The aim of the study was to investigate EMG signal features during fatigue and recovery at three locations of the vastus medialis and lateralis muscles.

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Non-uniform electromyographic activity
during fatigue and recovery of the vastus
medialis and lateralis muscles
Article in Journal of Electromyography and Kinesiology · June 2008
DOI: 10.1016/j.jelekin.2006.12.004 · Source: PubMed
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2. Non-uniform electromyographic activity during fatigue and recovery
of the vastus medialis and lateralis muscles
Nosratollah Hedayatpour, Lars Arendt-Nielsen, Dario Farina *
Center for Sensory-Motor Interaction (SMI), Department of Health Science and Technology, Aalborg University,
Fredrik Bajers Vej 7D-3, 9220 Aalborg East, Denmark
Received 11 October 2006; received in revised form 13 December 2006; accepted 13 December 2006
Abstract
The aim of the study was to investigate EMG signal features during fatigue and recovery at three locations of the vastus medialis and
lateralis muscles. Surface EMG signals were detected from 10 healthy male subjects with six 8-electrode arrays located at 10%, 20%, and
30% of the distance from the medial (for vastus medialis) and lateral (vastus lateralis) border of the patella to the anterior superior spine
of the pelvic. Subjects performed contractions at 40% and 80% of the maximal force (MVC) until failure to maintain the target force,
followed by 20 2-s contractions at the same force levels every minute for 20 min (recovery). Average rectified value, mean power spectral
frequency, and muscle fiber conduction velocity were estimated from the EMG signals in 10 epochs from the beginning of the contraction
to task failure (time to task failure, mean ± SD, 70.7 ± 25.8 s for 40% MVC; 27.4 ± 16.8 s for 80% MVC) and from the 20 2 s time inter-
vals during recovery. During the fatiguing contraction, the trend over time of EMG average rectified value depended on location for both
muscles (P < 0.05). After 20-min recovery, mean frequency and conduction velocity of both muscles were larger than in the beginning of
the fatigue task (P < 0.05) (supernormal values). Moreover, the trend over time of mean frequency during recovery was affected by loca-
tion and conduction velocity values depended on location for both muscles (P < 0.05). The results indicate spatial dependency of EMG
variables during fatigue and recovery and thus the necessity of EMG spatial sampling for global muscle assessment.
Ó 2006 Elsevier Ltd. All rights reserved.
Keywords: Multi-channel EMG; Conduction velocity; Vasti muscles; Recovery
1. Introduction
Muscle fatigue is defined as an exercise-induced decrease
in maximal force-generating capacity of a muscle which
may result from the metabolic accumulation, fuel reduction
(Saltin and Karlsson, 1975), neuromuscular dysfunction
(Bigland-Ritchie, 1984) and impairment of voluntary acti-
vation (Bigland-Ritchie et al., 1978). Recovery after fatigue
plays an important role in sport success and in preventing
muscle fiber damage during exercise training (Parra et al.,
2000; Clarkson and Tremblay, 1988). The recovery process
implies the return of all mentioned parameters from abnor-
mal to normal condition (Fletcher, 1907; Ivy et al., 2002;
Lannergren et al., 1989).
In large muscles, such as quadriceps, muscle fibers may
have different pinnation angles and this allows a wide
distribution of tensions. Muscle tension primarily depends
on morphological and architectural features of muscle
fibers (Coyle et al., 1979; Ichinose et al., 1998). Specific
tasks may be performed by preferential activation of differ-
ent muscle parts. Accordingly, previous studies have
reported a non-uniform distribution of electromyographic
(EMG) activity over muscles during sustained contraction
(Li and Sakamoto, 1996; Holtermann et al., 2005). A long
lasting muscle hyperactivity with non-uniform motor unit
recruitment has also been correlated to the distribution of
muscle soreness symptoms 48 h after eccentric exercise
(Friden et al., 1986).
1050-6411/$ - see front matter Ó 2006 Elsevier Ltd. All rights reserved.
doi:10.1016/j.jelekin.2006.12.004
*
Corresponding author. Tel.: +45 96358821; fax: +45 98154008.
E-mail address: df@hst.aau.dk (D. Farina).
Available online at www.sciencedirect.com
Journal of Electromyography and Kinesiology 18 (2008) 390–396
www.elsevier.com/locate/jelekin

3. Surface EMG signals are often used to investigate fati-
gue-induced changes at the muscle fiber membrane level
(Merletti et al., 1990). However, there have been only a
few reports on EMG features during recovery from fatigue
(e.g., van der Hoeven et al., 1993; van der Hoeven and
Lange, 1994). Moreover, no study investigated spatial
dependence of EMG features with recovery. Therefore,
the aim of the study was to investigate EMG signal features
during fatigue and recovery at three locations of the vastus
medialis and lateralis muscles.
2. Materials and methods
2.1. Subjects
Ten healthy, male subjects (age, mean ± SD, 25.6 ± 3.6 yr,
body mass 70.4 ± 12.9 kg, height 1.77 ± 0.09 m) participated to
the study. The study was conducted in accordance with the
Declaration of Helsinki, approved by the Local Ethics Commit-
tee, and written informed consent was obtained from all subjects
prior to inclusion.
2.2. General procedures
The subject sat comfortably on a chair fixed with a belt at the
hip with the right knee 90° flexed. A strap connected by a chain to
a load cell was attached to the ankle to measure knee extension
isometric force. Force was provided to the subject as visual
feedback on an oscilloscope. The subject performed three maxi-
mal voluntary contractions (MVC) separated by 2-min rest.
During each MVC contraction, verbal encouragement was pro-
vided. The highest force was considered the reference MVC for
submaximal contraction levels. After the MVCs, surface EMG
electrodes were placed on the vastus medialis and lateralis mus-
cles, as described below. The subject trained with the visual
feedback on force and, 10 min later, performed two contractions
at 40% and 80% MVC (random order) until task failure, with a
resting period of 40 min in between. After the sustained con-
traction, EMG signals were recorded at intervals of 1 min for
20 min, during 2-s contractions at the same force level as during
the fatiguing contraction. An additional 2-s contraction was
performed before the second contraction at the same force level as
the first contraction. Skin temperature was measured at the belly
of both muscles using skin thermometers (Ellab Ltd., Copenha-
gen, Denmark).
2.3. EMG recordings
Surface EMG signals were recorded from thee sites over the
vastus medialis and lateralis muscles with linear electrode arrays.
The lengths from the anterior superior spine of the pelvic (ASSP)
to the medial and lateral border of the patella were measured as
anatomical references for vastus medialis and lateralis, respec-
tively (Zipp, 1982). Three adhesive arrays (ELSCH008, SPES
Medica, Salerno, Italy) of eight equi-spaced electrodes (inter-
electrode distance 5 mm, electrodes 5 mm · 1 mm) (Masuda et al.,
1985; Merletti et al., 2003) were placed at a distance from the
patella of 10%, 20% and 30% (distal, middle and proximal site) of
the measured anatomical lengths (Fig. 1). At each site, the ori-
entation of the array was selected during test contractions by
moving a dry array at different angles until a clear propagation of
the action potentials without evident shape changes was observed
(Masuda et al., 1985).
Before electrode placement, the skin was lightly abraded. To
assure proper electrode–skin contact, 20–30 lL of conductive gel
were inserted into the cavities of the adhesive electrode array.
Surface EMG signals were amplified bipolarly (EMG amplifier,
EMG-16, LISiN – OT Bioelettronica, Torino, Italy; bandwidth
10–500 Hz), sampled at 2048 Hz, and stored after 12 bit A/D
conversion.
2.4. Signal analysis
In the fatiguing contraction, EMG signals were divided into
epochs of duration 10% of the time to task failure. For each
epoch, average rectified value and mean power spectral frequency
were estimated from the central single differential channel of the
array while muscle fiber conduction velocity was computed
(Farina et al., 2001) from the maximum number of channels
showing propagation of the action potentials with minimal shape
changes without the presence of the innervations zone (visual
selection of the channels). The same channels were used to com-
pute the same EMG variables during each of the 2-s contractions
in the recovery phase. Average rectified value is reported as the
value at the skin surface before amplification.
2.5. Statistical analysis
Three-way repeated measures analysis of variance (ANOVA)
was used to assess the dependency of EMG variables on con-
traction force (40% and 80% MVC), location of the array on the
muscle (distal, middle, proximal), and time interval (10 time
intervals for the fatigue phase and 20 for the recovery phase).
Three-way ANOVA was also used to compare the EMG variable
values in the beginning of the fatiguing contraction and after 20-
min recovery (with factors contraction force, location on the
muscle, and two time intervals in the beginning and end of the
task). Two-way ANOVA (factors location and two time intervals
Vastus
Medialis
Vastus
Lateralis
Distal Array
Middle Array
Proximal Array
ASSP
Patella
Lateral Border
Patella
Medial Border
10%
20%
30%
ASSP/Patella
Lateral Border
Line
ASSP/Patella
Medial Border
Line
Fig. 1. Schematic representation of the locations of adhesive electrode
arrays over the vastus medialis and lateralis muscles. The three locations
correspond to distances from the patella of 10% (distal), 20% (middle) and
30% (proximal) of the distance between the anterior superior spine of the
pelvic (ASSP) and medial (vastus medialis) or lateral (vastus lateralis)
border of the patella.
N. Hedayatpour et al. / Journal of Electromyography and Kinesiology 18 (2008) 390–396 391

4. in the beginning of the task and before the second contraction)
was used to verify that EMG variables returned to initial values
before the second contraction. Paired t-test was applied to com-
pare time to task failure at the two contraction levels and skin
temperatures. P-values less than 0.05 were considered significant.
Results are reported as mean and standard deviation (SD) in the
text and table and standard error (SE) in the figures.
3. Results
Time to task failure was 70.7 ± 25.8 s (40% MVC) and
27.4 ± 16.8 s (80% MVC) (significantly different, paired t-
test P < 0.001). Temperature at the beginning of the fatigu-
ing contraction was not different from the temperature at
task failure and lower than temperature after the 20-min
recovery (for all muscles and forces P < 0.05) (Table 1).
EMG variables before the beginning of the second contrac-
tion were not different with respect to the beginning of the
first contraction (recovery of initial values). Fig. 2 shows
example of recorded EMG signals.
3.1. Sustained contractions
EMG average rectified value of the vastus medialis
increased with relative force (F = 11.3, P < 0.01; 40%
MVC: 18.0 ± 8.7 lV; 80% MVC: 28.1 ± 15.0 lV),
depended on muscle location (F = 3.7, P < 0.05; from
distal to proximal: 29.9 ± 17.1 lV, 25.1 ± 15.3 lV, 15.8 ±
10.9 lV, first different from last P < 0.05), and time interval
(F = 2.1, P < 0.05; first larger than last three P < 0.05).
Moreover, there was a significant interaction among the
three factors (F = 2.1, P < 0.01), indicating a location-
dependent trend of EMG amplitude over time (Fig. 3).
Average rectified value for the vastus lateralis muscle
depended on contraction force (F = 14.3, P < 0.01; 40%
MVC: 19.9 ± 8.2 lV; 80% MVC: 26.4 ± 10.7 lV) and on
time interval (F = 3.1, P < 0.01; first larger than the third
and subsequent, P < 0.05). The decay over time depended
on the location over the muscle (interaction between time
and location, F = 1.9, P < 0.05).
For both vastus medialis and lateralis mean power
spectral frequency decreased over time (F > 2.2, P < 0.05;
in both cases, first time interval larger the last three, P <
0.05) (Fig. 4).
Conduction velocity of the vastus medialis depended on
location on the muscle (F = 6.5, P < 0.05, most distal differ-
ent from the other two locations, P < 0.05; 4.9 ± 1.1 m/s,
3.1 ± 0.8 m/s, 3.0 ± 0.9 m/s). Moreover, there was an inter-
action between contraction force and time interval (F = 3.0,
P < 0.01), with conduction velocity decreasing over time
(different for each time interval, P < 0.05) at 80% MVC but
not at 40% MVC. Conduction velocity of the vastus lateralis
Table 1
Skin temperature (mean ± SD, °C) at the beginning of the fatiguing
contraction, at the failure point, and after the 20-min recovery
Vastus medialis Vastus lateralis
40% MVC 80% MVC 40% MVC 80% MVC
Beginning 31.6 ± 0.6 32.2 ± 0.7 31.6 ± 0.6 32.1 ± 0.7
Failure point 31.8 ± 0.7 32.3 ± 0.7 31.8 ± 0.7 32.3 ± 0.7
After 20-min
recovery
32.7 ± 0.8 33.1 ± 0.7 32.8 ± 1.1 33.4 ± 0.7
Distal
Middle
Proximal
50 ms
nu
Vastus Medialis Vastus Lateralis
Fig. 2. Example of signals recorded with the six electrode arrays from vastus medialis and lateralis muscles during a contraction at 80% MVC. nu:
normalized units.
392 N. Hedayatpour et al. / Journal of Electromyography and Kinesiology 18 (2008) 390–396

5. depended on time (F = 2.6, P < 0.05) but only the first and
last intervals resulted different (smaller in the last, P < 0.05).
3.2. Recovery
Average rectified value for vastus medialis increased
with force level (F = 16.5, P < 0.01; 40% MVC:
14.8 ± 6.7 lV; 80% MVC: 24.7 ± 16.2 lV) and changed
with location (F = 3.8, P < 0.05; from distal to proximal:
25.1 ± 15.1 lV, 22.9 ± 13.1 lV, 15.9 ± 11.4 lV, first differ-
ent from last P < 0.05). Average rectified value for vastus
lateralis depended only on force (F = 31.8, P < 0.001;
40% MVC: 16.7 ± 5.3 lV; 80% MVC: 27.6 ± 13.1 lV)
(Fig. 3).
10
15
20
25
30
35
40
45
50
55
10
15
20
25
30
35
40
45
50
55
Endurance Endurance
Averagerectifiedvalue(mean±SE,μV)
Distal
Middle
Proximal
Vastus Medialis Vastus Lateralis
Percent
time-to-
task failure
Recovery (min)
10% 100% 1 20
Percent
time-to-
task failure
Recovery (min)
10% 100% 1 20
Fig. 3. EMG average rectified value (mean ± SE over the 10 subjects) in the 10 time intervals during the sustained contraction (increments of 10% of the
time to task failure) and the 20 time intervals (spaced by 1 min) during recovery. Contraction level 80% MVC.
Percent
time-to-
task failure
Recovery (min)
65
70
75
80
85
90
95
100
65
70
75
80
85
90
95
100
Task Failure
Task Failure
Meanpowerspectralfrequency(mean±SE,Hz)
Distal
Middle
Proximal
VastusMedialis VastusLateralis
10% 100%1 20 10% 100%1 20
Percent
time-to-
task failure
Recovery (min)
Fig. 4. EMG mean power spectral frequency (mean ± SE over the 10 subjects) in the 10 time intervals during the sustained contraction (increments of 10%
of the time to task failure) and the 20 time intervals (spaced by 1 min) during recovery. Contraction level 80% MVC.
N. Hedayatpour et al. / Journal of Electromyography and Kinesiology 18 (2008) 390–396 393

6. For both vastus medialis and lateralis, mean frequency
depended on time (F > 2.0, P < 0.01; first smaller than last,
P < 0.05) and on the interaction between time interval and
location (F > 2.1, P < 0.05), indicating a location-depen-
dent trend over time (Fig. 4).
Conduction velocity of vastus medialis depended on
location (F = 4.1, P < 0.05; most distal larger than most
proximal, 5.2 ± 1.0 m/s vs 4.3 ± 0.8 m/s).
Average rectified value for vastus medialis after 20-min
recovery was smaller than in the beginning of the endur-
ance contraction (F = 8.4, P < 0.05; 21.2 ± 4.2 lV vs
26.1 ± 5.1 lV). Mean frequency and conduction velocity
for both muscles were larger in the end of the 20-min recov-
ery than in the beginning of the endurance contraction
(F > 7.4, P < 0.05) (Fig. 4).
4. Discussion
EMG variables and their trends over time during sus-
tained contraction and recovery of the vastus medialis
and lateralis muscles depended on location over the mus-
cles. Moreover, conduction velocity and mean frequency
had supernormal values after 20-min recovery with respect
to the beginning of the task.
4.1. Sustained contraction
EMG amplitude or its trend over time depended on
location over the two muscles analyzed. Mean frequency
was the same in the three locations and conduction velocity
depended on location only for the vastus medialis muscle.
Mean frequency and conduction velocity decreased over
time during the sustained contraction. However, their
trends over time did not depend on location (no interaction
between time interval and location). On the contrary, for
both muscles, EMG amplitude changes during the sus-
tained contraction depended on location.
Dependence of EMG variables on location is in agree-
ment with previous findings on other muscles (Li and
Sakamoto, 1996; Holtermann et al., 2005). Non-uniform
EMG amplitude can be explained by non-uniform fiber
membrane properties or non-uniform motor unit recruit-
ment. In broad muscles with distributed mechanical
actions, muscle fibers are not all mechanically equivalent
with respect to their direction of force. In the distal portion
of the vasti, fibers are more obliquely distributed than in
the proximal portions (Weinstabl et al., 1989; Peeler
et al., 2005). This pattern of fiber orientation enables the
different parts of these muscles to contribute in various
types of activities, such as stabilization of the patella, exter-
nal and internal rotation of the tibia and extension of the
knee (Goodfellow and O’Connor, 1978). Variations in
morphological and architectural characteristics of muscle
fiber with location indicates that different parts of the vasti
muscles are differently activated during a specific task. In
agreement with the present results, Morrish et al. (2003)
observed a greater value of EMG amplitude in the oblique
portion of the vastus medialis than in the other parts of the
muscle.
4.2. Recovery
After 20-min recovery, in both muscles, mean frequency
and conduction velocity showed supernormal values while
EMG amplitude in vastus medialis was smaller than in the
beginning of the task. Moreover, the trend of mean fre-
quency during recovery was affected by recording location.
Simultaneous increase in mean frequency and conduc-
tion velocity indicated that the overshooting of mean fre-
quency was partly due to augmented conduction velocity.
A long lasting overshoot of conduction velocity was earlier
reported on elbow flexors and adductor pollicis muscle
after fatiguing isometric contraction (van der Hoeven
et al., 1993; van der Hoeven and Lange, 1994; Miller
et al., 1987). Numerous mechanisms have been suggested
for the increase in conduction velocity over normal values,
including changes in muscle temperature and muscle fiber
swelling.
An increase in muscle temperature in previous studies
resulted in lower EMG amplitude and higher conduction
velocity (Stewart et al., 2003; Winkel and Jørgensen,
1991), as a consequence of faster opening–closing of the
Na+
channels in which the diffusion time of Na+
ion is
decreased. In this study, skin temperature increased by
1 °C from the onset of contraction to the end of recovery
in both muscles. This small change is probably not suffi-
cient to explain the observed supernormal values (Merletti
et al., 1984).
Muscle fiber swelling is due to osmosis gradient differ-
ence between the interstitium and intracellular space of
working fibers (Lundvall et al., 1972) and is likely to play
a role in the observed results, as discussed by van der Hoe-
ven et al. (1993). An increase in water content of muscle
fibers has been reported following maximal fatiguing con-
traction (Sahlin et al., 1978; Sjogaard et al., 1985). The pri-
mary reason for increased intracellular water is the
production of lactate during anaerobic exercise (Lundvall
et al., 1972).
It was also observed that trends of EMG mean power
frequency during recovery depended on location. This
may be explained by a non-uniform metabolic accumula-
tion and lactate production. Accumulation of metabolites
depends indeed on the number of active motor units under
anaerobic condition which may be different in different
muscle regions. During muscle contraction, the metabolic
demands of the different regions of active quadriceps
increase muscle fiber diameter (Nielsen et al., 1990). Cleary
et al. (2006) reported larger increase in muscle size in the
distal portion than in other regions of the thigh, 30 min
after downhill running. This might be related to high per-
centage of fast twitch fibers in this region of the quadriceps
(Elder et al., 1982). Removal of metabolites may also
depend on location into the muscle due to regional capil-
lary and oxidative enzyme supply to muscle fibers (Tesch
394 N. Hedayatpour et al. / Journal of Electromyography and Kinesiology 18 (2008) 390–396

7. and Wright, 1983). Fiber type sensitivity to low pH and
temperature (Metzger and Moss, 1987) may be another
reason for the non-uniform recovery.
4.3. Assessment of EMG variables
The variability in EMG variables with location may
have also been due to factors not related to physiological
mechanisms, such as non-uniform subcutaneous layer
thickness, effect of fiber orientation on the bipolarly filtered
EMG, or contact impedance. Variability of these factors
with location cannot be ruled out. The main conclusion
is that EMG variables may substantially vary with elec-
trode location, in agreement with previous reports (e.g.,
Li and Sakamoto, 1996). Results obtained from a single
recording point may thus not represent the behavior of
the entire muscle and multiple recording points are
suggested, in particular in the case of large muscles where
different parts may be activated differently depending on
the task.
5. Conclusion
Supernormal values of conduction velocity and mean
frequency were observed in the vasti muscles after recov-
ery from sustained contraction. The initial value of EMG
amplitude depended on electrode location. The trends
over time of mean frequency during recovery depended
on the location over the muscle, indicating non-uniform
recovery of electrophysiological membrane properties.
The results highlight the spatial dependency of electro-
physiological mechanisms within the same muscle and
thus the necessity of EMG spatial sampling for global
muscle assessment.
References
Bigland-Ritchie B. Muscle fatigue and the influence of changing neural
drive. Clin Chest Med 1984;5:21–34.
Bigland-Ritchie B, Jones DA, Hosking GP, Edwards RH. Central
and peripheral fatigue in sustained maximum voluntary contrac-
tions of human quadriceps muscle. Clin Sci Mol Med 1978;54:
609–14.
Clarkson PM, Tremblay I. Exercise-induced muscle damage, repair, and
adaptation in humans. J Appl Physiol 1988;65:1–6.
Cleary MA, Sitler MR, Kendrick ZV. Dehydration and symptoms of
delayed-onset muscle soreness in normothermic men. J Athl Train
2006;41:36–45.
Coyle EF, Costill DL, Lesmes GR. Leg extension power and muscle fiber
composition. Med Sci Sports 1979;11:12–5.
Elder GC, Bradbury K, Roberts R. Variability of fiber type distributions
within human muscles. J Appl Physiol 1982;53:1473–80.
Farina D, Muhammad W, Fortunato E, Meste O, Merletti R, Rix H.
Estimation of single motor unit conduction velocity from surface
electromyogram signals detected with linear electrode arrays. Med Biol
Eng Comput 2001;39:225–36.
Fletcher WM. Lactic acid in amphibian muscle. J Physiol 1907;35:
247–309.
Friden J, Sfakianos PN, Hargens AR. Muscle soreness and intramus-
cular fluid pressure: comparison between eccentric and concentric
load. J Appl Physiol 1986;61:2175–9.
Goodfellow J, O’Connor J. The mechanics of the knee and prosthesis
design. J Bone Joint Surg Br 1978;60:358–69.
Holtermann A, Roeleveld K, Karlsson JS. Inhomogeneities in muscle
activation reveal motor unit recruitment. J Electromyogr Kinesiol
2005;15:131–7.
Ichinose Y, Kanehisa H, Ito M, Kawakami Y, Fukunaga T. Morpho-
logical and functional differences in the elbow extensor muscle between
highly trained male and female athletes. Eur J Appl Physiol Occup
Physiol 1998;78:109–14.
Ivy JL, Goforth Jr HW, Damon BM, McCauley TR, Parsons EC, Price
TB. Early postexercise muscle glycogen recovery is enhanced with a
carbohydrate–protein supplement. J Appl Physiol 2002;93:1337–44.
Lannergren J, Larsson L, Westerblad H. A novel type of delayed tension
reduction observed in rat motor units after intense activity. J Physiol
1989;412:267–76.
Li W, Sakamoto K. The influence of location of electrode on muscle fiber
conduction velocity and EMG power spectrum during voluntary
isometric contraction measured with surface array electrodes. Appl
Human Sci 1996;15:25–32.
Lundvall J, Mellander S, Westling H, White T. Fluid transfer between
blood and tissues during exercise. Acta Physiol Scand
1972;85:258–69.
Masuda T, Miyano H, Sadoyama T. The position of innervation zones in
the biceps brachii investigated by surface electromyography. IEEE
Trans Biomed Eng 1985;32:36–42.
Merletti R, Sabbahi MA, De Luca CJ. Median frequency of the
myoelectric signal. Effects of muscle ischemia and cooling. Eur J Appl
Physiol Occup Physiol 1984;52:258–65.
Merletti R, Knaflitz M, De Luca CJ. Myoelectric manifestations of
fatigue in voluntary and electrically elicited contractions. J Appl
Physiol 1990;69:1810–20.
Merletti R, Farina D, Gazzoni M. The linear electrode array: a useful
tool with many applications. J Electromyogr Kinesiol 2003;13:37–47.
Metzger JM, Moss RL. Greater hydrogen ion-induced depression of
tension and velocity in skinned single fibers of rat fast than slow
muscles. J Physiol 1987;393:727–42.
Miller RG, Giannini D, Milner-Brown HS, Layzer RB, Koretsky AP,
Hooper D, et al.. Effects of fatiguing exercise on high-energy
phosphates, force, and EMG: evidence for three phases of recovery.
Muscle Nerve 1987;10:810–21.
Morrish GM, Woledge RC, Haddad FS. Activity in three parts of the
quadriceps recorded isometrically at two different knee angles and
during a functional exercise. Electromyogr Clin Neurophysiol 2003;43:
259–65.
Nielsen B, Savard G, Richter EA, Hargreaves M, Saltin B. Muscle blood
flow and muscle metabolism during exercise and heat stress. J Appl
Physiol 1990;69:1040–6.
Parra J, Cadefau JA, Rodas G, Amigo N, Cusso R. The distribution of
rest periods affects performance and adaptations of energy metabolism
induced by high-intensity training in human muscle. Acta Physiol
Scand 2000;169:157–65.
Peeler J, Cooper J, Porter MM, Thliveris JA, Anderson JE.
Structural parameters of the vastus medialis muscle. Clin Anat
2005;18:281–9.
Sahlin K, Alvestrand A, Brandt R, Hultman E. Intracellular pH and
bicarbonate concentration in human muscle during recovery from
exercise. J Appl Physiol 1978;45:474–80.
Saltin B, Karlsson J. Muscle glycogen utilization during work of different
intensities. Adv Exp Med Biol 1975.
Sjogaard G, Adams RP, Saltin B. Water and ion shifts in skeletal muscle
of humans with intense dynamic knee extension. Am J Physiol
1985;248:190–6.
Stewart D, Macaluso A, De Vito G. The effect of an active warm-up on
surface EMG and muscle performance in healthy humans. Eur J Appl
Physiol 2003;89:509–13.
Tesch PA, Wright JE. Recovery from short term exercise: its relation to
capillary supply and blood lactate concentration. Eur J Appl Physiol
Occup Physiol 1983;52:98–103.
N. Hedayatpour et al. / Journal of Electromyography and Kinesiology 18 (2008) 390–396 395

8. van der Hoeven JH, Lange F. Supernormal muscle fiber conduction
velocity during intermittent isometric exercise in human muscle. J Appl
Physiol 1994;77:802–6.
van der Hoeven JH, van Weerden TW, Zwarts MJ. Long-lasting
supernormal conduction velocity after sustained maximal isometric
contraction in human muscle. Muscle Nerve 1993;16:312–20.
Weinstabl R, Scharf W, Firbas W. The extensor apparatus of the knee
joint and its peripheral vasti: anatomic investigation and clinical
relevance. Surg Radiol Anat 1989;11:17–22.
Winkel J, Jørgensen K. Significance of skin temperature changes in
surface electromyography. Eur J Appl Physiol Occup Physiol
1991;63:345–8.
Zipp P. Recommendations for the standardization of lead positions in
surface electromyography. Eur J Appl Physiol 1982;50:41–5.
Nosratollah Hedayatapour was born in Shirvan,
Iran, in 1972. He graduated in exercise physi-
ology from Tehran university, Iran, in 1997.
Since 2005, he is enrolled as a Ph.D. candidate
in biomedical science and engineering, sup-
ported by the Science Ministry of Iran, at the
Center for Sensory-Motor Interaction (SMI),
Aalborg, Denmark. He is currently involved in
projects in the field of electromyography and
muscle physiology.
Lars Arendt-Nielsen, born in 1958, received the
M.Sc.E.E. degree from Aalborg University,
Denmark, in 1983, with specialisation in bio-
medical engineering, and the Ph.D. degree in
1992. In 1994 he received his Dr.Sci. degree in
Medicine from the Medical Faculty, Aarhus
University, Denmark.
From 1983 to 1984 he was a Research fellow,
Department of Clinical Neurophysiology, The
National Hospital for Nervous Diseases, Lon-
don. Since 1988 he has been with the Depart-
ment of Medical Informatics and Image
Analysis, Aalborg University as an Associated Professor. In 1993 he was
appointed Professor in Biomedical Engineering and Principal investigator
at Center for Sensory-Motor Interaction, which was established in 1993 at
Aalborg University and in 1997 Head of the International Doctoral
School in Biomedical Science and Engineering, Aalborg University, with
55 Ph.D. students enrolled. During his career he has worked as guest
professor in Japan and Australia. He is member of the Danish Research
Council and the Danish Research Education Council. He has published
approx. 510 scientific papers within neuroscience with focus on motor
control and pain research and given more than 110 key-note lectures at
international conferences.
Dario Farina graduated summa cum laude in
Electronics Engineering (equivalent to M.Sc.)
from Politecnico di Torino, Torino, Italy, in
February 1998. During 1998 he was a Fellow
of the Laboratory for Neuromuscular System
Engineering in Torino. In 2001 and 2002 he
obtained the PhD degrees in Automatic Con-
trol and Computer Science and in Electronics
and Communications Engineering from the
Ecole Centrale de Nantes, Nantes, France,
and Politecnico di Torino, respectively. In
1999–2004 he taught courses in Electronics
and Mathematics at Politecnico di Torino and in 2002–2004 he was
Research Assistant Professor at the same University. Since 2004, he is
Associate Professor in Biomedical Engineering at the Department of
Health Science and Technology of Aalborg University, Aalborg, Den-
mark, where he teaches courses on biomedical signal processing, mod-
eling, and neuromuscular physiology. He regularly acts as referee for
approximately 20 scientific International Journals, is an Associate Editor
of IEEE Transactions on Biomedical Engineering, is on the Editorial
Boards of the Journal of Neuroscience Methods, the Journal of Elec-
tromyography and Kinesiology, and Medical and Biological Engineering
and Computing, and member of the Council ISEK (International Society
of Electrophysiology and Kinesiology). His main research interests are in
the areas of signal processing applied to biomedical signals, modeling of
biological systems, basic and applied physiology of the neuromuscular
system, and brain–computer interfaces. Within these fields he has
authored or co-authored more than 100 papers in peer-reviewed Jour-
nals. Dr. Farina is a Registered Professional Engineer in Italy.
396 N. Hedayatpour et al. / Journal of Electromyography and Kinesiology 18 (2008) 390–396
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