Control of maximal and submaximal vertical jumps
Summary (3 min read)
Introduction
- Human subjects are able to execute most motor tasksat different levels of performance.
- Providing control signals for submaximal performance of a task is, however, more difficult for a number of reasons.
- Once a certain rule is provided to adjust parameters within the generalized motor program, this program can be used to provide control signals for both maximal performance of a task and all levels of submaximal performance.
- Secondly, differences in control signals between maximal and submaximal squat jumping will be analyzed to see whether control signals for these two levels of performance are related.
Protocol
- Each subject performed maximal and submaximal jumps from the same static squatting position.
- The angles of both boards and the height of the hinge were set to match hip and knee segment angles and height of the hip joint as closely as possible.
- Before all subsequent jumps, subjects adjusted their initial position to the device to match the initial position of the first jump as accurately as possible.
- Subjects were instructed to jump to such a height, that they could just see the lightsource.
- After some practice jumps, each subject performed three maximal height jumps from which averaged maximal jump height was calculated.
Kinematics and Kinetics
- Calcaneus, lateral malleolus, knee joint (on the lateral collateral ligament at the height of the joint cleft), greater trochanter, and neck (at the height of the fifth cervical vertebra).
- These markers defined the 478 Official Journal of the American College of Sports Medicine http://www.msse.org position of the four body segments: feet, lower legs, upper legs, and head-arms-trunk (HAT).
- During jumping kinematic data were obtained using high speed video (VICON, Oxford Metrics Ltd.) at a sample rate of 100 Hz.
- Simultaneously, vertical and fore-aft components of the ground reaction force and its point of application were measured using a force platform (Kistler 9281B, Kistler Instruments Corp., Amherst, NY) and sampled at 200 Hz.
Electromyography
- Electromyographic signals (EMG signals) of eight muscles of one leg were recorded during the execution of the jumps using pairs of surface electrodes (Meditrace ECE 1801) after standard skin preparation techniques (2).
- The muscles selected were lateral and medial head of m. gastrocnemius, m. soleus, m. semitendinosus, long head of m. biceps femoris, m. vastus lateralis, m. rectus femoris, and m. gluteus maximus.
- The electrical signals of the muscles were amplified (Disa 15 C01, Disa Electronics, Skovlunde Denmark) and 7-Hz high-pass filtered to eliminate movement artifacts.
- Subsequently the electrical signals were rectified, 22-Hz low-pass filtered and sampled at 200 Hz, yielding smoothed rectified EMG signals (SREMG signals).
Treatment of Data
- For each subject, the three highest maximal jumps and the three lowest submaximal jumps were selected for further analysis.
- Kinematic and kinetic variables of different jumps were synchronized at the instant the subject left the ground (subsequently referred to as toe-off) and truncated to contain only the last 750 ms of the push-off phase before averaging.
- The SREMG recordings were synchronized the same way and additionally for each trial baseline activity (i.e., activity of the muscles before the jump was executed) was subtracted before averaging.
Electromyographic Data Analysis
- Differences in control signals to the muscles between maximal and submaximal jumps may consist of a combination of (i) a change in amplitude of control signals to the muscles, (ii) a change in shape of control signals to the muscles, and (iii) a change in relative timing of control signals to the muscles.
- Subsequently, for each muscle these ratios were averaged across subjects and it was tested whether the averaged ratio differed significantly from 1.0 using a Student t-test for paired comparisons at a level of significance of 5%.
- To quantify the difference in shape of the control signals to the muscles in maximal and submaximal jumping principal component analysis (PCA) was performed on averaged maximal and submaximal SREMG histories for each muscle (see also: 3,4).
- The onset of activity was taken as the instant of first sustained rise of the SREMG above the baseline.
Computer Simulations Using a Model of the Human Musculoskeletal System
- Computer simulations of the push-off phase of a vertical squat jump were performed using a model of the human musculoskeletal system which has already been described in detail elsewhere (e.g., 1,11).
- For the human calf muscles, parameter values for both the excitation and contraction dynamics are available which have been determined on the basis of experimental data obtained from these muscles (14).
- Among the output of the model is movement of the body segments.
- The effect of stimulation dynamics was incorporated into the model by letting control signals to all muscles rise at a finite rate to their final values.
- This reduced the control problem of vertical jumping to finding that combination of six muscle stimulation onset times which yielded the highest performance in terms of jump height.
Experimental Data
- The focus will be on the data of the vertical ground reaction force and SREMG recordings, since the former directly relates to the movement of the CM of the body and thus to performance and the latter is a measure for control signals to the muscles.
- It is encouraging that kinetic data show similar differences between maximal and submaximal jumps (i.e., less steep rise of the vertical component of the ground reaction force in case of submaximal jumping) for the majority of the subjects.
- Differences in SREMG amplitude were quantified by computing for each muscle the ratio of the time integrals of the SREMG histories in submaximal and maximal jumping.
- Figure 6 shows for each muscle the fraction of variance explained by the first principal component.
- There appears to be a tendency for the more proximal muscles to have their onset times earlier in the movement and for the distal muscles to have their onset times later on in case of submaximal jumping, which is consistent with the fact that the submaximal jump has a longer push-off phase.
Computer Simulations
- To investigate whether the changes in control signals pertaining to a maximal jump as derived in the previous section from analysis of SREMG histories are sufficient to obtain submaximal performance, computer simulations of the push-off phase in vertical squat jumping were performed.
- Secondly, onset times of m. gluteus maximus and hamstrings were shifted to instants earlier in the push-off and that of m. soleus to instants later in the push-off.
- This is due to the fact that in the model used for excitation dynamics (5), the equilibrium level of active state (the scaling factor for maximal force) is already 95% of its maximum at stimulation levels of the order of 0.4.
- Interestingly enough, the two key features observed in the experimental data are more or less reproduced in the model calculations.
- Both the amplitude reduction of control signals to the biarticular muscles and the shift in onset times contributed to this increased duration of the push-off in case of submaximal jumping.
DISCUSSION
- The authors set out to determine in the first place whether different subjects performed submaximal squat jumps of predefined height in a similar way.
- Only its results, the fact that muscle control signals in case of submaximal vertical squat jumping can be related to those of maximal vertical squat jumping by means of amplitude reduction and temporal shifting, are known.
- Differences remain between the simulated and experimental results.
- Especially, it is unknown whether excitation and contraction dynamics vary strongly from one muscle group to another.
- Qualitatively, however, the correspondence between the two is encouraging.
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Citations
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Cites background from "Control of maximal and submaximal v..."
...Yet, the majority of movements made by organisms are not maximal effort movements (Irschick and Losos, 1998), making it of paramount importance to understand how sub-maximal movements are controlled (Van Zandwijk et al., 2000; Vanrenterghem et al., 2004)....
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20 citations
Cites background from "Control of maximal and submaximal v..."
...Vertical jumping belongs to the class of explosive movements and involves a large number of joints such as the ankle, knee and hip [9, 13]....
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...DISCUSSION A large number of studies have paid attention to the biomechanical and neuro-physiological variables involved in vertical jumps [9, 12, 13, 14] and their influences on jumping....
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...Electrical output of a muscle is closely related to the neural control signal to the muscles [12, 13]....
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References
4,316 citations
"Control of maximal and submaximal v..." refers background in this paper
...An elegant alternative which circumvents the storage and novelty problem is based on the concept of generalized motor programs (9)....
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1,237 citations
"Control of maximal and submaximal v..." refers methods in this paper
...Electromyographic signals (EMG signals) of eight muscles of one leg were recorded during the execution of the jumps using pairs of surface electrodes (Meditrace ECE 1801) after standard skin preparation techniques (2)....
[...]
351 citations
114 citations
"Control of maximal and submaximal v..." refers background or result in this paper
...Since the fractions of explained variance by the first PC found in this study are somewhat higher than those reported in (3), it seems likely that for each muscle a single waveform is involved in the control of vertical jumping....
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...Flanders (3) reported for pointing movements that the first PC often accounted for over 80% of the variance of a set of EMG traces for each muscle....
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Frequently Asked Questions (8)
Q2. What is the role of the neural control signals in the control of movement?
Besides excitation and contraction dynamics, the dynamics of neural control signals can be a functional factor in the control of movement.
Q3. What was the subject's instruction during the jumps?
The subject was instructed keep his arms crossed behind his back during execution of the jumps, to jump without making preparatory countermovement and to initiate the jump as soon as possible after a beep signal.
Q4. What purpose was the study used to help the subject reproduce the same initial position each time?
To help the subject reproduce the same initial position each time a device was used which consists of two boards fixed to a pole in a hinge.
Q5. What are the differences in control signals to the muscles between maximal and submaximal jumps?
Differences in control signals to the muscles between maximal and submaximal jumps may consist of a combination of (i) a change in amplitude of control signals to the muscles, (ii) a change in shape of control signals to the muscles, and (iii) a change in relative timing of control signals to the muscles.
Q6. What is the role of the biarticular muscles in the coordination of multijoint movements?
a special role is attributed to biarticular muscles in the coordination of multijoint movements since they link the movements in different joints together (see e.g., 7).
Q7. Why is the amplitude of the control signals in the model used for excitation dynamics so?
This is due to the fact that in the model used for excitation dynamics (5), the equilibrium level of active state (the scaling factor for maximal force) is already 95% of its maximum at stimulation levels of the order of 0.4.
Q8. What was the difference in amplitude of the control signals to the muscles?
Before PCA, mean values were subtracted from the SREMG histories, and since in this part of the analysis the authors are only interested in differences in shape of control signals to the muscles and not in differences in amplitude, maximal and submaximal SREMG histories were normalized to unit variance.