Soft tissue vibrations occur during most sport activities. Vibrations are generated when the leg contacts the ground (e.g., running, jumping) or when a sport equipment hits an obstacle (e.g., skiing, cycling). Soft tissue vibrations can also be induced by vibration platforms, which are often used for whole-body vibration (WBV) training. The long-term and short-term effects of naturally occurring and/or artificially induced vibrations were studied, and the significant effects of vibrations on a large number of mechanical and physiological variables were found (4,8,20-22). In particular, it has been shown that WBV increase muscle activity and/or are associated with an increase in oxygen uptake (7,22,24,25). Vibrations are usually regarded as a by-product of sports activity with no role in the mechanics of locomotion (22). Exposure to vibrations was shown to increase muscle activity and, consequently, oxygen consumption (24,25,30). It was also speculated that vibrations might have a negative effect on sports performance and have a negative effect on energy expenditure during various sport activities (21). Conversely, when vibrations are used for training purposes, higher muscle activity and oxygen consumption are desirable, and in time, vibrations can act as a performance enhancer (21). Vibrations were also shown to have an effect on peripheral blood flow (17). It is therefore important to quantify the effects of vibrations on muscle tissue oxygenation and blood flow dynamics to improve the training and/or performance aspects of various activities that involve exposure to vibrations and to improve vibration training devices and vibration exercise techniques. Also, a better understanding of the effects of vibrations on muscle oxygenation and myogenic response could help with avoiding the risks or improving the benefits associated with certain types of vibrations.
Several studies have focused on the influence of vibrations on oxygen consumption both at a whole-body level (24) or at an individual muscle metabolic rate (6,32). Although most of these studies focused on finding changes in muscle oxygen consumption induced by vibrations at discrete moments in time, a dynamic approach to the effects of vibrations is still not available.
An individual muscle's metabolic rate can be determined by measuring the changes in oxygen saturation in the muscle. Under certain conditions such as arterial occlusion and aerobic exercise, oxygen utilization rate is a good approximation of the energy used by the muscles (5,11). This method was used in the past to quantify the effect of WBV or locally applied vibrations on muscle metabolic rate (6,32,33). However, the experimental design used in these studies did not allow for a clear interpretation of the data because local oxygen saturation is related to the blood flow but blood flow was not restricted/monitored in these studies (6,32). In a recent study (33), ischemia was induced by arterial occlusion, and the actual tissue oxygen utilization was quantified. However, the experiment was performed under a highly controlled isometric exercise, and only the oxygenation decrease phase was analyzed. In this context, it would be important to know what the effects of WBV on muscle oxygen consumption are during a dynamic exercise, independent of the potential changes in tissue blood flow.
Another aspect of the WBV's influence on tissue oxygen saturation is represented by the dynamics of muscle tissue oxygenation that occur during extended periods of vibration. A previous study investigated these aspects (32). However, the analysis methods used in this study did not capture the complex dynamics of tissue oxygenation nor were the results discussed in the context of tissue blood flow dynamics.
It has been shown that vibrations can dramatically alter the blood flow in the tissues. The methods used in previous studies cannot distinguish between changes in blood flow/perfusion and changes in oxygen saturation. Therefore, in the absence of blood flow information any interpretation of the results is just an approximation. To circumvent this limitation, ischemia is induced by arterial occlusion, thus allowing for a clear interpretation of the oxygen utilization data.
On the other hand, if the dynamics of the oxygen saturation is the desired outcome, the tissue blood flow becomes the determining factor, and unrestricted blood flow to the investigated tissue is required. These aspects were not/poorly addressed in previous studies, and these constitute the topic of this article.
Therefore, the goals of this study were (a) to quantify the relative effects of WBV on individual muscle oxygen utilization rate during a dynamic task and (b) to quantify the effects of vibrations on the relative dynamics of the muscle oxygen saturation and total hemoglobin concentration.
The tested hypotheses were as follows: (a) muscle oxygen utilization rate will increase with vibrations and (b) the variables that characterize the temporal pattern of muscle oxygen saturation and hemoglobin concentration will be significantly different for the vibration condition compared with the control condition.
Sixteen male subjects (age = 26.3 ± 5.1 yr, mass = 71.2 ± 4.8 kg (mean ± SD)) participated in this study and gave their written informed consent before participation. The study was approved by the ethics committee of the University of Calgary. All subjects were free of any injuries at the time of the experiments.
Near-infrared spectroscopy (NIRS), as used here, is a noninvasive technique designed to quantify the change in tissue concentration of oxygenated and deoxygenated forms of hemoglobin (O2Hb, HHb) and myoglobin (O2Mb, HMb), respectively (16). Because the absorption spectra of hemoglobin and myoglobin are identical, the method cannot distinguish between the two. However, myoglobin was shown to have a small contribution to the total concentration (15%-20%), and therefore, the combined concentration is usually used for tissue oxygenation measurements (2,18).
The spectrometer used in this study (NIRO 200; Hamamatsu Photonics, Shizuoka, Japan) provided tissue O2 saturation data in the form of tissue oxygenation index (TOI). TOI was expressed as a percentage of tissue O2 saturation. Another parameter provided by this device was the normalized total hemoglobin index (nTHI). The nTHI is a measure of the total hemoglobin in the tissue, and it is directly related to changes in tissue blood flow.
The NIRS method was successfully used to measure brain and muscle tissue oxygenation in previous studies (5,15). Two major limitations characteristic of this method were widely discussed in the past: (a) skin and fat tissue influence and (b) relative versus absolute oxygen saturation (18). In most practical situations, relative measurements suffice, and therefore, the two limitations can be circumvented by investigating the same tissue volume while varying the testing conditions. Also, relative and absolute changes in tissue oxygenation can be caused both by oxygen depletion and/or changes in tissue blood flow/perfusion. Therefore, when "true" tissue oxygen depletion rates are required, tissue blood flow has to be monitored and/or suppressed. The most common method used to circumvent this issue is complete arterial occlusion, which ensures a constant tissue blood concentration.
Subjects were asked to stand on a vibration platform (Vibra Pro 5500, Colton, CA) generating vertical vibrations of 4 mm in amplitude at a frequency of 16 Hz. The subjects were asked to stand with their feet 35 cm apart. For consistency, the locations on the vibration platform were marked with adhesive tapes. The protocol was similar to protocols used in previous studies (24,25).
An NIRS optode was placed on the belly of each of the right and left gastrocnemius medialis muscles. The distance between the source and the detector was fixed (4.5 cm). NIRS data were collected at a frequency of two samples per second.
Two bipolar EMG electrodes (20-mm interelectrode spacing; Ag-AgCl electrodes; Norotrode, Myotronics, Kent, WA) were placed on the right and left leg gastrocnemius medialis muscles. The electrodes were secured with stretch adhesive bandage to minimize possible motion artifacts and to prevent detachment from the skin during vibration. The EMG signal collected by each electrode pair was amplified 1000 times by a differential preamplifier located 3 cm from the electrodes. During the familiarization session, muscle activity was recorded for 5 s while the subjects were standing on their toes, with the heel at the maximum attainable height.
A metronome was used to generate audio cues at a frequency of 40 pulses per minute. The subjects were asked to repeatedly rise on their toes, from a normal standing position, at a rate of 40 repetitions per minute after the audible signals generated by the metronome. A warm-up and familiarization session of approximately 1 min was administrated to each subject before the test. The periodic motion consisted of lifting the heels of the platform to the maximum height allowed by the ankle joint's range of motion. During the familiarization session, the maximum height was determined and marked on a transparent, vertically standing ruler placed behind each heel and attached to the rigid structure of the vibration device. During the testing sessions, the height reached by the heel was constantly monitored to ensure testing consistency.
Each subject performed 67 repetitions per trial (100 s in total), with 10-min breaks between the trials to minimize the effects of fatigue. The subjects were required to stand relaxed on the platform in the testing position for 2 min before each session to ensure a steady-state pretest blood flow and oxygenation. All tissue oxygenation parameters were monitored during this time to ensure that the TOI returned to the preexercise levels and reached a steady state. Steady state was achieved when the slopes of the TOI and nTHI were lower than ±3%. After processing, each data set was analyzed by fitting a line to the data recorded during the last 15 s (30 data points) before the beginning of the exercise. If steady state was not achieved, the data set was rejected.
A pressure cuff was placed randomly on either the right or the left thigh and was inflated rapidly to 300 mm Hg immediately (<4 s) before the start of the exercise. The opposite limb was free of compression. Each testing session consisted of two trials: no vibrations (NV) and vibrations (VB). The setup and the exercise performed were identical for both trials. The order of the trials was randomized.
The tissue oxygenation decrease rates were computed from the total oxygenation index data measured in the arterially occluded (AO) leg by linearly fitting the linear section of the TOI concentration decay (Fig. 1). The rate of change of tissue oxygenation was computed as the slope of the regression line.
The tissue oxygenation recovery rate was computed from the TOI data recorded from the muscle that was not subjected to arterial occlusion (N/O). Total oxygenation index data between the minimum concentration point and the last recorded data point were fitted linearly. The recovery rate was defined as the slope of the regression line (Fig. 1).
The power spectrum of the TOI and nTHI data was computed using a fast Fourier transform (FFT) algorithm. To increase the resolution of the power spectrum, data were multiplied with a Hanning window and were padded with zeros to 1024 data points before FFT analysis.
To eliminate the movement artifacts, the EMG data were filtered using a wavelet high-pass filter with a cutoff frequency of 17 Hz. The EMG signal amplitude was computed using a root mean square (EMGrms) algorithm and averaging during the whole duration of the exercise. The EMGrms of the data recorded during the isometric contraction were used as reference (100%), and subsequent EMGrms values were computed as a percentage of the reference data.
A paired t-test was used to determine the statistical significance of the difference between the mean values of the measured variables (tissue oxygenation decay rate, tissue oxygenation recovery rate, and peak frequency) corresponding to the control and vibration conditions. The significance level was set at 0.05. Statistical analysis was performed with commercial SPSS software, version 16.0 (SPSS Inc., Chicago, IL).
The depletion rates (r), computed as the slope of the regression line, for the control condition were 4.03 ± 0.57 and 3.82 ± 0.72 for the AO and N/O legs, respectively. The vibration condition increased the depletion rate to 4.62 ± 0.81 and 3.94 ± 0.74 for the AO and N/O legs, respectively. The difference between the vibration and control condition was statistically significant for the AO condition (P = 0.008) but not significant for the N/O condition (P = 0.16; Table 1).
For the AO condition, total oxygenation index decreased to almost zero (at around 15 s) and remained unchanged throughout the exercise. In the N/O leg, the total oxygenation index decreased until it reached a minimum (at around 20 s) and increased linearly (r > 0.95) for the remainder of the exercise. The slope of the regression line (r) corresponding to this section was computed for the N/O leg only (Figs. 1 and 2). The mean slope of the regression line corresponding to the control and vibration conditions was 0.26 ± 0.11 and 0.35 ± 0.16 for TOI and 0.0044 ± 0.001 and 0.0051 ± 0.001 for nTHI. The difference between the control and vibration conditions was statistically significant for both the TOI and nTHI (P = 0.036 and P = 0.021, respectively).
The frequency spectra of the nTHI and TOI showed two distinctive peaks: at 0.7 Hz and at a lower frequency (around 0.1 Hz; Fig. 3). The 0.7-Hz peak was identified as the frequency of the dynamic task repetition and was ignored in the analysis. The mean frequency of the lower-frequency peak corresponding to the TOI and nTHI data was 0.074 ± 0.028 and 0.076 ± 0.031 Hz for the vibration condition, respectively, and 0.119 ± 0.052 and 0.118 ± 0.046 Hz for the control condition, respectively. The difference between the control and vibration conditions for the TOI and nTHI was statistically significant (P = 0.031 and P = 0.017, respectively; Table 1). The difference between the control and vibration conditions for both the TOI and nTHI mean peak frequencies was not statistically significant.
Muscle activity computed as a percentage of the individual pretest isometric contraction was 88% ± 12.7% and 89% ± 11.3% for the AO and N/O legs, respectively, during the vibration condition and 73% ± 8.5% and 71% ± 9.1% for the control condition, respectively. EMG activity was larger for the vibration condition compared with the control condition. The increase due to the vibrations was statistically significant for both the AO and N/O legs (P = 0.007 and P = 0.012, respectively). The difference between the AO and N/O legs was not statistically significant.
Tissue oxygenation and metabolic rate.
This study has shown that vibrations increased the muscle oxygen utilization rate during a dynamic exercise in both the AO and N/O legs. However, only in the AO leg was the oxygen utilization rate significantly higher for the vibration condition, suggesting that unobstructed blood flow has the potential to partially offset the increased oxygen consumption due to vibrations. Therefore, only the oxygenation data recorded from the AO leg allow for an unambiguous interpretation of the oxygenation data. Thus, the rate of oxygen consumption in the gastrocnemius muscle increased by approximately 15% because of the vibrations (Table 1). A similar trend was observed in a previous study (33). However, the frequency (20 Hz) and the exercise (isometric contraction) used in that study allows only for a limited comparison. No comparisons are possible with other previous studies that quantified the effects of vibrations on tissue oxygenation because these studies did not monitor and/or occlude the blood flow, and therefore, the oxygenation data in these studies do not reflect only changes in oxygen consumption (6,32).
Tissue oxygenation recovery.
During the oxygenation decrease phase (Fig. 1; 0-30 s), the tissue oxygen saturation in both the AO and N/O legs followed the same linear pattern, albeit at different rates. Immediately after the minimum depletion was attained, the TOI values diverged, increasing linearly during the following 70 s for the N/O leg and the remaining constant (close to 0) for the AO leg.
The divergence could be explained by a blood flow compensatory mechanism triggered by increased muscle activity. This is manifested by increasing the blood flow in the N/O leg, and this was shown experimentally in several studies (12,13,27). This assumption is supported by the observed increase in nTHI, which measures the total hemoglobin in the investigated tissue (Fig. 2).
The vibration situation further increased the recovery rate by approximately 34% when compared with the no-vibrations situation. This finding is consistent with previous studies that have shown that acute vibration exposure can temporarily increase the blood flow in the muscle tissue (17). Thus, vibrations seem to increase the tissue oxygenation recovery rate when compared with the control situation, and the effects of exercise and vibrations seem to be cumulative.
A possible explanation for the observed increase in the tissue oxygenation recovery rate could be vasodilation. It has been shown that the blood vessels' mechanical stressors (shear and stretch) can induce a myogenic response (9,10). This is probably due to an increase in the vasodilatory factors' bioavailability (27,29). It is expected therefore that mechanical vibrations could trigger a myogenic response via one or more of the mechanical signal transduction mechanisms (e.g., stress-induced depolarization). This assumption is indirectly supported by a previous study that has shown that vibrations and vibration-like stimuli can induce a hemodynamic response (26). In this context, the observed nTHI increase could be explained as an increase in blood flow, perhaps due to an increase in the bioavailability of vasodilatory factors. This is consistent with the observed increase in nTHI (Table 1). However, because the vasodilatory factors' bioavailability was not monitored in this study, this mechanism is rather speculative.
Tissue oxygenation oscillations.
The periodic nature of tissue oxygenation observed during the recovery phase was investigated using spectral analysis. The frequency spectrum for three distinct situations is shown in Figure 3. Two distinct frequency peaks were identified for both the N/O legs, and only one peak was identified for the AO leg. The higher-frequency peak has the frequency of the periodic exercise, and this was identified as a motion artifact caused by the periodic probe movement because of exercise. A lower-frequency peak was also identified in the N/O leg, and this seems to be shifted to lower frequencies in the vibrations situation. The low-frequency peak seems to be closely related to tissue blood flow. Two main facts support this assumption: (a) in the occluded leg, these oscillations do not occur; and (b) the spectrum of the nTHI and TOI data is quasi-identical (data not shown).
Tissue oxygenation oscillations were found in earlier studies unrelated to the topic of this study (19,28). There is only a limited understanding of the mechanisms responsible for the observed oscillations. The most cited reason is the vasomotion phenomenon that consists of periodic dilation and contraction of blood vessels, which can lead to periodic oscillations of TOI and nTHI data (23). The data shown in this study support this mechanism because the AO leg did not show an oscillatory pattern.
Furthermore, the shift toward lower frequencies due to vibrations could probably be explained by the vasodilatory factors' increased bioavailability. In an earlier study, nitric oxide synthesis inhibition was shown to increase the amplitude and the frequency of periodic blood flow oscillations (14). Conversely, an increase in the nitric oxide concentration could lead to a decrease in the amplitude and frequency of blood flow oscillations. Because vibrations might induce an increase in the nitric oxide synthesis, this could potentially lead to a decrease in the frequency and the amplitude of the vasomotion oscillations. This was actually observed.
The fact that both TOI and nTHI showed the same pattern suggests that tissue oxygenation pattern is closely related to the oxygenated Hb. However, there seems to be a delay between the changes in nTHI and changes in TOI, and more complex analysis methods (e.g., coherence analysis) are required to elucidate the relation between the two. However, this goes beyond the aim of this article, and this could constitute the topic of a separate study.
Confounding factors and recommendations.
Muscle activity increased with WBV exposure by 18% when compared with the control situation. The observed increase was within the range of values measured by previous studies (1,25). The amplitude and mean spectral density of the EMG signal did not change significantly in time within a trial (data not shown). This suggests that the exercise did not induce a significant muscle fatigue, and therefore, the effects of the fatigue can be ignored (3).
The influence of arterial occlusion on the contra lateral limb was investigated in a pilot study. When both legs were free of occlusion, TOI and nTHI patterns were identical with the patterns observed when the flow in only one leg was occluded; therefore, the effects of AO on the contralateral limb can be ruled out. These findings are supported by previous studies that showed that muscle activity did not change significantly with occlusion during a similar submaximal exercise (31).
Pilot testing with isometric contraction showed the same periodic pattern of TOI; therefore, the oscillatory pattern does not seem to depend on the type of exercise. Although no results in this sense were presented by previous studies, a visual inspection of previously reported tissue oxygenation data shows a quasiperiodic oscillation during isometric exercises (6). No statistical data regarding the frequency of these oscillations are available, however.
In the lower limb, of particular interest for tissue oxygenation measurements are the hydrostatic effects that can overlap with the exercise effects. Changing from the (usually) seated resting position to the upright position induces massive changes in peripheral tissue blood flow because of the changes in vascular hydrostatics. These changes occur during a relatively extended period (in our experiment up to 90 s) and can dramatically alter the results because of the overlapping of the exercise and hydrostatic effects. Some of the previous studies did not seem to properly address this issue (6). A visual inspection of preexercise oxygenation data reported in previous studies shows relatively large slopes moments before exercise, a clear indication that a preexercise steady state was not achieved (6). Care should therefore be taken in future studies to reach a steady state before the start of the exercise to minimize the confounding hydrostatic effects.
This study has shown that the muscle tissue oxygenation dynamics is more complex than previously thought. This makes the (typically) discrete point analysis comparison between the oxygenation data corresponding to different conditions very difficult because, at discrete points in time, the magnitude of the oxygenation data might be given by a periodic fluctuation due to the periodic oscillation and not due to a general trend. If precise measurements are required, it is imperative to compare the effects of a given treatment in the proper time scale and/or proper domain (frequency/time) that takes into account the periodic data pattern. In this particular study, we used linear regression to determine a global characteristic (recovery rate) of the oxygenation data and a frequency analysis to account for the periodic oscillations.
On the basis of these observations, the recovery data can be decomposed into a linear increase in the oxygenation data (probably due to vasodilation and indirectly increased blood flow) and a periodic oscillation modulating this linear increase (probably due to vasomotion). Vibrations seem to affect both the linear and the oscillatory component, and it would be interesting to study the mechanisms that might be responsible for these effects.
Mechanical vibrations used in this study induced a substantial increase in tissue blood flow-measured as a significant increase of total hemoglobin index-in the gastrocnemius medialis muscle. On the basis of these observations, one could envision a possible application of vibrations, as a tissue blood flow and/or oxygen saturation enhancer for patients with peripheral blood flow deficiency. However, several questions would have to be answered to confidently use vibrations as a means of improving peripheral blood flow. For instance, the mechanism responsible for the observed increase in blood flow in response to vibrations is largely unknown. Also, it is not known whether the effects are long lasting or if this is an immediate response. Depending on the answers to these (and other) questions, it might be possible to use vibrations as a means of enhancing tissue oxygenation and/or blood flow.
This study has also shown that the frequency of the oscillatory component of tissue oxygen saturation was affected by vibrations. It seems that mechanical vibrations might have an effect on tissue blood flow regulation at a fundamental level. It could be argued that the observed effect on the blood flow oscillations might be a by-product of the observed global tissue blood flow changes, but it might also be explained by an alteration of the tissue oxygen uptake mechanism. However, because little it is known about the blood flow/tissue oxygenation oscillations per se, any proposed mechanisms are highly speculative.
In conclusion, this study has shown, to the best of our knowledge, for the first time, the effects of WBV on muscle tissue oxygenation during a dynamic task without the confounding effects of blood flow. Also, it is our understanding that this was the first time when the periodic dynamics of the oxygen saturation after the initial depletion stage was reported in the context of muscle response to WBV. Vibrations seem to have an effect on both the tissue oxygenation depletion and recovery rate and on the periodic oscillations of tissue oxygenation and blood flow.
This study was financially supported by the Natural Sciences and Engineering Research Council of Canada, the da Vinci Foundation, Calgary, and adidas AG.
The authors have no conflict of interest to declare.
The results of the present study do not constitute endorsement by the American College of Sports Medicine.
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