ELECTROMYOGRAPHIC STUDY OF A SEQUENCE OF YAU-MAN KUNG FU PALM STRIKES
WITH AND WITHOUT IMPACT
Institute of Research and Development, University of Vale do Paraíba, São
José dos Campos, SP, Brazil.
15 February 2007
Journal of Sports Science and Medicine (2007)
6(CSSI-2), 23 - 27
Google Scholar for Citing Articles
|In martial arts and contact sports, strikes are often trained
in two different ways: with and without impacts. This study aims to
compare the electromyographical activity (EMG) of the triceps brachii
(TB), biceps brachii (BB) and brachioradialis (BR) muscles during
strikes with and without impacts. Eight Yau-Man Kung Fu practitioners
participated in the experiment. Each participant performed 5 sequences
of 5 consecutive KF Yau-Man palm strikes with no impact intercalated
with 5 sequences of 5 repetitions targeting a KF training shield.
Surface EMG signals were obtained from the TB, BB, and RB for 3.0
seconds using an eight-channel module with a total amplifier gain
of 2000 and sampled at 3500 Hz. The EMG analyses were done in the
time (rms) and frequency (wavelet) domains. For the frequency domain,
Morlet wavelet power spectra were obtained and an original method
was used to quantify statistically significant regions on the power
spectra. The results both in the time and frequency domains indicate
a higher TB and BR muscle activity for the strikes with impacts. No
significant difference was found for the BB in the two different scenarios.
In addition, the results show that the wavelet power spectra pattern
for the three analysed muscles obtained from the strikes with and
without impacts were similar.
WORDS: Electromyography, wavelet transform, impact, martial
Martial Arts has a history of thousands of years. During the past
1500 years, many different styles of Kung Fu (KF) have been developed
in China and several of them are still being practiced. The Yau-Man
style of KF was developed during the Ch'ing Dynasty (1644-1911)
with the purpose to help Chinese revolutionaries in the war against
the Manchu invaders (Neto et. al, 2007).
The Yau-Man KF was developed from the collective knowledge of several
other ancient styles. The strikes of Yau-Man KF differ from most
other combat sports' strikes because they usually begin closer to
the target or opponent. Other distinguished characteristic of the
Yau-Man strikes is that the movements are terminated before full
extension of the arms (Neto et al., 2007).
In most martial arts and contact sports strikes are often trained
in two different ways: with and without impacts. In the last couple
of years, there have been studies that focused on strikes with impacts
(Neto et al., 2007;
Walilko et. al., 2005)
and without impacts (Neto and Magini, 2007;
Ribeiro et al., 2006).
However, the authors are not aware of any article that compared
either physiological or biomechanical variables in both scenarios.
This study aims to compare the EMG of the triceps brachii (TB),
biceps brachii (BB) and brachioradialis (BR) muscles during strikes
with and without impacts.
Kung Fu Yau-Man practitioners (training experience of 2.8
± 3 years; 1 year minimum) were selected to participate in
the experiment. The participants' average height, mass and
age were 1.76 (SD = 0.05) m, 75 (SD = 9.2) Kg, and 21.8 (SD
= 5.9) years. Each participant performed 5 sequences of 5
consecutive KF Yau-Man palm strikes without impact intercalated
with 5 sequences of 5 repetitions targeting a KF training
shield. A detailed description of this movement can be found
on Neto et al., 2007.
Surface EMG signals were obtained from the biceps brachii
(BB), brachioradialis (BR) (two of the main antagonist muscles)
and triceps brachii (TB) (main agonist muscle) at the dominant
side of the body. The participants were allowed to position
themselves in relation to the shield and to adjust its height
as they wished.
This methodology was approved by the University of Vale do
Paraíba Ethics in Research Committee (Protocol #: L008/2005/CEP)
and all participants or legal responsible provided their informed
The surface EMG signals were obtained according to standard
procedures (De Luca, 1997)
for 3.0 seconds using an eight-channel module (model EMG800C,
EMGSystem, Brazil) with a total amplifier gain of 2000 and
sampled at 3500 Hz. A 12 bits AD converter digitalized the
analogue signals with a sampling frequency of anti-aliasing
of 2.0 kHz for each channel and an input range of 5mV. Active
bipolar superficial electrodes consisting of two rectangular
parallel bars of Ag/AgCl (1 cm in length, 0.2 cm in width
and separated by 1 cm) were used and coupled to a rectangular
acrylic resin capsule 2.2 cm in length, 1.9 cm in width and
0.6 cm in high with an internal amplifier (with gain of 20)
in order to reduce the effects of electromagnetic interference
and other noises. After shaving and cleaning the skin with
alcohol, the electrodes were placed on the muscles guided
by bone prominences and the route of the muscle fibbers. EMG
sensors and sensor placement procedures were in agreement
with recommendations resulted from SENIAM studies (Hermens
and Freriks, 2000).
All EMG data was processed off-line with Matlab 7.0.1 (MathWorks
Inc) following standard procedures (De Luca, 1997).
The EMG signals were filtered (Butterworth order 4, band pass
50-500Hz) to eliminate noise from the movement of artefacts
and to consider the band of the power spectrum of higher energy.
The lower frequency threshold was chosen because of the greater
arm speed in martial arts strikes compared to most other types
of arm movements (Neto and Magini, 2007).
The EMG signals were analysed in the time and frequency domains.
For the time domain analysis the EMG signals were full wave
rectified and then linear smoothed using a low pass Butterworth
order 4 filter with a cut frequency of 14 Hz (Bolgla and Uhl,
The mean amplitude for this linear envelope was determined
and it was used to normalize the EMG signals from which root
mean square (rms) values were calculated. For the frequency
domain, the EMG signals were normalized by the standard deviation.
The frequency domain analyses were done by Morlet wavelet.
Wavelet power spectra were generated using the algorithm developed
by C. Torrence and G. Compo (1998
- available at URL: http://paos.colorado.edu/research/wavelets).
The wavelet power spectra can be seen as a flat three-dimensional
graph; the y-axis gives the period (s), the x-axis gives the
time (s) and different colours indicate the different power
values (V2). Another information given in the spectra
is the statistically significant regions of the spectra, which
are delimited by thick contours. An algorithm was developed
in Matlab 7.0.1 (MathWorks Inc.) to determine the sum of the
significant power (SSP) on the wavelet power spectra. SSP
values were calculated adding up power values that fell inside
the significance contours.
The comparisons of rms and SSP values from the strikes with
and without impact were done using a balanced Multivariate
Analyses of Variance for repeated measures. The Turkey method
was used for a pair wise comparison of means. Intrasubject
coefficient of variation (IACV) for each muscle with and without
impact were calculated by dividing the standard deviation
of the SPS and rms values for the five sequences of strikes
for each participant by its respective mean. Intersubject
coefficient of variation (IECV) were calculated for each muscle
with and without impact by dividing the standard deviation
of the SPS and rms values for all sequences of strikes by
their respective means. All statistical analyses were conducted
using MINITAB® 14.12.0 (Minitab Inc.) at the 0.05 level of
significance. The power spectra thick contour encloses regions
of greater than 95% confidence in the qui-square test for
a red-noise process with a lag-1 coefficient of 0.72 (Torrence
and Compo, 1998).
Both rms (see Table 1) and
SSP (see Table 2) results indicate
a significant higher TB and BR muscle activity for the strikes with
impacts considering the repeated measures for all eight participants
(p < 0.01 for both rms and SSP). No significant difference was
found in the EMG of the BB for the two different scenarios (p =
0.26 for rms and p = 0.12 for SSP). The average of all 48 values
of SSP IACV (0.074 ± 0.043) was smaller than the corresponding average
rms IACV (0.095 SD 0.088) (p = 0.03 for paired t-test). The average
of all 6 values of SSP IECV (0.153 ± 0.041) was also smaller than
the corresponding average rms IECV (0.275 ± 0.139), however because
of the sample sizes the statistic reliability is lower (p = 0.05
for paired t-test).
Although it was collected three seconds of EMG signals from the
muscles, in average, only a period of one second presented significant
contours on the power spectra. The results show that the wavelet
power spectra pattern for the three analysed muscles obtained from
the strikes with and without impacts were similar (see Figure
1 and Figure 2). For all
strikes, it was observed that the TB was the first muscle to present
a significant contour on their spectra. The TB spectra present three
main regions of significant contour(s). The third region in general
presents more than one contour and it extends more in time. The
BB and BR presented very similar spectra. They also presented three
distinct main regions containing significant contour(s); the regions
were shifted by approximately 100-200 ms in relation to the regions
in the TB spectra.
of variation found for the rms values are in agreement with values
reported by other researchers (Bolgla and Uhl, 2007).
According to many researchers, the normalization method used in
this experiment to calculate the values of rms provides lower IACV
and IECV (Burden et al., 2003;
Knutson et al., 1994).
A comparison of the rms and the original SSP methods used in this
that the SSP method resulted in lower IACV and IECV (see Tables
1 and 2).
Lower IACV indicates greater reliability of the measurements, while
the advantages of using methods that result in lower IECV are well
documented in the literature (Yang and Winter, 1984).
These results confirm the validity of the SSP method used. Since
there were only six data points for the comparison of the IECV of
the rms and SSP, further studies should be done to confirm the hypothesis
that the SSP method may be a more stable and precise method for
measuring significant muscle activity than the rms method.
The reason for the higher TB (an agonist muscle for the strike)
activity in the strikes with impact might be more psychological
than biomechanical, possibly due to greater participant's motivation
when performing the strikes with impact. The reason for the higher
BR activity, on the other hand, is probably due to the importance
of this muscle in stabilizing the wrist and elbow joints when receiving
the reaction force from the impact.
The result that an approximate time of only one second presented
significant contours on the power spectra suggests that the participants
took approximately one second to perform the sequences of five palm
strikes. This result is in agreement with previous high-speed camera
study that found the duration of one palm strike to be in the order
of 200 ms (Neto et al., 2007).
The wavelet power spectra from the three analysed muscles (Figure 1 and 2) illustrate
the muscle roles during the five strikes performed in each sequence.
The first significant contour on the TB powers spectra demonstrates
a muscle activity responsible for pushing the right hand during
the first palm strike. This region is followed in time by a significant
contour both in the BB and BR spectra, which correspond to muscle
activity responsible to brake the right hand's movement and pull
it back while the left hand is being pushed during the first left
strike. After that, the same pattern in wavelet power spectra repeats
for the second right hand palm strike followed by the second left
hand palm strike. For the third right hand palm, more extended significant
regions in the spectra can be seen, which implies longer muscles'
activity. It can be speculated that, for both strikes with and without
impact, the participants keep tightening their muscles once the
arm stops. These isometric muscles' contractions, once the movement
stops, are often performed in martial arts.
study compares the EMG activity of the TB, BB and BR muscles during
strikes with and without impacts. The EMG analyses were done in the
time and frequency domains. For the frequency domain, an original
method was used to quantify statistically significant regions on the
wavelet power spectra, and it was proven be very reliable. The results
indicate that there are greater TB and BR muscle activities for the
strikes with impacts. The reasons for this greater muscle activity
are expected to be both psychological, such as greater motivation,
and biomechanical, such as the need for stabilizing the joints during
the impacts. In addition, the results show that the wavelet power
spectra pattern for the three analysed muscles obtained from the strikes
with and without impacts were similar. The results suggest that training
forms or "katas" should not replace training with pads.
Although in both types of training the movements performed present
very similar muscle activation characteristics, the magnitude of the
contraction of some muscle are greater for the movements done with
pads. In consequence, the relative time spend in each type of training
should be determined depending on the application. For example, for
participants that need to increase strength either for combats or
breaking demonstrations, training with pads should be more relevant
than without pads. In addition, the methodology developed in this
article has other applications, such as muscle control and rehabilitation
evaluations for athletes and non-athletes.
authors would like to thank CNPq and CAPES for financial support,
Prof. Maurício Bolzan, Regiane Albertini de Carvalho, Thais Helena
de Freitas and Ana Carolina Marzullo for helping obtaining the data,
and all volunteers.
EMG analysis of a sequence of Kung Fu strikes demonstrates higher
Triceps Brachii and Brachioradialis muscle activity for strikes
with impact than strikes without impact.
original reliable method for quantifying EMG wavelet transform
results is presented.
wavelet power spectra describe muscle roles during a Kung Fu sequence
Employment: PhD student, Institute of Research Development,
Degree: MSc, BSc.Hons.
Research interests: Biomechanics of Sports.
Employment: Director, Department of Computer Science, Univap,
Degree: PhD, MSc, BSc.
Research interests: Mathematical modelling of biological
Employment: Director, Institute of Research and Development,
Degree: PhD, MSc, BSc.
Research interests: Biomedical engineering.