Energetics and mechanics of terrestrial locomotion. IV. Total mechanical energy changes as a function of speed and body size in birds and mammals.

This is the third in a series of four papers examining the link between the energetics and mechanics of terrestrial locomotion. It reports measurements of the mechanical work required (ECM, tot) to lift and reaccelerate an animal's centre of mass within each step as a function of speed and body size during level, constant average speed locomotion. A force platform was used in this study to measure ECM, tot for small bipeds, quadrupeds and hoppers. We have already published similar data from large animals. The total power required to lift and reaccelerate the centre of mass (ECM, tot) increased nearly linearly with speed for all the animals. Expressed in mass-specific terms, it was independent of body size and could be expressed by a simple equation: ECM, tot/Mb = 0.685 vg + 0.072 where ECM, tot/Mb has the units of W kg-1 and vg is speed in m s-1. Walking involves the same pendulum-like mechanism in small animals as has been described in humans and large animals. Also, running, trotting and hopping produce similar curves of ECM, tot as a function of time during a stride for both the small and large animals. Galloping, however, appears to be different in small and large animals. In small animals the front legs are used mainly for braking, while the back legs are used to reaccelerate the centre of mass within a stride. In large animals the front and hind legs serve to both brake and reaccelerate the animal; this difference in mechanics is significant in that it does not allow the utilization of elastic energy in the legs of small animals, but does in the legs of large animals.

Heglund, N.C., Fedak, M.A., Taylor, C.R., & Cavagna, G.A. (1982). Energetics and mechanics of terrestrial locomotion: IV. Total mechanical energy changes as a function of speed and body size in birds and mammals. Journal of Experimental Biology, 97,5746. Ingen Schenau, G.J. van, Bobbert, M.F., & Haan, A. de. (1997). Does elastic energy enhance work and efficiency in the stretch-shortening cycle? Journal of Applied Biomechanics, 13,389-415. Kushmerick, M.J., & Paul, R.J. (1976). Relationship between initial chemical reactions and oxidative recovery metabolism for single isometric contractions of frog sartorius at 0 degrees C. Journal of Physiology, 254,711-727. K r w R., &Taylor, C.R. (1990). The cost of generating force: A new perspective. Nature, 346,265-267. Marsh, R.L., & Olson, J.M. (1994). Power output of scallop adductor muscle during contractions replicating the in vivo mechanical cycle. Journal of Experimental Biology, 193, 139-156. Rall, R.J. (1985). Energetic aspects of skeletal muscle contraction: Implication of fiber types. Exercise and Sport Sciences Reviews, 13,33-74. Roberts, T.J., Marsh, R.L., Weyand, P.G., &Taylor, C.R. (1997). Muscular force in running turkeys: The economy of minimizing work. Science, 275,1113-1 115.

Pilates: Release or recruit?

Cyclists frequently use a non-seated posture when accelerating, climbing steep hills, and sprinting, yet the biomechanical difference between seated and non-seated cycling remains unclear. The purpose of our first study was to test the effects of posture (seated and non-seated) and cadence (70 rpm and 120 rpm) on lower-limb joint power distribution, effective mechanical advantage, and muscle activity during very high power output cycling. Fifteen subjects rode on an instrumented ergometer at 50% of their individualised instantaneous maximal power (10.7±2.0 W/kg; above the reported threshold for seated to non-seated transition) in different postures (seated and non-seated) and at different cadences (70 rpm and 120 rpm), whilst lower-limb muscle activity, full-body motion capture, and crank radial and tangential forces were recorded. A scaled, full-body musculoskeletal model was used to solve inverse kinematics and inverse dynamics to determine joint displacements and net joint moments. Statistical comparisons were made using repeated measure, two-way analyses of variance (posture–cadence). Our results showed significant main effects of posture and cadence on the distribution of lower-limb joint power. A key finding was that the non-seated posture increased negative power at the knee, with an associated significant decrease of net power at the knee. The contribution of knee power decreased by 15% at both 70 and 120 rpm (~0.8 W/kg) when non-seated compared with seated. Subsequently, hip power and ankle power contributions were significantly higher when non-seated compared with seated at both cadences. In both postures, knee power was 9% lower at 120 rpm compared with 70 rpm (~0.4 W/kg). These results evidenced that the contribution of knee joint power to leg power was reduced by switching from a seated to non-seated posture during very high power output cycling; however, the size of the reduction is cadence dependent.Previous research and field observations also suggest that, when riding off the saddle, a rider's centre of mass (CoM) goes through a rhythmic vertical oscillation during each crank cycle. Just like in walking and running, the pattern of CoM movement may have a significant impact on the mechanical power that needs to be generated and dissipated by muscle. To date, neither CoM movement strategies during non-seated cycling, nor the limb mechanics that allow this phenomenon to occur have been quantified. In our second study we measured vertical displacement of the body's CoM and the associated changes in total mechanical energy during non-seated cycling at various combinations of power output (10%, 30%, and 50% of instantaneous maximal power output (Pmax.i) and cadence (70 rpm and 120 rpm). Our analysis revealed that cyclists increased vertical CoM motion at higher power outputs but raised and lowered their CoM during the same phases of the crank cycle under all conditions. This phasing of vertical CoM motion appears to be a movement strategy to facilitate an exchange of mechanical energy to the crank; theoretically at rates as high as 18% of peak crank power. These findings suggest that cyclists can utilise vertical motion of their CoM to reduce the contribution of the muscles to overall mechanical power output requirements.When riding off the saddle during climbing and sprinting, cyclists appear to coordinate the rhythmic, vertical oscillations of their CoM with the side-to-side lean of the bicycle. In our third study we investigated the idea that the coupling of CoM movement and bicycle lean could be a strategy to more effectively generate crank power. A combined kinematic and kinetic approach was used to understand how different constraints on bicycle lean influence CoM movement and limb mechanics during non-seated cycling on rollers. Thirteen participants cycled in a non-seated posture at a power output of 5 W/kg and a cadence of 70 rpm under three conditions: unconstrained lean on rollers, under instruction to self-restrict bicycle lean on rollers, and constrained lean in a bicycle trainer. Our results showed that riders generated higher peak crank forces and their CoM underwent greater fluctuations in total mechanical energy when leaning the bicycle a preferred amount compared to when self-restricting lean. The resultant crank force vector was also more closely aligned to the hip and knee joint when leaning the bicycle meaning that greater peak forces were produced using similar net joint moments and EMG activity within the lower limb. We interpret these findings to suggest that leaning the bicycle during non-seated cycling when no lateral support is provided allows a greater non-muscular contribution to crank force and power.In summary, these investigations have established a fundamental but new understanding of the underlying mechanics and energetics of the phenomenon of non-seated cycling, while also pointing towards the potentially detrimental influence of self-restricting bicycle lean when cycling in a non-seated posture at high-power outputs. These findings should be of interest to the fields of biomechanics, exercise physiology, and motor control, as well as those involved with optimising rider and bicycle performance.

To date, neither the CoM movement strategies during nonseated cycling nor the limb mechanics that allow this phenomenon to occur have been quantified. Here we estimate how much power can be contributed by a rider's CoM at each instant during the crank cycle by combining a kinematic and kinetic approach to measure CoM movement and joint powers of 15 participants riding in a nonseated posture at three individualized power outputs (10%, 30%, and 50% of peak maximal power) and two different cadences (70 and 120 rpm). The peak-to-peak amplitude of vertical CoM displacement increased significantly with power output and with decreasing cadence. Accordingly, the greatest peak-to-peak amplitude of CoM displacement (0.06 ± 0.01 m) and change in total mechanical energy (0.54 ± 0.12 J·kg) occurred under the combination of high-power output and low cadence. At the same combination of high-power output and low cadence, we found that the peak rate of CoM energy loss (3.87 ± 0.93 W·kg) was equal to 18% of the peak crank power. Consequently, it appears that for a given power output, changes in CoM energy contribute to peak instantaneous power output at the crank, thus reducing the required muscular contribution. These findings suggest that the rise and fall of a rider's CoM acts as a mechanical amplifier during nonseated cycling, which has important implications for both rider and bicycle performance.

About eccentric exercise

Maturation of Fast and Slow Motor Units during Synapse Elimination in the Rabbit Soleus Muscle

Amyotrophic lateral sclerosis (ALS) is characterized by selective and progressive degeneration of motoneurons (MNs). Although the etiology of the disease is unknown, glutamate toxicity and reactive oxygen species toxicity have been strongly implicated in ALS pathophysiology, Training exercise has been proposed to provide a beneficial therapy during the early or late stages of ALS; however, some studies showed deleterious effects of exercise on survival in ALS.

The storage and recovery of elastic strain energy in muscles and tendons increases the economy of locomotion in running vertebrates. In this investigation, we compared the negative and positive external work produced at individual limb joints of running dogs to evaluate which muscle-tendon systems contribute to elastic storage and to determine the extent to which the external work of locomotion is produced by muscles that shorten actively rather than by muscles that function as springs. We found that the negative and positive external work of the extensor muscles is not allocated equally among the different joints and limbs. During both trotting and galloping, the vast majority of the negative work was produced by the two distal joints, the wrist and ankle. The forelimb produced most of the negative work in both the trot and the gallop. The hindlimb produced most of the positive work during galloping, but not during trotting. With regards to elastic storage, our results indicate that the forelimb of dogs displays a greater potential for storage and recovery of elastic energy than does the hindlimb. Elastic storage appears to be more important during trotting than during galloping, and elastic storage appears to be more pronounced in the extensor muscles of the distal joints than in the extensor muscles of the proximal joints. Furthermore, our analysis indicates that a significant portion of the external work of locomotion, 26 % during trotting and 56 % during galloping, is produced by actively shortening muscles. We conclude that, although elastic storage of energy is extremely important to the economy of running gaits, actively shortening muscles do make an important contribution to the work of locomotion.

POINT-COUNTERPOINTRebuttal from FarinaPublished Online:01 Nov 2008https://doi.org/10.1152/japplphysiol.90598.2008cMoreSectionsPDF (36 KB)Download PDF ToolsExport citationAdd to favoritesGet permissionsTrack citations ShareShare onFacebookTwitterLinkedInEmailWeChat Although von Tscharner and Nigg (8) focus on the time-frequency analysis of the surface EMG and the results obtained in a number of experimental studies (e.g., Refs. 6, 7), their point of view illustrates the general issues that I outlined in my Counterpoint (1). A fundamental confusion is apparent in one of the opening statements of my colleagues: “A refined subdivision of fibers was proposed correlating fiber types with EMG spectral properties” (8). According to this statement, slow and fast fibers are defined as fibers with surface action potentials with relative energy mainly at low and high frequencies, respectively, and this definition is considered more appropriate (“refined”) than the schemes based on histochemistry (type I and II) and physiology (slow and fast twitch). Surface EMG spectral properties are thus used to directly define, rather than indirectly identify, muscle fiber types, which is the central issue in this debate. Consistent with this perspective, the main evidence that my colleagues present to illustrate their Point (8) consists in the wavelet transform of surface EMG signals recorded during running. They associate high (low) frequencies in the surface EMG to recruitment of fast (slow) motor units, although they do not provide a direct measure or a theoretical rationale to prove this association when a histochemical or physiological definition of fiber type is used.In response to the unequivocal experimental evidence of inconsistency of surface EMG spectral properties with motor unit recruitment strategies in simple cases when these strategies are predictable (e.g., 2, 3, 10), my colleagues reply that when studying “single-task experiments such as isometric ramped increase in force…substantial changes in the power spectra should not be expected.” However, surprisingly, they support their own interpretations with results reported for this type of contraction (4, 5, 9). While my colleagues consider the lack of consistency of the association between EMG spectral analysis and recruitment strategies irrelevant because it comes from “single-task experiments”), the occasional observation of this association during the same type of “single-ask experiments” is used as the basis for a “refined subdivision” of fiber types.The assertion by von Tscharner and Nigg (8) that surface EMG spectral properties provide information about recruitment strategies and fiber-type proportions is based on distinguishing between surface motor unit action potentials and not on the physiological properties of the motor units.REFERENCES1 Farina D. Counterpoint: Spectral properties of the surface EMG do not provide information about motor unit recruitment and muscle fiber type. J Appl Physiol; doi:10.1152/japplphysiol.90598.2008a.Link | ISI | Google Scholar2 Gabriel DA, Kamen G. Experimental and modeling investigation of spectral compression of biceps brachii SEMG activity with increasing force levels. J Electromyogr Kinesiol. 2007 Dec 11. [Epub ahead of print].Google Scholar3 Gerdle B, Karlsson S, Crenshaw AG, Fridén J. The relationships between EMG and muscle morphology throughout sustained static knee extension at two submaximal force levels. Acta Physiol Scand 160: 341–351, 1997.Crossref | PubMed | Google Scholar4 Karlsson S, Gerdle B. Mean frequency and signal amplitude of the surface EMG of the quadriceps muscles increase with increasing torque—a study using the continuous wavelet transform. J Electromyogr Kinesiol 11: 131–140, 2001.Crossref | ISI | Google Scholar5 Solomonow M, Baten C, Smit J, Baratta R, Hermens H, D'Ambrosia R, Shoji H. Electromyogram power spectra frequencies associated with motor unit recruitment strategies. J Appl Physiol 68: 1177–1185, 1990.Link | ISI | Google Scholar6 von Tscharner V, Goepfert B. Estimation of the interplay between groups of fast and slow muscle fibers of the tibialis anterior and gastrocnemius muscle while running. J Electromyogr Kinesiol 16: 188–197, 2006.Crossref | ISI | Google Scholar7 von Tscharner V, Goepfert B, Nigg BM. Changes in EMG signals for the muscle tibialis anterior while running barefoot or with shoes resolved by non-linearly scaled wavelets. J Biomech 36: 1169–1176, 2003.Crossref | ISI | Google Scholar8 von Tscharner V, Nigg BM. Point: Spectral properties of the surface EMG provide information about motor unit recruitment and muscle fiber type. J Appl Physiol; doi:10.1152/japplphysiol.90598.2008.Link | ISI | Google Scholar9 Wakeling JM, Syme DA. Wave properties of action potentials from fast and slow motor units of rats. Muscle Nerve 26: 659–668, 2002.Crossref | PubMed | ISI | Google Scholar10 Westbury JR, Shaughnessy TG. Associations between spectral representation of the surface electromyogram and fiber type distribution and size in human masseter muscle. Electromyogr Clin Neurophysiol 27: 427–435, 1987.Google Scholar Download PDF Previous Back to Top Next FiguresReferencesRelatedInformation More from this issue > Volume 105Issue 5November 2008Pages 1675-1675 Copyright & PermissionsCopyright © 2008 the American Physiological Societyhttps://doi.org/10.1152/japplphysiol.90598.2008cHistory Published online 1 November 2008 Published in print 1 November 2008 Metrics

This is the second paper in a series examining the link between energetics and mechanics of terrestrial locomotion. In this paper, the changes in the kinetic energy of the limbs and body relative to the centre of mass of an animal (EKE, tot) are measured as functions of speed and body size. High-speed films (light or X-ray) of four species of quadrupeds and four species of bipeds running on a treadmill were analysed to determine EKE, tot. A mass-specific power term, EKE, tot/Mb was calculated by adding all of the increments in EKE during an integral number of strides and dividing by the time interval for the strides and body mass. The equations relating EKE, tot/Mb and speed were similar for all bipeds and quadrupeds regardless of size. One general equation for the rate at which muscle and tendons must supply energy to accelerate the limbs and body relative to the centre of mass seems to apply for all of the animals: E'KE, tot/Mb = 0.478 vg1.53 where E'KE, tot/Mb has the units W kg-1 and vg is ground speed in m s-1. Therefore, E'KE, tot/Mb does not change in parallel with the mass-specific rate at which animals consume energy (Emetab/Mb), either as a function of speed or as a function of body size.

Axially moving materials can represent many engineering devices such as power transmission belts, elevator cables, plastic films, magnetic tapes, paper sheets, textile fibers, band saws, aerial cable tramways, and crane hoist cables @1–3#. Energetics of axially moving materials is of considerable interest in the study of axially moving materials. The total mechanical energy associated with axially moving materials is not constant when the materials travel between two supports. It is a fundamental feature of free transverse vibration of axially moving materials, while the total energy is constant for an undamped non-translating string or beam. Chubachi @4# first discussed periodicity of the energy transfer in an axially moving string. Miranker @5# analyzed energetics of an axially moving string, and derived an expression for the time rate of change of the string energy. Barakat @6# considered the energetics of an axially moving beam and found that energy flux through the supports can invalidate the linear theories of both the axially moving string and beam at sufficiently high transporting speed. Tabarrok, Leech and Kim @7# showed that the total energy of a travelling beam without tension is periodic in time. Wickert and Mote @8# pointed out that Miranker’s expression represents the local rate of change only because it neglected the energy flux at the supports, and they presented the temporal variation of the total energy related to the local rate of change through the application of the onedimensional transport theorem. They also calculated the temporal variation of energy associated with modes of moving strings and beams. Renshaw @9# examined the change of the total mechanical energy of two prototypical winching problems, which provided strikingly different examples of energy flux at a fixed orifice of an axially moving system. Lee and Mote @10,11# presented a generalized treatment of energetics of translating continua, including axially moving strings and beams. They considered the case that there were nonconservative forces acting on two boundaries. Renshaw, Rahn, Wickert and Mote @12# examined the energy of axially moving strings and beams from both Lagrangian and Eulerian views. Their studies indicated that Lagrangian and Eulerian energy functionals are not conserved for axially moving continua. Zhu and Ni @13# investigated energetics of axially moving strings and beams with arbitrarily varying lengths. Although both the Eulerian and Lagrangian functionals for the total mechanical energy of axially moving materials are generally not constant, there do exist alternative functionals that are con-

During tetanic contractions of fast motor units (MUs), an early increase in force (boost) is followed by a slight decline to a plateau (sag). This boost is present at the onset of activity but disappears during rhythmically repeated contractions at short intervals; however, it may be restituted after a period of rest. Nevertheless, background of the boost, especially the minimum time required to restore this effect is unknown, and the present study aimed to address this gap. The functional isolation of a single MU was achieved by splitting the L5 or L4 ventral roots into thin filaments, which were electrically stimulated with rectangular electrical pulses. We recorded series of three 504 ms tetanic contractions (triplets) evoked at 35 Hz repeated once per second, with the boost visible in the first tetanus. The triplets were evoked at progressively shorter time intervals, ranging from 90 to 2 s. The boost in successive triplets reduced when the intervals became critically short. The reduction of boost was estimated by the decrease in sag amplitude following the peak force associated with the boost. In fast fatigue-resistant MUs, the sag amplitude decreased by 25% at an average interval of 29.80 s and by 50% at an interval of 16.84 s. For fast fatigable MUs, the interval required to restitute the studied effect was longer: a 25% reduction in sag corresponded to an interval of 82.29 s, and a 50% reduction corresponded to 54.07 s. The results suggest that the physiological basis for the restitution of initial force (boost) is the kinetics of muscle energy status recovery following initial exercise.

PURPOSE: The purpose of this study was to examine the relationship between changes in total mechanical energy (ME) and oxygen consumption during treadmill running in the severe intensity domain. METHODS: Seven subjects (3 males, 4 females) volunteered for this study (mean age ±SD = 25.4 ± 2.5 yrs; mass = 66.6 ±7.0 kg). After a separate familiarization session, subjects performed an incremental treadmill test to exhaustion (1% grade, speed increment = 0.5 mph per minute) from which the ventilatory threshold, respiratory compensation threshold, and peak VO2 were determined. On a subsequent day, subjects performed a constant speed treadmill run at a speed above the respiratory compensation threshold but below the speed at VO2 peak. During this run, gas exchange data was continuously recorded. In addition, 3-D kinematic data was captured over a 10 second epoch every 30 seconds using an 8-camera Motion Analysis system at 120 Hz. The total ME was calculated using the no transfer approach for a 13 segment anthropometric model. The total ME was calculated for each epoch was normalized to J/kg/m. After removing the first minute of the run data, both VO2 and ME were regressed against time within each subject. The slopes of the individual regressions were analyzed by constructing 95% confidence intervals around the mean slopes. In addition, the correlation between the VO2 and ME slopes was calculated. RESULTS: The mean ME slope was .0093 + 0.04 J/kg/m per min (95% CI = −0.26 − 0.045) and the mean VO2 slope was 74.3 + 94.8 mlO2 per min (95% CI = −13.4 - 161.9). The correlation between the ME and VO2 slopes was negative (r=−0.75, p =0.03), although was likely driven by the leverage associated with one subject with both the largest VO2 slope and the most negative ME slope. CONCLUSIONS: The results do not support the hypothesis that increases in oxygen consumption during severe intensity running at a constant speed are driven by changes in total mechanical energy.

The storage and recovery of elastic energy in muscle-tendon springs is important in running, hopping, trotting, and galloping. We hypothesized that animals select the stride frequency at which they behave most like simple spring-mass systems. If higher or lower frequencies are used, they will not behave like simple spring-mass systems, and the storage and recovery of elastic energy will be reduced. We tested the hypothesis by having humans hop forward on a treadmill over a range of speeds and hop in place over a range of frequencies. The body was modeled as a simple spring-mass system, and the properties of the spring were measured by use of a force platform. Our subjects used nearly the same frequency (the "preferred frequency," 2.2 hops/s) when they hopped forward on a treadmill and when they hopped in place. At this frequency, the body behaved like a simple spring-mass system. Contrary to our predictions, it also behaved like a simple spring-mass system when the subjects hopped at higher frequencies, up to the maximum they could achieve. However, at the higher frequencies, the time available to apply force to the ground (the ground contact time) was shorter, perhaps resulting in a higher cost of generating muscular force. At frequencies below the preferred frequency, as predicted by the hypothesis, the body did not behave in a springlike manner, and it appeared likely that the storage and recovery of elastic energy was reduced. The combination of springlike behavior and a long ground contact time at the preferred frequency should minimize the cost of generating muscular force.