Effects of Synchronizing Foot Strike and Cardiac Phase on Exercise Hemodynamics in Patients With Cardiac Resynchronization Therapy: A Within-Subjects Pilot Study to Fine-Tune Cardio-Locomotor Coupling for Heart Failure.

BACKGROUND: Despite advances in medical and cardiac resynchronization therapy (CRT), individuals with chronic congestive heart failure (CHF) have persistent symptoms, including exercise intolerance. Optimizing cardio-locomotor coupling may increase stroke volume and skeletal muscle perfusion as previously shown in healthy runners. Therefore, we tested the hypothesis that exercise stroke volume and cardiac output would be higher during fixed-paced walking when steps were synchronized with the diastolic compared with systolic portion of the cardiac cycle in patients with CHF and CRT. METHODS: Ten participants (58±17 years of age; 40% female) with CHF and previously implanted CRT pacemakers completed 5-minute bouts of walking on a treadmill (range, 1.5-3 mph). Participants were randomly assigned to first walking to an auditory tone to synchronize their foot strike to either the systolic (0% or 100±15% of the R-R interval) or diastolic phase (45±15% of the R-R interval) of their cardiac cycle and underwent assessments of oxygen uptake (V̇o2; indirect calorimetry) and cardiac output (acetylene rebreathing). Data were compared through paired-samples t tests. RESULTS: V̇o2 was similar between conditions (diastolic 1.02±0.44 versus systolic 1.05±0.42 L/min; P=0.299). Compared with systolic walking, stroke volume (diastolic 80±28 versus systolic 74±26 mL; P=0.003) and cardiac output (8.3±3.5 versus 7.9±3.4 L/min; P=0.004) were higher during diastolic walking; heart rate (paced) was not different between conditions. Mean arterial pressure was significantly lower during diastolic walking (85±12 versus 98±20 mm Hg; P=0.007). CONCLUSIONS: In patients with CHF who have received CRT, diastolic stepping increases stroke volume and oxygen delivery and decreases afterload. We speculate that, if added to pacemakers, this cardio-locomotor coupling technology may maximize CRT efficiency and increase exercise participation and quality of life in patients with CHF.

A general relationship links gait mechanics and running ground reaction forces.

The relationship between gait mechanics and running ground reaction forces is widely regarded as complex. This viewpoint has evolved primarily via efforts to explain the rising edge of vertical force-time waveforms observed during slow human running. Existing theoretical models do provide good rising-edge fits, but require more than a dozen input variables to sum the force contributions of four or more vague components of the body's total mass (mb). Here, we hypothesized that the force contributions of two discrete body mass components are sufficient to account for vertical ground reaction force-time waveform patterns in full (stance foot and shank, m1=0.08mb; remaining mass, m2=0.92mb). We tested this hypothesis directly by acquiring simultaneous limb motion and ground reaction force data across a broad range of running speeds (3.0-11.1 m s-1) from 42 subjects who differed in body mass (range: 43-105 kg) and foot-strike mechanics. Predicted waveforms were generated from our two-mass model using body mass and three stride-specific measures: contact time, aerial time and lower limb vertical acceleration during impact. Measured waveforms (N=500) differed in shape and varied by more than twofold in amplitude and duration. Nonetheless, the overall agreement between the 500 measured waveforms and those generated independently by the model approached unity (R2=0.95±0.04, mean±s.d.), with minimal variation across the slow, medium and fast running speeds tested (ΔR2≤0.04), and between rear-foot (R2=0.94±0.04, N=177) versus fore-foot (R2=0.95±0.04, N=323) strike mechanics. We conclude that the motion of two anatomically discrete components of the body's mass is sufficient to explain the vertical ground reaction force-time waveform patterns observed during human running.

Foot speed, foot-strike and footwear: linking gait mechanics and running ground reaction forces.

Running performance, energy requirements and musculoskeletal stresses are directly related to the action-reaction forces between the limb and the ground. For human runners, the force-time patterns from individual footfalls can vary considerably across speed, foot-strike and footwear conditions. Here, we used four human footfalls with distinctly different vertical force-time waveform patterns to evaluate whether a basic mechanical model might explain all of them. Our model partitions the body's total mass (1.0 Mb) into two invariant mass fractions (lower limb=0.08, remaining body mass=0.92) and allows the instantaneous collisional velocities of the former to vary. The best fits achieved (R(2) range=0.95-0.98, mean=0.97 ± 0.01) indicate that the model is capable of accounting for nearly all of the variability observed in the four waveform types tested: barefoot jog, rear-foot strike run, fore-foot strike run and fore-foot strike sprint. We conclude that different running ground reaction force-time patterns may have the same mechanical basis.

Sprint exercise performance: does metabolic power matter?

Prevailing physiological paradigms explain both sprint and endurance exercise performance in terms of the availability of metabolic energy. However, for all-out efforts of 60 s or less, the prevailing view is no longer viable. Contemporary evidence indicates that sprinting performance is determined by musculoskeletal force application, with a duration dependency explained by the intrinsically rapid rates at which skeletal muscle fatigues in vivo.

Sex differences in human running performance: smaller gaps at shorter distances?

Human, but not canine or equine running performance, is significantly stratified by sex. The degree of stratification has obvious implications for classification and regulation in athletics. However, whether the widely cited sex difference of 10%-12% applies equally to sprint and endurance running events is unknown. Here, different determining factors for sprint (ground force/body mass) versus endurance performance (energy supply and demand) and existing trends, led us to hypothesize that sex performance differences for sprint running would increase with distance and be relatively small. We quantified sex performance differences using: 1) the race times of the world's fastest males and females (n = 40 each) over a 15-year period (2003-2018) at nine standard racing distances (60-10,000 m), and 2) the 10-m segment times of male (n = 14) and female (n = 12) athletes in World Championship 100-m finals. Between-sex performance time differences increased with sprint event distance (60 m-8.6%, 100 m-9.6%, 200 m-11.0%, 400 m-11.7%) and were smaller than the relatively constant mean (12.4 ± 0.3%) observed across the five longer events from 800 to 10,000 m. Between-sex time differences for the 10-m segments within the 100-m dash event increased throughout spanning 5.6%-14.2% from the first to last segment. We conclude that sex differences in sprint running performance increase with race and running distance.NEW & NOTEWORTHY Sex performance differences for sprint running bursts are small (<6%), but widen as the distance sprinted increases (range: 5.6%-14.2%). The distance dependency identified here for sprinting differs from the prevailing literature view of between-sex performance differences for the human running of 10%-12% regardless of distance. The variable sprint margins observed reflect the relative performance benefits shorter females have for brief, acceleration-dependent efforts versus those taller males have for longer steadier-speed sprint efforts.

Does restricting arm motion compromise short sprint running performance?

BACKGROUND: Synchronized arm and leg motion are characteristic of human running. Leg motion is an obvious gait requirement, but arm motion is not, and its functional contribution to running performance is not known. Because arm-leg coupling serves to reduce rotation about the body's vertical axis, arm motion may be necessary to achieve the body positions that optimize ground force application and performance. RESEARCH QUESTION: Does restricting arm motion compromise performance in short sprints? METHODS: Sprint performance was measured in 17 athletes during normal and restricted arm motion conditions. Restriction was self-imposed via arm folding across the chest with each hand on the opposite shoulder. Track and field (TF, n = 7) and team sport (TS, n = 10) athletes completed habituation and performance test sessions that included six counterbalanced 30 m sprints: three each in normal and restricted arm conditions. TS participants performed standing starts in both conditions. TF participants performed block starts with extended arms for the normal condition and elevated platform support of the elbows for the crossed-arm, restricted condition. Instantaneous velocity was measured throughout each trial using a radar device. Average sprint performance times were compared using a Repeated Measures ANOVA with Tukey post-hoc tests for the entire group and for the TF and TS subgroups. RESULTS: The 30 m times were faster for normal vs. restricted arm conditions, but the between-condition difference was only 1.6% overall and < 0.10 s for the entire group (4.82 ± 0.46 s vs. 4.90 ± 0.46 s, respectively; p < 0.001) and both TF (4.55 ± 0.34 vs. 4.63 ± 0.32 s; p < 0.001) and TS subgroups (5.01 ± 0.46 vs. 5.08 ± 0.47 s; p < 0.001). SIGNIFICANCE: Our findings suggest that when arm motion is restricted, compensatory upper body motions can provide the rotational forces needed to offset the lower body angular momentum generated by the swinging legs. We conclude that restricting arm motion compromised short sprint running performance, but only marginally.

Artificially long legs directly enhance long sprint running performance.

This comment addresses the incomplete presentation and incorrect conclusion offered in the recent manuscript of Beck et al. (R. Soc. Open Sci. 9, 211799 (doi:10.1098/rsos.211799)). The manuscript introduces biomechanical and performance data on the fastest-ever, bilateral amputee 400 m runner. Using an advantage standard of not faster than the fastest non-amputee runner ever (i.e. performance superior to that of the intact-limb world record-holder), the Beck et al. manuscript concludes that sprint running performance on bilateral, lower-limb prostheses is not unequivocally advantageous compared to the biological limb condition. The manuscript acknowledges the long-standing support of the authors for the numerous eligibility applications of the bilateral-amputee athlete. However, it does not acknowledge that the athlete's anatomically disproportionate prosthetic limb lengths (+15 cm versus the World Para Athletics maximum) are ineligible in both Olympic and Paralympic track competition due to their performance-enhancing properties. Also not acknowledged are the slower sprint performances of the bilateral-amputee athlete on limbs of shorter length that directly refute their manuscript's primary conclusion. Our contribution here provides essential background information and data not included in the Beck et al. manuscript that make the correct empirical conclusion clear: artificially long legs artificially enhance long sprint running performance.

Real-world walking economy: can laboratory equations predict field energy expenditure?

We addressed a practical question that remains largely unanswered after more than a century of active investigation: can equations developed in the laboratory accurately predict the energy expended under free-walking conditions in the field? Seven subjects walked a field course of 6,415 m that varied in gradient (-3.0 to +5.0%) and terrain (asphalt, grass) under unloaded (body weight only, Wb) and balanced, torso-loaded (1.30 × Wb) conditions at self-selected speeds while wearing portable calorimeter and GPS units. Portable calorimeter measures were corrected for a consistent measurement-range offset (+13.8 ± 1.8%, means ± SD) versus a well-validated laboratory system (Parvomedics TrueOne). Predicted energy expenditure totals (mL O2/kg) from four literature equations: ACSM, Looney, Minimum Mechanics, and Pandolf, were generated using the speeds and gradients measured throughout each trial in conjunction with empirically determined terrain/treadmill factors (asphalt = 1.0, grass = 1.08). The mean energy expenditure total measured for the unloaded field trials (981 ± 91 mL O2/kg) was overpredicted by +4%, +13%, +17%, and +20% by the Minimum Mechanics, ACSM, Pandolf, and Looney equations, respectively (corresponding predicted totals: 1,018 ± 19, 1,108 ± 26, 1,145 ± 37, and 1,176 ± 24 mL O2/kg). The measured loaded-trial total (1,310 ± 153 mL O2/kg) was slightly underpredicted by the Minimum Mechanics equation (-2%, 1,289 ± 22 mL O2/kg) and overpredicted by the Pandolf equation (+13%, 1,463 ± 32 mL O2/kg). Computational comparisons for hypothetical trials at different constant speeds (range: 0.6-1.8 m/s) on variable-gradient loop courses revealed between-equation prediction differences from 0% to 37%. We conclude that treadmill-based predictions of free-walking field energy expenditure are equation-dependent but can be highly accurate with rigorous implementation.NEW & NOTEWORTHY Here, we investigated the accuracy with which four laboratory-based equations can predict field-walking energy expenditure at freely selected speeds across varying gradients and terrain. Empirical tests involving 6,415-m trials under two load conditions indicated that predictions are significantly equation dependent but can be highly accurate (i.e., ±4%). Computations inputting identical weight, speed, and gradient values for different theoretical constant-speed trials (0.6-1.8 m/s) identified between-equation prediction differences as large as 37%.

The mass-specific energy cost of human walking is set by stature.

The metabolic and mechanical requirements of walking are considered to be of fundamental importance to the health, physiological function and even the evolution of modern humans. Although walking energy expenditure and gait mechanics are clearly linked, a direct quantitative relationship has not emerged in more than a century of formal investigation. Here, on the basis of previous observations that children and smaller adult walkers expend more energy on a per kilogram basis than larger ones do, and the theory of dynamic similarity, we hypothesized that body length (or stature, L(b)) explains the apparent body-size dependency of human walking economy. We measured metabolic rates and gait mechanics at six speeds from 0.4 to 1.9 m s(-1) in 48 human subjects who varied by a factor of 1.5 in stature and approximately six in both age and body mass. In accordance with theoretical expectation, we found the most economical walking speeds measured (J kg(-1) m(-1)) to be dynamically equivalent (i.e. similar U, where U=velocity(2)/gravity · leg length) among smaller and larger individuals. At these speeds, stride lengths were directly proportional to stature whereas the metabolic cost per stride was largely invariant (2.74±0.12 J kg(-1) stride(-1)). The tight coupling of stature, gait mechanics and metabolic energy expenditure resulted in an inverse relationship between mass-specific transport costs and stature (E(trans)/M(b)∝L(b)(-0.95), J kg(-1) m(-1)). We conclude that humans spanning a broad range of ages, statures and masses incur the same mass-specific metabolic cost to walk a horizontal distance equal to their stature.

The fastest runner on artificial legs: different limbs, similar function?

The recent competitive successes of a bilateral, transtibial amputee sprint runner who races with modern running prostheses has triggered an international controversy regarding the relative function provided by his artificial limbs. Here, we conducted three tests of functional similarity between this amputee sprinter and competitive male runners with intact limbs: the metabolic cost of running, sprinting endurance, and running mechanics. Metabolic and mechanical data, respectively, were acquired via indirect calorimetry and ground reaction force measurements during constant-speed, level treadmill running. First, we found that the mean gross metabolic cost of transport of our amputee sprint subject (174.9 ml O(2)*kg(-1)*km(-1); speeds: 2.5-4.1 m/s) was only 3.8% lower than mean values for intact-limb elite distance runners and 6.7% lower than for subelite distance runners but 17% lower than for intact-limb 400-m specialists [210.6 (SD 13.2) ml O(2)*kg(-1)*km(-1)]. Second, the speeds that our amputee sprinter maintained for six all-out, constant-speed trials to failure (speeds: 6.6-10.8 m/s; durations: 2-90 s) were within 2.2 (SD 0.6)% of those predicted for intact-limb sprinters. Third, at sprinting speeds of 8.0, 9.0, and 10.0 m/s, our amputee subject had longer foot-ground contact times [+14.7 (SD 4.2)%], shorter aerial [-26.4 (SD 9.9)%] and swing times [-15.2 (SD 6.9)%], and lower stance-averaged vertical forces [-19.3 (SD 3.1)%] than intact-limb sprinters [top speeds = 10.8 vs. 10.8 (SD 0.6) m/s]. We conclude that running on modern, lower-limb sprinting prostheses appears to be physiologically similar but mechanically different from running with intact limbs.

Running ground reaction forces across footwear conditions are predicted from the motion of two body mass components.

Although running shoes alter foot-ground reaction forces, particularly during impact, how they do so is incompletely understood. Here, we hypothesized that footwear effects on running ground reaction force-time patterns can be accurately predicted from the motion of two components of the body's mass (mb): the contacting lower-limb (m1 = 0.08mb) and the remainder (m2 = 0.92mb). Simultaneous motion and vertical ground reaction force-time data were acquired at 1,000 Hz from eight uninstructed subjects running on a force-instrumented treadmill at 4.0 and 7.0 m/s under four footwear conditions: barefoot, minimal sole, thin sole, and thick sole. Vertical ground reaction force-time patterns were generated from the two-mass model using body mass and footfall-specific measures of contact time, aerial time, and lower-limb impact deceleration. Model force-time patterns generated using the empirical inputs acquired for each footfall matched the measured patterns closely across the four footwear conditions at both protocol speeds (r2 = 0.96 ± 0.004; root mean squared error = 0.17 ± 0.01 body-weight units; n = 275 total footfalls). Foot landing angles (θF) were inversely related to footwear thickness; more positive or plantar-flexed landing angles coincided with longer-impact durations and force-time patterns lacking distinct rising-edge force peaks. Our results support three conclusions: 1) running ground reaction force-time patterns across footwear conditions can be accurately predicted using our two-mass, two-impulse model, 2) impact forces, regardless of foot strike mechanics, can be accurately quantified from lower-limb motion and a fixed anatomical mass (0.08mb), and 3) runners maintain similar loading rates (ΔFvertical/Δtime) across footwear conditions by altering foot strike angle to regulate the duration of impact. NEW & NOTEWORTHY Here, we validate a two-mass, two-impulse model of running vertical ground reaction forces across four footwear thickness conditions (barefoot, minimal, thin, thick). Our model allows the impact portion of the impulse to be extracted from measured total ground reaction force-time patterns using motion data from the ankle. The gait adjustments observed across footwear conditions revealed that runners maintained similar loading rates across footwear conditions by altering foot strike angles to regulate the duration of impact.

Walking economy is predictably determined by speed, grade, and gravitational load.

The metabolic energy that human walking requires can vary by more than 10-fold, depending on the speed, surface gradient, and load carried. Although the mechanical factors determining economy are generally considered to be numerous and complex, we tested a minimum mechanics hypothesis that only three variables are needed for broad, accurate prediction: speed, surface grade, and total gravitational load. We first measured steady-state rates of oxygen uptake in 20 healthy adult subjects during unloaded treadmill trials from 0.4 to 1.6 m/s on six gradients: -6, -3, 0, 3, 6, and 9°. Next, we tested a second set of 20 subjects under three torso-loading conditions (no-load, +18, and +31% body weight) at speeds from 0.6 to 1.4 m/s on the same six gradients. Metabolic rates spanned a 14-fold range from supine rest to the greatest single-trial walking mean (3.1 ± 0.1 to 43.3 ± 0.5 ml O2·kg-body-1·min-1, respectively). As theorized, the walking portion (V̇o2-walk = V̇o2-gross - V̇o2-supine-rest) of the body's gross metabolic rate increased in direct proportion to load and largely in accordance with support force requirements across both speed and grade. Consequently, a single minimum-mechanics equation was derived from the data of 10 unloaded-condition subjects to predict the pooled mass-specific economy (V̇o2-gross, ml O2·kg-body + load-1·min-1) of all the remaining loaded and unloaded trials combined (n = 1,412 trials from 90 speed/grade/load conditions). The accuracy of prediction achieved (r2 = 0.99, SEE = 1.06 ml O2·kg-1·min-1) leads us to conclude that human walking economy is predictably determined by the minimum mechanical requirements present across a broad range of conditions.NEW & NOTEWORTHY Introduced is a "minimum mechanics" model that predicts human walking economy across a broad range of conditions from only three variables: speed, surface grade, and body-plus-load mass. The derivation/validation data set includes steady-state loaded and unloaded walking trials (n = 3,414) that span a fourfold range of walking speeds on each of six different surface gradients (-6 to +9°). The accuracy of our minimum mechanics model (r2 = 0.99; SEE = 1.06 ml O2·kg-1·min-1) appreciably exceeds that of currently used standards.

Energy expenditure during level human walking: seeking a simple and accurate predictive solution.

Accurate prediction of the metabolic energy that walking requires can inform numerous health, bodily status, and fitness outcomes. We adopted a two-step approach to identifying a concise, generalized equation for predicting level human walking metabolism. Using literature-aggregated values we compared 1) the predictive accuracy of three literature equations: American College of Sports Medicine (ACSM), Pandolf et al., and Height-Weight-Speed (HWS); and 2) the goodness-of-fit possible from one- vs. two-component descriptions of walking metabolism. Literature metabolic rate values (n = 127; speed range = 0.4 to 1.9 m/s) were aggregated from 25 subject populations (n = 5-42) whose means spanned a 1.8-fold range of heights and a 4.2-fold range of weights. Population-specific resting metabolic rates (V̇o2 rest) were determined using standardized equations. Our first finding was that the ACSM and Pandolf et al. equations underpredicted nearly all 127 literature-aggregated values. Consequently, their standard errors of estimate (SEE) were nearly four times greater than those of the HWS equation (4.51 and 4.39 vs. 1.13 ml O2·kg(-1)·min(-1), respectively). For our second comparison, empirical best-fit relationships for walking metabolism were derived from the data set in one- and two-component forms for three V̇o2-speed model types: linear (∝V(1.0)), exponential (∝V(2.0)), and exponential/height (∝V(2.0)/Ht). We found that the proportion of variance (R(2)) accounted for, when averaged across the three model types, was substantially lower for one- vs. two-component versions (0.63 ± 0.1 vs. 0.90 ± 0.03) and the predictive errors were nearly twice as great (SEE = 2.22 vs. 1.21 ml O2·kg(-1)·min(-1)). Our final analysis identified the following concise, generalized equation for predicting level human walking metabolism: V̇o2 total = V̇o2 rest + 3.85 + 5.97·V(2)/Ht (where V is measured in m/s, Ht in meters, and V̇o2 in ml O2·kg(-1)·min(-1)).

High-speed running performance: a new approach to assessment and prediction.

We hypothesized that all-out running speeds for efforts lasting from a few seconds to several minutes could be accurately predicted from two measurements: the maximum respective speeds supported by the anaerobic and aerobic powers of the runner. To evaluate our hypothesis, we recruited seven competitive runners of different event specialties and tested them during treadmill and overground running on level surfaces. The maximum speed supported by anaerobic power was determined from the fastest speed that subjects could attain for a burst of eight steps (approximately 3 s or less). The maximum speed supported by aerobic power, or the velocity at maximal oxygen uptake, was determined from a progressive, discontinuous treadmill test to failure. All-out running speeds for trials of 3-240 s were measured during 10-13 constant-speed treadmill runs to failure and 4 track runs at specified distances. Measured values of the maximum speeds supported by anaerobic and aerobic power, in conjunction with an exponential constant, allowed us to predict the speeds of all-out treadmill trials to within an average of 2.5% (R2 = 0.94; n = 84) and track trials to within 3.4% (R2 = 0.86; n = 28). An algorithm using this exponent and only two of the all-out treadmill runs to predict the remaining treadmill trials was nearly as accurate (average = 3.7%; R2 = 0.93; n = 77). We conclude that our technique 1) provides accurate predictions of high-speed running performance in trained runners and 2) offers a performance assessment alternative to existing tests of anaerobic power and capacity.

Energetics and mechanics of human running on surfaces of different stiffnesses.

Mammals use the elastic components in their legs (principally tendons, ligaments, and muscles) to run economically, while maintaining consistent support mechanics across various surfaces. To examine how leg stiffness and metabolic cost are affected by changes in substrate stiffness, we built experimental platforms with adjustable stiffness to fit on a force-plate-fitted treadmill. Eight male subjects [mean body mass: 74.4 +/- 7.1 (SD) kg; leg length: 0.96 +/- 0.05 m] ran at 3.7 m/s over five different surface stiffnesses (75.4, 97.5, 216.8, 454.2, and 945.7 kN/m). Metabolic, ground-reaction force, and kinematic data were collected. The 12.5-fold decrease in surface stiffness resulted in a 12% decrease in the runner's metabolic rate and a 29% increase in their leg stiffness. The runner's support mechanics remained essentially unchanged. These results indicate that surface stiffness affects running economy without affecting running support mechanics. We postulate that an increased energy rebound from the compliant surfaces studied contributes to the enhanced running economy.

Total energy expenditure estimated using foot-ground contact pedometry.

Routine walking and running, by increasing daily total energy expenditure (TEE), can play a significant role in reducing the likelihood of obesity. The objective of this field study was to compare TEE estimated using foot-ground contact time (Tc)-pedometry (TEE(PEDO)) with that measured by the criterion doubly labeled water (DLW) method. Eight male U.S. Marine test volunteers [27 +/- 4 years of age (mean +/- SD); weight = 83.2 +/- 10.7 kg; height = 182.2 +/- 4.5 cm; body fat = 17.0 +/- 2.9%] engaged in a field training exercise were studied over 2 days. TEE(PEDO) was defined as (calculated resting energy expenditure + estimated thermic effect of food + metabolic cost of physical activity), where physical activity was estimated by Tc-pedometry. Tc-pedometry was used to differentiate inactivity, activity other than exercise (i.e., non-exercise activity thermogenesis, or NEAT), and the metabolic cost of locomotion (M(LOCO)), where M(LOCO) was derived from total weight (body weight + load weight) and accelerometric measurements of Tc. TEE(PEDO) data were compared with TEEs measured by the DLW (2H2(18)O) method (TEE(DLW)): TEE(DLW) = 15.27 +/- 1.65 MJ/day and TEE(PEDO) = 15.29 +/- 0.83 MJ/day. Mean bias (i.e., TEE(PEDO) - TEE(DLW)) was 0.02 MJ, and mean error (SD of individual differences between TEE(PEDO) and TEE(DLW)) was 1.83 MJ. The Tc-pedometry method provided a valid estimate of the average TEE of a small group of physically active subjects where walking was the dominant activity.

Are running speeds maximized with simple-spring stance mechanics?

Are the fastest running speeds achieved using the simple-spring stance mechanics predicted by the classic spring-mass model? We hypothesized that a passive, linear-spring model would not account for the running mechanics that maximize ground force application and speed. We tested this hypothesis by comparing patterns of ground force application across athletic specialization (competitive sprinters vs. athlete nonsprinters, n = 7 each) and running speed (top speeds vs. slower ones). Vertical ground reaction forces at 5.0 and 7.0 m/s, and individual top speeds (n = 797 total footfalls) were acquired while subjects ran on a custom, high-speed force treadmill. The goodness of fit between measured vertical force vs. time waveform patterns and the patterns predicted by the spring-mass model were assessed using the R(2) statistic (where an R(2) of 1.00 = perfect fit). As hypothesized, the force application patterns of the competitive sprinters deviated significantly more from the simple-spring pattern than those of the athlete, nonsprinters across the three test speeds (R(2) <0.85 vs. R(2) ≥ 0.91, respectively), and deviated most at top speed (R(2) = 0.78 ± 0.02). Sprinters attained faster top speeds than nonsprinters (10.4 ± 0.3 vs. 8.7 ± 0.3 m/s) by applying greater vertical forces during the first half (2.65 ± 0.05 vs. 2.21 ± 0.05 body wt), but not the second half (1.71 ± 0.04 vs. 1.73 ± 0.04 body wt) of the stance phase. We conclude that a passive, simple-spring model has limited application to sprint running performance because the swiftest runners use an asymmetrical pattern of force application to maximize ground reaction forces and attain faster speeds.

Predicting metabolic rate across walking speed: one fit for all body sizes?

We formulated a "one-size-fits-all" model that predicts the energy requirements of level human walking from height, weight, and walking speed. Our three-component model theorizes that the energy expended per kilogram per stride is independent of stature at mechanically equivalent walking speeds. We measured steady-state rates of oxygen uptake of 78 subjects who spanned a nearly twofold range of statures (1.07-2.11 m) and sevenfold range of body masses (16-112 kg) at treadmill speeds from 0.4 to 1.9 m/s. We tested the size independence of the model by deriving best-fit equations in the form of the model on four stature groups (n ≥ 15): short, moderately short, moderately tall, and tall. The mean walking metabolic rates predicted by these four independently derived equations for the same set of reference subjects (n = 16; stature range: 1.30-1.90 m) agreed with one another to within an average of 5.2 ± 3.7% at the four intermediate speeds in our protocol. We next evaluated the model's gross predictive accuracy by dividing our 78 subjects into 39 stature-matched pairs of experimental and validation group subjects. The model best-fit equation derived on the experimental group subjects predicted the walking metabolic rates of the validation group subjects to within an average of 8.1 ± 6.7% (R(2) = 0.90; standard error of estimate = 1.34 ml O2·kg(-1)·min(-1)). The predictive error of the American College of Sports Medicine equation (18.0 ± 13.1%), which does not include stature as a predictor, was more than twice as large for the same subject group. We conclude that the energy cost of level human walking can be accurately predicted from height, weight, and walking speed.

The biological limits to running speed are imposed from the ground up.

Running speed is limited by a mechanical interaction between the stance and swing phases of the stride. Here, we tested whether stance phase limitations are imposed by ground force maximums or foot-ground contact time minimums. We selected one-legged hopping and backward running as experimental contrasts to forward running and had seven athletic subjects complete progressive discontinuous treadmill tests to failure to determine their top speeds in each of the three gaits. Vertical ground reaction forces [in body weights (W(b))] and periods of ground force application (T(c); s) were measured using a custom, high-speed force treadmill. At top speed, we found that both the stance-averaged (F(avg)) and peak (F(peak)) vertical forces applied to the treadmill surface during one-legged hopping exceeded those applied during forward running by more than one-half of the body's weight (F(avg) = 2.71 +/- 0.15 vs. 2.08 +/- 0.07 W(b); F(peak) = 4.20 +/- 0.24 vs. 3.62 +/- 0.24 W(b); means +/- SE) and that hopping periods of force application were significantly longer (T(c) = 0.160 +/- 0.006 vs. 0.108 +/- 0.004 s). Next, we found that the periods of ground force application at top backward and forward running speeds were nearly identical, agreeing to within an average of 0.006 s (T(c) = 0.116 +/- 0.004 vs. 0.110 +/- 0.005 s). We conclude that the stance phase limit to running speed is imposed not by the maximum forces that the limbs can apply to the ground but rather by the minimum time needed to apply the large, mass-specific forces necessary.