Exploring How the Arms Can Help the Legs in Facilitating Gait Rehabilitation.

Inspired by the ideas from the fields of gait rehabilitation, neuroscience, and locomotion biomechanics and energetics, a body of work is reviewed that has led to propose a conceptual framework for novel "self-assistive" walking devices that could further promote walking recovery from incomplete spinal cord injuries. The underlying rationale is based on a neural coupling mechanism that governs the coordinated movements of the arms and legs during walking, and that the excitability of these neural pathways can be exploited by actively engaging the arms during locomotor training. Self-assistive treadmill walking rehabilitation devices are envisioned as an approach that would allow an individual to actively use their arms to help the legs during walking. It is hoped that the conceptual framework inspires the design and use of self-assistive walking devices that are tailored to assist individuals with an incomplete spinal cord injury to regain their functional walking ability.

Metabolic Costs of Walking with Weighted Vests.

INTRODUCTION: The US Army Load Carriage Decision Aid (LCDA) metabolic model is used by militaries across the globe and is intended to predict physiological responses, specifically metabolic costs, in a wide range of dismounted warfighter operations. However, the LCDA has yet to be adapted for vest-borne load carriage, which is commonplace in tactical populations, and differs in energetic costs to backpacking and other forms of load carriage. PURPOSE: The purpose of this study is to develop and validate a metabolic model term that accurately estimates the effect of weighted vest loads on standing and walking metabolic rate for military mission-planning and general applications. METHODS: Twenty healthy, physically active military-age adults (4 women, 16 men; age, 26 ± 8 yr old; height, 1.74 ± 0.09 m; body mass, 81 ± 16 kg) walked for 6 to 21 min with four levels of weighted vest loading (0 to 66% body mass) at up to 11 treadmill speeds (0.45 to 1.97 m·s -1 ). Using indirect calorimetry measurements, we derived a new model term for estimating metabolic rate when carrying vest-borne loads. Model estimates were evaluated internally by k -fold cross-validation and externally against 12 reference datasets (264 total participants). We tested if the 90% confidence interval of the mean paired difference was within equivalence limits equal to 10% of the measured walking metabolic rate. Estimation accuracy, precision, and level of agreement were also evaluated by the bias, standard deviation of paired differences, and concordance correlation coefficient (CCC), respectively. RESULTS: Metabolic rate estimates using the new weighted vest term were statistically equivalent ( P < 0.01) to measured values in the current study (bias, -0.01 ± 0.54 W·kg -1 ; CCC, 0.973) as well as from the 12 reference datasets (bias, -0.16 ± 0.59 W·kg -1 ; CCC, 0.963). CONCLUSIONS: The updated LCDA metabolic model calculates accurate predictions of metabolic rate when carrying heavy backpack and vest-borne loads. Tactical populations and recreational athletes that train with weighted vests can confidently use the simplified LCDA metabolic calculator provided as Supplemental Digital Content to estimate metabolic rates for work/rest guidance, training periodization, and nutritional interventions.

Estimating Metabolic Energy Expenditure During Level Running in Healthy, Military-Age Women and Men.

ABSTRACT: Looney, DP, Hoogkamer, W, Kram, R, Arellano, CJ, and Spiering, BA. Estimating metabolic energy expenditure during level running in healthy, military-age women and men. J Strength Cond Res 37(12): 2496-2503, 2023-Quantifying the rate of metabolic energy expenditure (M) of varied aerobic exercise modalities is important for optimizing fueling and performance and maintaining safety in military personnel operating in extreme conditions. However, although equations exist for estimating oxygen uptake during running, surprisingly, there are no general equations that estimate M. Our purpose was to generate a general equation for estimating M during level running in healthy, military-age (18-44 years) women and men. We compiled indirect calorimetry data collected during treadmill running from 3 types of sources: original individual subject data (n = 45), published individual subject data (30 studies; n = 421), and published group mean data (20 studies, n = 619). Linear and quadratic equations were fit on the aggregated data set using a mixed-effects modeling approach. A chi-squared (χ2) difference test was conducted to determine whether the more complex quadratic equation was justified (p < 0.05). Our primary indicator of model goodness-of-fit was the root-mean-square deviation (RMSD). We also examined whether individual characteristics (age, height, body mass, and maximal oxygen uptake [V̇O2max]) could minimize prediction errors. The compiled data set exhibited considerable variability in M (14.54 ± 3.52 W·kg-1), respiratory exchange ratios (0.89 ± 0.06), and running speeds (3.50 ± 0.86 m·s-1). The quadratic regression equation had reduced residual sum of squares compared with the linear fit (χ2, 3,484; p < 0.001), with higher combined accuracy and precision (RMSD, 1.31 vs. 1.33 W·kg-1). Age (p = 0.034), height (p = 0.026), and body mass (p = 0.019) were associated with the magnitude of under and overestimation, which was not the case for V̇O2max (p = 0.898). The newly derived running energy expenditure estimation (RE3) model accurately predicts level running M at speeds from 1.78 to 5.70 m·s-1 in healthy, military-age women and men. Users can rely on the following equations for improved predictions of running M as a function of running speed (S, m·s-1) in either watts (W·kg-1 = 4.43 + 1.51·S + 0.37·S2) or kilocalories per minute (kcal·kg-1·min-1 = 308.8 + 105.2·S + 25.58·S2).

A simple method reveals minimum time required to quantify steady-rate metabolism and net cost of transport for human walking.

The U-shaped net cost of transport (COT) curve of walking has helped scientists understand the biomechanical basis that underlies energy minimization during walking. However, to produce an individual's net COT curve, data must be analyzed during periods of steady-rate metabolism. Traditionally, studies analyze the last few minutes of a 6-10 min trial, assuming that steady-rate metabolism has been achieved. Yet, it is possible that an individual achieves steady rates of metabolism much earlier. However, there is no consensus on how to objectively quantify steady-rate metabolism across a range of walking speeds. Therefore, we developed a simple slope method to determine the minimum time needed for humans to achieve steady rates of metabolism across slow to fast walking speeds. We hypothesized that a shorter time window could be used to produce a net COT curve that is comparable to the net COT curve created using traditional methods. We analyzed metabolic data from 21 subjects who completed several 7 min walking trials ranging from 0.50 to 2.00 m s-1. We partitioned the metabolic data for each trial into moving 1, 2 and 3 min intervals and calculated their slopes. We statistically compared these slope values with values derived from the last 3 min of the 7 min trial, our 'gold' standard comparison. We found that a minimum of 2 min is required to achieve steady-rate metabolism and that data from 2-4 min yields a net COT curve that is not statistically different from the one derived from experimental protocols that are generally accepted in the field.

Step-to-step variability indicates disruption to balance control when linking the arms and legs during treadmill walking.

We recently discovered that a rope-pulley system that mechanically coupling the arms, legs and treadmill during walking can assist with forward propulsion in healthy subjects, leading to significant reductions in metabolic cost. However, walking balance may have been compromised, which could hinder the potential use of this device for gait rehabilitation. We performed a secondary analysis by quantifying average step width, step length, and step time, and used their variability to reflect simple metrics of walking balance (n = 8). We predicted an increased variability in at least one of these metrics when using the device, which would indicate disruptions to walking balance. When walking with the device, subjects increased their average step width (p < 0.05), but variability in step width and step length remained similar (p's > 0.05). However, the effect size for step length variability when compared to that of mechanical perturbation experiments suggest a minimal to moderate disruption in balance (Rosenthal ES = 0.385). The most notable decrement in walking balance was an increase in step time variability (p < 0.05; Cohen's d = 1.286). Its effect size reveals a moderate disruption when compared to the effect sizes observed in those with balance deficits (effect sizes ranged between 0.486 to 1.509). Overall, we conclude that healthy subjects experienced minimal to moderate disruptions in walking balance when using with this device. These data indicate that in future clinical experiments, it will be important to not only consider the mechanical and metabolic effects of using such a device but also its potential to disrupt walking balance, which may be exacerbated in patients with poor balance control.

Simple models highlight differences in the walking biomechanics of young children and adults.

Adults conserve metabolic energy during walking by minimizing the step-to-step transition work performed by the legs during double support and by utilizing spring-like mechanisms in their legs, but little is known as to whether children utilize these same mechanisms. To gain a better understanding, we studied how children (5-6 years) and adults modulate the mechanical and metabolic demands of walking at their preferred speed, across slow (75%), preferred (100%) and fast (125%) step frequencies. We quantified (1) the positive mass-specific work done by the trailing leg during step-to-step transitions and (2) the leg's spring-like behavior during single support. On average, children walked with a 36% greater net cost of transport (COT; J kg-1 m-1) than adults (P=0.03), yet both groups increased their net COT at varying step frequencies. After scaling for speed, children generated ∼2-fold less trailing limb positive scaled mechanical work during the step-to-step transition (P=0.02). Unlike adults, children did not modulate their trailing limb positive work to meet the demands of walking at 75% and 125% of their preferred step frequency. In single support, young children operated their stance limb with much greater compliance than adults ( versus 11.35; P=0.023). Our observations suggest that the mechanics of walking in children aged 5-6 years are fundamentally distinct from the mechanics of walking in adults and may help to explain a child's higher net COT. These insights have implications for the design of assistive devices for children and suggest that children cannot be simply treated as scaled-down versions of adults.

Using a simple rope-pulley system that mechanically couples the arms, legs, and treadmill reduces the metabolic cost of walking.

BACKGROUND: Emphasizing the active use of the arms and coordinating them with the stepping motion of the legs may promote walking recovery in patients with impaired lower limb function. Yet, most approaches use seated devices to allow coupled arm and leg movements. To provide an option during treadmill walking, we designed a rope-pulley system that physically links the arms and legs. This arm-leg pulley system was grounded to the floor and made of commercially available slotted square tubing, solid strut channels, and low-friction pulleys that allowed us to use a rope to connect the subject's wrist to the ipsilateral foot. This set-up was based on our idea that during walking the arm could generate an assistive force during arm swing retraction and, therefore, aid in leg swing. METHODS: To test this idea, we compared the mechanical, muscular, and metabolic effects between normal walking and walking with the arm-leg pulley system. We measured rope and ground reaction forces, electromyographic signals of key arm and leg muscles, and rates of metabolic energy consumption while healthy, young subjects walked at 1.25 m/s on a dual-belt instrumented treadmill (n = 8). RESULTS: With our arm-leg pulley system, we found that an assistive force could be generated, reaching peak values of 7% body weight on average. Contrary to our expectation, the force mainly coincided with the propulsive phase of walking and not leg swing. Our findings suggest that subjects actively used their arms to harness the energy from the moving treadmill belt, which helped to propel the whole body via the arm-leg rope linkage. This effectively decreased the muscular and mechanical demands placed on the legs, reducing the propulsive impulse by 43% (p < 0.001), which led to a 17% net reduction in the metabolic power required for walking (p = 0.001). CONCLUSIONS: These findings provide the biomechanical and energetic basis for how we might reimagine the use of the arms in gait rehabilitation, opening the opportunity to explore if such a method could help patients regain their walking ability. TRIAL REGISTRATION: Study registered on 09/29/2018 in ClinicalTrials.gov (ID-NCT03689647).

Effects of course design (curves and elevation undulations) on marathon running performance: a comparison of Breaking 2 in Monza and the INEOS 1:59 Challenge in Vienna.

Eliud Kipchoge made two attempts to break the 2-hour marathon, in Monza and then Vienna. Here we analyse only the effects of course elevation profile and turn curvatures on his performances. We used publicly available data to determine the undulations in elevation and the radii of the curves on the course. With previously developed equations for the effects of velocity, slope, and curvature on oxygen uptake, we performed simulations to quantify how much the elevation changes and curves of the Vienna course affect a runner's oxygen uptake (at a fixed velocity) or velocity (at a fixed oxygen uptake). We estimate that, after the initial downhill benefit, the course led to an overall oxygen uptake penalty of only 0.03%. When compared to a perfectly level straight course, we estimate that the combined effects of the undulations and curves of the Vienna course incurred a penalty of just 1.37 seconds. Kipchoge ran 2:00:25 in Monza Italy. Comparison with the Monza course profile indicates a 46.2 second (1.09% oxygen uptake) advantage of Vienna's course while the fewer curves of Vienna contributed ~ 1 second. The Vienna course was very well-chosen because it minimized the negative effects of elevation changes and curves.Abbreviations: CoT: Oxygen cost of transport; CV˙O2: Curved rate of oxygen consumption; V˙O2: Rate of oxygen consumption; WA: World Athletics.

Do humans exploit the metabolic and mechanical benefits of arm swing across slow to fast walking speeds?

Humans naturally select conditions to minimize their net cost of transport (COT) during walking. One way to do this is by exploiting the mechanical benefit of arm swing which reduces whole-body rotation about the vertical axis and thus, minimizes the free vertical moment (FVM) that the foot applies to the ground. Humans appear to exploit these benefits of arm swing at speeds that are considered optimal, but we sought to determine if these benefits are conserved across slow to fast walking speeds. If true, arm swing may be a key feature that helps to minimize the net COT regardless of one's walking speed. We hypothesized that at all speeds, walking with arm swing would be less costly compared to walking without arm swing. As a secondary aim, we also explored if reductions in the peak FVM could explain the metabolic benefits of arm swing. Twenty-one young, healthy subjects walked with and without arm swing at speeds ranging from 0.50 to 2.00 m/s while we recorded metabolic, kinematic and kinetic data. At slow speeds (≤1.00 m/s), net COT was similar when walking with or without arm swing (p > 0.05). However, at intermediate and fast speeds (≥1.00 m/s), arm swing reduced the net COT by ~7-13% (all p's < 0.05). Additionally, peak FVM magnitudes decreased with arm swing, suggesting that it may partially explain the metabolic benefit of arm swing. Overall, we find that arm swing provides a net metabolic benefit during walking, but this benefit is constrained to intermediate and fast walking speeds.

A low-cost method for carrying loads during human walking.

Humans often perform tasks that require them to carry loads, but the metabolic cost of carrying loads depends on where the loads are positioned on the body. We reasoned that carrying loads at the arms' center of mass (COM) during walking might be cheap because arm swing is thought to be dominated by passive pendulum dynamics. In contrast, we expected that carrying loads at the leg COM would be relatively expensive because muscular actuation is necessary to initiate and propagate leg swing. Therefore, we hypothesized that carrying loads at the arm COM while swinging would be cheaper than carrying loads at the leg COM. We further hypothesized that carrying loads at the arm COM while swinging would be more expensive than carrying loads at the waist, where the mass does not swing relative to the body. We measured net metabolic power, arm and leg motion, and the free vertical moment while subjects (n=12) walked on a treadmill (1.25 m s-1) without a load, and with 8 kg added to the arms (swinging versus not swinging), legs or waist. We found that carrying loads on the arms or legs altered arm swinging amplitude; however, the free vertical moment remained similar across conditions. Most notably, the cost of carrying loads on the swinging arms was 9% less than carrying at the leg COM (P<0.001), but similar to that at the waist (P=0.529). Overall, we found that carrying loads at the arm COM is just as cheap as carrying loads at the waist.

Evidence of a tunable biological spring: elastic energy storage in aponeuroses varies with transverse strain in vivo.

Tendinous structures are generally thought of as biological springs that operate with a fixed stiffness, yet recent observations on the mechanical behaviour of aponeuroses (broad, sheet-like tendons) have challenged this general assumption. During in situ contractions, aponeuroses undergo changes in both length and width and changes in aponeuroses width can drive changes in longitudinal stiffness. Here, we explore if changes in aponeuroses width can modulate elastic energy (EE) storage in the longitudinal direction. We tested this idea in vivo by quantifying muscle and aponeuroses mechanical behaviour in the turkey lateral gastrocnemius during landing and jumping, activities that require rapid rates of energy dissipation and generation, respectively. We discovered that when aponeurosis width increased (as opposed to decreased), apparent longitudinal stiffness was 34% higher and the capacity of aponeuroses to store EE when stretched in the longitudinal direction was 15% lower. These data reveal that biaxial loading of aponeuroses allows for variation in tendon stiffness and energy storage for different locomotor behaviours.

Modeling the Benefits of Cooperative Drafting: Is There an Optimal Strategy to Facilitate a Sub-2-Hour Marathon Performance?

BACKGROUND: During a race, competing cyclists often cooperate by alternating between leading and drafting positions. This approach allows them to maximize velocity by using the energy saved while drafting, a technique to reduce the overall drag by exploiting the leader's slipstream. We have argued that a similar cooperative drafting approach could benefit elite marathon runners in their quest for the sub-2-hour marathon. OBJECTIVE: Our aim was to model the effects of various cooperative drafting scenarios on marathon performance by applying the critical velocity concept for intermittent high-intensity running. METHODS: We used the physiological characteristics of the world's most elite long-distance runners and mathematically simulated the depletion and recovery of their distance capacity when running above and below their critical velocity throughout a marathon. RESULTS: Our simulations showed that with four of the most elite runners in the world, a 2:00:48 (h:min:s) marathon is possible, a whopping 2 min faster than the current world record. We also explored the possibility of a sub-2-hour marathon using multiple runners with the physiological characteristics of Eliud Kipchoge, arguably the best marathon runner of our time. We found that a team of eight Kipchoge-like runners could break the sub-2-hour marathon barrier. CONCLUSION: In the context of cooperative drafting, we show that the best team strategy for improving marathon performance time can be optimized using a mathematical model that is based on the physiological characteristics of each athlete.

How Biomechanical Improvements in Running Economy Could Break the 2-hour Marathon Barrier.

A sub-2-hour marathon requires an average velocity (5.86 m/s) that is 2.5% faster than the current world record of 02:02:57 (5.72 m/s) and could be accomplished with a 2.7% reduction in the metabolic cost of running. Although supporting body weight comprises the majority of the metabolic cost of running, targeting the costs of forward propulsion and leg swing are the most promising strategies for reducing the metabolic cost of running and thus improving marathon running performance. Here, we calculate how much time could be saved by taking advantage of unconventional drafting strategies, a consistent tailwind, a downhill course, and specific running shoe design features while staying within the current International Association of Athletic Federations regulations for record purposes. Specifically, running in shoes that are 100 g lighter along with second-half scenarios of four runners alternately leading and drafting, or a tailwind of 6.0 m/s, combined with a 42-m elevation drop could result in a time well below the 2-hour marathon barrier.

Determinants of aponeurosis shape change during muscle contraction.

Aponeuroses are sheet-like elastic tendon structures that cover a portion of the muscle belly and act as insertion sites for muscle fibers while free tendons connect muscles to bones. During shortening contractions, free tendons are loaded in tension and lengthen due to the force acting longitudinally along the muscle׳s line of action. In contrast, aponeuroses increase in length and width, suggesting that aponeuroses are loaded in directions along and orthogonal to the muscle׳s line of action. Because muscle fibers are isovolumetric, they must expand radially as they shorten, potentially generating a force that increases aponeurosis width. We hypothesized that increases in aponeurosis width result from radial expansion of shortening muscle fibers. We tested this hypothesis by combining in situ muscle-tendon measurements with high-speed biplanar fluoroscopy measurements of the turkey׳s lateral gastrocnemius (n=6) at varying levels of isotonic muscle contractions. The change in aponeurosis width during periods of constant force depended on both the amount of muscle shortening and the magnitude of force production. At low to intermediate forces, aponeurosis width increased in direct proportion to fiber shortening. At high forces, aponeurosis width increased to a lesser extent or in some cases, decreased slightly during fiber shortening. Our results demonstrate that forces generated from radial expansion of shortening muscle fibers tend to drive increases in aponeurosis width, whereas longitudinal forces tend to decrease aponeurosis width. Ultimately, it is these two opposing forces that drive changes in aponeurosis width and alter series elastic stiffness during a muscle contraction.

Fatigue-induced adjustment in antagonist coactivation by old adults during a steadiness task.

The purpose of this study was to determine the adjustments in the level of coactivation during a steadiness task performed by young and old adults after the torque-generating capacity of the antagonist muscles was reduced by a fatiguing contraction. Torque steadiness (coefficient of variation) and electromyographic activity of the extensor and flexor carpi radialis muscles were measured as participants matched a wrist extensor target torque (10% maximum) before and after sustaining an isometric contraction (30% maximum) with wrist flexors to task failure. Time to failure was similar (P = 0.631) for young (417 ± 121 s) and old (452 ± 174 s) adults. The reduction in maximal voluntary contraction torque (%initial) for the wrist flexors after the fatiguing contraction was greater (P = 0.006) for young (32.5 ± 13.7%) than old (21.8 ± 6.6%) adults. Moreover, maximal voluntary contraction torque for the wrist extensors declined for old (-13.7 ± 12.7%; P = 0.030), but not young (-5.4 ± 13.8%; P = 0.167), adults. Torque steadiness during the matching task with the wrist extensors was similar before and after the fatiguing contraction for both groups, but the level of coactivation increased after the fatiguing contraction for old (P = 0.049) but not young (P = 0.137) adults and was twice the amplitude for old adults (P = 0.002). These data reveal that old adults are able to adjust the amount of antagonist muscle activity independent of the agonist muscle during steady submaximal contractions.

Effect of running speed and leg prostheses on mediolateral foot placement and its variability.

This study examined the effects of speed and leg prostheses on mediolateral (ML) foot placement and its variability in sprinters with and without transtibial amputations. We hypothesized that ML foot placement variability would: 1. increase with running speed up to maximum speed and 2. be symmetrical between the legs of non-amputee sprinters but asymmetrically greater for the affected leg of sprinters with a unilateral transtibial amputation. We measured the midline of the body (kinematic data) and center of pressure (kinetic data) in the ML direction while 12 non-amputee sprinters and 7 Paralympic sprinters with transtibial amputations (6 unilateral, 1 bilateral) ran across a range of speeds up to maximum speed on a high-speed force measuring treadmill. We quantified ML foot placement relative to the body's midline and its variability. We interpret our results with respect to a hypothesized relation between ML foot placement variability and lateral balance. We infer that greater ML foot placement variability indicates greater challenges with maintaining lateral balance. In non-amputee sprinters, ML foot placement variability for each leg increased substantially and symmetrically across speed. In sprinters with a unilateral amputation, ML foot placement variability for the affected and unaffected leg also increased substantially, but was asymmetric across speeds. In general, ML foot placement variability for sprinters with a unilateral amputation was within the range observed in non-amputee sprinters. For the sprinter with bilateral amputations, both affected legs exhibited the greatest increase in ML foot placement variability with speed. Overall, we find that maintaining lateral balance becomes increasingly challenging at faster speeds up to maximum speed but was equally challenging for sprinters with and without a unilateral transtibial amputation. Finally, when compared to all other sprinters in our subject pool, maintaining lateral balance appears to be the most challenging for the Paralympic sprinter with bilateral transtibial amputations.

The metabolic cost of human running: is swinging the arms worth it?

Although the mechanical function is quite clear, there is no consensus regarding the metabolic benefit of arm swing during human running. We compared the metabolic cost of running using normal arm swing with the metabolic cost of running while restricting the arms in three different ways: (1) holding the hands with the arms behind the back in a relaxed position (BACK), (2) holding the arms across the chest (CHEST) and (3) holding the hands on top of the head (HEAD). We hypothesized that running without arm swing would demand a greater metabolic cost than running with arm swing. Indeed, when compared with running using normal arm swing, we found that net metabolic power demand was 3, 9 and 13% greater for the BACK, CHEST and HEAD conditions, respectively (all P<0.05). We also found that when running without arm swing, subjects significantly increased the peak-to-peak amplitudes of both shoulder and pelvis rotation about the vertical axis, most likely a compensatory strategy to counterbalance the rotational angular momentum of the swinging legs. In conclusion, our findings support our general hypothesis that swinging the arms reduces the metabolic cost of human running. Our findings also demonstrate that arm swing minimizes torso rotation. We infer that actively swinging the arms provides both metabolic and biomechanical benefits during human running.

Partitioning the metabolic cost of human running: a task-by-task approach.

Compared with other species, humans can be very tractable and thus an ideal "model system" for investigating the metabolic cost of locomotion. Here, we review the biomechanical basis for the metabolic cost of running. Running has been historically modeled as a simple spring-mass system whereby the leg acts as a linear spring, storing, and returning elastic potential energy during stance. However, if running can be modeled as a simple spring-mass system with the underlying assumption of perfect elastic energy storage and return, why does running incur a metabolic cost at all? In 1980, Taylor et al. proposed the "cost of generating force" hypothesis, which was based on the idea that elastic structures allow the muscles to transform metabolic energy into force, and not necessarily mechanical work. In 1990, Kram and Taylor then provided a more explicit and quantitative explanation by demonstrating that the rate of metabolic energy consumption is proportional to body weight and inversely proportional to the time of foot-ground contact for a variety of animals ranging in size and running speed. With a focus on humans, Kram and his colleagues then adopted a task-by-task approach and initially found that the metabolic cost of running could be "individually" partitioned into body weight support (74%), propulsion (37%), and leg-swing (20%). Summing all these biomechanical tasks leads to a paradoxical overestimation of 131%. To further elucidate the possible interactions between these tasks, later studies quantified the reductions in metabolic cost in response to synergistic combinations of body weight support, aiding horizontal forces, and leg-swing-assist forces. This synergistic approach revealed that the interactive nature of body weight support and forward propulsion comprises ∼80% of the net metabolic cost of running. The task of leg-swing at most comprises ∼7% of the net metabolic cost of running and is independent of body weight support and forward propulsion. In our recent experiments, we have continued to refine this task-by-task approach, demonstrating that maintaining lateral balance comprises only 2% of the net metabolic cost of running. In contrast, arm-swing reduces the cost by ∼3%, indicating a net metabolic benefit. Thus, by considering the synergistic nature of body weight support and forward propulsion, as well as the tasks of leg-swing and lateral balance, we can account for 89% of the net metabolic cost of human running.