Vol. 93, Issue 3, 1093-1103, September 2002
Muscle activity damps the soft tissue resonance that occurs
in response to pulsed and continuous vibrations
James M.
Wakeling,
Benno M.
Nigg, and
Antra I.
Rozitis
Human Performance Laboratory, Faculty of Kinesiology,
University of Calgary, Calgary, Alberta, Canada T2N
1N4
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ABSTRACT |
This study tested the
hypotheses that when the excitation frequency of mechanical stimuli to
the foot was close to the natural frequency of the soft tissues of the
lower extremity, the muscle activity increases 1) the
natural frequency and 2) the damping to minimize resonance.
Soft tissue vibrations were measured with triaxial accelerometers, and
muscle activity was measured by using surface electromyography from the
quadriceps, hamstrings, tibialis anterior, and triceps surae groups
from 20 subjects. Subjects were presented vibrations while standing on
a vibrating platform. Both continuous vibrations and pulsed bursts of
vibrations were presented, across the frequency range of 10-65 Hz.
Elevated muscle activity and increased damping of vibration power
occurred when the frequency of the input was close to the natural
frequency of each soft tissue. However, the natural frequency of the
soft tissues did not change in a manner that correlated with the
frequency of the input. It is suggested that soft tissue damping may be the mechanism by which resonance is minimized at heel strike during running.
damping; frequency; heel strike; impact; muscle; running
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INTRODUCTION |
SOFT TISSUES ACT AS
WOBBLING masses that vibrate in a damped manner in response to
direct mechanical excitation (31). Muscle activity alters
the vibration characteristics of the soft tissues with increases in
muscle force correlating to increases in their frequency and damping
coefficients (31). The natural frequencies of the triceps
surae, quadriceps, and tibialis anterior range from ~10 Hz for the
relaxed condition to 50 Hz for a fully active state (31).
If the excitation frequency of a mechanical stimulus is close to the
natural frequency of the soft tissues, then those tissues should be
expected to resonate.
During walking and running, the impact shock that occurs at heel strike
is indirectly transmitted to the soft tissues via the skeleton. Peak
impact forces at heel strike are reached within 30 ms (7,
23) and so have an excitation frequency in the range of
10-20 Hz. Soft tissue resonance should thus be expected to occur
at heel strike; however, observations show that such vibrations are
strongly damped with typically no more than a couple of cycles. It has
been shown that long-term exposure to vibrations can have detrimental
effects on the soft tissues including reductions in motor unit firing
rates and muscle contraction force (2) and decreases in
nerve conduction velocity and attenuated sensory perception (10,
13). Therefore it has been proposed that during walking and
running the soft tissues of the lower extremity have a strategy of
minimizing the soft tissue vibrations (24).
Muscle activity in the lower extremities responds to the
excitation frequency of the impact shock at heel strike
(36), in a processes referred to as muscle tuning.
However, the mechanisms of muscle tuning have not yet been identified.
Increasing the natural frequency of the soft tissues away from the
excitation frequency and increasing the damping coefficient of the
tissue are two possible strategies by which the soft tissues could
reduce tissue resonance. Both these strategies are possible using
muscle activity (31) and may be the mechanisms behind
muscle tuning during walking and running.
The purpose of this study was to identify how the lower extremity
muscles minimize the soft tissue resonance that occurs in response to
pulsed and continuous mechanical vibration. In particular, two
hypotheses were tested: 1) muscle activity increases the
natural frequency to minimize resonance when the excitation frequency is close to the natural frequency of the soft tissues, and
2) muscle activity increases the damping to minimize
resonance when the excitation frequency is close to the natural
frequency of the soft tissues. These hypotheses were tested in an
abstracted context of walking and running, whereby mechanical vibration
was delivered to the soft tissues indirectly through skeleton via the
plantar surfaces of the foot. Furthermore, the body geometry was chosen
to mimic the positioning and muscle activity that occurs at heel strike
during running.
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METHODS |
Approach to the problem.
To test hypotheses about the vibration response to impact forces that
typically occur during running, the impact related vibration task was
presented to subjects while they stood on a vibration platform. For one
test, a series of pulsed 5-mm displacements, with excitation frequency
of 13.1 Hz, were presented at 0.5-s intervals to mimic compression of a
running shoe at heel strike. This test was repeated for excitation
frequencies ranging from 10 to 65 Hz to span the expected range of
natural frequencies in the soft tissues of the lower extremity. The
amplitude of the displacements for these tests was scaled so that the
vibration power delivered to the body was constant. The experiment was
repeated with bursts of continuous vibrations that matched the
amplitude and excitation frequencies of the pulsed set. Subjects were
required to stand with a limb posture that satisfied a compromise
between achieving a similar geometry and muscle activity pattern within the lower extremity to that observed at heel strike during running. Myoelectric activity and soft tissue vibrations were measured from the
quadriceps, hamstrings, tibialis anterior, and triceps surae muscle
groups. The intensity of muscle activity and the dissipated vibration
power were compared for the different excitation regimes presented to
the subjects.
Subjects.
Ten male (age 25.6 ± 1.2 yr, mass 75.6 ± 2.8 kg; means ± SE) and 10 female (age 23.1 ± 0.5 yr, mass 61.1 ± 2.0 kg) subjects were tested. The subjects were athletic and were students
at the Sporthochschule, Köln. Subjects gave their informed,
written consent to participate in accordance with the University of
Calgary's Conjoint Health Research Ethics Board policy on research
using human subjects.
Muscle and soft tissue masses within the lower extremity were estimated
from a series of length, breadth, girth, and skinfold measurements. An
Executive Diameter steel tape was used to measure the proximal and
distal thigh and the proximal and distal calf lengths and the
subgluteal, midthigh, knee girth, ankle, and maximum calf girths while
the subjects stood. The midthigh position was located at half the
vertical distance between the greater trochanter (trochanterion) and
the superior margin of the lateral tibial condyle (tibiale laterale).
The midcalf position was located at the point of maximum girth of the
calf between the tibiale laterale and the inferior aspect of the
lateral malleolus (sphyrion fibulare). The proximal and distal thigh
were the thigh segments above and below the midthigh, respectively. The
calf measurements were similarly divided into proximal and distal
sections, above and below the midcalf. The width of the biepicondylar
femur and bimalleolare was measured using a GPM anthropometer
(SibnerHegner, Zurich, Switzerland). The patellar, midthigh, proximal
calf, midcalf, and medial calf skinfolds were measured with a
Harpenden caliper with a constant pressure of 10 g/mm2.
These anthropologic measurements were used to estimate the
segmental volume and mass (21, 29). Empirical, predictive
regression equations were used to estimate the segmental mass without
the bone (9) and finally the masses of the quadriceps,
hamstrings, tibialis anterior, and triceps surae soft tissues
(8).
Protocol.
Vibrations were applied to the subjects' feet via a hydraulically
driven platform (Schenck, Darmstadt) that was made available at the
University of Bochum (Fig. 1). The
platform was driven by a displacement-control system and was capable of
delivering 12.5-kN force. The hydraulic actuator was isolated from the
building by being mounted on an 8-ton mass linked to the floor via a
spring-damper system. The table displacement was controlled by a
personal computer using a National Instruments DAQCard-6062E 12-bit
data acquisition card, updating at 1,000 Hz.
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Fig. 1.
Subjects stood on a vibrating platform driven by a
hydraulic actuator. During each trial, the subject would rest his or
her hands on a safety bar that could stop the vibration if pressed. The
position of the accelerometers is illustrated by the arrows.
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Measurements on the lower leg occurred while the subjects stood with a
knee-flexion angle of 37°. During measurements on the thigh, the
subjects stood with a knee-flexion angle of 23°. A slightly flexed
knee was used to mimic the knee posture at heel strike during running.
Pilot testing of five subjects showed that these knee-flexion angles
resulted in muscle activities being 20-193% of those found at
heel strike during running. Standing with the heel in contact with the
vibration platform resulted in uncomfortable and unsustainable
vibrations traveling through the body. However, the long vibration
loads during the experiment could be sustained by subjects standing on
their forefeet with the heels raised 1 cm above the ground.
The test consisted of a cycle of 3 s of vibration followed by
3 s of no platform movement. During each vibration period, the frequency and amplitude of the platform vibration were kept constant. Frequencies of 10.0, 13.1, 17.1, 22.3, 29.1, 38.1, 49.7, and 65.0 Hz
were tested and covered the range of natural frequencies previously described for the lower extremity muscles at different activation levels (31). These eight frequencies were presented in a
randomized block. The randomized block was then repeated five times so
that the subject experienced a total of 40 periods of vibration in each
test. One such test was performed while measurements were taken from
the lower leg, and then the test was repeated while measurements were taken from the thigh. Tests were made when each period of vibration contained continuous sinusoidal oscillations of the
platform. The peak-to-peak amplitude of the platform displacement was 5 mm at 13.1 Hz to mimic expected shoe compression during running. The
displacement amplitude was scaled at the other frequencies so that the
power delivered by the platform was constant across all frequencies. A
second set of tests was performed in which each period of table
movement consisted of pulses of seven bursts of isolated table
displacements separated by 0.5-s intervals. The amplitude and duration
of each displacement were changed to result in effective amplitudes and
cycle frequencies that matched the continuous vibration experiments.
Further experiments were made to determine the natural vibration
frequencies of the soft tissues. In these experiments, 120-s periods of
white noise (band-pass filtered between 5 and 100 Hz) were used to
drive the platform displacements.
The response variables determined for the lower extremities were the
myoelectric activity in the rectus femoris, biceps femoris (long head),
tibialis anterior, and medial gastrocnemius muscles. Myoelectric
activity was measured from the muscle bellies by using round bipolar
surface electrodes (Ag/AgCl) after removal of the hair and cleaning of
the skin with isopropyl wipes. Each electrode was 10 mm in diameter and
had an interelectrode spacing of 22 mm. A ground electrode was placed
on the lateral condyle of the knee. The electromyograms (EMGs) were
preamplified at source (Biovision, Wehrheim, Germany). Tissue
vibrations were also measured from the soft tissues of the quadriceps,
hamstrings, tibialis anterior, and triceps surae muscle groups. Soft
tissue vibrations were measured from the muscle bellies of the vastus
lateralis, biceps femoris (long head), tibialis anterior, and lateral
gastrocnemius by using skin-mounted triaxial accelerometers (EGAX
accelerometer, nominal frequency response 0-600 Hz; Entran
Devices). Accelerometers (<5 g) were attached to the skin surface by
using Hollister medical adhesive glue, and a stretch adhesive bandage
preloaded the accelerometer to improve the congruence of motion with
the soft tissues (31, 32). One uniaxial accelerometer was
mounted directly to the bottom surface of the platform to measure the
platform movement. Myoelectric and acceleration signals were recorded
at 2,400 Hz on the DAQCard-6062E 12-bit data acquisition card.
Vibration analysis.
Frequency spectra were generated for the acceleration signals in each
direction by using Fourier transforms to yield the amplitude of the
acceleration as a function of frequency a(f). The
soft tissue mass is considered a rigid mass for the analysis. For each given frequency f, the mean inertial power P required to
oscillate the soft tissue mass m is given by
Therefore the total inertial power P't
required for the oscillation in the given direction is given by
Soft tissue oscillations occur in all three orthogonal
directions, and the total inertial power Pt required for
the whole soft tissues vibration is given by the resultant power from
the three directions (x, y, z)
At the beginning of each period of vibration, the body could not
anticipate its response. However, during the periods of continuous
vibration, the soft tissue responses were apparent after 150 ms and
resulted in a decrease in the amplitude of the acceleration (Fig.
2). A steady Pt was
calculated for a 1-s steady period that began 1 s after the onset
of the vibration. The difference in inertial power Pt
between the table and the soft tissue represents the power dissipated
by the soft tissue during its steady response to the continuous
vibration. Similarly, when exposed to bursts of pulsed vibrations, the
body could not anticipate its response to the initial burst.
However, soft tissue responses were typically apparent for all
subsequent pulses (pulses 2-7) and resulted in a
decrease in the amplitude of the acceleration (Fig.
3). A mean Pt was calculated
from the maximum peak-to-peak accelerations from each of pulses
2-7. Again, the difference in inertial power Pt
between the table and the soft tissue represents the power dissipated
by the soft tissue during its steady response to the pulses of
vibration. The power dissipation was considered as showing a response
to the experimental interventions if a maximum in the power dissipation
occurred in the range of frequencies tested.
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Fig. 2.
Electromyogram (EMG) trace from the medial gastrocnemius
(A) and acceleration traces from the triceps surae
(B-D) during 1 burst of continuous
vibrations. Acceleration traces are shown for the direction normal to
the skin surface (B), parallel to the tibia (C),
and mediolateral (D). Platform acceleration is shown in E,
with the corresponding displacement in F. The excitation
frequency was 10 Hz, and the natural frequency for the triceps surae
for this subject was 15 Hz. The equivalent EMG trace for the rectus
femoris is shown in G.
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Fig. 3.
EMG trace from the medial gastrocnemius (A) and
acceleration traces from the triceps surae
(B-D) during 1 set of pulsed vibrations.
Acceleration traces are shown for the direction normal to the skin
surface (B), parallel to the tibia (C), and
mediolateral (D). Platform acceleration is shown in
E, with the corresponding displacement in F. The
excitation frequency of each pulse was 10 Hz, and the natural frequency
for the triceps surae for this subject was 15 Hz. The equivalent EMG
trace for the rectus femoris is shown in G.
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The natural free vibration frequency was calculated from the soft
tissue accelerations that followed each pulse of vibration using
methods described by Wakeling and Nigg (32). Acceleration data were taken from the time window starting 100 ms after the onset of
each pulse and lasting for 230 ms. An exponentially damped sinusoidal
model was fitted to the data with a least squares fit. When the
Rank-Pearson correlation coefficient between the measured and modeled
vibration had a value >0.85, the natural frequency was taken to be
equal to the sinusoidal frequency in the model. Natural frequencies
were calculated for the direction parallel to the major axis of the
limb segment and for impacts 2-7 from each burst.
EMG analysis.
The EMG signals were resolved into the myoelectric intensity in
time-frequency space by use of wavelet techniques (30). A
set of 11 wavelets was used with center frequencies ranging from 7 Hz
(wavelet 0) to 395 Hz (wavelet 10). The intensity
of the myoelectric signal is the power of the signal contained within a
given frequency band and is equivalent to twice the square of the root
mean square activity (36). The total intensity was calculated across wavelets 1-10, which is equivalent to
band-pass filtering the signal between 11 and 432 Hz. EMG signal was
interpolated across the frequency band at which movement artifacts may
have occurred. For each response, the interpolation was taken from 2 Hz
above to 2 Hz below the peak soft tissue vibration frequency. This
process did not systematically alter the calculated EMG intensity; however, it did reliably remove the movement artifact at these frequencies.
Previous studies have shown that, when this recording apparatus is
used, distinct patterns of myoelectric activity can be identified at
the frequency bands 25-75 Hz and 150-300 Hz
(35), and these are likely the signals from different
muscle fiber types (33, 35). The myoelectric signals were
thus also resolved into their intensities in these high- and
low-frequency bands.
During the continuous vibration experiments, the mean intensity of the
EMG was determined for a 250-ms quiet period that ended 250 ms before
each vibration began and then for a 1-s steady period that began 1 s after the onset of the vibration. A relative measure of the EMG
intensity was taken as the ratio of the mean EMG intensity during the
1-s steady-state vibration period to the mean EMG intensity during the
250-ms quiet period before each vibration. The EMG intensity was
considered as showing a response to the experimental interventions if
it showed a maximum in the range of frequencies tested. For the pulsed
bursts of vibrations, the mean EMG intensity was calculated for the
50-ms preactivation window that immediately preceded each pulse. The
intensity was calculated for the preactivation before the initial
pulse, and a mean intensity was calculated for the preactivations to
pulses 2-7.
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RESULTS |
Soft tissue resonance frequencies.
The male subjects had greater soft tissue masses than the female
subjects (Table 1), and this difference
was significant (P < 0.05, ANOVA). Analysis of
covariance using mass as a covariate and muscle and gender as factors
showed that there was no significant effect of the gender on either the
natural or mean resonance frequencies. Therefore, the results for both
genders were pooled for further analysis.
Sample resonance spectra from when the subjects stood on white-noise
platform displacements can be seen in Fig.
4. The peak of such spectra give the
natural frequency, and the mean ± SE natural frequencies pooled
across all 20 subjects were 14.4 ± 0.6, 15.9 ± 1.4, 14.7 ± 0.3, and 15.2 ± 0.3 Hz for the tibialis anterior,
triceps surae, quadriceps, and hamstrings, respectively. The resonance
spectra for the tibialis anterior and triceps surae were more skewed
toward the higher frequencies than the resonance spectra for the
quadriceps and hamstring soft tissues. This skewness resulted in
significantly higher mean frequencies for the tibialis anterior and
triceps surae (22.1 ± 0.8 and 20.1 ± 0.7 Hz, respectively) than for the quadriceps and hamstrings (14.4 ± 0.3 and 14.7 ± 0.3 Hz, respectively), as shown by a Tukey's honestly significant difference pairwise comparison test following ANOVA (
= 0.05).
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Fig. 4.
Resonance spectra from soft tissues from 1 subject exposed to the
white noise input signal. Natural frequency (NF) and mean frequency
(MF) are given for each resonance spectrum.
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Soft tissue and muscle response to continuous vibrations.
Response spectra for both the EMG intensity and the power dissipation
during the continuous-oscillation experiments are shown in Fig.
5. There were a total of 75 such
responses for power dissipation and 31 responses for the EMG intensity
out of a possible 80 subject-muscle combinations. The majority of cases
in which responses did not occur resulted in the greatest EMG intensity
and power dissipation occurring at the 10-Hz input signal. Both
response spectra showed peaks close to the natural frequencies of the
soft tissue masses. The shapes of the response spectra were similar to
those of the resonance spectra for each soft tissue. Thus, when the
input frequency was close to the natural frequency of each soft tissue,
there was an increase in the muscle activity in that tissue, which
resulted in an increase in the vibration damping and power dissipation. When the data were calculated from all the response cases observed, and
not just those in which responses occurred in both EMG and power
dissipation, the resulting response spectra showed all the same
features as those in Fig. 5. The results from the continuous-vibration trials thus support the hypothesis that when the frequency of the input
force is the same as the natural frequency of the soft tissue packages
there is an increase in both the muscle activity and the vibration
power dissipated by that tissue.
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Fig. 5.
Resonance spectra and the response spectra for
sinusoidal oscillations shown for the tibialis anterior (A),
triceps surae (B), quadriceps (C), and hamstrings
(D) soft tissue groups. The mean resonance spectrum is shown
by the thick trace with dashed lines showing ±SE.  ,
Power dissipated during the steady-vibration period between the
vibration platform and each soft tissue group.  , Ratio
of the EMG intensity from the steady vibration period to the quiet
previbration period. The resonance spectra and EMG traces have
been normalized to a maximum value of 1 for each graph. The means for
each line have only been calculated for subjects who show a response in
both EMG and power dissipation.
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The EMG intensity during the 1-s steady-vibration periods was greater
than the EMG intensity during the no-vibration quiet periods across all
frequencies tested. These increases in EMG intensity occurred in the
total intensity as well as in the low- and high-myoelectric-frequency
bands (Table 2). ANOVA for each muscle
showed that there was no significant difference between the relative
increases for the total intensity and at the high- and low-frequency
bands. The total EMG intensities when the subjects were tested at a
13.1-Hz input frequency (n = 20) were 6.3 ± 1.5, 3.3 ± 0.8, 1.8 ± 0.2, and 4.2 ± 1.3 times the
intensity of quiet EMG for the tibialis anterior, medial gastrocnemius,
rectus femoris, and biceps femoris, respectively.
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Table 2.
The relative EMG intensity during the 1-s steady continuous-vibration
period compared with the quiet period
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Soft tissue and muscle response to pulsed vibrations.
The data were only able to resolve responses in power dissipation in 17 cases for the pulsed-vibration experiments. Reduced major-axis
regression analysis showed that there were significant correlations in
the power dissipation between the mean response to the pulsed
vibrations and the mean response to the continuous vibration for all
four soft tissue groups, with the coefficients of determination
0.96 < r2 < 0.99. The maximum power
dissipated in the pulsed case was 19-35% of that for the maximum
power dissipated in the continuous vibration case. Increases in soft
tissue power dissipation thus occurred in response to pulsed vibrations
that were close to the natural frequency in a similar manner to the
responses to continuous vibration. The results from the
pulsed-vibration trials thus support the hypothesis that when the
frequency of the input force is the same as the natural frequency of
the soft tissue packages there is an increase the vibration power
dissipated by that tissue.
The natural frequencies (NF) of the soft tissues during the
pulsed-vibration trials showed a broad response to the pulse duration of the test impacts, with peaks occurring at input frequencies between
17.1 and 29.1 Hz (Table 3). The maximum
NF (NFmax) were between 14.6 and 44.9% greater than the NF
at the 10-Hz input frequencies. The NF increased at a lower
rate than the increases in input frequency between the 10-Hz input
frequency and the input frequency at which NFmax occurred.
When NFmax occurred, it was smaller than the input
frequency for all four soft tissue masses. The results from the
continuous-vibration trials thus do not support the hypothesis that
when the frequency of the input force is the same as the natural
frequency of the soft tissue packages there is an increase in the
natural frequency of that tissue.
Postdisplacement peaks of EMG intensity occurred ~80 ms after each
onset of the platform displacement during the pulsed-vibration tests.
These postdisplacement peaks in myoelectric intensity occurred predominantly at the low (25-75 Hz) EMG frequency band. A typical postdisplacement peak is shown in Fig. 6,
A and B, for impact 1 from a 3-s
burst; however, the traces from the subsequent pulses (2-7) show similar postdisplacement activities. After
the first pulse, the body responded to the subsequent pulses
2-7 with altered muscle activity immediately before each
pulsed platform displacement. Figure 6, C and D,
shows the relative change in EMG activities for pulses
2-7 compared with the EMG intensity for pulse 1.
The response to the pulses 2-7 consisted of an increase
in the myoelectric activity at the high (150-300 Hz)-EMG-frequency
band, and this increase occurred within the 50-ms period before the
table displacement.
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Fig. 6.
A: mean EMG intensity from the medial
gastrocnemius for 1 subject for the initial impacts for the 5 trials at
a 13.1-Hz pulse frequency. B: intensities for the high
(150-300 Hz; dashed line)- and low (25-75 Hz; solid
line)-EMG-frequency bands (mean, thick line ± SE, thin lines;
n = 5) for these initial impacts. C: mean
EMG intensity for the subsequent 6 impacts for the 5 trials
(n = 30) shown as their ratio to the mean EMG for the
initial impacts. D: intensities for the high (150-300
Hz; dashed line)- and low (25-75 Hz; solid line)-EMG-frequency
bands shown as their ratio to the mean EMG intensity at the respective
frequency band for the initial impacts (mean ± SE;
n = 30). In all graphs, the onset of each pulse
occurred at a time of 0 ms.
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During the pulsed-vibration tests, there was an increase in the total
EMG intensity in the 50-ms preactivation phase relative to the quiet
EMG intensity. Specific increases in intensity occurred in the
high-EMG-frequency band and decreases in the intensity occurred at the
low-EMG-frequency band (Table 4). ANOVA
for the tibialis anterior, medial gastrocnemius, and rectus femoris
showed that these relative changes in total, high-EMG-frequency band, and low-EMG-frequency band intensities were significantly different. The increase in total EMG intensity in the preactivation phase was
significant for the medial gastrocnemius and biceps femoris, and the
increase in intensity at the high-EMG-frequency band was significant
for all four muscles tested. The EMG intensity in the preactivation
phase showed a response to the pulse duration of the impacts for a
total of 24 cases out of the 80 possible subject-muscle combinations.
The majority of cases, in which responses did not occur, resulted in
the greatest EMG intensity occurring at the 10-Hz input signal. The
total EMG intensities when the tissues were exposed to pulses at a
13.1-Hz input frequency (n = 20) were 1.2 ± 0.1, 1.3 ± 0.1, 2.2 ± 0.6, and 2.1 ± 0.7 times the
intensity of quiet EMG for the tibialis anterior, medial gastrocnemius, rectus femoris, and biceps femoris, respectively. Responses to the
pulsed vibrations thus occur as increases in the total intensity of the
50-ms preactivation EMG activity and in particular an increase in the
intensity at the high-EMG-frequency band. The results from the
pulsed-vibration trials thus support the hypothesis that when the
frequency of the input force is close to the natural frequency of the
soft tissue masses there is an increase in the muscle activity within
that tissue.
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Table 4.
The EMG intensity during the 50-ms pre-activation periods for the
pulsed impacts relative to the EMG intensity during the quiet period
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DISCUSSION |
Peaks in the EMG intensity occurred when the vibration input
frequency was close to the natural frequency of each respective soft
tissue (Fig. 5). However, the response of the power dissipation and the
natural frequencies of the soft tissues were not equivalent (Figs. 5
and 6; Table 4). The response to the vibrations during this experiment
consisted of a sharp peak in the power-dissipation curve, which
corresponded to an increase in the damping of the vibration when the
input frequency was close to the natural frequency of the soft tissues.
The natural frequencies of the soft tissues, on the other hand, showed
much broader and smaller peaks, which did not follow the changes in the
input frequency. It would appear from these results that the muscle
tuning reaction to the vibration input was primarily one of an increase
in the vibration damping, and the changes in frequency may have been a
consequence of the altered muscle activity. Similar results have been
shown for vibration damping in the horse leg, where digital flexor
muscles are implicated in damping high-frequency vibrations while only
causing a minor change in the frequency characteristics of the limb
(37).
Limitations to the experimental design.
The experimental procedure was physically demanding for the subjects.
For this reason only athletic persons were chosen as test subjects.
Nevertheless, one subject showed visible muscle tremors that were
presumably the result of fatigue. The results from this subject were
excluded from further analysis. To minimize fatigue-related effects,
the order in which the vibration stimuli were presented was randomized
into a repeated-block design. If muscle fatigue occurred toward the end
of the experiment, then this randomized design should remove possible
bias from the results.
The amplitude of the vibrations was varied between test frequencies so
that the resultant powers of the input vibrations were the same across
all frequencies. This design was chosen so that the power dissipated
owing to the vibrations could be compared across the range of inputs.
However, measurements of the platform displacements using an
accelerometer showed that the displacement at the 10-Hz input frequency
was greater than required, resulting in a greater input power. For this
reason, if a subject were to show the greatest power dissipation in
response to the 10-Hz input, we could not be sure whether this reflects
the greater power in the input or a greater response of the body.
However, every time there was a peak in the response at frequencies
greater than 10 Hz, we can be sure that this is a response of the soft
tissues of the lower extremity to the input vibration. It is possible that subjects who did not show a response at frequencies greater than
10 Hz may have responded to inputs of 10 Hz or less.
The power dissipated by the soft tissues was calculated according to
the assumption that the soft tissue moved as one rigid body. In some
cases the resonance spectra for the soft tissues (Fig. 4) showed that
there were a number of distinct resonant frequencies. This indicates
that the soft tissues vibrated as a continuum mass rather than a rigid
body. The power dissipated from the soft tissues was calculated across
all frequencies from the measured vibration and therefore accounts for
the power dissipated at all distinct frequencies. However, waves of
vibration will travel within a flexible structure in addition to its
gross motion. Damping of these waves involves additional power
dissipation that cannot be accounted for by using this experimental
design. The values presented from this study may thus be
underestimations of the actual power dissipated by the soft tissues. To
account for power dissipation from waves within the tissue, future
experiments would require acceleration measurements from multiple sites
across each soft tissue.
Mechanisms for muscle tuning.
The body relies on several mechanisms to regulate shock transmission
through the body in response to impact forces: bone, cartilage,
synovial fluids, soft tissues, joint kinematics, and muscular activity.
Of these mechanisms, the body has immediate control over the joint
kinematics and the muscle activity. The purpose of this study was to
test damping mechanisms that can be altered by the body and thus that
can be actively tuned to the excitation conditions. Impact energy can
be dissipated from the knee and ankle joints because of joint
compliance (14, 19), and this compliance can be altered by
changes in joint angle and the forces of muscles crossing the joint.
The vibration characteristics of the soft tissues change with joint
angle as a result of changes in both muscle force and passive tension
in structures such as the skin and connective tissue (31).
To maintain joint compliance as constant as possible, the knee and
ankle joint angles were controlled before each set of vibrations, and
the subjects were required to stand with a static posture. Therefore,
the predominant active process that changed in response to the
presented vibrations was the muscle activity that changed the vibration
characteristics of the soft tissues.
The results from this study demonstrate that the soft tissues of the
lower extremities vibrate in a damped manner after exposure to pulsed
or continuous vibrations. In order for the soft tissues to vibrate in
such a manner they must have viscoelastic properties. Two major
components within the muscle-tendon units that contribute to the
stiffness of the system are the tendon and the attached cross bridges
within the muscle (22, 26). Mechanical energy can be
stored and returned from the elastic structures of the tendon and the
attached cross bridges during soft tissue vibrations. Damping of the
vibrations results in a net dissipation of mechanical energy. Damping
may occur at the structural or material levels of the soft tissues. The
muscle structure changes during force production as more cross bridges
are attached, and the damping coefficients of the soft tissues increase
with muscle force (31). Energy is absorbed during
high-frequency vibration of activated muscle (11) that is
not absorbed by muscle in rigor (17). Thus energy
absorption by the muscle during vibrations can be attributed to the
detachment and cycling of cross bridges. Such dissipation of mechanical
work by the muscle appears as vibration damping in these experiments.
The power dissipated by a muscle during vibration depends on the
amplitude of the vibration and the kinetics and the number of attached
cross bridges. Cross-bridge models have predicted that the digital
flexor muscles in the horse can dissipate 2 J per cycle during a 10-Hz
vibration (37), which equates to 20 W/kg muscle. In this
study, the muscle mass-specific peak power dissipations (Fig. 5) were
1.56 ± 0.16, 2.29 ± 0.16, 2.29 ± 0.16, and 2.30 ± 0.11 W/kg for the tibialis anterior, triceps surae, quadriceps, and
hamstring muscles, respectively. In this study, the lower extremity
muscles were not fully activated, and so lower values for power
dissipation would be expected than for the horse model in which it was
assumed that power dissipation occurred from all cross bridges. The
power dissipated in this study is at a level that can be explained by
cross-bridge kinetics within the muscle.
Muscle response to vibration.
Bursts of muscle activity occurred immediately before the onset
of platform displacement during the pulsed-vibration experiments. These
bursts of muscle activity did not occur before the first burst of
vibration of each set, but they occurred for the subsequent bursts 2-7 (Fig. 6, C and D).
When a muscle is activated, it takes time before the muscle force is
fully developed, and for isometric twitches in mammalian slow muscle
this time is in the range 58-110 ms (6). Because of
the time delay between the onset of muscle activation and the
development of muscle force, the muscles must be activated before an
expected action occurs. In this study, muscle preactivation occurred as
an anticipatory response to the pulsed impacts. Similar muscle
preactivations have been observed in response to cyclic heel-strike
impacts from a human pendulum experiment (36) and before
landing from falls of different heights (28). The EMG
intensity during the 50-ms preactivation period before each burst of
vibration occurred predominantly in the high (150-300
Hz)-EMG-frequency band (Table 4). Myoelectric signals within this
high-frequency band have been shown to be characteristic of fast motor
unit activity (33, 35). It is, therefore, likely that the
muscle activity required for the vibration-tuning task in the
preactivation period of this study was from predominantly the faster
motor units of the lower extremity muscles.
If the contractile element remained isometric during the vibrations,
then it could not perform or dissipate any mechanical work. Small
changes in muscle strain, however, would allow the contractile element
to dissipate power by cyclically generating force while it was
stretched and relaxing that force while it shortened. Such a mechanism
would only be possible if the muscle could modulate its force at the
same frequency as the vibration frequency. For example, the period of a
13.1-Hz cycle of vibration is 76 ms, and the muscle must be able to
perform a contraction and relaxation cycle within this time if it is to
dissipate power from such an oscillation. Mammalian slow-twitch fibers
have slow contraction-relaxation kinetics and slow rates of myosin
ATPase activity (1) with, for instance, contraction times
for the cat gastrocnemius muscle ranging between 58 and 110 ms
(6). Such long contraction kinetics would reduce the
effectiveness of slow-twitch muscle fibers from dissipating power from
the vibration stimuli in this experiment. However, fast-twitch muscle
fibers can have twitch contraction times as short as 20 ms
(6) and so would be better suited to the dissipation of
the vibration power. This prediction supports the observations from
this study that the muscle tuning response to the pulsed impacts occurs
as an increase in the EMG intensity in the high-EMG-frequency band, which likely corresponds to the fast motor unit activity.
A burst of muscle activity occurred immediately after each impact
during the pulsed vibrations. The peak EMG intensity in these
postimpact events occurred ~80 ms after each onset of the table
movement, with the initial increase in EMG occurring in as little as 50 ms (Fig. 6, A and B). These bursts of muscle
activity typically occurred after every impact and were likely due to
stretch reflexes. These bursts of muscle activity predominated in the low (25-75 Hz)-EMG-frequency band, which likely represents the activity of predominantly slower motor units (33). Thus
the bursts of muscle activity after each impact may not generate
significant force until at least 100 ms after the onset of the impact.
The soft tissue vibrations following the pulsed impacts had little more
than one or two cycles before they were substantially damped (Fig. 3),
and there was significant damping even within the first cycle of each
impact. Therefore, it is unlikely that the bursts of muscle activity
that occurred after each pulse of vibration would have contributed
significantly to the damping of the vibration caused by each pulse of vibration.
The muscle response to the continuous-vibration trials occurred
as a general increase in the muscle activity (Table 2). The data cannot
discriminate whether increases in EMG intensity occurred preferentially
in the high (150-300 Hz)- or low (25-75 Hz)-frequency bands.
Similarly, because of the continuous nature of the vibrations, the EMG
signal from stretch reflexes cannot be discriminated from that for
anticipatory, feed-forward responses. Reflex muscle contraction, the
tonic vibration reflex, can be evoked by using continuous mechanical
vibration (15). The tonic vibration reflex is mainly attributable to the muscle spindle Ia fibers that are able to respond
to vibration frequencies of up to 200 Hz (4-5, 27). However, it has not clearly been demonstrated whether the pathways involved in the tonic vibration reflex are monosynaptic or
polysynaptic. Motor unit firing patterns are phase-locked to the
vibration frequency, although at higher excitation rates the motor
units fire at a subharmonic of the excitation frequency (3,
16). The motor unit discharge rate during tonic vibration
reflexes in the triceps surae reaches 10 Hz, so at higher excitation
frequencies not every cycle of vibration elicits a motor unit response
(3). Dissipation of vibration power requires that the
muscle performs net negative work, i.e., that it produces more force
during lengthening than during shortening. Therefore, if power is to be
dissipated, the phasic muscle activation during the tonic vibration
reflex must satisfy the requirements that the muscle generates force at
the correct time relative to the vibration.
Soft tissue vibrations during walking and running.
Impact forces during heel-toe running typically have a maximum between
10 and 30 ms (7, 23) and a major frequency component between 10 and 20 Hz. This frequency range spans the natural
frequencies of the soft tissues measured in this study, which were
~15 Hz. Thus there is potential for vibrations in the soft tissues to occur as a result from the impact forces. Shoe material hardness alters
the loading rate of the impact force during running (12, 18, 20,
25) and thus may alter the tuning requirement for each soft
tissue. Indeed, it has been shown that the muscle activity required for
tuning the tissues to the impact force changes when the loading rate of
the impact force was altered on a pendulum experiment (36)
and also for overground running (34).
The results from this present study showed that the mechanical
properties of the soft tissues in the lower extremities were tuned in
response to the frequency content of each vibration input. The
experimental protocol was designed to mimic the frequencies of actual
impact forces that occur during running. However, the experiment
consisted of a static task and not the dynamic movement of a locomotor
activity. It remains to be seen whether similar changes in frequency
and damping occur during running. The results from this experiment also
show that the muscle activity patterns in the lower extremity are
modified as a response to changes in the excitation frequency of input
signals (e.g., impact forces). Such changes can be achieved with the
material properties of a shoe midsole (12, 18, 20, 25).
However, further work needs to be done to identify the natural
frequencies that occur in the soft tissues at heel strike during
walking and running.
| |
ACKNOWLEDGEMENTS |
We thank Drs. Joachim Mester and Clemens Treier for providing the
infrastructure and support in Germany that was necessary to make these
experiments possible.
| |
FOOTNOTES |
Financial support was given by Adidas, the Alberta Heritage Foundation
for Medical Research, and the DaVinci Foundation.
Address for reprint requests and other correspondence: J. M. Wakeling, Human Performance Laboratory, Faculty of Kinesiology, Univ. of Calgary, Calgary, Alberta, Canada T2N 1N4 (E-mail:
wakeling{at}kin.ucalgary.ca).
The costs of publication of this
article were defrayed in part by the
payment of page charges. The article
must therefore be hereby marked
"advertisement"
in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
May 17, 2002;10.1152/japplphysiol.00142.2002
Received 25 February 2002; accepted in final form 14 May 2002.
| |
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ABSTRACT
INTRODUCTION
