized to be the ability of the central nervous system to economically activate fatiguing muscle to optimize force production (33). As there were no significant main effects found for MMG MPF in the present study, changes in the pattern of MMG amplitude could have resulted from a combination of both decreased activation of fast-twitch fibers, decreased compliance, and muscle wisdom.
Although there were changes in the pattern of response for EMG amplitude and MPF (Figures 2 and 3), these changes did not differ across experimental conditions. The results of the current study were similar to those of Beck et al. (7), who also reported a lack of differences in EMG across conditions, including the control. It was suggested that this may have resulted from the inability of the bipolar surface EMG to detect pattern changes (19,48) and these factors may also have affected our results. For example, bipolar surface EMG signals collected from large muscles (i.e., the vastus lateralis) are generated from a large sample of activated motor units. This large sample of motor units may not have been representative of the activities of all motor units involved during the activity, or those affected by the recovery conditions. Therefore, the potential inability to detect these changes by the surface EMG could account for the similarity in EMG patterns across all 4 conditions, including the control.
The results of the present study indicated that using a recovery intervention involving active rest, passive diverting activity, or a combination of the 2 attenuated the decline in torque production during a subsequent bout of maximal isokinetic exercise. Further research is necessary to test alternative activities such as complex math problems, word searches, puzzles, memory tasks, and dynamic muscle actions involving small-uninvolved muscle groups. Although previous research has found similar results regarding motor control strategies, additional research is necessary to explain the strategies used during the various forms of recovery and rest intervals. As reported in previous investigations, it seems that recovery interventions using low-level contractions or diverting activity are equivalent as a means for recovery from isokinetic strength exercise, but future research is needed. In any case, the results of the present study suggest that coaches should have their athletes engage in some type of passive or active diverting activity, rather than passive rest, when performing fatiguing bouts of exercise similar to those used in this study.
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Keywords:Copyright © 2014 by the National Strength & Conditioning Association.
recovery; fatigue; isokinetics; EMG; MMG