Journal of Sports Science and Medicine (2007) 6(CSSI-2), 23-27
http://www.jssm.org
Received: 15 February 2007 / Accepted: 07 August 2007 / Published (online): 01 October 2007
Electromyographic study of a sequence of Yau-Man Kung Fu palm strikes with
and without impact
Osmar Pinto Neto , Marcio Magini and Marcos T.T. Pacheco
Institute of Research and Development, University of Vale do Paraíba, So José dos Campos, SP, Brazil
Abstract
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 YauMan
Kung Fu practitioners participated in the experiment. Each
participant performed 5 sequences of 5 consecutive KF YauMan
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.
Key words: Electromyography, wavelet transform, impact,
martial arts, biomechanics.
Introduction
Chinese 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 YauMan
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.
Methods
Eight 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 written consent.
Materials
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).
Data analyses
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
Research article
Kung Fu strikes with and without impact24
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, 2007). 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.
Statistics
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).
Results
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.
Discussion
The coefficients 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 study
Table 1. Average values of rms for each participant's sequence of strikes with and without impact plus intrasubject coefficient
of variation (IACV) and total mean plus intersubject coefficient of variation (IECV).
rms(IACV) Triceps Brachii Biceps Brachii Brachioradialis
Subjects
Without Im-
pact
With
Impact
Without Im-
pact
With
Impact
Without Im-
pact
With
Impact
1 2.56 (.11) 2.96 (.13) 2.48 (.05) 2.09 (.09) 2.56 (.03) 4.14 (.08)
2 2.24 (.06) 2.59 (.05 2.04 (.09) 2.01 (.08) 2.40 (.13) 2.64 (.05)
3 2.50 (.06) 2.68 (.03) 2.97 (.05) 2.81 (.06) 2.88 (.05) 2.81 (.07)
4 3.18 (.09) 3.42 (.02) 2.89 (.04) 2.89 (.03) 2.55 (.14) 2.77 (.02)
5 1.98 (.10) 3.14 (.25) 3.57 (.42) 6.13 (.43) 2.06 (.04) 3.04 (.18)
6 3.45 (.02) 3.59 (.05) 2.62 (.06) 2.73 (.02) 3.61 (.06) 3.63 (.05)
7 3.06 (.13) 2.99 (.08) 3.55 (.21) 3.28 (.16) 3.37 (.20) 3.40 (.07)
8 2.12 (.10) 4.22 (.07) 1.66 (.03) 1.64 (.01) 1.84 (.07) 3.21 (.15)
Mean (IECV) 2.62 (.21) 3.18 (.18) 2.72 (.31) 2.95 (.54) 2.66 (.24) 3.18 (.17)
Neto et al. 25
Table 2. Average values of SSP (105
V) for each participant's sequence of strikes with and without impact plus intrasubject
coefficient of variation (IACV) and total mean plus intersubject coefficient of variation (IECV).
SSP(IACV) Triceps Brachii Biceps Brachii Brachioradialis
Subjects
Without Im-
pact
With
Impact
Without Im-
pact
With
Impact
Without Im-
pact
With
Impact
1 8.53 (.05) 9.11 (.19) 7.46 (.07) 7.36 (.15) 9.11 (.05) 9.49 (.07)
2 9.60 (.10) 9.95 (.02) 8.60 (.04) 9.54 (.03) 7.74 (.09) 8.61 (.09)
3 7.21 (.07) 7.32 (.04) 7.43 (.05) 7.07 (.07) 7.48 (.06) 7.74 (.08)
4 8.19 (.03) 8.11 (.05) 7.02 (.05) 6.97 (.03) 7.89 (.03) 7.69 (.07)
5 9.79 (.06) 11.3 (.18) 9.87 (.07) 9.86 (.16) 6.90 (.09) 7.45 (.13)
6 5.91 (.03) 5.80 (.06) 8.33 (.03) 8.44 (.08) 7.24 (.06) 7.62 (.07)
7 7.75 (.08) 7.99 (.05) 7.12 (.13) 7.57 (.09) 7.83 (.09) 9.18 (.16)
8 9.16 (.14)) 10.1 (.05) 8.48 (.03) 9.32 (.06) 8.40 (.01) 9.27 (.07)
Mean (IECV) 8.29 (.17) 8.69 (.22) 8.04 (.13) 8.28 (.16) 7.84 (.10) 8.43 (.14)
revealed 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 hand
Figure 1. Wavelet transform power spectrum for the TB, BB and BR for one of the sequence of strikes without impact. A
colour scale gives the power (V2
) of the periods; intensity increases from dark blue to dark red. The thick contour on the
spectra encloses significant regions (=0.05). Global Wavelet Spectrum (GWS) is the graph of power versus period for the
whole duration of the strike analysed. Peaks above the dashed line in the GWS graphs are significant ( = 0.05).
Kung Fu strikes with and without impact26
Figure 2. Similar to the wavelet transform power spectrum of Fig. 1 but for a sequence of strikes with impact.
palm 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.
Conclusion
This 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.
Acknowledgments
The 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.
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Key points
* 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.
* An original reliable method for quantifying EMG wavelet
transform results is presented.
* EMG wavelet power spectra describe muscle roles during
a Kung Fu sequence of strikes.
AUTHORS BIOGRAPHY
Osmar Pinto NETO
Employment
PhD student, Institute of Research Development,
Univap, Brazil.
Degrees
MSc, BSc.Hons
Research interest
Biomechanics of Sports.
E-mail: osmar@univap.br
Marcio MAGINI
Employment
Director, Department of Computer Science,
Univap, Brazil.
Degrees
PhD, MSc, BSc.
Research interest
Mathematical modelling of biological
systems.
E-mail: magini@univap.br
Marcos T.T. PACHECO
Employment
Director, Institute of Research and Development,
Univap, Brazil.
Degrees
PhD, MSc, BSc.
Research interest
Biomedical engineering.
E-mail: mtadeu@univap.br
Osmar Pinto Neto
Univap - IP&D, Av. Shishima Hifumi, 2911, So José dos
Campos, So Paulo, Brazil, 12.244-000