Walking, running, and resting under time, distance, and average speed constraints: optimality of walk–run–rest mixtures

Long, Lina; Srinivasan, Manoj

doi:10.1098/rsif.2012.0980

Cited by 71 publications

(72 citation statements)

References 48 publications

(90 reference statements)

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“…The sideways walking metabolic rate increased monotonically with speed v (figure 1b). Similar to normal walking [2,4,10], the total sideways walking metabolic rate per unit mass, _ E (including the resting cost), is approximated well, using least squares, by: _ E ¼ a 0 þ a 2 v 2 : For metabolic rate data pooled over the subject population ( figure 1b) . See the electronic supplementary material, S4 for these coefficients' error estimates.…”

Section: Resultsmentioning

confidence: 99%

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Sideways walking: preferred is slow, slow is optimal, and optimal is expensive

Handford

Srinivasan

2014

Biol. Lett.

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When humans wish to move sideways, they almost never walk sideways, except for a step or two; they usually turn and walk facing forward. Here, we show that the experimental metabolic cost of walking sideways, per unit distance, is over three times that of forward walking. We explain this high metabolic cost with a simple mathematical model; sideways walking is expensive because it involves repeated starting and stopping. When walking sideways, our subjects preferred a low natural speed, averaging 0.575 m s 21 (0.123 s.d.). Even with no prior practice, this preferred sideways walking speed is close to the metabolically optimal speed, averaging 0.610 m s 21 (0.064 s.d.). Subjects were within 2.4% of their optimal metabolic cost per distance. Thus, we argue that sideways walking is avoided because it is expensive and slow, and it is slow because the optimal speed is low, not because humans cannot move sideways fast.

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Section: Resultsmentioning

confidence: 99%

“…Humans walk and run in a manner that approximately minimizes metabolic energy expenditure [1][2][3][4]. However, most evidence for metabolic energy optimality has been for natural gaits, such as walking and running.…”

Section: Introductionmentioning

confidence: 99%

Sideways walking: preferred is slow, slow is optimal, and optimal is expensive

Handford

Srinivasan

2014

Biol. Lett.

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“…In terms of gait parameters such as average stride length, frequency, and width, there are generally multiple combinations that can satisfy a single goal such as walking speed [1–3]. And for a given speed, it has long been observed that the preferred stride length coincides with minimum metabolic energy expenditure [4–6].…”

Section: Introductionmentioning

confidence: 99%

Influence of contextual task constraints on preferred stride parameters and their variabilities during human walking

Ojeda

Rebula

Kuo

et al. 2015

Medical Engineering & Physics

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Walking is not always a free and unencumbered task. Everyday activities such as walking in pairs, in groups, or on structured walkways can limit the acceptable gait patterns, leading to motor behavior that differs from that observed in more self-selected gait. Such different contexts may lead to gait performance different than observed in typical laboratory experiments, for example, during treadmill walking. We sought to systematically measure the impact of such task constraints by comparing gait parameters and their variability during walking in different conditions over-ground, and on a treadmill. We reconstructed foot motion from foot-mounted inertial sensors, and characterized forward, lateral and angular foot placement while subjects walked over-ground in a straight hallway and on a treadmill. Over-ground walking was performed in three variations: with no constraints (self-selected, SS); while deliberately varying walking speed (self-varied, SV); and while following a toy pace car programmed to vary speed (externally-varied, EV). We expected that these conditions would exhibit a statistically similar relationship between stride length and speed, and between stride length and stride period. We also expected treadmill walking (TM) would differ in two ways: first, that variability in stride length and stride period would conform to a constant-speed constraint opposite in slope from the normal relationship; and second, that stride length would decrease, leading to combinations of stride length and speed not observed in over-ground conditions. Results showed that all over-ground conditions used similar stride length-speed relationships, and that variability in treadmill walking conformed to a constant-speed constraint line, as expected. Decreased stride length was observed in both TM and EV conditions, suggesting adaptations due to heightened awareness or to prepare for unexpected changes or problems. We also evaluated stride variability in constrained and unconstrained tasks. We observed that in treadmill walking, lateral variability decreased while forward variability increased, and the normally-observed correlation between wider foot placement and external foot rotation was eliminated. Preferred stride parameters and their variability appear significantly influenced by the context and constraints of the walking task.

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“…by avoiding unnecessary high velocities [31,32]. Another possibility to save energy is to take short routes to the destination (see Fig.…”

Section: Preference For the Shortest Pathmentioning

confidence: 99%

Oppilatio+ - A data and cognitive science based approach to analyze pedestrian flows in networks

et al. 2017

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Public transport services are a widespread and environmentally friendly option for mobility. In the majority of cases, passengers of public transport services will have to walk from a subway, train, or bus station to their desired travel destination. In an urban environment with a network of narrow streets, this can lead to crowd congestions during rush hour, due to the fact that passengers tend to arrive in waves. In order to monitor and analyze such crowding behavior, city planners, crowd managers, and organizers of public events must ascertain which routes these pedestrians will take from the respective station to their destination. The Oppilatio + approach is suitable for solving this problem. It is an easy-to-apply approach to predict way-finding behavior with a minimal set of information. The necessary data includes the schedule of incoming transport vehicles at the stations and the time-stamped count of pedestrians at the respective destinations. Under these conditions, the Oppilatio + approach is suitable for estimating the distribution of pedestrians on all possible walkways between stations and destinations. This information helps crowd control experts to recognize weak spots in the infrastructure and help event organizers to ensure an undisturbed arrival at their event. We validated our approach using two field experiments. The first one was a field study on a public event, and the second one was a case study for a large Swiss train station.

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Walking, running, and resting under time, distance, and average speed constraints: optimality of walk–run–rest mixtures

Cited by 71 publications

References 48 publications

Sideways walking: preferred is slow, slow is optimal, and optimal is expensive

Sideways walking: preferred is slow, slow is optimal, and optimal is expensive

Influence of contextual task constraints on preferred stride parameters and their variabilities during human walking

Oppilatio+ - A data and cognitive science based approach to analyze pedestrian flows in networks

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