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Surface Electromyographic Activities of Upper Body Muscles during High-intensity Cycle Ergometry

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The aim of this study was to investigate upper body muscle activity during a 30 s Wingate test. Eighteen physically active participants performed a Wingate test while muscle activity was recorded from the brachioradialis (BR), biceps brachii (BB), triceps brachii (TB) and upper trapezius (UT). Measurements were obtained at rest, during a function maximal contraction (FMC) and during the 30 s Wingate test, whilst participants were positioned in a seated position on the cycle ergometer. All muscles were significantly active for the duration of the test. When normalized as a %FMC no differences in activity were found between muscles. Across the 30 s, power output was found to significantly decrease, whereas no changes were found in upper body muscle activity. All muscles investigated were active during the Wingate test and therefore confirmed previous findings that the upper body significantly contributes to power profiles obtained during high intensity cycle ergometry in addition to its role in stabilizing the body.
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Surface Electromyographic Activities
of Upper Body Muscles during High-
intensity Cycle Ergometry
Marie Clare McCormickab, Hugh Watsonc, Alan Simpsonc, Lon Kilgorec
& Julien S Bakerc
a Institute of Clinical Exercise and Health Science, Exercise Science
Research Laboratory, School of Science, Faculty of Science and
Technology, University of the West of Scotland, Hamilton ML3 OJB,
UK
b Division of Sport and Exercise Sciences, School of Social & Health
Sciences, University of Abertay, Bell Street, Dundee DD1 1HG, UK
c Institute of Clinical Exercise and Health Science, Exercise Science
Research Laboratory, School of Science, Faculty of Science and
Technology, University of the West of Scotland, Hamilton, Scotland,
ML3 OJB, UK
Published online: 21 Mar 2014.
To cite this article: Marie Clare McCormick, Hugh Watson, Alan Simpson, Lon Kilgore & Julien S
Baker (2014) Surface Electromyographic Activities of Upper Body Muscles during High-intensity
Cycle Ergometry, Research in Sports Medicine: An International Journal, 22:2, 124-135, DOI:
10.1080/15438627.2014.881817
To link to this article: http://dx.doi.org/10.1080/15438627.2014.881817
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Surface Electromyographic Activities of Upper
Body Muscles during High-intensity Cycle
Ergometry
MARIE CLARE MCCORMICK
Institute of Clinical Exercise and Health Science, Exercise Science Research Laboratory, School
of Science, Faculty of Science and Technology, University of the West of Scotland, Hamilton
ML3 OJB, UK; and Division of Sport and Exercise Sciences, School of Social & Health Sciences,
University of Abertay, Bell Street, Dundee DD1 1HG, UK
HUGH WATSON, ALAN SIMPSON, LON KILGORE,
and JULIEN S BAKER
Institute of Clinical Exercise and Health Science, Exercise Science Research Laboratory, School
of Science, Faculty of Science and Technology, University of the West of Scotland, Hamilton,
Scotland, ML3 OJB, UK.
The aim of this study was to investigate upper body muscle activity
during a 30 s Wingate test. Eighteen physically active participants
performed a Wingate test while muscle activity was recorded from
the brachioradialis (BR), biceps brachii (BB), triceps brachii (TB)
and upper trapezius (UT). Measurements were obtained at rest,
during a function maximal contraction (FMC) and during the
30 s Wingate test, whilst participants were positioned in a seated
position on the cycle ergometer. All muscles were significantly
active for the duration of the test. When normalized as a %FMC
no differences in activity were found between muscles. Across the
30 s, power output was found to significantly decrease, whereas no
changes were found in upper body muscle activity. All muscles
investigated were active during the Wingate test and therefore
Received 11 February 2013; accepted 19 August 2013.
No sources of funding were used to assist in the preparation of this study. The authors are
grateful to the participants for their involvement in this study. All of the authors have no
conflicts of interest.
Address Corresponding to Marie Clare McCormick, Institute of Clinical Exercise and Health
Science, Exercise Science Research Laboratory, School of Science, Faculty of Science and
Technology, University of the West of Scotland, Hamilton ML3 OJB, UK. Email: marieclare.
mccormick@uws.ac.uk
Research in Sports Medicine, 22:124135, 2014
Copyright © Taylor & Francis Group, LLC
ISSN: 1543-8627 print/1543-8635 online
DOI: 10.1080/15438627.2014.881817
124
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confirmed previous findings that the upper body significantly con-
tributes to power profiles obtained during high intensity cycle
ergometry in addition to its role in stabilizing the body.
KEYWORDS anaerobic power, cycle ergometry, electromyography
INTRODUCTION
High intensity cycle ergometry is widely used to assess indices of muscular
performance during maximal exercise (Baker, Gal, Davies, Bailey, & Morgan,
2001). Recently the potential contribution of the upper extremities and trunk
muscles to cycling has been recognized (Gregor & Concomi, 2000) with research
suggesting that, via the handlebar grip, there is a contribution to power produc-
tion from the upper body (Baker & Davies, 2009; Baker et al., 2001,2002). Surface
electromyography (sEMG) data suggests that during high intensity cycle ergo-
metry with a normal handlebar grip, the amplitude of the sEMG signal of the
forearm musculature is similar, if not greater than, the signal amplitude during a
100% maximum voluntary contraction (MVC) (Baker et al., 2001). It has been
suggested that articulation with the handlebar allows the upper body to isome-
trically stabilize body position and pull the body downward to help overcome the
high resistive loads during cycle ergometry so providing a counterbalancing force
for the lower limbs (Baker, Thomas & Davies, 2009) and that the hand, arm,
shoulder and abdomen form a muscular sling that rhythmically moves back and
forth in supporting the trunk and pelvis during cycling (Schmidt, 1994).
Furthermore, research supports the use of a firm handgrip to help maintain
body position relative to the ergometer, thus ensuring that the forces generated
when forcefully extending the hips and legs are efficiently directed at rotation of
the pedals (Baker & Davies, 2009).
It is known that the lower body muscles primarily involved in power
production are the vastus lateralis and vastus medialis (Blake, Champoux, &
Wakeling, 2012). However, as little attention has been given to the effect of
the upper body musculature on high intensity cycle ergometer performance, it
is currently unknown which muscles or muscle groups of the upper body
contribute most to the task. During high intensity cycle ergometry the bra-
chioradialis (BR) acts as a pronator/supinator and elbow flexor that likely
assists with maintaining grip position. The biceps brachii (BB) flexes the
elbow while the triceps brachii (TB) acts to hold the elbow in extension and
adducts the shoulder in normal cycling posture. The upper segment of the
trapezius (UT) elevates the scapulae, assists in isometrically holding the
scapulae and stabilizes the glenohumeral and acromioclavicular joints both
important in maintaining body position on a bike (Martini, 2006). Based on the
roles of these superficial muscles, the present study used sEMG to describe the
activity of the BR, BB, TB and UT during a 30 s Wingate test. It was
Surface Electromyographic Activities of Upper Body Muscles 125
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hypothesized that sEMG would reveal significantly upper body activation,
which would not be directly related to power output during the 30 s test.
METHODOLOGY
Participants
Eighteen healthy, physically active individuals who were not trained cyclists
(nine male 24.1 ± 3.3 yrs; 178.7 ± 7.1 cm; 74.2 ± 12.3 kg and nine female
25.3 ± 5.6 yrs; 167.1 ± 7.9 cm; 61.5 ± 7.1 kg) volunteered to participate in the
study. Body mass and stature were measured prior to testing and recorded to
the nearest 0.1 kg and 0.1 cm respectively. All participants completed an
informed consent form and medical history questionnaire and all methods
used were approved by the university ethical committee. Any individuals with
a history of cardiovascular/cardiorespiratory illness were excluded from the
study. Prior to experimental testing, all participants were familiarized with
high intensity cycle ergometry testing and the baseline isometric contractions.
Participants were instructed to maintain their normal diet during the days
leading up to and on the days of testing. To avoid dehydration they were
asked to refrain from vigorous exercise and avoid the consumption of caffeine
and alcohol during the 24 hours preceding the testing date. Food was not
consumed during testing and water was available ad libitum.
Surface Electromyography
Muscle activity was recorded via sEMG from the BR, BB, TB and UT on the
right-hand side of the body (Gonzalez-Izal et al., 2010). Prior to electrode
placement, skin was shaved, lightly abraded and cleaned with alcohol. Pre-
gelled (Ag-AgCl) bipolar surface electrodes (Blue Sensor, Ambu, Ballerup,
DK) were placed over the belly of each muscle with a distance of 25 mm
between the electrodescentres. The grounding electrode was placed over the
left ulnar styloid process and the skin marked with a permanent marker
following the familiarization session, to ensure electrodes were placed in the
same position in the subsequent testing session.
sEMG signals were pre-amplified (×1000) (Neurolog remote AC pre-
amplifier, NL824, Digitimer Ltd, Hertfordshire, UK), filtered (10500 Hz)
(Neurolog filter, NL125, Digitimer Ltd, Hertfordshire, UK), converted from
analogue to digital signal (Power 1401, Cambridge Electronic Design,
Cambridge, UK) and sampled at a rate of 2000 Hz.
sEMG Baseline Measurements
During the first testing session, baseline muscle activity of the BB, BR, TB and
UT was recorded from participants at rest. All measurements were obtained
126 M. C. McCormick et al.
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while participants were seated on the cycle ergometer with a standard over-
hand grip on the handlebar, identical to body position during the cycle
ergometer test. To allow EMG data to be normalized, muscle activity was
also recorded during a functional maximal contraction (FMC) using joint
angles specific to the activity for all four muscles. Each isometric FMC lasted
23 s with a rest interval of 60 s between the three trials. The highest output
served as the reference maximal contraction. The FMCs were recorded with
participants positioned in a seated position with no leg movement. The FMC
of the BR was obtained through a maximal handgrip on the handlebar. To
execute FMC of the BB and TB, participants pulled and pushed, maximally
upon the handlebars. UT FMC was accomplished by an isometric shoulder
shrug against an isometric and antagonistic latissimus dorsi co-contraction,
balancing shoulder elevation and depression. EMG activity during the FMCs
served as reference standards to assess relative activity of the musculature
during cycle ergometry. Muscle activity during the 30 s Wingate test was
normalized by calculating it as a percentage of FMCs.
Cycle Ergometer Protocol
During the second testing session, participants completed one 30 s Wingate test,
while sEMG recorded muscle activity from the BR, BB, TB and UT. A Monark
894E Peak cycle ergometer (Monark, Vansbro, SWE) was used for all experi-
mental testing. The cycle ergometer was connected to a PC to allow for data
capture via the Monark anaerobic test software (version 2.24.2). Saddle height
was adjusted for each participant, ensuring the knee remained slightly flexed at
the completion of the power stroke (approximately 170175° at extension). Toe
clips were used to ensure that the participantsfeet were held firmly in place
and in contact with the pedals throughout the tests. All participants completed a
standardized warm up protocol, pedalling for 3 minutes at 60 rpm with a 2 kg
flywheel resistance. During the Wingate protocol participants were instructed to
remain seated in the saddle for the duration of the test and maintain a standard
overhand handlebar grip. They were given a rolling start of approximately 5 s to
generate an unloaded acceleration of pedal cadence to 60 rpm. At 60 rpm the
weight basket automatically dropped and participants pedalled with maximum
effort for a period of 30 s against a fixed resistive load of 75 grams per kilogram
total body mass (7.5% of body mass) (Bar-Or, 1987). Verbal encouragement
was given equitably to each participant in all testing.
Data Processing
All sEMG data were processed using WinEDR V3.1.9 (Dr John Dempster,
University of Strathclyde, Glasgow, UK). Root mean square (RMS) values
were calculated by the following formula; T=1s
Surface Electromyographic Activities of Upper Body Muscles 127
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RMS ¼mtðÞ
jj
½¼1=TZtþT
t
m2tðÞdt

1=2
(1)
The calculated RMS values were used to describe signal amplitude as an
estimate of muscle activity at rest, during isometric FMCs and during the
Wingate tests. Data are presented as RMS (±SD).
Statistical Analysis
Statistically analysis was performed using Statistical Package for Social
Sciences (SPSS) software (Version 18) (IBM, Armonk, NY, USA). Normality
of data distribution was tested by a Shapiro-Wilks test. Between-group differ-
ences were calculated using a repeated measures analysis of variance
(ANOVA). Multiple comparisons on paired data were made using a paired
t-test or Wilcoxon test. A paired t-test was used to identify differences in
muscle activity at rest and during a FMC. Data collected during the Wingate
test were non-parametric, therefore a Wilcoxon test was used to identify
differences in muscle activity at rest and during a Wingate test and muscle
activity during a FMC and during a Wingate test. A related-samples Friedmans
Two-Way ANOVA with subsequent pairwise comparisons was used to assess
any changes in muscle activity over the 30 s Wingate test. A repeated measure
ANOVA with subsequent Bonferonni post-hoc analysis was used to determine
changes in power output over the duration of the test. Relationships between
upper body limb activity (RMS) and power output were assessed using
Spearmans correlation coefficient. Statistical significance was set a priori at
P< 0.05. All data is presented as mean ±SD.
RESULTS
No differences were found between groups with regards to muscle activ-
ity, therefore male and female data was subsequently analysed as one
group.
Processed sEMG
Muscle activity in all four muscles, represented by sEMG amplitude (RMS),
during the FMCs and Wingate test was significantly greater than muscle
activity recorded at rest on the cycle ergometer (P<0.001;P<0.05
respectively). Muscle activity during the FMCs was significantly greater
than muscle activity during the 30 s Wingate test, this was similar for all
muscles (P<0.05)(Table 1).
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Normalized values for sEMG amplitude, using a 1 s window, were
obtained at sequential 5 s intervals during the Wingate test. There were no
significant changes in signal amplitude over the duration of the test for the BR
(P= 0.413), BB (P= 0.256), TB (P= 0.855). However, signal amplitude did
change over time in the UT (P= 0.01) with muscle activity being significantly
greatly at 1015 s than at 2530 s (Figure 1).
Between-muscle differences were assessed using normalized values and
only the TB was relatively more active compared with the BB at each time
point (%FMC) (P< 0.05). There were no other differences between muscles
(P> 0.05).
TABLE 1 Muscle activity, represented by sEMG amplitude (RMS) at rest, during a FMC
(functional maximal contraction) and average muscle activity recorded at 5 s intervals during
the Wingate test. Values are group mean RMS (±SD)
Rest FMC 05s 510 s 1015 s 1520 s 2025 s 2530 s
BR 0.07 ± 0.08
a
1.34 ± 0.71
b
0.46 ± 0.27 0.38 ± 0.16 0.49 ± 0.35 0.46 ± 0.32 0.45 ± 0.31 0.31 ± 0.19
BB 0.09 ± 0.09
a
1.02 ± 0.62
b
0.23 ± 0.12 0.22 ± 0.10 0.23 ± 0.11 0.22 ± 0.15 0.23 ± 0.14 0.15 ± 0.06
TB 0.09 ± 0.04
a
0.65 ± 0.35
b
0.35 ± 0.23 0.32 ± 0.21 0.31 ± 0.20 0.34 ± 0.26 0.36 ± 0.26 0.36 ± 0.24
UT 0.02 ± 0.01
a
0.53 ± 0.37
b
0.21 ± 0.13 0.27 ± 0.20 0.26 ± 0.15 0.22 ± 0.12 0.21 ± 0.13 0.16 ± 0.11
a
Resting values significantly lower than values recorded during FMC and at all time intervals during the
30 sWingate test;
b
MVE significantly greater than muscle activity recorded during 30sWingate test (P<
0.05).
FIGURE 1 Muscle activity displayed as a percentage of the functional maximal contraction
(FMC) at sequential 5 s interval across the 30 s Wingate test. No significant differences were
found across the 30 s period (P> 0.05).
Surface Electromyographic Activities of Upper Body Muscles 129
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Power Output
Power output (W/kg) was averaged at 5 s intervals. No significant differ-
ences were found between power output at 05 s (8.86 ± 2.01 W/kg) and
510 s (8.89 ± 1.61 W/kg) (P= 1.00) and no differences between power
outputat05and1015 s (P= 0.068). Power output at 05sand510 s
was significantly higher than at 1520 s; 2025 s and 2530 s (7.79 ± 1.17;
6.97 ± 1.01; 6.27 ± 0.81; 5.70 ± 0.83 W/kg respectively) (P<0.01).At510 s
power output was also significantly greater than at 1015 s (P< 0.01). Each
subsequent sequential power output from 1015 s to 2530 s was signifi-
cantly lower than the preceding time interval (p< 0.05), highlighting the
progressive decline in power output over the 30 s Wingate test.
There was no correlation between upper body muscle activity and power
output across the 30 s Wingate test (p> 0.05).
Raw sEMG
The raw sEMG signal obtained from a selected participant during the Wingate
test demonstrates very regular and sequential bursts of activity for the duration
of the test. Generally, BR and BB activation was followed immediately by TB
activation, as highlighted in Figure 2. It also highlights the clear regular bursts
of muscle activation representing the cyclic pulling and pushing actions upon
the handlebars.
BR
5.0
2.5
0.0
–2.5
–5.0
5.0
2.5
0.0
–2.5
–5.0
5.0
2.5
0.0
–2.5
–5.0
5.0
2.5
0.0
–2.5
–5.0
BB
TB
UT
FIGURE 2 Section of the sEMG signal of a participant recorded during a 30 s Wingate test.
Dashed lines highlight the co-contraction of the BR and BB, immediately followed by TB
activation. BR, brachioradialis; BB, biceps brachii, TB, triceps brachii; UT, upper trapezius.
130 M. C. McCormick et al.
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DISCUSSION
The principle aim of this investigation was to explore upper body muscle
activity during high intensity cycle ergometry using sEMG. Baker and collea-
gues (2001,2002,2009) previously established a relationship between power
output and handlebar grip suggesting that the upper body musculature sig-
nificantly contributes to power output during high intensity cycle ergometry.
While handlebar grip has been examined, identification of the muscles of the
upper body contributing to the lower body power transfer has only been
speculated. The muscles investigated in the present study were the BR, BB, TB
and UT. All four muscles investigated were found to be significantly more
active during cycling compared to resting values obtained while seated on the
cycle ergometer (p< 0.05) but less active than during a FMC (p< 0.01). This
therefore confirms the previous suggestion that during the Wingate test, the
upper body muscles are contributing to power output but also that they are
not contracting maximally.
The amplitude of the EMG signal, reported as RMS of the EMG, was used
within the present investigation to describe muscular activity (Jobson, Hopker,
Arkesteijn, & Passfield, 2012). Signal amplitude has been used as an estimate
of muscle activity as both the force exerted by the muscle and the amplitude
of the EMG signal have been reported to depend on the number of recruited
motor units (MU) and the firing rate of each active MU (Vollestad, 1997). An
increase in the amplitude of the sEMG signal is often observed during repe-
titive or sustained submaximal contractions (Vollestad, 1997) and has been
attributed to both the recruitment of additional MUs to compensate for the
decrease in contraction force and to an increase in the MU firing rate and/or
synchronization of MU recruitment (Dimitrova & Dimitrov, 2002). Numerous
authors have reported findings in agreement with this and have demonstrated
an increase in amplitude during both sustained and dynamic sub-maximal
isometric contractions (Arendt-Nielsen & Mills, 1988; Lloyd, 1971; Macdonald,
Farina, & Marcora, 2008; Masuda, Masuda, Sadoyama, Inaki, & Katsuta, 1999;
Moritani, Nagata, & Muro, 1982; Potvin & Bent, 1997). More recently, Fukuda
et al. (2010) demonstrated a positive linear relationship between contraction
force and RMS of the sEMG signal, further highlighting the association
between force production and amplitude.
However, in the present study there were no changes in signal amplitude
over the 30 s test, measured at 5 s intervals, for any of the four muscles
investigated (P> 0.05). This reflects the sub-maximal intermittent nature of the
upper body contractions and therefore suggests that there is no increase in
muscle force as the sprint progresses. The lack of changes in muscle force
production in the upper body may be related to the oscillatory nature of
cycling, which implies that agonist and antagonist muscles are able to share
the workload, with no requirements to recruit additional MUs to maintain the
contraction force. Furthermore, with the muscles being intermittently active,
Surface Electromyographic Activities of Upper Body Muscles 131
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hyperaemia will be able to provide the muscles with sufficient oxygen to
maintain aerobic energy metabolism and therefore prevent possible energy
depletion and/or metabolite accumulation (Jobson et al., 2012). Similar to the
findings of the present study, Hunter and colleagues (2003) found no change
in signal amplitude in the lower limbs during a similar protocol. They sug-
gested this may be a result of insufficient afferent command from type III and
IV receptors to the central nervous system, reducing central drive and a
resulting change in EMG amplitude. Although unlikely to be a valid explana-
tion for the results of the present study, it highlights the variability of sEMG
analysis. The results therefore suggest acceptance of the null hypothesis as
upper body muscle contraction did not change over the duration of the sprint
despite a significant decline in power output (W/kg), which is indicative of a
decrease in overall cycling performance.
The submaximal nature of the upper body contractions, as demonstrated
in the sEMG data, confirm the previous suggestion that the primary function of
the upper body is to stabilize body position and provide a counterbalancing
force for the lower limbs. However, in real-world cycling performance, there
may be a greater activation of the upper body musculature, in particular in a
standing position, where the upper body and trunk muscles are supporting
additional weight due to the loss of saddle support, in order to control balance
and to swing both the body and bicycle side to side (Duc, Bertucci, Pernin, &
Grappe, 2008).
The large inter-participant variability in the present study (a common
finding in sEMG analysis), indicated by large standard deviations throughout
the data, make it difficult to determine an objective quantitative relationship
between upper body activity and high intensity cycle ergometry performance
(Figure 1). This variability is further increased due to the nature of cycling
where muscle activity and co-ordination can differ considerably between
individuals (Blake, Champoux, & Wakeling, 2012), particularly as the indivi-
duals within this study were not trained cyclists.
However, as an exploratory investigation, visual inspection of the raw
EMG data may provide the most pertinent insight into muscle activity. Raw
EMG recording contains important information and therefore can be used as a
first understanding of neuromuscular control during exercise (So, Ng & Ng,
2005). The raw EMG signal (Figure 2) recorded during the present study
demonstrates a linkage to the oscillatory nature of cycling. The bursts of
activity are representative of the alternate pushing and pulling motions upon
the handlebars (Baker et al., 2001) and may also provide some valuable
information relating to the working phase of the muscle with respect to the
three crank phases as described by So et al., (2005), as the downstroke
(propulsive), the upstroke (recovery) and the pulling phase where the foot
is pushed forward at top dead centre. Observations of participants during the
cycle ergometer test revealed that in general the bursts of activity observed on
the EMG trace in the TB occur during the upstroke of the leg (due to elbow
132 M. C. McCormick et al.
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extension) and the bursts of activity in the BR and BB generally occur at the
same time during the downstroke of the leg (due to elbow flexion) (Figure 2).
No clear pattern emerged from the UT data and this may be due to its role as a
tonic muscle that is associated with stabilization during exercise. This warrants
further investigation combining sEMG and biomechanical analysis.
Every effort was made to control for the limiting factors commonly asso-
ciated with the outcomes of sEMG analysis (De Luca, 1997). The effect of
subcutaneous tissue layers acting as low pass filters, so influencing signal con-
duction (Pincivero, Green, Mark & Campy, 2000) is one factor. Minor electrode
displacement causing sEMG to be recorded from different muscle locations can
also affect the signal due to the heterogeneity of muscle fibres (Rainoldi,
Melchiorri & Caruso, 2004), alongside muscle crosstalk producing electrical
activity that artifactually registers on the sEMG thus amplifying the recorded
muscles activity. This may be a particular problem in the BR due its close
proximity to several other small forearm muscles (Kong, Hallbeck & Jung, 2010).
CONCLUSION
It is clear that all muscles investigated were active during the 30 s Wingate test
and therefore have a considerable role in optimal high intensity cycling
performance. Therefore, when using high-intensity cycle ergometry as a test
of muscular performance it is important that investigators consider the poten-
tial influences of the upper body to the power outputs achieved, through both
the handlebar grip and position of the trunk. Handlebar grip should therefore
be standardized in any experimental procedures.
Further investigation is necessary to fully quantify the contribution of the
upper body relative to power output and to evaluate the relative contributions
of both the abdominal and back musculature.
In terms of real world cycling performance cyclists and their coaches
should not underestimate the importance of establishing a strength base in the
upper body to support cycling performance both in training and competition.
The upper body is likely to be particularly influential during sustained uphill
climbs where there is a continued high resistance that cannot be overcome.
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Surface Electromyographic Activities of Upper Body Muscles 135
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... In the present study, the effects of SIT and continuous MIT on glucose and fatty acid uptake were comprehensively investigated in different muscles in healthy middle-aged men. The main results show that, although upper-body muscles are activated during Wingate-type exercise (24), insulin-stimulated GU in the upper-body muscles did not increase in response to SIT training. Insulin-stimulated GU increased significantly only in the QF muscle group. ...
... This is against our hypothesis, which expected that SIT would induce a larger increase in GU in upper body muscles. The reason for this is unclear, as other studies show that upper body muscles are mechanically activated during the Wingate test (24), the protocol used in a repeated manner for training also in the present study. It is plausible that, even if arm muscles are heavily activated during sprinting activity, due to a fairly long and inactive recovery period overall, activity is not high enough for major improvements in metabolism. ...
Article
Full-text available
We tested the hypothesis that sprint interval training (SIT) causes larger improvements in glucose and free fatty acid uptake in lower and upper body muscles than moderate intensity training (MIT). Twenty-eight healthy, untrained, middle-aged men were randomized into SIT (n = 14, 4-6 x 30 s of all-out cycling / 4 min recovery) and MIT groups (n = 14, 40-60 min cycling at 60 % of VO2peak) and completed six training sessions within two weeks. Pre-and-post measurements included VO2peak, whole-body (M-value), muscle-specific insulin-stimulated glucose uptake (GU), and fasting fatty acid uptake (FFAU) measured with positron emission tomography in thigh (quadriceps femoris; QF and hamstrings) and upper body (deltoids, biceps and triceps brachii) muscles. VO2peak and M-value improved significantly by 6 and 12 %, respectively in SIT, and 3 and 8 % in MIT. GU increased significantly only in the QF and there was no statistically significant difference between the training modes. GU increased in all four heads of QF in response to SIT but only in the vasti muscles in response to MIT, while in rectus femoris, the response was completely lacking. Training response in FFAU in QF was smaller and non-significant, but it also differed between the training modes in the rectus femoris. In conclusion, SIT and MIT increased insulin-stimulated glucose uptake only in the main working muscle QF and not in the upper body muscles. In addition, the biarticular rectus femoris did not respond to moderate-intensity training reflecting most probably poor activation of it during moderate intensity cycling. Copyright © 2014, Journal of Applied Physiology.
... The VL was chosen because it is the most important muscle of the leg cycling action (1,27). The TB was chosen given its relative importance in cycling in terms of supporting the upper body (1,27), while the TRAP was selected because it is continuously active during cycling (35), and, when fatigued, it can attenuate cycling performance (23). Based on previous data suggesting that the iDISK can be used as an indicator of Tm during steady-state rest in a thermoneutral environment (3), our hypothesis was that the generated iDISK-based estimation models would provide valid noninvasive estimations of VL, TB, and TRAP Tm during rest, cycling exercise, and postexercise recovery. ...
... Therefore, knowledge of TB Tm during cycling via the iDISK technique will be valuable for training and performance enhancement. On the other hand, we chose to provide an iDISK estimation model for the TRAP, because it is continuously active during cycling (35), and, when fatigued, it can attenuate cycling performance (23). Yet the TRAP is only submaximally activated during cycling (24), a finding that is confirmed by our data showing exercise-induced increases of Ͻ1.5°C in this muscle, compared with the ϳ3.5°C increase in VL Tm during exercise. ...
Article
We introduced non-invasive and accurate techniques to estimate muscle temperature (Tm) of vastus lateralis (VL), triceps brachii (TB), and trapezius (TRAP) during rest, exercise, and post-exercise recovery using the insulation disk (iDISK) technique. Thirty-six volunteers (24 men; 12 women; 73.0±12.2 kg; 1.75±0.07 m; 24.4±5.5 years; 49.2±6.8 peak oxygen uptake) underwent periods of rest, cycling exercise at 40% of peak oxygen uptake, and post-exercise recovery in three environments: NORMAL (24°C, 56% relative humidity), HOT-HUMID (30°C, 60% relative humidity), and HOT-DRY (40°C, 24% relative humidity). Participants were randomly allocated into the 'model' and the 'validation' groups. Results in the model group demonstrated that Tm (VL: 36.65±1.27°C; TB: 35.76±1.73°C; TRAP: 36.53±0.96°C) was increased compared to iDISK (VL: 35.67±1.71°C; TB: 34.77±2.27°C; TRAP: 35.98±1.34°C) across all environments (p<0.001). Stepwise regression analysis generated models that accurately predicted Tm (predTm) of VL (R(2)=0.73-0.91), TB (R(2)=0.85-0.93), and TRAP (R(2)=0.84-0.86) using iDISK and the difference between the current iDISK temperature and that recorded between one to four minutes before. Cross-validation analyses in the validation group demonstrated small differences (p<0.05) of no physiological significance, small effect size of the differences, and strong associations (r=0.85-0.97; p<0.001) between Tm and predTm. Moreover, narrow 95% limits of agreement and low percent coefficient of variation were observed between Tm and predTm. It is concluded that the developed non-invasive, practical, and inexpensive techniques provide accurate estimations of VL, TB, and TRAP Tm during rest, cycling exercise, and post-exercise recovery. Copyright © 2014, Journal of Applied Physiology.
... PPO measurement has traditionally been attributed to the activity of the lower body musculature. Previous work and recent investigations in our laboratory have shown that the upper body may significantly contribute to PPO [2][3][4]. Surface electromyography (sEMG) has revealed that several upper body muscles (brachioradialis (BR), biceps brachii (BB), triceps brachii (TB), and upper trapezius (UT)) are continually active during high intensity cycle ergometry when a standard handlebar grip is used [4]. With the current cycle ergometer design, evidence suggests that the forearm muscles and therefore the handlebar grip are influential to overcome high resistive loads to produce an optimum PPO. ...
... Previous work and recent investigations in our laboratory have shown that the upper body may significantly contribute to PPO [2][3][4]. Surface electromyography (sEMG) has revealed that several upper body muscles (brachioradialis (BR), biceps brachii (BB), triceps brachii (TB), and upper trapezius (UT)) are continually active during high intensity cycle ergometry when a standard handlebar grip is used [4]. With the current cycle ergometer design, evidence suggests that the forearm muscles and therefore the handlebar grip are influential to overcome high resistive loads to produce an optimum PPO. ...
Article
Full-text available
It has been reported previously that the upper body musculature is continually active during high intensity cycle ergometry. The aim of this study was to examine the effects of prior upper body exercise on subsequent Wingate (WAnT) performance. Eleven recreationally active males (20.8 ± 2.2 yrs; 77.7 ± 12.0 kg; 1.79 ± 0.04 m) completed two trials in a randomised order. In one trial participants completed 2 × 30 s WAnT tests (WAnT1 and WAnT2) with a 6 min recovery period; in the other trial, this protocol was preceded with 4 sets of biceps curls to induce localised arm fatigue. Prior upper body exercise was found to have a statistically significant detrimental effect on peak power output (PPO) during WAnT1 (P < 0.05) but no effect was observed for mean power output (MPO) (P > 0.05). Handgrip (HG) strength was also found to be significantly lower following the upper body exercise. These results demonstrate that the upper body is meaningfully involved in the generation of leg power during intense cycling.
... Some authors reported that "Every effort was made to control for the limiting factors [ . . . ] crosstalk" [73] or that electrode placement characteristics "were critically considered to minimize cross-talk between muscles" [151], while no evidence sustaining these claims can be found in their methodological choices. Other authors cited the recommendations on electrode placement reported in Basmajian's book Muscle Alive-a milestone in EMG history-but did not follow them and used large electrodes and relatively large IEDs [97,135]. ...
Article
Full-text available
The brachioradialis muscle (BRD) is one of the main elbow flexors and is often assessed by surface electromyography (sEMG) in physiology, clinical, sports, ergonomics, and bioengineering applications. The reliability of the sEMG measurement strongly relies on the characteristics of the detection system used, because of possible crosstalk from the surrounding forearm muscles. We conducted a scoping review of the main databases to explore available guidelines of electrode placement on BRD and to map the electrode configurations used and authors’ awareness on the issues of crosstalk. One hundred and thirty-four studies were included in the review. The crosstalk was mentioned in 29 studies, although two studies only were specifically designed to assess it. One hundred and six studies (79%) did not even address the issue by generically placing the sensors above BRD, usually choosing large disposable ECG electrodes. The analysis of the literature highlights a general lack of awareness on the issues of crosstalk and the need for adequate training in the sEMG field. Three guidelines were found, whose recommendations have been compared and summarized to promote reliability in further studies. In particular, it is crucial to use miniaturized electrodes placed on a specific area over the muscle, especially when BRD activity is recorded for clinical applications.
... Following this, mean values were calculated across participants. Normal distribution for all variables was assessed using the Shapiro-Wilk test (McCormick et al., 2014). A null hypothesis for the tests was accepted due to all p values being higher than 0.05. ...
Article
Full-text available
The study aimed to determine whether or not commercial golf gloves influence performance variables and forearm muscle activity during golf play. Fifteen golfers participated in the laboratory based study, each performing 8 golf swings with a Driver and 7-iron whilst wearing a glove and 8 without wearing the glove. Club head speed, ball speed and absolute carry distance performance variables were calculated. Surface electromyography was recorded from the flexor digitorum superficialis and extensor carpi radialis brevis on both forearm muscles. Club head speed, ball speed and absolute carry distance was significantly higher when using the Driver with the glove in comparison to the Driver without the glove (p < 0.05). No significant differences were evident when using the 7-iron and no significant differences were displayed in muscle activity in either of the conditions. Findings from this study suggest that driving performance is improved when wearing a glove.
... Normal distribution for all variables was assessed using the Shapiro-Wilk test (McCormick et al. 2014). If normal distribution (P > 0.05) was not granted, a log transformation was conducted on the specific data sets. ...
Article
Full-text available
The purpose of this study was to compare the electromyography (EMG) patterns of the thoracic and lumbar regions of the erector spinae (ES) muscle during the golf swing whilst using four different golf clubs. Fifteen right-handed male golfers performed a total of twenty swings in random order using the driver, 4-iron, 7-iron and pitching-wedge. Surface EMG was recorded from the lead and trail sides of the thoracic and lumbar regions of the ES muscle (T8, L1 and L5 lateral to the spinous-process). Three-dimensional high-speed video analysis was used to identify the backswing, forward swing, acceleration, early and late follow-through phases of the golf swing. No significant differences in muscle-activation levels from the lead and trail sides of the thoracic and lumbar regions of the ES muscle were displayed between the driver, 4-iron, 7-iron and pitching-wedge (P > 0.05). The highest mean thoracic and lumbar ES muscle-activation levels were displayed in the forward swing (67–99% MVC) and acceleration (83–106% MVC) phases of the swing for all clubs tested. The findings from this study show that there were no significant statistical differences between the driver, 4-iron, 7-iron and pitching-wedge when examining muscle activity from the thoracic and lumbar regions of the ES muscle.
... Statistical Analysis: Normal distribution for all variables was assessed using the Shapiro-Wilk test. 34 If normal distribution was not granted, a log transformation was conducted on the specific data sets. Following this, a paired T-Test was used to determine significant differences, if any, between muscle activity before and after the golf practice session. ...
Article
Lower back pain is commonly associated with golfers. The study aimed: to determine whether thoracic- and lumbar-erector-spinae muscle display signs of muscular fatigue after completing a golf practice session, and to examine the effect of the completed practice session on club head speed, ball speed and absolute carry distance performance variables. Fourteen right-handed male golfers participated in the laboratory-based-study. Surface electromyography (EMG) data was collected from the lead and trail sides of the thoracic- and lumbar-erector-spinae muscle. Normalized root mean squared (RMS) EMG activation levels and performance variables for the golf swings were compared before and after the session. Fatigue was assessed using median frequency (MDF) and RMS during the maximum voluntary contraction (MVC) performed before and after the session. No significant differences were observed in RMS thoracic- and lumbar-erector-spinae muscle activation levels during the five phases of the golf swing and performance variables before and after the session (p > .05). Significant changes were displayed in MDF and RMS in the lead lower lumbar and all trail regions of the erector-spinae muscle when comparing the MVC performed before and after the session (p < .05). Fatigue was evident in the trail side of the erector-spinae muscle after the session.
... Participants were given 5 minutes recovery time between each contraction. The highest recording output served as the reference MVC (McCormick, Watson, Simpson, Kilgore, & Baker, 2014). During the contractions, the forearm was secured in a previously validated rig in order to minimize elbow and shoulder movement. ...
Article
The study describes the differences in surface electromyography (EMG) activity of two forearm muscles in the lead and trail arm at specific phases of the golf swing using a 7-iron with three different grip sizes among amateur and professional golfers. Fifteen right-handed male golfers performed five golf swings using golf clubs with three different grip sizes. Surface EMG was used to measure muscle activity of the extensor carpi radialis brevis (ECRB) and flexor digitorum superficialis (FDS) on both forearms. There were no significant differences in forearm muscle activity when using the three golf grips within the group of 15 golfers (p > 0.05). When using the undersize grip, club head speed significantly increased (p = 0.044). During the backswing and downswing phases, amateurs produced significantly greater forearm muscle activity with all three grip sizes (p < 0.05). In conclusion, forearm muscle activity is not affected by grip sizes. However, club head speed increases when using undersize grips.
... Placement of the EMG electrodes was determined using anatomical landmarks and verified with isometric contractions of the muscle. The skin was shaved when covered with hair, and cleaned with alcohol before placing the 90 Y. Wang et al. electrodes in order to improve the electrode-skin contact (Corrigan & Li, 2014;Mercer, Applequist & Masumoto, 2013;McCormick, Watson, Simpson, Kilgore, & Baker, 2014). All the signals were digitized at the sampling frequency of 1000 Hz with a 16-bit resolution. ...
Article
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The aim of this article was to explore age-related differences in the muscle modes (M-modes) during voluntary body sway (VS). M-modes were defined as trunk and leg muscles organized into groups with parallel scaling of muscle activation level within a group. We hypothesized that, in comparison with young performers, older adults would show changes in the compositions of M-modes stabilizing the anterior-posterior (AP) center of pressure (COP) displacement. Young (27.5 ± 7.3 yr, 164.6 ± 9.7 cm and 58.4 ± 10.6 kg) and older (69.4 ± 6.4 yr, 160.0 ± 7.0 cm and 58.9 ± 7.5 kg) subjects performed the VS task in the AP direction while trying to minimize sway in the medio-lateral direction. EMG signals of 10 postural muscles were recorded and analyzed. Principal component analysis (PCA) was used to identify three M-modes within the space of integrated indices of muscle activity. The main findings were (1) that there were no age-related differences in magnitude of the COP displacement or amount of variance explained by the principal components (m-modes), and (2) that the number of times co-contraction and mixed m-modes were used were significantly higher for older adults, and the number of times reciprocal m-modes were used were significantly higher for young adults. These observations suggest that aging is associated with a reduced ability to unite dorsal and ventral muscles of the body, which may be reflective of the CNS developing a useful strategy when faced with self-triggered perturbations.
Article
Full-text available
Background: The surface electromyography (EMG) is a technique to capture and measure electrical activity and muscle action potential. It is applied to specify the production of force and to analyze muscle fatigue. The Root Mean Square (RMS) value has been used to quantify the electric signal because it reflects the physiological activity in the motor unit during contraction. Purpose: To evaluate a possible linear relationship between the RMS value of the EMG signal and the contraction force of the rectus femoris, vastus medialis, lateralis, biceps femoris, semitendinosus, and brachial biceps muscles. Methods: The analysis was performed on 24 females, university students with a mean age of 20 (± 6) years that practice physical activity regularly. The RMS value of the EMG signal of the mentioned muscles was measured during isometric contraction every 10 seconds with loads of 2, 4, 6, and 8 kilograms, and were normalized by the percentage in relation to the maximum isometric voluntary contraction (MIVC). The position of the volunteers during the analysis was standardized and the angle of the adjacent joint was monitored by an electrogoniometer. Results: The results of this experimental condition demonstrated that the RMS value of the EMG signal is an increasing linear function of the imposed load. This positive correlation was found for the rectus femoris (p < 0. 01), vastus lateralis (p < 0. 01), vastus medialis (p < 0. 01), biceps femoris (p < 0. 01), semitendinosus (p < 0. 01), and brachial biceps muscles (p < 0. 001). Conclusion: A linear relationship with the required torque was found between the contraction force and the RMS value of the EMG signal in females for the analyzed muscles.
Article
This lecture explores the various uses of surface electromyography in the field of biomechanics. Three groups of applications are considered: those involving the activation timing of muscles, the force/EMG signal relationship, and the use of the EMG signal as a fatigue index. Technical considerations for recording the EMG signal with maximal fidelity are reviewed, and a compendium of all known factors that affect the information contained in the EMG signal is presented. Questions are posed to guide the practitioner in the proper use of surface electromyography. Sixteen recommendations are made regarding the proper detection, analysis, and interpretation of the EMG signal and measured force. Sixteen outstanding problems that present the greatest challenges to the advancement of surface electromyography are put forward for consideration. Finally, a plea is made for arriving at an international agreement on procedures commonly used in electromyography and biomechanics.
Article
Studies have indicated that the muscles work in a systematic and coordinated way to generate and direct power from the human body to the crank during cycling. Understanding of the muscle involvement or recruitment pattern during cycling will be useful for developing specific and effective muscle training and rehabilitation programs for cyclists. Moreover, it will also facilitate the use of the cycling ergometer for therapeutic purpose. This paper reviews the current literature on muscle recruitment pattern during cycling and the effects of muscle fatigue, cadence, riding posture and seat height on this recruitment pattern. In the power phase or ‘downstroke’, the hip, knee and ankle joints extend simultaneously for the pushing action, whilst in the recovery phase or ‘upstroke’, they flex together to pull the pedal back to the top dead center of the crank cycle. Recent studies have indicated that in this repeated sequence, the mono-articular muscles are mainly involved in the generation of positive work whereas the biarticular muscles are responsible for regulating force transmission. Some muscles co-activate during cycling to provide synergistic actions and other functional needs.
Article
studies have shown that traditional forces may be too light to elicit maximal performances and that opti- mization protocols can produce higher peak power outputs. Conceptually, selecting the optimal resistive force according to TBM may not be the best approach. Fat-free mass or active muscle tissue may be a more preferable alternative. Because body mass, and not composition, is the most commonly used index to deter- mine cycle ergometer resistive force, over- or underestimations in power calculations may occur. The aim of this paper is to outline friction-loaded cycle ergometer performance using resistive forces derived from TBM and fat-free mass, to quantify the upper body contribution to high-intensity cycle ergometry. A further aim is to outline mechanical issues related to cycle ergometer design and to quantify discrepancies in resistive force application. (J Exerc Sci Fit  Vol 7  No 2 (Suppl)  S51-S60  2009)
Article
Cycling is a repetitive activity using coordinated muscle recruitment patterns to apply force to the pedals. With more muscles available for activation than required, some patterns produce high power, whereas some are more efficient. The purpose of this study was to identify relationships between muscle coordination and factors affecting muscle coordination to explain changes in overall mechanical efficiency (ηO). Surface EMG, kinematics, and pedal forces were measured at 25%, 40%, 55%, 60%, 75%, and 90% V˙O(2max). Principal component analysis was used to establish muscle coordination, kinematic, and pedal force patterns associated with high and low ηO. At 55%-60% V˙O(2max), ηO was maximized and was highly related to the muscle coordination patterns. At high ηO, there was more medial and lateral gastrocnemii and soleus; less gluteus maximus, rectus femoris, and tibialis anterior; later medial and lateral vastii and biceps femoris; and earlier semitendinosus muscle activity resulting in an even distribution and synchronization of peak activity. Also, the ankle was more plantar flexed through the top and downstroke of the pedal cycle and more dorsiflexed during the upstroke for high ηO. The ηO was independent of the pedal force application. The results indicate that increased ηO is achieved through the coordination of muscles crossing the same joint, sequential peak activation from knee to hip to ankle, and reliance on multiple muscles for large joint torques. Also, muscle activity variability across the top and bottom of the cycle indicates that left and right leg muscle coordination may play a significant role in efficient cycling. These findings imply that cycling at 55%-60% V˙O(2max) will maximize the rider's exposure to high efficient muscle coordination and kinematics.
Article
The fraction of crosstalk was examined from the surface EMG signals collected from digit- and wrist-dedicated flexors with a blind signal separation (BSS) algorithm. Six participants performed static power grip tasks in a neutral posture at four different exertion levels of 25%, 50%, 75%, and 100% MVC. The signals were collected from the flexor digitorum superficialis, flexor digitorum profundus, flexor carpi radialis, palmaris longus, and flexor carpi ulnaris using a bipolar electrode configuration. The percentage of root mean square (RMS) was used as an amplitude-based index of crosstalk by normalizing the signals including crosstalk to those excluding crosstalk by the BSS algorithm for each %MVC exertion. The peak R(2) value of a cross-correlation function was also calculated as a correlation-based index of crosstalk for a group of forearm flexors by force level and algorithm application. The fraction of crosstalk ranged from 32% to 50% in the wrist-dedicated flexors and from 11% to 25% in the digit-dedicated flexors. Since surface EMG signals had such high levels of crosstalk, reduction methods like the BSS algorithm should be employed, as the BSS significantly reduced crosstalk in the forearm flexors 33% over all muscles and exertion levels. Thus, it is recommended that BSS be utilized to reduce crosstalk for the digit- and wrist-dedicated flexors during gripping tasks.