Lower muscle co-contraction in flutter kicking for competitive swimmers

Human Movement Science 45 (2016) 40–52

Contents lists available at ScienceDirect

Human Movement Science journal homepage: www.elsevier.com/locate/humov

Lower muscle co-contraction in flutter kicking for competitive swimmers Yuji Matsuda a,⇑, Masami Hirano b, Yosuke Yamada c, Yasushi Ikuta d, Teruo Nomura e, Hiroaki Tanaka f,g, Shingo Oda h a

Department of Sports Sciences, Japan Institute of Sports Sciences, Tokyo, Japan Department of Sports and Health Sciences, Aichi Shukutoku University, Aichi, Japan c Department of Nutritional Science, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan d Graduate School of Education, Osaka Kyoiku University, Osaka, Japan e Graduate School of Science and Technology, Kyoto Institute of Technology, Kyoto, Japan f Fukuoka University Institute for Physical Activity, Faculty of Sports and Health Science, Fukuoka University, Fukuoka, Japan g Central Research Institute for Physical Activity, Fukuoka University, Fukuoka, Japan h Faculty of Health and Well-being, Kansai University, Osaka, Japan b

a r t i c l e

i n f o

Article history: Received 18 March 2015 Revised 22 October 2015 Accepted 2 November 2015

Keywords: Front crawl EMG Proficiency Lower limb

a b s t r a c t The purpose of this study was to examine the difference in muscle activation pattern and co-contraction of the rectus and biceps femoris in flutter-kick swimming between competitive and recreational swimmers, to better understand the mechanism of repetitive kicking movements during swimming. Ten competitive and 10 recreational swimmers swam using flutter kicks at three different velocities (100%, 90%, and 80% of their maximal velocity) in a swimming flume. Surface electromyographic signals (EMG) were obtained from the rectus (RF) and biceps femoris (BF), and lower limb kinematic data were obtained at the same time. The beginning and ending of one kick cycle was defined as when the right lateral malleolus reached its highest position in the vertical axis. The offset timing of muscle activation of RF in the recreational swimmers was significantly later at all velocities than in the competitive swimmers (47–48% and 26–33% of kick time of one cycle for recreational and competitive swimmers, respectively), although the kinematic data and other activation timing of RF and BF did not differ between groups. A higher integrated EMG of RF during hip extension and knee extension induced a higher level of muscle co-contraction between RF and BF in the recreational swimmers. These results suggest that long-term competitive swimming training can induce an effective muscle activation pattern in the upper legs. Ó 2015 Elsevier B.V. All rights reserved.

1. Introduction Swimming is performed in water with the buoyancy force acting in the opposite direction to that of gravity, and the hydrodynamic force (drag force and lift force) generated by body movement. The hydrodynamic force increases as the square of segmental velocity. The properties of water cause differences between motion in water and on land in the kinematics and/ or kinetics, motor control and neuromuscular function of human movements (Masumoto & Mercer, 2008; Pöyhönen,

⇑ Corresponding author. E-mail address: [email protected] (Y. Matsuda). http://dx.doi.org/10.1016/j.humov.2015.11.001 0167-9457/Ó 2015 Elsevier B.V. All rights reserved.

Y. Matsuda et al. / Human Movement Science 45 (2016) 40–52

41

Keskinen, Hautala, Savolainen, & Mälkiä, 1999). For example, the walking velocity, stride length, step frequency (Barela & Duarte, 2008; Shono et al., 2007), and EMG activity of lower limbs during walking in water are lower than those on land (Masumoto, Takasugi, Hotta, Fujishima, & Iwamoto, 2004). In addition, the maximal H reflex/M-wave ratio decreases during immersion in water, mainly because of an increase in hydrostatic pressure and/or a reduction in gravitational force (Pöyhönen & Avela, 2002). EMG activity in water was significantly lower than that on land during knee extension maximal voluntary contraction (MVC) in a seated position, despite the lack of difference in force output between them (Pöyhönen et al., 1999). A swimmer moves forward using hydrodynamic force created with their limb movement in water, while locomotion on land uses ground reaction force. The propulsive force is mainly created by the upper limbs in the front crawl stroke, and thus the majority of previous studies of swimming movements have examined the movements and motor control of the upper limbs (Hollander et al., 1986; Kudo, Vennell, & Wilson, 2013; Takagi et al., 2014). Swimmers push water backward using their upper limbs to generate the propulsive force, which is mainly generated by the hand and forearm, and both the hand angle relative to the water and hand velocity affect the magnitude and direction of the propulsive force (Schleihauf, 1979). Swimmers fix their wrist and elbow joint at a given time in the underwater phase, which is controlled by the co-contraction of the extensor carpi ulnaris and flexor carpi ulnaris (Caty et al., 2007) and biceps brachii and triceps brachii (Lauer, Figueiredo, Vilas-Boas, Fernandes, & Rouard, 2013). These co-contractions are observed more in the earlier stroke phase than the later stroke phase, which can be interpreted as a strategy used for ensuring joint stiffness against the drag force generated by hand and arm movements, leading to high propulsion efficiency. Compared with the upper limbs, the propulsive force generated by the lower limbs may not directly contribute to increasing the swimming velocity (Deschodt, Arsac, & Rouard, 1999; Gourgoulis et al., 2014; Hollander et al., 1986; Yanai, 2001). Kick movements in front crawl swimming contribute to prevent the legs from sinking (Yanai, 2001) and decreasing the trunk inclination (Gourgoulis et al., 2014), and thus velocity during front crawl with kicks is higher than that without kicks (Deschodt et al., 1999). Deschodt et al. (1999) also reported that the underwater wrist trajectory is modified by the action of the legs. These previous studies suggest that the kick movement in front crawl plays a crucial role in the development of swimming skills. A kicking movement for front crawl is defined as the action where the right and left legs move alternately and repeatedly, and the hip, knee and ankle flexion and extension are the main joint motions. Sanders (2007) examined children who participated in a ‘‘learn to swim” program and found that they moved their ankle, knee, and hip more simultaneously than adult swimmers who were experienced in competitive swimming. Oka, Okamoto, Yoshizawa, and Tokuyama (1979) reported a case study in which the lower limb muscle activation pattern and kinematics during flutter kick swimming in the water for an infant approached those of a skilled adult through swimming practice and physical growth. In this study, muscle activation was not quantified and compared with different levels by using statistics. Therefore, the relationship between the muscular activities of kick movements and swimming skills has not been well understood in previous studies. In multi-joint movements, torque at one joint is produced not only by muscular activity, but also by non-muscular forces such as interaction and gravity torques (Furuya & Kinoshita, 2007; Hirashima, Kadota, Sakurai, Kudo, & Ohtsuki, 2002). For example, Hirashima et al. (2002) reported that the skilled hand used the interaction torque more compared with the nonskilled hand when throwing a ball. Furuya and Kinoshita (2007) reported that expert pianists exploit the interaction and gravity torques to accelerate the distal joint when stroking the piano keys. In contrast, their novice group used the muscular torque more than the interaction and gravity torques, and the co-contraction of the agonist and antagonist muscle activity for a novice was significantly higher than that for an expert pianist. The higher muscle co-contraction between the agonist and antagonist muscles were wasted in terms of the disturbing activity of the antagonist muscle on the agonist muscle. The increase in co-contraction level led to a high energy cost (Lay, Sparrow, Hughes, & O’Dwyer, 2002). In finger tapping, finger oscillation, and drum sticking, which are repetitive movements at high frequency like a swimming kick, the antagonist muscle co-contraction level was lower for skilled subjects and/or the skilled hand (i.e., the dominant hand) compared with the non-skilled (Aoki & Kinoshita, 2001; Fujii, Kudo, Ohtsuki, & Oda, 2009; Heuer, 2007). Swimming kicks are performed in water, and buoyancy and hydrodynamic forces act on the swimmer. It is unknown whether expert swimmers exploit non-muscular forces such as gravity and interaction torques. It is hypothesized that skilled swimmers have lower co-contraction than unskilled swimmers during swimming kicks, as in previous studies of throwing a ball, stroking a piano key, playing a drum, or finger tapping. In front crawl swimming, swimmers change their swimming velocity and stroke rate according to the swimming distance (50–1500 m) (Seifert, Chollet, & Bardy, 2004). Therefore, kick movements are performed not only at maximal effort and/or frequency, but also at submaximal effort and/or frequency. In the lower leg muscles of street dancers, co-contraction between agonist and antagonist lower limb muscles were compared between novice and experienced dancers at several different frequencies (Miura, Kudo, Ohtsuki, Kanehisa, & Nakazawa, 2013). The results showed that although co-contraction levels between rectus femoris (RF) and biceps femoris (BF) were not different between the two groups when moving at a slow rate, they were significantly lower in the experienced dancers than in the novices at fast rate. Therefore, in kick movements during swimming, it is possible that the muscle activation pattern would show a significant interaction between skill level and swimming velocity, but no studies have examined the relationship between swimming velocity and the EMG pattern of the lower limbs in swimming. The purpose of this study is to compare the muscle activation and co-contraction levels of RF and BF during flutter kicking between competitive and recreational swimmers at several swimming velocities.

42

Y. Matsuda et al. / Human Movement Science 45 (2016) 40–52

2. Methods 2.1. Procedure Ten competitive swimmers (age: 20.0 ± 0.9 years; height: 178.1 ± 4.0 m; weight; 73.3 ± 6.0 kg) and 10 recreational swimmers (age: 21.4 ± 0.7 years; height: 173.5 ± 3.5 m; weight; 64.9 ± 5.8 kg) were voluntarily participated in this study. The 100-m best times of the competitive swimmers in front crawl were 54.1 ± 1.0 s. The recreational swimmers had learned swimming at physical education classes in their schools and none belonged to a swimming team as a competitive swimmer. The recreational swimmers could swim at least 100 m without a break in front crawl, but did not have an official 100 m best time because they had not been in competition. In accordance with the Declaration of Helsinki, the participants were given a clear explanation of the experimental procedure and provided written informed consent before participating in the study. The experimental procedure was approved by the Ethics Committee of the Graduate School of Human Environmental studies of Kyoto University. The participants performed a warm-up and practice consisting of submaximal flutter kick swimming using a kickboard in a swimming flume for 10 min (Fig. 1). Participants were instructed to remain in place and keep their head above the water at all times. In the main experiment, participants swam with flutter kicks using the kickboard in the swimming flume for 20 s with six different velocities, which were set from 0.7 to 1.2 m
s1 and from 1 to 1.5 m
s1 for the recreational and the competitive swimmers, respectively. The ranges were determined by a preliminary experiment. Flow speed in the flume was controlled at 0.1 m
s1 increments. The rest period between each trial was at least 10 min. The order of swimming velocities was determined at random in each participant. No recreational swimmers could swim for 20 s at 1.3 m
s1, and no competitive swimmers could swim for 20 s at 1.6 m
s1. Maximal velocity (100%) was defined as the highest velocity at which the swimmer could remain in the same place for 20 s. Then, swimming velocities of 80% and 90% of maximal velocity were calculated, and the corresponding trials to 80%, 90%, and 100% of maximal velocity were used for further analyses with an acceptable margin of ±3%. Eighty per cent and 90% of the swimmer’s maximal velocity is in close accordance with the 400 m and 100 m race pace for competitive swimmers (Seifert et al., 2004). 2.2. Data acquisition Surface EMG signals were obtained from the RF and BF using pre-amplified bipolar Ag/AgCl surface electrodes (5-mm diameter, 25-mm interelectrode distance) with bandpass filtering between 10 and 1000 Hz (FA-DL-141; 4Assist, Tokyo, Japan) (Fig. 2). The electrode placement was preceded by shaving, abrasion, and cleaning of the skin with alcohol to reduce the source impedance. A waterproof adhesive bandage was used to cover the electrodes to isolate them from the water (Ikuta et al., 2012). The video view and the EMG data were synchronized with LED signals. EMG data were recorded using a 16-bit analog-to-digital converter (PowerLab; ADInstruments, New South Wales, Australia) at a sampling frequency of 2 kHz. A video camera (HDR-CX270; Sony, Tokyo, Japan) recording at 60 frames
s1 was used to film the swimmers in the sagittal plane. Markers were placed on the greater trochanter, lower costal margin, knee, and lateral malleolus (Fig. 3). The lower trunk segment was defined by the lower costal margin and grater trochanter. The thigh segment was defined by the greater

Electrode AD converter PC

Video Camera

Fig. 1. Schematic illustration of experimental setting. Subjects swam in swimming flume in flutter kicking. Surface electromyography (EMG) electrodes were attached to record the activity of rectus (RF) and biceps femoris (BF).

Y. Matsuda et al. / Human Movement Science 45 (2016) 40–52

43

Fig. 2. Typical examples of EMG signals of RF and BF in a competitive (left) and a recreational swimmer (right). The first and second rows show the rectified EMG signals of the RF and BF. The third and fourth rows show the smoothed EMG signals of the RF and BF. The fifth and sixth rows show the angle and angular velocity of hip and knee joint. The vertical dashed lines indicate the kick time detected from video analysis.

Fig. 3. Determination of the hip and knee angle.

trochanter and knee. The shank segment was defined by the knee and malleolus. Hip angle was calculated as the angle between the lower trunk and thigh segments. Knee angle was calculated as the angle between the thigh and shank segments. Each angle was defined as shown in Fig. 3.

44

Y. Matsuda et al. / Human Movement Science 45 (2016) 40–52

2.3. EMG analysis – onset and offset timing EMG signals were full-wave rectified and smoothed using a low-pass filter at 50 Hz. The onset of the EMG signals was defined as the point at which the EMG amplitude in mV exceeded a threshold and after which EMG amplitude remained above that threshold continuously for at least 25 ms (Fujii et al., 2009; Hodges & Bui, 1996; Kudo & Ohtsuki, 1998). The threshold value was set to the mean background activity (BGA) in mV plus 4 SD (Kudo & Ohtsuki, 1998). The offset of the EMG signals was defined as the point at which the EMG amplitude in mV fell below the threshold. The mean and SD of BGA in mV was determined for each participant using the EMG signal over 200 ms during the rest period before the trial. The onset and offset timing were normalized by each kick cycle time, which was defined based on kinematic analysis as described below. The onset and offset timing were determined over 10 kick cycles and averaged. 2.4. EMG analysis – IEMG Rectified and smoothed EMG signals were integrated in four phases as follows. Phase 1: hip flexion and knee flexion; phase 2: hip flexion and knee extension; phase 3: hip extension and knee extension; phase 4: hip extension and knee flexion. Integrated EMG was divided into the phase duration, and was expressed as a percentage of IEMGmax. The IEMGmax was defined as the maximum integral value of a 40 ms time window among ten kick cycles in the 100% condition for each participant (Lauer et al., 2013). Numerical calculations for all trials were conducted using a program written in Matlab (Mathworks, Boston, MA USA). 2.5. EMG analysis – co-contraction Smoothed EMG signals were normalized using the maximum values obtained from a ten kick cycle when a participant swam in the 100% condition. The percent co-contraction between RF and BF was calculated according to Eq. (1) (Frost, Dowling, Dyson, & Bar-Or, 1997; Winter, 1990). The percent co-contraction was determined over 10 kick cycles and averaged.

%COCON ¼ 2 

common area A B  100 area A þ area B

ð1Þ

where %COCON is the percent co-contraction between RF and BF, area A is the area below the EMG smoothed curve of RF, area B is the area below the EMG smoothed curve of BF, and the common area A & B is the common area of RF and BF. % COCON was calculated in the four phases. 2.6. Video analysis The markers filmed by the video camera were manually digitized frame by frame (Frame Dias IV; DKH, Tokyo, Japan) for a 10-kick cycle. A low-pass Butterworth filter with a cut-off frequency of 5 Hz was used for the analysis. The angular velocities for the knee and hip were calculated by differentiating the angle data over 10 kick cycles (Fig. 4). Positive maximal angular velocity for the hip and knee joints was defined as the maximal angular velocity for hip flexion and knee extension. Negative maximal angular velocity for the hip and knee joints was defined as maximal angular velocity for hip extension and knee flexion. The phase difference between the hip and knee joint movements, meaning time delay between these joints, was obtained using cross-correlation analysis. The phase difference was defined at the time the highest cross correlation coefficient was observed and normalized by the kick time in each participant. The beginning and ending of one kick cycle was defined as when the right lateral malleolus reached its highest position in the vertical axis. Kick time was defined as the time required for one kick cycle. Kick length was obtained by multiplying the flow speed of the swimming flume by the kick time. These analyses were conducted over 10 kick cycles, and the variables were averaged. 2.7. Statistical analysis Means and standard deviations were calculated for all the measured and calculated parameters. Each parameter was compared between the velocity conditions (Velocity; 80%, 90%, and 100% of maximal velocity) and the skill levels (Group; competitive and recreational) by two-way repeated analysis of variance (ANOVA). In each comparison, Velocity was treated as a within-participants variable, and Group was treated as a between-participants variable. When ANOVA revealed a significant interaction, groups were evaluated separately and the Tukey’s post hoc test was used to examine differences between velocity conditions. A level of P < 0.05 indicated significance. A cross correlation analysis was conducted with using knee and hip angle data to determine the phase difference between knee and hip joint.

45

Angulaar velocity(degree・s-1)

Y. Matsuda et al. / Human Movement Science 45 (2016) 40–52

300

Maximal knee extension

Knee 200 Maximal hip flexion

Hip

100 0 -100 Maximal hip extension

-200 Maximal knee flexion

-300 0 Hip

100 50 Kick time (% of kick cycle) Flexion

Knee

Flexion

Extension Extension

Flexion Flexion

Fig. 4. Typical changes in hip (dashed line) and knee (gray line) angular velocity for a competitive swimmer.

3. Results Maximal swimming velocities were 1.39 ± 0.12 m
s1 and 1.08 ± 0.06 m
s1 for competitive and recreational swimmers, respectively. Table 1 shows the kick time and kick length in all velocity conditions. The kick time decreased with increasing velocity. For kick time there was no difference between the two groups, although the kick length for competitive swimmers was significantly higher than that for recreational swimmers. Table 2 shows the maximal angular velocity for the hip and knee in the different velocity conditions. The maximal angular velocity for hip extension at 80% was significantly lower than that at 100% for both recreational and competitive swimmers. The maximal angular velocity for knee flexion and extension increased with increasing swimming velocity in both groups. No significant differences of hip and knee maximal angular velocity were observed for any maximal angular velocity between the groups. Fig. 5 shows the relative timing of the beginning of the flexion and extension phases for the hip and knee. The beginning of the flexion and extension phases did not change with increasing velocity and were not different between competitive and recreational swimmers. Table 3 shows the phase difference of the knee and hip angles. There was no difference between the competitive and recreational swimmers for any velocities. Fig. 6 shows the onset and offset timing of EMG for RF and BF. A two-way ANOVA did not show a significant interaction of velocity  group for the EMG offset of the RF (F(2, 36) = 0.74, P = 0.49). The main effect of Group was significant for the EMG offset of the RF (F(2, 18) = 916.27, P < 0.01), and the EMG offset for RF in the recreational swimmers was significantly later than that in the competitive swimmers. The RF offset for the competitive swimmers was about 30% of the kick cycle, which was the early phase of knee extension (Fig. 6). The RF offset for the recreational swimmers was about 50% of the kick cycle, which was the middle and terminal phase of knee extension. When testing the onset of the RF and BF activations and the offset of the BF activation, the interaction and the main effect of velocity and group were not significant. Fig. 7 shows the IEMG of the RF during the four phases. In terms of the IEMG of the RF during the four phases, a two-way ANOVA did not show a significant interaction of velocity  group. The main effects of group during phase 2 and phase 3 were significant (F(2, 18) = 7.78, P = 0.01 and F(2, 18) = 21.92, P < 0.01, respectively). The IEMGs of the RF during phase 2 and phase 3 for recreational swimmers were significantly higher than those for competitive swimmers. The main effects of velocity during phase 1 and phase 2 were significant (F(2, 36) = 19.34, P < 0.01 and F(2, 36) = 8.55, P = 0.01, respectively). The IEMGs

Table 1 Velocity, kick time, and kick length (mean ± SD).

* a b

Swimming speed

80% of maximal velocity

90% of maximal velocity

Group

Recreational

Competitive

Recreational

Competitive

Recreational

Competitive

Velocity (m
s1) Kick time (s) KICK length (m
kick1)

0.88 ± 0.06 0.32 ± 0.05 0.28 ± 0.05

1.09 ± 0.09* 0.35 ± 0.07 0.38 ± 0.09*

0.98 ± 0.06a 0.29 ± 0.04 0.29 ± 0.04

1.27 ± 0.12*,a 0.33 ± 0.06 0.42 ± 0.10*

1.08 ± 0.06a,b 0.27 ± 0.04 0.29 ± 0.04

1.39 ± 0.09*,a,b 0.29 ± 0.06a 0.41 ± 0.08*

Significant difference with recreational swimmers. Significant difference with 80%. Significant difference with 90% of maximal velocity (P < 0.05).

Maximal velocity (100%)

46

Y. Matsuda et al. / Human Movement Science 45 (2016) 40–52

Table 2 Maximal angular velocity in lower limb segment (mean ± SD).

a b

Swimming speed

80% of maximal velocity

90% of maximal velocity

Maximal velocity (100%)

Group

Recreational

Competitive

Recreational

Recreational

Competitive

Competitive

Hip

Extension (degree
s1) Flexion (degree
s1)

122.6 ± 33.2 107.2 ± 30.7

111.4 ± 23.2 104.0 ± 17.9

119.2 ± 29.3 107.1 ± 27.7

118.0 ± 28.3 105.9 ± 17.1

133.5 ± 33.5a 112.9 ± 27.2a

139.4 ± 24.8a 123.8 ± 23.3a

Knee

Extension (degree
s1) Flexion (degree
s1)

343.5 ± 68.8 301.0 ± 45.9

340.9 ± 71.7 320.2 ± 34.1

396.5 ± 73.9a 365.4 ± 70.9a

365.4 ± 68.4a 344.2 ± 33.3a

427.1 ± 73.7a,b 380.4 ± 53.8a,b

409.1 ± 73.8a,b 399.1 ± 66.3a,b

Significant difference with 80%. Significant difference with 90% of maximal velocity (P < 0.05).

(A)

flexion

extension

80% recreational 90% 100% 80% competitive 90% 100% 0

(B)

25 50 75 Kick time (% of kick cycle) extension

100

flexion

80% recreational

90% 100% 80%

competitive

90% 100% 0

25

50 75 Kick time (% of kick cycle)

100

Fig. 5. The timing of flexion and extension phases in hip (A) and knee (B) for recreational and competitive swimmers. There was no interaction between group and velocity and main effect of group and velocity in hip and knee timing for the extension and flexion phase.

Table 3 Phase difference between hip and knee joint movements calculated by cross-correlation analysis (mean ± SD).

a

Swimming speed (%)

Recreational swimmers

Competitive swimmers

Phase difference (s)

80 90 100

0.109 ± 0.035 0.105 ± 0.041 0.110 ± 0.035

0.123 ± 0.048 0.127 ± 0.037 0.116 ± 0.028

Phase difference (%)

80 90 100

20.49 ± 6.07 21.59 ± 8.77 23.91 ± 6.99a

21.34 ± 7.04 23.10 ± 5.43 24.26 ± 6.44a

Significant difference with 80% (P < 0.05).

during phase 1 and phase 2 were increased with increasing swimming velocity. Fig. 8 shows the IEMG of the BF during the four phases. For the IEMG of the BF during the four phases, a two way ANOVA did not show a significant interaction of velocity  group. The main effects of group during the four phases were not significant. The main effect of velocity during phase 3

47

Y. Matsuda et al. / Human Movement Science 45 (2016) 40–52

(A)

recreational

competitive

80% 90% 100%

*

80% 90% 100% 0

25 50 75 Kick time (% of kick cycle)

100

(B) recreational

competitive

80% 90% 100% 80% 90% 100% 0

25 50 75 Kick time (% of kick cycle)

100

Fig. 6. Activation timing of RF (A) and BF (B) for recreational (black) and competitive swimmers (gray). The error bars indicate the standard deviation (S.D.). Asterisk shows significant difference with recreational swimmers (P < 0.05).

and phase 4 was significant (F(2, 36) = 13.38, P < 0.01 and F(2, 36) = 15.31, P = 0.01, respectively). The IEMGs during phase 3 and phase 4 were increased with increasing swimming velocity. A two-way ANOVA did not show a significant interaction of velocity  group for %COCON in the four phases (Fig. 9). The main effect of group was significant during phase 3 (F(2, 18) = 7.10, P = 0.02). The co-contraction level during hip extension and knee extension for competitive swimmers was significantly lower than that for recreational swimmers at all velocities. The main effect of velocity was not significant during the four phases. 4. Discussion The offset timing of RF activation was significantly slower in recreational swimmers than in competitive swimmers (30% of kick cycle for the competitive swimmers vs. 50% of kick cycle for the recreational swimmers) at all swimming velocities. Moreover the percentage of IEMG of the RF for competitive swimmers during phase2 (hip flexion and knee extension) and phase3 (hip extension and knee extension) was significantly lower than that for recreational swimmers at all velocities. In contrast, the activation timing of the BF and IEMG of the BF in 4 phases was not significantly different between the two groups for all velocities. The co-contraction level between the RF and BF for competitive swimmers during phase3 was significantly lower than that for recreational swimmers, which was associated with the lower RF activation during hip flexion and knee extension phase for competitive swimmers. Nevertheless, note that the lower limb kinematics were not significantly different between the two groups. The maximal angular velocity of knee and hip during extension and flexion was not different between competitive and recreational swimmers. Moreover, there was no significant difference in the phase difference of the hip and knee joint movement between skill levels. Sanders (2007) reported that the children in the ‘‘learn to swim” program moved their lower limb with a small phase difference of the hip and knee joint movements; in contrast, the adult skilled swimmers moved their lower limbs with a large phase difference of the hip and knee joint movements. In the present study, the recreational

48

Y. Matsuda et al. / Human Movement Science 45 (2016) 40–52

(A)

60

(B)

recreational competitive

*

40 30

† 30 20

10

10

†

0 80

90

100

80

(D)

60

90

100

90

100

60

recreational

recreational

competitive

50

40

IEMG (%)

IEMG (%)

†

40

20

50

*

50

*

0

(C)

competitive

*

IEMG (%)

IEMG (%)

50

recreational

60

30 20

competitive

40 30 20

†

10

†

†

0

10 0

80

90

100

80

Fig. 7. IEMG of RF during hip flexion and knee flexion (A), hip flexion and knee extension (B), hip extension and knee extension (C), and hip extension and knee flexion (D) for recreational (black) and competitive swimmers (gray). The error bars indicate the standard deviation (S.D.). Asterisk shows significant difference with swimming velocity (P < 0.05). Dagger shows significant difference with recreational swimmers (P < 0.05).

swimmers had not participated in competitive swimming on a daily basis. However, the recreational swimmers could swim at least 100 m without a break, and thus the group difference in kinematics did not reach statistical significance. The offset time of RF activation for the competitive swimmers was about 30% of the kick cycle, which was the early knee extension phase. The offset time of RF activation for the recreational swimmers was about 50% of the kick cycle, which was when the middle phase of the knee extension, and hip flexion had already started. This is probably related to the use of nonmuscular forces, e.g., inertia, gravitational force, and interaction torque. Pöyhönen et al. (2001) compared the RF and BF activation patterns using EMG during seated knee extension and flexion between 0° and 115° in water with repetitive and single trials. They reported that the muscular activity of RF during knee extension during repetitive trials was activated only for the first 45°. In contrast, the activity of RF continued until at full extension during single extension trials. They suggested that the more quickly reducing RF activity in the repetitive trials compared with the single trials was because of a strategy involving the change of direction from extension to flexion in repetitive movements. Moreover, the authors also suggested that the participants exploited the added mass force, assisting the knee extension, to extend the knee from 70° to 0° without muscle force. Added mass is recognized as the inertial force produced in water, and is generated by the acceleration and deceleration of a mass (Caspersen, Berthelsen, Eik, Pâkozdi, & Kjendlie, 2010). However, it should be noted that muscles other than RF not measured in the present study may affect the results, and further research should be performed to investigate this possibility. EMG activation patterns change after short- and/or long-term practice. For example, after 10 days rowing ergometer training, the activity of vastus lateralis and biceps brachii change from a tonic to a more phasic pattern (Lay, Sparrow, Hughes, & O’Dwyer, 2002). In the previous study, metabolic economy was measured, and the results suggested that reductions in muscle activation are associated with reduced metabolic energy cost. When drumming with drumsticks, drummers show more reciprocal wrist muscle activation patterns after long-term practice (Fujii et al., 2009). The competitive swimmers in the present study had been swimming for more than 10 years, and in every practice session they had moved their lower limbs numerous times. Therefore, their lengthy experience would produce an effective muscle activation pattern, meaning that the RF for the competitive swimmers activates only in the early knee extension phase. In this case, the competitive swimmers probably used non-muscular forces (e.g., interaction, added force, and gravitational force) during knee

49

Y. Matsuda et al. / Human Movement Science 45 (2016) 40–52

(A)

(B) 60

60 recreational

50

40

IEMG (%)

IEMG (%)

50

recreational

competitive

30

40 30

20

20

10

10

0

0 80

(C) 60

competitive

90

100

80

90

100

(D) 60

recreational

recreational

competitive * 50

50

competitive *

40

IEMG (%)

IEMG (%)

*

30

40 30

20

20

10

10

0

0 80

90

100

80

90

100

Fig. 8. IEMG of BF during hip flexion and knee flexion (A), hip flexion and knee extension (B), hip extension and knee extension (C), and hip extension and knee flexion (D) for recreational (black) and competitive swimmers (gray). The error bars indicate the standard deviation (S.D.). Asterisk shows significant difference with swimming velocity (P < 0.05).

extension as in the results examined in previous studies on multi-joint movement (Furuya & Kinoshita, 2007; Furuya, Osu, & Kinoshita, 2009). In both competitive and recreational swimmers, the BF activated starting at 30% of the kick cycle, and at that time swimmers had not yet started their hip extension and knee flexion. In previous studies, the activation of BF has been started at the point when the knee was in extension phase during repetitive knee extension and flexion trials in a seated position in water, which is consistent with the results of the present study (Pöyhönen et al., 1999). This activation of BF during knee extension has the function of changing the direction from extension to flexion. Co-contraction levels decrease with proficiency during repetitive movements at high frequency such as finger tapping and playing a drum (Aoki & Kinoshita, 2001; Fujii et al., 2009). In these previous studies, the co-contraction levels were examined only at maximal frequency, and the decreases in co-contraction levels throughout training would be related to exploiting effective feedforward control to compensate for unpredictable dynamic forces. In the present study, the level of co-contraction for competitive swimmers was significantly lower than that for recreational swimmers not only at maximal velocity, but also at submaximal velocity. Even if the velocity is slow, swimmers need to control the buoyancy, gravity, and hydrodynamic forces that they do not experience in their daily lives on land. For recreational swimmers it is difficult to control these forces while keeping balanced and swimming forward even at slow velocity, which leads to higher cocontraction at all velocities. In contrast, competitive swimmers can exploit the forces effectively with feedforward control acquired through long-term practice. During arm strokes in front crawl for competitive swimmers, the extensor and flexor carpi ulnaris muscle for the international swimmers are co-activated during the insweep phase (Caty et al., 2007). The biceps brachii and triceps brachii muscles for the international level swimmers are more co-activated during the aquatic elbow flexion and the aerial elbow extension than aquatic elbow extension and the aerial elbow flexion (Lauer et al., 2013). In these previous studies, the co-contraction level of the agonist and antagonist muscles was quantified using a co-contraction index and was compared

50

Y. Matsuda et al. / Human Movement Science 45 (2016) 40–52

50

%COCON(%)

(B)

60 recreational competitive

recreational

40 30 20 10

90

100

30 20

*

*

recreational competitive *

80

(D)

30 20 10

100

90

100

60 50

40

90

recreational

%COCON(%)

%COCON(%)

50

40

0 80

60

competitive

10

0

(C)

60 50

%COCON(%)

(A)

competitive

40 30 20 10

0

0 80

90

100

80

Fig. 9. %COCON during hip flexion and knee flexion (A) and hip flexion and knee extension (B) and hip extension and knee extension (C) and hip extension and knee flexion (D) for recreational (black) and competitive swimmers (gray). The error bars indicate the standard deviation (S.D.). Asterisk shows significant difference with recreational swimmers (P < 0.05).

with different arm stroke phase. Cappaert, Pease, and Troup (1996) reported that elbow fixation is related to the determinants of propulsion efficiency in front crawl, while Lauer et al. (2013) stated that the higher co-contraction of the upper limbs may be a strategy adopted by top swimmers to produce upper limb movements. The propulsive force is mainly created by the upper limbs (Hollander et al., 1986). Furthermore, swimming velocity with arm-only swimming is 90% of the velocity of whole body swimming (Deschodt et al., 1999). It is known that a higher level of co-contraction is related to an increase in joint stiffness (Lee, Rogers, & Granata, 2006). The higher the load supported in the elbow flexion/extension movement, the higher the level of co-contraction that was observed (Praagman, Chadwick, Van der Helm, & Veeger, 2010). Therefore, higher co-contraction of the upper limbs might be a strategy to increase the joint stiffness to counteract the higher hydrodynamic forces generated by the upper limbs compared with the lower limbs for competitive swimmers. In contrast, lower co-contraction during knee extension in the lower limbs is associated with higher swimming skill in the present study. The propulsive force generated by the lower limbs may not directly contribute to an increase in swimming velocity because of the lower propulsive force of the lower limbs compared with that of the upper limbs. The movement frequency of kicking is three times as fast as that of the arm stroke during six beat kick swimming, and the internal work of kick movements is more than five times larger than that of arm movements (Zamparo, Pendergast, Mollendorf, Termin, & Minetti, 2005). Muscle co-contraction is sometimes recognized as ‘‘wasted contraction”, as the antagonist muscle activities cancel the agonist muscle activities (Thoroughman & Shadmehr, 1999). In cycling and running, higher co-contraction is related to higher energy expenditure Candotti et al., 2009; Moore, Jones, & Dixon, 2014). Therefore, we suggest that the lower co-contraction of the lower limbs is a strategy that aims to decrease the higher internal work of the kick rather than to increase the power output of one kick compared with an arm stroke. In the present study, the participants swam in a swimming flume but not in a pool. Using a swimming flume for the experiment has some advantages: the participant stays the same position, and the swimming velocity can be accurately controlled. However, the water flow conditions between a swimming flume and an actual pool are different. Comparing overground and treadmill running, some kinematic and kinetic variables and muscle activation patterns of the lower limbs were

Y. Matsuda et al. / Human Movement Science 45 (2016) 40–52

51

slightly different between the two conditions (Nigg, De Boer, & Fisher, 1995; Wank, Frick, & Schmidtbleicher, 1998). These studies suggest that the kinematics, kinetics and muscle activation patterns are not the same between swimming flume and pool swimming. In addition, the swimmer swam with flutter kicks using the kickboard and keeping their head above water in the present study. The timing of hip rolling was not the same between flutter kick using the kickboard and front crawl, and trunk inclination during the task of the present study would be increased compared with front crawl because of keeping the head above water. This might lead to differences in kinematics and EMG activation. Further studies are needed to address these limitations. 5. Conclusion During flutter-kick swimming, the duration of RF activation was significantly longer, and the normalized IEMG of the RF during hip extension and knee extension for recreational swimmers was significantly higher than that for competitive swimmers at all velocities. This resulted in smaller co-contraction between the RF and BF during hip extension and knee extension for competitive swimmers. Competitive swimmers acquire these lower limb muscle activation patterns through their longterm practice in swimming fast. Conflict of interest None of the authors of this paper has a financial or personal relationship with other people or organizations that could inappropriately influence or bias the content of the paper. Acknowledgments We would like to thank all of the participants for the time and effort. The study was supported by Kouzuki Foundation for Sports and Education. References Aoki, T., & Kinoshita, H. (2001). Temporal and force characteristics of fast double-finger, single-finger and hand tapping. Ergonomics, 44(15), 1368–1383. http://dx.doi.org/10.1080/00140130110107452. Barela, A. M., & Duarte, M. (2008). Biomechanical characteristics of elderly individuals walking on land and in water. Journal of Electromyography and Kinesiology, 18(3), 446–454. Candotti, C. T., Loss, J. F., Bagatini, D., Soares, D. P., da Rocha, E. K., de Oliveira, A. R., et al (2009). Cocontraction and economy of triathletes and cyclists at different cadences during cycling motion. Journal of Electromyography and Kinesiology, 19(5), 915–921. http://dx.doi.org/10.1016/j.jelekin.2008.04.008. Cappaert, J. M., Pease, D. L., & Troup, J. P. (1996). Biomechanical highlights of world champion and Olympic swimmers. In J. P. Troup, A. P. Hollander, D. Strasse, S. W. Trappe, J. M. Cappaert, & T. A. Trappe (Eds.), Biomechanics and medicine in swimming VII (pp. 76–80). London: E& FN Spon. Caspersen, C., Berthelsen, P. A., Eik, M., Pâkozdi, C., & Kjendlie, P.-L. (2010). Added mass in human swimmers: Age and gender differences. Journal of Biomechanics, 43(12), 2369–2373. Caty, V., Aujouannet, Y., Hintzy, F., Bonifazi, M., Clarys, J. P., & Rouard, A. H. (2007). Wrist stabilisation and forearm muscle coactivation during freestyle swimming. Journal of Electromyography and Kinesiology, 17(3), 285–291. http://dx.doi.org/10.1016/j.jelekin.2006.02.005. Deschodt, V. J., Arsac, L. M., & Rouard, A. H. (1999). Relative contribution of arms and legs in humans to propulsion in 25-m sprint front-crawl swimming. European Journal of Applied Physiology and Occupational Physiology, 80(3), 192–199. http://dx.doi.org/10.1007/s004210050581. Frost, G., Dowling, J., Dyson, K., & Bar-Or, O. (1997). Cocontraction in three age groups of children during treadmill locomotion. Journal of Electromyography and Kinesiology, 7(3), 179–186. Fujii, S., Kudo, K., Ohtsuki, T., & Oda, S. (2009). Tapping performance and underlying wrist muscle activity of non-drummers, drummers, and the world’s fastest drummer. Neuroscience Letters, 459(2), 69–73. http://dx.doi.org/10.1016/j.neulet.2009.04.055. Furuya, S., & Kinoshita, H. (2007). Roles of proximal-to-distal sequential organization of the upper limb segments in striking the keys by expert pianists. Neuroscience Letters, 421(3), 264–269. Furuya, S., Osu, R., & Kinoshita, H. (2009). Effective utilization of gravity during arm downswing in keystrokes by expert pianists. Neuroscience, 164(2), 822–831. Gourgoulis, V., Boli, A., Aggeloussis, N., Toubekis, A., Antoniou, P., Kasimatis, P., et al (2014). The effect of leg kick on sprint front crawl swimming. Journal of Sports Sciences, 32(3), 278–289. http://dx.doi.org/10.1080/02640414.2013.823224. Heuer, H. (2007). Control of the dominant and nondominant hand: Exploitation and taming of nonmuscular forces. Experimental Brain Research, 178(3), 363–373. Hirashima, M., Kadota, H., Sakurai, S., Kudo, K., & Ohtsuki, T. (2002). Sequential muscle activity and its functional role in the upper extremity and trunk during overarm throwing. Journal of Sports Sciences, 20(4), 301–310. http://dx.doi.org/10.1080/026404102753576071. Hodges, P. W., & Bui, B. H. (1996). A comparison of computer-based methods for the determination of onset of muscle contraction using electromyography. Electroencephalography and Clinical Neurophysiology, 101(6), 511–519. Hollander, A. P., De Groot, G., van Ingen Schenau, G. J., Toussaint, H. M., De Best, H., Peeters, W., et al (1986). Measurement of active drag during crawl arm stroke swimming. Journal of Sports Sciences, 4(1), 21–30. http://dx.doi.org/10.1080/02640418608732094. Ikuta, Y., Matsuda, Y., Yamada, Y., Kida, N., Oda, S., & Moritani, T. (2012). Relationship between decreased swimming velocity and muscle activity during 200-m front crawl. European Journal of Applied Physiology, 112(9), 3417–3429. http://dx.doi.org/10.1007/s00421-012-2321-0. Kudo, K., & Ohtsuki, T. (1998). Functional modification of agonist-antagonist electromyographic activity for rapid movement inhibition. Experimental Brain Research, 122(1), 23–30. Kudo, S., Vennell, R., & Wilson, B. (2013). The effect of unsteady flow due to acceleration on hydrodynamic forces acting on the hand in swimming. Journal of Biomechanics, 46(10), 1697–1704. http://dx.doi.org/10.1016/j.jbiomech.2013.04.002. Lauer, J., Figueiredo, P., Vilas-Boas, J. P., Fernandes, R. J., & Rouard, A. H. (2013). Phase-dependence of elbow muscle coactivation in front crawl swimming. Journal of Electromyography and Kinesiology, 23(4), 820–825. http://dx.doi.org/10.1016/j.jelekin.2013.02.004. Lay, B. S., Sparrow, W. A., Hughes, K. M., & O’Dwyer, N. J. (2002). Practice effects on coordination and control, metabolic energy expenditure, and muscle activation. Human Movement Science, 21(5–6), 807–830.

52

Y. Matsuda et al. / Human Movement Science 45 (2016) 40–52

Lee, P. J., Rogers, E. L., & Granata, K. P. (2006). Active trunk stiffness increases with co-contraction. Journal of Electromyography and Kinesiology, 16(1), 51–57. Masumoto, K., & Mercer, J. A. (2008). Biomechanics of human locomotion in water: An electomyographic analysis. Exercise and Sport Sciences Reviews, 36(3), 160–169. Masumoto, K., Takasugi, S.-I., Hotta, N., Fujishima, K., & Iwamoto, Y. (2004). Electromyographic analysis of walking in water in healthy humans. Journal of Physiological Anthropology and Applied Human Science, 23(4), 119–127. Miura, A., Kudo, K., Ohtsuki, T., Kanehisa, H., & Nakazawa, K. (2013). Relationship between muscle cocontraction and proficiency in whole-body sensorimotor synchronization: A comparison study of street dancers and nondancers. Motor Control, 17(1), 18–33. Moore, I. S., Jones, A. M., & Dixon, S. J. (2014). Relationship between metabolic cost and muscular coactivation across running speeds. Journal of Science and Medicine in Sport, 17(6), 671–676. Nigg, B. M., De Boer, R. W., & Fisher, V. (1995). A kinematic comparison of overground and treadmill running. Medicine and Science in Sports and Exercise, 27 (1), 98–105. Oka, H., Okamoto, T., Yoshizawa, M., & Tokuyama, H. (1979). Electromyographic and cinematographic study of. In Paper presented at the swimming III: Proceedings of the third international symposium of biomechanics in swimming. Edmonton, Canada: University of Alberta. Pöyhönen, T., & Avela, J. (2002). Effect of head-out water immersion on neuromuscular function of the plantarflexor muscles. Aviation, Space, and Environmental Medicine, 73(12), 1215–1218. Pöyhönen, T., Keskinen, K. L., Hautala, A., Savolainen, J., & Mälkiä, E. (1999). Human isometric force production and electromyogram activity of knee extensor muscles in water and on dry land. European Journal of applied Physiology and Occupational Physiology, 80(1), 52–56. Pöyhönen, T., Kyröläinen, H., Keskinen, K. L., Hautala, A., Savolainen, J., & Mälkiä, E. (2001). Electromyographic and kinematic analysis of therapeutic knee exercises under water. Clinical Biomechanics, 16(6), 496–504. Praagman, M., Chadwick, E., Van der Helm, F., & Veeger, H. (2010). The effect of elbow angle and external moment on load sharing of elbow muscles. Journal of Electromyography and Kinesiology, 20(5), 912–922. Sanders, R. H. (2007). Kinematics, coordination, variability, and biological noise in the prone flutter kick at different levels of a ‘‘learn-to-swim” programme. Journal of Sports Sciences, 25(2), 213–227. http://dx.doi.org/10.1080/02640410600631025. Schleihauf, R. E. (1979). A hydrodynamic analysis of swimming propulsion. In J. T. A. E. Bedingfield (Ed.), Swimming III (pp. 70–117). Baltimore: University Park Press. Seifert, L., Chollet, D., & Bardy, B. G. (2004). Effect of swimming velocity on arm coordination in the front crawl: A dynamic analysis. Journal of Sports Sciences, 22(7), 651–660. http://dx.doi.org/10.1080/02640410310001655787. Shono, T., Masumoto, K., Fujishima, K., Hotta, N., Ogaki, T., & Adachi, T. (2007). Gait patterns and muscle activity in the lower extremities of elderly women during underwater treadmill walking against water flow. Journal of Physiological Anthropology, 26(6), 579–586. Takagi, H., Shimada, S., Miwa, T., Kudo, S., Sanders, R., & Matsuuchi, K. (2014). Unsteady hydrodynamic forces acting on a hand and its flow field during sculling motion. Human Movement Science, 38, 133–142. http://dx.doi.org/10.1016/j.humov.2014.09.003. Thoroughman, K. A., & Shadmehr, R. (1999). Electromyographic correlates of learning an internal model of reaching movements. The Journal of Neuroscience, 19(19), 8573–8588. Wank, V., Frick, U., & Schmidtbleicher, D. (1998). Kinematics and electromyography of lower limb muscles in overground and treadmill running. International Journal of Sports Medicine, 19(7), 455–461. Winter, D. A. (1990). Biomechanics and motor control of human movement. John Wiley & Sons. Yanai, T. (2001). Rotational effect of buoyancy in frontcrawl: Does it really cause the legs to sink? Journal of Biomechanics, 34(2), 235–243. Zamparo, P., Pendergast, D., Mollendorf, J., Termin, A., & Minetti, A. (2005). An energy balance of front crawl. European Journal of Applied Physiology, 94(1–2), 134–144.