APPLIED SCIENCES Biodynamics
Multi-segment coordination: fatigue effects ANDRE L. F. RODACKI, NEIL E. FOWLER, and SIMON J. BENNETT The Manchester Metropolitan University, Department of Exercise and Sport Sciences, Alsager, Staffordshire, UNITED KINGDOM, ST7 2HL; and Universidade Federal do Parana´, Departamento de Educac¸a˜o Fı´sica, Jardim Botaˆnico, Curitiba, Parana´, BRAZIL
ABSTRACT RODACKI, A. L. F., N. E. FOWLER, and S. J. BENNETT. Multi-segment coordination: fatigue effects. Med. Sci. Sports Exerc., Vol. 33, No. 7, 2001, pp. 1157–1167. Purpose: The aim of this study was to investigate the segmental coordination of vertical jumps under fatigue. Methods: Twelve subjects performed maximal countermovement jumps with and without fatigue, which was imposed by maximal continuous jumps in place until their maximal jump height corresponded to 70% of the nonfatigued condition. Video, ground reaction forces, and electromyographic signals were recorded to analyze the segmental coordination of countermovement jumps before (CMJ1) and after (CMJ2) fatigue. The magnitude of joint extension initiation, peak joint angular velocity, and peak net power around the ankle, knee, and hip joints and their respective times were determined. Results: CMJ2 was characterized by a longer contact time, which was accompanied with an earlier movement initiation and several differences (P ⬍ 0.05) in the variables used to describe coordination. When the movement duration was normalized with respect to the contact phase duration, the differences between CMJ1 and CMJ2 were not sustained. A consistent pattern was indicated, in which the segmental coordination did not differ between jump conditions. When the magnitude of the muscle activation was set aside, a remarkably consistent muscle activation time was noticed between conditions. Conclusions: It was indicated that countermovement jumps were performed with a consistent well-timed motion of the segments. A “common drive,” which acts without the knowledge of the muscle properties, was suggested as mediating and controlling the muscle activation timing between agonist-antagonist muscle pairs. Key Words: BIOMECHANICS, MOTOR CONTROL, SKILL TECHNIQUE, TIMING, MOVEMENT STRATEGY
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performance under fatigue, these studies did not assess the intersegment coordination (timing and sequencing of segmental movements and muscle activation). Because studies analyzing how the neuromuscular system reorganizes the segmental movement coordination during vertical jump movements under fatigue may provide valuable information to understand the control of explosive multi-segment movements, research on this issue is required. Some work on the effects of fatigue on the segmental motion and muscle activation in other tasks has been performed. Forestier and Nougier (17) described different segment coordination patterns in response to fatiguing upper limb multi-segment movements during throwing. The subjects appeared to increase the rigidity of the system and the proximal-distal segment motion order, which is generally observed during this type of movement, was no longer followed. This increased rigidity may be interpreted as an attempt of the neuromuscular system to reduce the degrees of freedom into a more manageable number, i.e., constraining the interjoint relationships in order to simplify the movement execution and control (5). Similar strategies have been reported during movement acquisition of other multi-joint movements (32), but it is not known whether similar mechanisms will occur when maximal countermovement jumps are performed under fatigue.
he ability of an athlete to propel the center of mass as high as possible is an important factor in the performance of various sports such as volleyball and basketball. The training of the explosive power output of the athlete’s lower limbs generally includes routines of several successive maximal vertical jumps, which can easily lead to fatigue. Although the effects of fatigue on neuromuscular system function have been broadly reported (16), there have been few studies on the effects of fatigue upon the biomechanical characteristics of vertical jumping, such as the magnitude and timing of angular displacement, angular velocity, force, impulse, contact time, and muscular activation. Studies involving vertical jumps when fatigued have been performed (25,33), but they were restricted to the analysis of the neuronal mechanisms influencing the stretch-shortening cycle, such as preactivation, joint stiffness, and stretch-shortening reflex regulation (19,25). Despite describing several parameters of the movement and providing substantial information about the mechanisms controlling vertical jumping
0195-9131/01/3307-1157/$3.00/0 MEDICINE & SCIENCE IN SPORTS & EXERCISE® Copyright © 2001 by the American College of Sports Medicine Received for publication June 2000. Accepted for publication October 2000.
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Bonnard et al. (9) also studied multi-segment movements under fatigue and showed that hopping could be maintained for long periods of time by using two different strategies (earlier preactivation and trade-offs between muscles across different joint levels). This indicates the existence of compensatory mechanisms used to counterbalance the loss in the force-generating properties of the muscles due to fatigue. In vertical countermovement vertical jumps, it is conceivable that changes in stiffness regulation under fatigue conditions (18) would have an effect upon the motion of the segments and a different coordination pattern may emerge. Because the sequential motion of the segments is influenced and ultimately determined by muscular forces, which under fatigue may experience a change, distinctive patterns of segment motions and/or muscle activation may emerge. Under fatigue, defined as the inability of the neuromuscular system to sustain the required or expected power output around a joint (13), the segmental coordination of vertical jumps may be rearranged. Therefore, if a relationship between control and muscle strength exists, it would be expected that a reorganization of the segmental movement and/or muscle activation pattern would occur when muscle strength is changed (decreased) due to fatigue. On the other hand, some studies describing the importance of a specific coordination strategy during maximal vertical jumps (6,8) have shown a close relationship between strength and control and have demonstrated that increases in muscle strength only led to increases in jump height if the control (coordination) is rearranged (reoptimized). According to Bobbert and Van Soest (8) and Van Zandwijk et al.(31), vertical jumps are guided by a template motor program for certain classes of movements, in which the output is achieved by tuning certain parameters of the task. It has been suggested that the execution of such explosive movements must rely on a preprogrammed muscle stimulation pattern, which does not depend on the muscle force-generating properties. Hence, maximal countermovement jump performances can only be achieved by letting the subjects repeatedly solve the task, i.e., practicing the movement with their changed muscle properties. This process would allow the subjects to reoptimize the stimulation control signals and achieve greater performances after a certain period of practice (training). These findings suggest the existence of a robust muscle stimulation pattern that cannot be easily changed, even when the ability of the muscles to produce torque around a joint is changed (increased by rising the muscle strength level or decreased by the impairments imposed by fatigue processes). Therefore, reorganization of the segmental movement and/or muscle activation pattern of maximal countermovement jumps may not occur under fatigue conditions due to a preprogrammed stimulation pattern, which guides the movement execution, irrespective of the changes imposed in the muscle force-generating properties. The aim of the present study was to investigate how the neuromuscular system reorganizes multi-segment movements (maximal vertical jumps) under fatigue. The muscle activation pattern and the power output generated around each joint of the 1158
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lower limb were used in an attempt to explain the differences between experimental conditions. It was hypothesized that, with fatigue, the subjects would use different segment motion strategies, in which the proximal-distal order is altered and a more simultaneous sequence appears in order to maintain maximum vertical jump outputs.
METHODS Twelve healthy male subjects (age, 23.8 ⫾ 4.8 yr old; height, 180 ⫾ 5.5 cm and body mass, 76.0 ⫾ 12.7 kg), actively engaged in various sports (6 volleyball players; 4 rugby players; 2 multi-sport), were informed of the procedures involved in this study and gave their written informed consent to act as subjects, in accordance with the ACSM policy statement regarding the use of human subjects and informed consent. All subjects were experienced in vertical jumping and included such exercises in their exercising routines. Fatigue was induced by requesting the subjects to perform successive maximal vertical countermovement jumps (CMJ) in the same place. Apart from the arms, which were kept against the chest, the CMJs were performed according to the subjects’ preferred style, i.e., to bend their knees to a freely chosen angle. The interval between successive CMJs was kept as minimal as possible in such a way that the subsequent jump was initiated as soon as the subject assumed an upright and balanced posture. The exercise was stopped when the subject could no longer reach 70% of the jump height (measured by the flight time) achieved in a maximal jump for two consecutive trials. The maximal jump height was assessed immediately before the fatiguing exercise by selecting the best (highest) jump from three maximal countermovement jumps. The height of these three CMJs was recorded by an electronic mat device (Tapeswitch Signal Mat, model 1723, Tapeswitch, Farmingdale, NY), which calculated the jump height from the flight time. An assessment of this equipment revealed a small root mean square error (5.5 ⫾ 2.4 mm) and a high correlation coefficient (r ⫽ 0.996), when compared with data of 10 vertical jumps simultaneously collected using a force platform (Kistler®, model 9281B, sampling at 1000 Hz, Kistler amplifier model 9805, Winterhur, Switzerland). Video, force, and electromyographic data of these three CMJs were also recorded, but only the trial that resulted the greatest jump height was selected to represent the subject’s performance in the nonfatigued condition (CMJ1). Because the jump mat was kept on the top of the force platform during the fatiguing exercises, it was possible to monitor the performance of each jump. Once the subject’s performance dropped below 70% of the maximal jump height for two consecutive jumps, three further trials were performed with simultaneous kinematic, force, and electromyographic data collected. The jump that produced the greatest jump height was selected to represent the subject’s best performance in the fatigued condition (CMJ2). Despite the problems related to the use of the flight time to calculate jump height (2), the differences in the height of the center of http://www.acsm-msse.org
FIGURE 1—The four-body segment model and the joint angle convention. The muscles soleus (SOL), gastrocnemius (GAS), semitendinosus (ST), vastus lateralis (VL), rectus femoris (RF), and gluteus maximus (GM) are indicated. Adapted from Bobbert and Van Soest, 1994 (8).
mass between the take-off and landing instants were assumed to be similar in both jump conditions and were considered as a systematic error. All subjects received verbal feedback about the performance and were encouraged to jump maximally throughout the fatiguing exercise. Reflective marks were placed on the right side of the subject’s body to represent the following sites: 1) fifth metatarsal joint, 2) lateral malleolus, 3) lateral femoral epicondyle of the knee, 4) the most prominent protuberance of the greater trochanter, and 5) neck at the level of the fifth cervical vertebrae. By using a two-dimensional kinematic optoelectric system (ELITE), subjects were filmed (100 Hz), and the marker points were filtered using spline functions. These filtered body markers defined the position of the foot (FOT), shank (SHA), thigh (THI), and upper body (TRU) and were used to calculate joint angular displacement, velocity, and acceleration of the ankle (ANK), knee (KNE), and hip (HIP). MULTI-SEGMENT COORDINATION: FATIGUE EFFECTS
Figure 1 provides visual information of the four-body segment model and also shows the joint angle convention. Surface electromyographic signals were recorded from gastrocnemius lateralis (GAS; over the area of the greatest muscle bulk on the lateral calf), soleus (SOL; over the lateral edge, where the muscle protrudes below the GAS) vastus medialis (VM; over the area of the greatest muscle bulk just medial to the rectus femoris on the distal half of the thigh), rectus femoris (RF; over the midpoint between the anterior superior iliac spine and the patella superior border), semitendinosus (ST; midway on a line between the ischial tuberosity and the head of the fibula), and gluteus maximum (GLU; over the bulkiest part of the muscle belly’s middle). The electrode placement sites followed the recommendation of Acierno et al. (1). Electromyographic signals were obtained using disposable bipolar surface electrodes (Ag/ AgCl, Bio-tabs MSB®, 3M, Bracknell, United Kingdom, with leadoff area 2.75 cm2), placed with center-to-center distance of 1.5 cm and border-to-border distance of 1.0 cm. Reference electrodes (3M Red Dot®, type 2237, Ag/AgCl with foam tape and solid gel) were used at the most distant point possible away from the electrode sites (approximately 10 –15 cm). The electromyographic signals were preamplified in subminiature amplifiers before transmission via FM radio telemetry (operating at 459 MHz, with channel bandwidth of 1000 Hz) to a recording device no further than 3 m away. The miniature preamplifiers (33 ⫻ 21 ⫻ 9 mm) provided a gain of 1000, bandwidth of 15 kHz, noise of less than ⫺52 dB, and input impedance less than 108 ohms. Data were sampled at 200 Hz. Previous analyses of this laboratory has revealed that the relatively low sampling frequency used in this study did not affect the characteristics of the electromyographic signals used in this study, when compared with the signals obtained with higher sampling frequencies (e.g., 800 Hz). The raw electromyograms were processed into a linear envelope (EEMG). The EEMGs were calculated using the MYO-DAT 5.0 EMG analysis software® (MIE Medical Research Ltd, Leeds, UK) by applying a second-order lowpass filter with a cut-off frequency of 6 Hz. A force platform (Kistler®, model 9281B, Kistler Instruments), synchronized with the kinematic and electromyographic measurements and sampling at 1000 Hz, provided force-time traces. The kinematic analysis was combined with the ground reaction forces to calculate net moments at the ankle, knee, and hip joints. The moment of inertia of each segment was estimated by using the Drillis and Contini’s (12) equations. Extension moments were considered positive at all joints. Net powers around the joints were also calculated by multiplication of the net moments and joint angular velocities. All kinetic data were normalized with respect to body weight (BW). To assess the segmental coordination of this task, it was necessary to determine the time at which initiation of extension (IEX) and peak angular velocity (PAV) of the ankle (ANK), knee (KNE), and hip (HIP) occurred during the propulsive phase of the movement. The timing and the sequential relationship were given by the difference in time at which IEX of each joint occurred (8,21). For instance, a Medicine & Science in Sports & Exercise姞
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negative value between the IEX of the hip and knee joints (IEXHIP –IEXKNE) indicates that the proximal segment movement preceded its distal counterpart. The IEX was defined as the first instant (frame) after the deepest joint excursion (flexion). Because the IEX was determined kinematically (from joint angular displacement data), it is estimated that an error of 5 ms may have occurred. PAV was selected because it has been shown to be relatively invariant during the propulsive phase (21). To analyze the sequence and temporal organization of the movement, the first and the last data points corresponding respectively to the beginning of the negative (NEG) and the end of the positive (POS) phases were used to define the contact time (CT). The beginning of the NEG phase was determined kinematically by assessing the instant in which the subjects initiated the vertical downward displacement, measured by the displacement of the vertical coordinate of the body mass center. The initiation of the movement was considered as the instant in which the vertical coordinate of the body mass center decreased more than 5.0% from the position assumed before starting the movement. The end of the NEG phase was defined as the instant in which the knee joint angular displacement reaches its deepest excursion. The POS phase was defined as the period between the first instant after the minimum knee joint angular position and take-off (TO) instant (34), which was determined with the help of the force data. At the end of the NEG phase and the beginning of the POS phase, there is a period of transition, a transient phase (TR), in which the changes in the knee joint angular velocity are minimal. For analysis purposes, the TR phase was determined when the angular velocity of the knee joint ranged between ⫹30°s⫺1 and ⫺30°s⫺1. To better compare the temporal characteristics of the electromyographic signals between conditions (the relative peak activation), the EEMGs were normalized with respect to the signal magnitude. For each muscle, the highest electromyographic signal value obtained during the performance of each trial was used as reference and set at 100%. In the next sections, the normalized electromyographic signals are referred to as EMG. Muscle activation was quantified during the downward and push-off phases by dividing the integrated EMG signal (the area under the muscle activation curve) by the duration of each movement phase. Changes in muscle activation were expressed as a percentage of the initial values (CMJ1). So, if a muscle is more active in the fatigued condition, this will lead to a positive value. The electromyographic signals of the six muscles examined in this study were compared in relation to the initiation (switch on, ON) and peak muscle activation (PK). ON was arbitrarily considered as the first instant in which muscle activation first rose continuously and was equal or higher than 20% PK, whereas PK was defined as the highest activation during the push-off phase. Leg stiffness was calculated to represent the overall stiffness of the lower limb during the negative phase of the movement and was calculated from the ratio of the peak ground reaction force to the displacement of the body mass center during the NEG phase of the movement (15). Due to 1160
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the central anatomical location and its importance in movement control, the stiffness of the knee joint was also calculated. The knee stiffness during the negative phase was determined from the coefficient of linear regression of the moment-angle relationship between the initiation of the movement (the instant in which the net moment assumes a positive value) and the deepest excursion of the knee joint. To analyze the relative temporal characteristics a second analysis was performed, in which all variables were normalized with respect to movement duration (CT) of each jump condition, which was set as 100% (TO ⫽ 100%). This normalization process was conducted by applying spline functions using a computer routine, and the effect of this procedure on data series was deemed minimal because only temporal factors of both conditions were manipulated. To compare the variables selected to describe the kinematic, kinetic, and electromyographic data across the experimental conditions (CMJ1 vs CMJ2), a two-tailed t-test for paired comparisons was applied in each selected variable. A Kolgomorov-Smirnov test was applied and confirmed data normality. The significance level was set at P ⬍ 0.05 for all analyses. Descriptive statistical analysis (mean and SD) was employed to describe the characteristics of each variable. All statistic analyses were performed in the Statistica® package software, version 5.5 A (Stat Soft Inc.®, Tulsa, OK).
RESULTS Fatiguing exercises and the countermovement jump performance. Subjects were able to execute maximal countermovement jumps of 0.334 ⫾ 0.044 m (CMJ1), and their performance dropped to 70.9 ⫾ 4.0% (CMJ2 ⫽ 0.236 ⫾ 0.031 m) of the CMJ1 values after 30.6 ⫾ 6.9 continuous jumps. Kinematics and kinetics. The angular displacement and velocity of the ankle, knee, and hip joints in the nonfatigued (CMJ1) and in the fatigued (CMJ2) conditions are shown in Figure 2. Table 1 summarizes the comparisons between several kinematic and kinetic parameters between CMJ1 and CMJ2. The temporal characteristics of the movement presented in this section are relative to take-off, which was set as zero. So, the terms “later” and “earlier” mean closer to and further away from the TO instant, respectively. An increased CT was identified and indicates that movement initiation occurred earlier (10.3%) relative to take-off in the CMJ2 than in CMJ1 (P ⬍ 0.05). The analysis of the CT phases revealed that the NEG, TR, and POS phases were 9.6%, 11.3%, and 12.2% longer (P ⬍ 0.05) in CMJ2 than in CMJ1. Despite the longer CT duration in CMJ2, the duration of the NEG and POS phases was proportional to the increases in duration of the CT and did not differ (P ⬎ 0.05) between conditions. The knee angular displacement, measured at the IEX, was greater (7.6°; P ⬍ 0.05) in CMJ1 than in CMJ2, revealing that the subjects flexed their knee joints less when fatigued. Ankle and hip joint angular displacements remained relatively unchanged between conditions and indicated that http://www.acsm-msse.org
TABLE 1. Absolute and normalized characteristics of the countermovement jumps performed with (CMJ2) and without (CMJ1) fatigue. Absolute Data
CT duration (ms) NEG duration (ms) TR duration (ms) POS duration (ms) BMCstanding—BMCIEX (m) BMCtake-off—BMCstanding (m) Leg stiffness—NEG (N/BW/m) Knee stiffness—NEG (N䡠m/BW/deg*10⫺3) Ankle IEX joint angle (degrees) IEX time (ms) PAV—POS (deg䡠s⫺1) PAV time—POS (ms) Peak power—POS (W/BW) Time to peak power (ms) Knee IEX joint angle (degrees) IEX time (ms) PAV—POS (deg䡠s⫺1) PAV time—POS (ms) Peak power—POS (W/BW) Time to peak power (ms) Hip IEX joint angle (degrees) IEX time (ms) PAV—POS (deg䡠s⫺1) PAV time—POS (ms) Peak power—POS (W/BW) Time to peak power (ms) Delay between IEXHIP—IEXKNE (ms) Delay between IEXKNE—IEXANK (ms)
Time Normalized Data—% CT
CMJ1
CMJ2
Variation (%)
995 ⫾ 89 717 ⫾ 63 44 ⫾ 4 278 ⫾ 40 0.49 ⫾ 0.13 0.24 ⫾ 0.07 3.0 ⫾ 1.2 4.7 ⫾ 1.6
1098 ⫾ 61 786 ⫾ 64* 49 ⫾ 5 312 ⫾ 56* 0.39 ⫾ 0.14* 0.27 ⫾ 0.11 5.2 ⫾ 2.0* 8.2 ⫾ 3.0*
⫹10.3% ⫹9.6% ⫹11.3% ⫹12.2% ⫺20.4% ⫹12.5% ⫹73.3% ⫹74.4%
— 72.1 ⫾ 4.4 4.4 ⫾ 1.1 27.9 ⫾ 2.7 — — — —
— 71.6 ⫾ 4.1 4.5 ⫾ 1.2 28.4 ⫾ 3.3 — — — —
— 0.6% 2.2% 1.8% — — — —
94.1 ⫾ 7.0 271 ⫾ 54 584.4 ⫾ 91.6 80 ⫾ 18 1.87 ⫾ 0.7 90 ⫾ 16
97.7 ⫾ 7.6 288 ⫾ 69 452.6 ⫾ 86.0* 132 ⫾ 38* 1.36 ⫾ 0.4 140 ⫾ 33*
⫹3.8% ⫹6.2% ⫺22.5% ⫹65.0% ⫺27.2% ⫹46.6%
— 72.7 ⫾ 4.9 — 91.9 ⫾ 2.0 — 90.9 ⫾ 4.1
— 73.7 ⫾ 4.9 — 88.0 ⫾ 2.2 — 87.3 ⫾ 5.7
— ⫹1.3% — ⫺4.2% — ⫺3.9%
89.5 ⫾ 12.4 278 ⫾ 40 716.2 ⫾ 80.2 68 ⫾ 13 1.70 ⫾ 0.7 113 ⫾ 18
97.1 ⫾ 12.2* 312 ⫾ 56* 538.6 ⫾ 85.9* 120 ⫾ 37* 1.33 ⫾ 0.4* 140 ⫾ 28*
⫹8.5% ⫹11.8% ⫺24.8% ⫹76.4% ⫺21.7% ⫹23.8%
72.1 ⫾ 3.0 — 93.2 ⫾ 2.1 — 88.6 ⫾ 4.0
71.6 ⫾ 3.3 — 98.9 ⫾ 2.6 — 87.2 ⫾ 4.8
⫺0.6% — ⫹6.1% — ⫺1.5%
68.6 ⫾ 13.5 378 ⫾ 36 487.0 ⫾ 51.5 80 ⫾ 21 1.28 ⫾ 0.4 300 ⫾ 61 100 ⫾ 6 7 ⫾ 44
69.9 ⫾ 12.3 425 ⫾ 37* 401.1 ⫾ 45.8* 128 ⫾ 40* 1.13 ⫾ 0.6 260 ⫾ 70 114 ⫾ 6 23 ⫾ 54
⫹1.8% ⫹12.4% ⫺17.6% ⫹60.0% ⫺11.7% ⫹13.3% ⫹14.0% ⫹228.0%
— 62.0 ⫾ 6.1 — 91.9 ⫾ 2.1 — 69.8 ⫾ 6.9 10.1 ⫾ 3.0 0.6 ⫾ 2.4
— 61.2 ⫾ 2.2 — 88.3 ⫾ 2.2 — 76.3 ⫾ 7.1 10.4 ⫾ 2.6 2.1 ⫾ 3.3
— ⫹1.2% — ⫺3.9% — ⫹9.3% ⫹2.9% ⫹250.0%
CMJ1
CMJ2
Variation (%)
The percentage of variation is expressed in relation to the changes in the fatigued condition (CMJ2) in relation to the initial condition (CMJ1). CT, contact time; NEG, negative phase; POS, positive phase; BMC, body mass centre; IEX, initiation of the joint extension; IEX time, time to initiation of the joint extension; PAV, peak angular velocity; PAV time, time to peak angular velocity. * Denotes significant differences between experimental conditions (P ⬍ 0.05).
most changes in movement amplitude occurred at the knee joint level. The displacement of the body mass center during the NEG phase was greater (P ⬍ 0.05) in CMJ1 than in CMJ2, but did not differ (P ⬎ 0.05) at the TO instant. At the hip and knee joints, there was a tendency (P ⬍ 0.05) to initiate the POS phase earlier (12.1%) in CMJ2 in comparison with CMJ1. This tendency was also detected at the ankle joint, but the differences (6.2%) were not significant (P ⬎ 0.05). During the NEG phase, no differences (P ⬎ 0.05) in PAV magnitude or timing were detected at any joint level. In CMJ2, at the end of the POS phase, PAV was considerably reduced (P ⬍ 0.05) in all joints and also occurred earlier (a leftward phase shift) in relation to CMJ1 (see Fig. 2). Net peak power around the knee joint decreased (21.7%; P ⬍ 0.05) with fatigue. The same tendency was found around the ankle and hip joints, where the net peak power also decreased during the POS phase in CMJ2 (27.2%, 11.7%, respectively), but significant differences were not found (P ⬎ 0.05). The phase shift detected in the fatigued condition was not present in the POS phase of the movement (P ⬎ 0.05) when the data series were normalized with respect to CT duration. After normalizing the movement with respect to CT duration, the only difference (P ⬍ 0.05) that occurred during the NEG phase was detected at the knee and hip peak angular velocity timing, which occurred slightly later (5.4 and 14.6%, respectively) in CMJ2 in comparison with CMJ1. MULTI-SEGMENT COORDINATION: FATIGUE EFFECTS
The stiffness of the knee joint is shown in Figure 3 and suggests that the NEG phase of the movement was divided in two parts. During the first part, the knee joint net moments remained without large variations, whereas the knee joint was flexed similarly in both conditions. During the second part of the NEG phase, the net moments around the knee increased steeply, resulting in the greatest stiffness slope during this phase of the movement. This greater steepness found during the second part of the NEG phase indicated that greater (P ⬍ 0.05) knee stiffness occurred in CMJ2 in comparison with CMJ1. In CMJ2, this second part occurred when the knee joint was relatively less flexed (CMJ1 ⫽113.0° ⫾ 6.1°; CMJ2 ⫽ 125.2° ⫾ 8.0°) than in CMJ1, i.e., the knee joint stiffness increased earlier in CMJ2. The overall stiffness of the leg also showed greater (P ⬍ 0.05) values in CMJ2 than in CMJ1 during the second part of the NEG phase. A proximal-distal order was present in most jumps, in which IEXHIP consistently occurred approximately 100 ms before other joints, irrespective of the fatigue condition (CMJ1 ⫽ 100 ⫾ 6 ms; CMJ2 ⫽ 114 ⫾ 6 ms). The differences between IEXKNE and IEXANK were much smaller (CMJ1 ⫽ 7 ⫾ 44 ms; CMJ2 ⫽ 23 ⫾ 54 ms) and more variable than that observed between IEXHIP–IEXKNE. Indeed, a proximal-distal order between knee and ankle was not always found, and other joint reversal sequences were identified. In some cases, IEXANK and IEXKNE occurred simultaneously (CMJ1 ⫽ 0 cases; CMJ2 ⫽ 2 cases), and in Medicine & Science in Sports & Exercise姞
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FIGURE 2—Angular displacement and velocity of the ankle, knee, and hip joints before (CMJ1) and at the end (CMJ2) of fatigue. The vertical lines represent the movement and the push-off initiation during the fatigued (dotted lines, “POS”) and nonfatigued (solid lines, “PRE”) conditions. The take-off instant was set as zero and is also indicated (vertical dashed line).
other cases, IEXANK preceded IEXKNE (CMJ1 ⫽ 3 cases; CMJ2 ⫽ 4 cases). Electromyographic analysis. The electromyographic activation of the six muscles investigated in this study is presented in Figures 4 and 5, whereas Table 2 shows the relative amount of muscle activation between conditions. To provide a better temporal representation of the movement and to reduce the inherent intersubject variation, the magnitudes of the electromyographic patterns shown in Figures 4 and 5 are relative to the peak muscle activation of each muscle obtained in each experimental condition. The electromyographic analysis revealed that most muscles showed higher activation in the fatigued condition during the NEG and POS phases (P ⬍ 0.05), but these increases were much more pronounced during the latter movement phase. During the propulsive phase of the CMJ2 1162
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condition, increases in muscle activation of the knee extensor muscles (VL and RF) were similar to their respective antagonist pairs (GM and ST) and increased, on average, by 43.0% in relation to the muscle activation detected in CMJ1. GAS also showed greater (9.1%) muscle activation in CMJ2 than in CMJ1 during the PO phase. SOL activation did not differ (P ⬎ 0.05) between conditions. All muscles showed a significant earlier activation (94 ms, ranging from 66 to 125 ms) in CMJ2 during the POS phase. This earlier activation was not detected (P ⬎ 0.05) after normalizing the EMG signals in relation to CT duration, where the muscle activation onset between conditions did not vary more than 4.0% of the CT. When the relative duration of the CT (time-normalized data series) was taken into account, all muscles showed almost an identical temporal pattern between conditions, suggesting that a strong http://www.acsm-msse.org
TABLE 2. Average (⫾ SD) changes in muscle activation amplitude of six muscles assessed during the negative and positive phases at the end of a series of consecutive countermovement jumps. Variation (% in relation to CMJ1) Muscle
NEG (%)
POS (%)
SOL GAS VL RF ST GM
⫹1.3 ⫾ 1.8 ⫹5.6 ⫾ 2.2* ⫹22.3 ⫾ 7.3* ⫹26.4 ⫾ 8.1* ⫹22.5 ⫾ 3.1* ⫹23.7 ⫾ 2.7*
⫹2.1 ⫾ 1.8 ⫹9.1 ⫾ 3.4* ⫹42.6 ⫾ 7.2* ⫹45.5 ⫾ 8.1* ⫹43.6 ⫾ 3.9* ⫹42.3 ⫾ 2.6*
The variation in muscle activation is expressed in percentage and is relative to the nonfatigued condition (CMJ1); significant differences (P ⬍ 0.05) are marked (*).
muscle activation sequence occurred, irrespective of the fatigue state. In some cases, the similar muscle activation found between CMJ1 and CMJ2 resulted in superimposed signals, where ON and PK did not differ (P ⬎ 0.05).
DISCUSSION The present study was aimed at determining the effects of fatigue upon intersegmental coordination in maximal countermovement jumps. Setting aside disparities in absolute values, the kinematic, kinetic, and electromyographic profiles observed in the nonfatigued condition of healthy active subjects were quite comparable with those reported in the literature, where skilled jumpers performed maximal countermovement jumps with similar technique (7). Average maximal jump height was similar to other studies (e.g., 20). The results showed that the continuous maximal jumps reduced vertical jump performance to a level close to that stipulated as the critical jump height performance threshold (70%) set in this study. Although small intersubject variations occurred, the reductions imposed in the countermovement jump performance were considered as satisfactory for the purposes of this investigation. The smaller knee angular displacement observed in the fatigued condition in comparison with the nonfatigued condition confirms the arguments proposed by Hortoba´gyi et al. (20) that the longer duration of the movement is not related to increases in knee and hip joint amplitude. It was suggested that increases in movement length and performance decline would be an effect of a long period imposed between the end of the negative and the beginning of the positive phase. This was not supported in this study because the transient phase duration remained relatively unaltered between conditions and noticeable changes were only detected in the negative and positive phases of the movement. The increased length of the negative and positive phases and the similar length of the transient phase between conditions can be explained as follows. In the nonfatigued condition, immediately after initiating the negative phase of the movement, there is a short period in which the leg extensor muscles are passively stretched by the rotation of the joints, before being voluntarily recruited to decelerate the joints to slow down the downward displacement of the body center of mass and resist the pull of the gravitational forces. In the fatigued condition, the subjects also followed such a sequence, but they started to resist the first part of the MULTI-SEGMENT COORDINATION: FATIGUE EFFECTS
FIGURE 3—Leg stiffness (upper panel) and knee joint stiffness (lower panel) in the fatigued (CMJ2) and nonfatigued (CMJ1) conditions— subject “AR.” The negative (NEG), transient (TR), and positive (POS) phases are indicated. The initiation of the positive phase (IEX) and the take-off are indicated by the dashed lines, whereas the arrows show the movement progression direction. The center of mass was normalized with respect to standing position, which was set as zero.
descending phase of the movement slightly earlier, i.e., before the knee joints reached a deep excursion into a flexed position (Fig. 2). The knee joint stiffness traces in the fatigued condition suggests that the rigidity of the knee increased steeply when this joint was in a relatively more extended position than in the nonfatigued condition. If the subjects recruited their impaired muscles too late (i.e., when the knee was in a deeper position and the muscle tendon units were relatively more stretched), greater sarcomere “slipping” and myofibrillar disruption (23) would occur due to the great internal tension that is applied on a decreased number of cross-bridges that are recruited during eccentric contractions (24). Therefore, in the fatigued condition, the subjects stiffened the leg segments earlier to decelerate their joints more gradually than in the nonfatigued condition. This may be a strategy used to avoid muscle damage and improve the control of the movement in a situation where the subjects do not rely on the ability of their fatigued muscles to react promptly and control the descending phase. The use of a more extended knee angle at the end of the negative phase has been shown in other studies (15,19) and is generally interpreted as a strategy employed to sustain (or maximize) the performance under fatigue. It has been demonstrated that the efficiency of stretch-shortening cycle does not depend only on the magnitude (extension) of the stretch imposed during the negative phase but rather on the rate of Medicine & Science in Sports & Exercise姞
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FIGURE 4 —The electromyographic signals from soleus (SOL), gastrocnemius (GAS), and vastus lateralis (VL). The movement initiation, the initiation of the push-off phase, and the take-off instant in the fatigued (CMJ2) and nonfatigued (CMJ1) conditions are labeled. The muscle activation was normalized with respect to the maximal activation during the movement in each jump condition.
the stretch (35). Fast stretch allied with small movement amplitude is suggested as to increase muscle stiffness, which helps the subjects to build up large eccentric force at the end of the negative phase and tolerate greater stretch loads (22). By increasing the leg stiffness during the negative phase (see Fig. 3), the duration of the transient phase in the fatigued condition was held short in both exercising conditions, allowing for a short coupling time of the eccentric to the concentric phase. This can be interpreted as an attempt to enhance or sustain as high as possible the vertical jump performance during the subsequent phase of fatigued movements. Depressed actin-myosin cross-bridged formation (29) is frequently reported in exercises involving peripheral fatigue and is likely to have had an influence on the ability of the subjects to sustain maximal performance. Despite affecting both movement phases, the concentric phase has been reported as being much more affected by fatigue processes 1164
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(33). Thus, contractile mechanism impairment (29) is the likely argument to explain the longer duration of the positive phase and the drop in the magnitude of the peak joint angular velocity and peak joint power observed during the propulsive phase of the movement. The greater muscle activation detected during the positive phase of the movement may be a response of the neuromuscular system, which has to activate the fatigued muscle fibers more intensively (or even to recruit new motor unit pools) in an effort to maintain the maximum jump height. This can be a response of an autonomous regulative mechanism to counteract the neuromuscular functional diminution (36). Additional motor unit pool recruitment as well as firing synchronization may result in electrical action potential superposition, resulting in increased electromyographic activity (4). The differences between the greater activation of the GAS and similar activation of the SOL that emerged with http://www.acsm-msse.org
FIGURE 5—The electromyographic signals from rectus femoris (RF), semitendinosus (ST), and gluteus maximum (GM). The movement initiation, the initiation of the push-off phase, and the take-off instant in the fatigued (CMJ2) and nonfatigued (CMJ1) conditions are labeled. The muscle activation was normalized with respect to the maximal activation during the movement in each jump condition.
fatigue are in agreement with the findings of Moritani et al. (25). They support the idea of a selective fatigue process, where greater changes occur in the “fast” GAS than in the “slow” SOL in a task of continuous maximal hopping. The activation of the knee extensor (VL and RF) and knee flexor (ST) muscles increased with fatigue in both phases of the movement, but more pronounced activation was detected during the positive phase. Interestingly, and despite the greater stress supposedly imposed upon the knee extensor muscles, both muscle groups (extensors and flexors) showed an equivalent increase in muscle activation throughout the movement. The increased activation noticed during the propulsive phase can be explained by a proportional muscle activation that occurs when one component of the agonist-antagonist pair is raised (10). According to De Luca and Mambrito (11), simultaneous increases in muscle activation between the muscles with opposite functions are controlled by a central coactivation MULTI-SEGMENT COORDINATION: FATIGUE EFFECTS
mechanism, which is regulated by a “common drive.” According to this hypothesis, when an agonist-antagonist pair is participating in a task, the “common drive” (a movement pattern generator) controls the motoneuron pool of each muscle by a single input, treating both muscles as a single functional entity (26). Although the reasons for decline in the magnitude of the peak angular velocity and net power around the joints are relatively evident under fatigue, the causes for the change in the time of these peaks are not very clear. An explanation is possible using the hypothesis of a “common drive” modulating the muscle activation of muscle group counterparts. For instance, if it is assumed that under fatigue, the strength impairment experienced by the quadriceps group (viewed here as the main propellers of the movement) is much more pronounced than that suffered by the hamstrings, the hamstrings/quadriceps torque ratio would be increased in the fatigued condition. The difference in the forces produced Medicine & Science in Sports & Exercise姞
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by the relatively “preserved” hamstrings and the “exhausted” quadriceps (increased hamstrings/quadriceps torque ratio), coupled with a neural mechanism that activates both muscle groups simultaneously, would not only decrease the magnitude of the peaks but also induce these peaks to occur earlier in comparison to the nonfatigued condition. Future studies isolating fatigue upon different muscle groups (i.e., manipulating the hamstrings/quadriceps torque ratio) in countermovement jumps may constitute an attractive opportunity to test this hypothesis. The arguments proposed by Van Ingen Schenau et al. (30) that changes in muscle activation timing should be accomplished to avoid deterioration of the coordination pattern when the properties of the musculoskeletal system are changed (due to fatigue) were not confirmed. The shape of the normalized EMG traces revealed a quite comparable activation pattern between conditions, in which trade-offs between muscles did not occur. Only muscle activation amplitude was affected, whereas the temporal characteristics of the EMG traces remained relatively stable. This can explain the similarities found in the topological characteristics of the movement— used to describe the motion of the segments relative to each other—and the consistent and robust pattern employed in both jump conditions. The hypothesis of a “common drive” mediating the activation of agonist-antagonist muscle pairs is also an appealing argument to explain the well-timed muscle activation and the movement pattern consistency that has been reported in the literature (7,14). Van Zandwijk et al. (31) found similar results in their study, where maximal and submaximal jumps were performed. Interestingly, they also suggested that the central nervous system primarily modulates the muscle activation amplitude, whereas the recruitment timing is held relatively constant. It is well established that, in rapid ballistic movements, once the input is dispatched from the central command to the motoneurons, the motor unit discharge cannot be drastically modified by a new command or proprioceptive feedback (28). The maximal interval between joint reversals and the consistent muscle activation timing support the idea of subconscious control signals that affect the generation of optimal solutions (not necessarily high performances). The use of a “common drive” would simplify the problem of the large number of control signals that would have to be stored within the central nervous system. These predetermined set of commands and their weights, generated within specific circuits of the neural network (e.g., synaptic connections), can control movement execution. Simulation (8) and experimental (6) data have shown that the execution of explosive movements “relies heavily on preprogrammed muscle stimulation patterns”, indicating the existence of a pattern that is barely changed. The precise timing of muscle actions has been attributed to a preprogrammed neural input—acquired with practice (training), which is used as a template and guides the movement execution, regardless of the muscle force-generating properties. It was shown (8) that considerable increases in muscle strength (up to 20%) did not produce increases in jump 1166
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height while control (muscle stimulation) remained unchanged. Improvement in performance was only achieved when the neural input (stimulation) was reorganized (reoptimized) by allowing the subjects practice with their changed muscle properties (strengthened) in order to (re)establish an optimal control. According to Bobbert and Van Soest (8), solving the task by repeatedly practicing (training) the movement may help the subjects to reoptimize the neural input (stimulation) and consequently their performance achievement. This reoptimization may constitute a learning process in which the concomitant activation of agonist-antagonist muscle sets is reorganized (3) according to the force-generating properties that are changed (increased or decreased) along the training/ practice process. These findings reinforce the principle of training “specificity,” in which the adaptations and the effectiveness of a program of exercises that aim to improve a certain movement output are closely related to the characteristics (type of contraction, velocity, joint angle, etc.) of the training stimulus (27). The results of this study suggest that an “optimal” solution, leading to maximal countermovement jump performances, was not achieved. So, the subjects did not use a coordination strategy that would allow them to make use of the best available muscle strength.
CONCLUSIONS A proximal-distal sequence, in which hip joint extension initiation is followed by knee and/or ankle joint extension, was found. The hip joint reversal preceded the reversals of other joints, but knee and ankle reversals did not always follow the same sequence, e.g., a proximal-distal order. This was not susceptible to fatigue. Therefore, the hypothesis that, with fatigue, the subjects use different segment motion strategies and the proximal-distal order is altered into a more simultaneous sequence was not confirmed. Despite of the decline in jump height, the subjects appeared to use a robust pattern, as if they were guided by a fixed set of commands (neural input or stimulation signal control), which ensured consistent responses, irrespective of the force-generating properties of the muscular apparatus. This may explain the consistent pattern that has been reported in the literature when vertical jumps are performed under different circumstances. Assuming that surface electromyographic signals are closely related and represent the neural input, a unique solution (stimulation signal control) was offered to propel the center of mass maximally, i.e., as high as possible. It is obvious that the decline in the ability of the muscles to produce force was the major factor responsible for the decreases observed in jump height output. However, the early occurrence of the peak joint angular velocity may have contributed to jump height decrease and indicated that an “optimal” solution (high countermovement jump performance) was not found under fatigue. It is conspicuous that coordination plays an important role in maximal countermovement jump performance and must be considered as an essential part of training programs designed to increase the http://www.acsm-msse.org
height of the jump, irrespective of the skill and training level of the performer. The findings of this is study are in agreement with other experiments and support the arguments proposed by Bobbert and coworkers (6,8) that, when the characteristics of the movement used to develop muscle strength do not coincide with the functional requirements of the task, control is not optimal and consequently performance is not maximal, unless accompanied with periods of specific practice of the movement. The hypothesis of a “common drive” is an attractive explanation for such movement pattern stability, but further experimental investigation manipulating the hamstrings/quad-
riceps torque ratio is necessary in order to confirm whether the central nervous system uses template motor programs as a strategy to reduce the complexity of multi-segment movements control, irrespective of the muscle properties. This project was supported by Grant from CAPES (Brazilian Ministry of Education and Sport). The authors are grateful to Mr. Graham Clark for his help during the data collection, Tom McKee for the technical support, and Dr. Vassilios Baltzopoulos and Mr. Calvin Morris for their helpful comments in this article. Address for correspondence: Andre Luiz Felix Rodacki, The Manchester Metropolitan University, Department of Exercise and Sport Sciences, Hassal Road, Alsager, Staffordshire, UK, ST7 2HL; E-mail:
[email protected].
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