User:Richgellis/sandbox





Preferred Walking Speed is the speed at which humans or other animals choose to walk. In the absence of significant external factors, humans tend to walk at approximately ~1.4 m/s (3.1 MPH). Although humans are capable of walking at speeds from nearly 0 m/s to upwards of 2.5 m/s, humans typically choose to use only a small range within these speeds. Individuals find exceptionally fast or slow speeds uncomfortable. The preferred walking speed of healthy humans is normally distributed with a standard deviation of 0.1 m/s (0.22 MPH). Horses have also demonstrated normal, narrow distributions of preferred walking speed within a given gait, which suggests that the process of speed selection may follow similar patterns across species. Preferred walking speed has important clinical applications as an indicator of mobility and independence. For example, elderly or people suffering from osteoarthritis prefer to walk more slowly. Improving (increasing) preferred walking speed has therefore been a significant clinical goal in these populations.

People have suggested mechanical, energetic, physiological and psychological factors as contributors to speed selection. Likely, individuals face a tradeoff between the numerous costs associated with locomotion and select a speed which minimizes these costs. For example, humans may trade off time to destination, which is minimized at fast walking speeds, and metabolic rate, muscle force or joint stress, which are minimized at slow walking speeds. Broadly, increasing value of time, motivation, or metabolic efficiency may cause people to walk more quickly. Conversely, aging, joint pain, instability, incline, metabolic rate and visual gain cause people to walk more slowly.

Value of Time


Economic theory suggests that individuals place have some value of time. For walks of a fixed distance, you can minimize the time to destination by walking more quickly. Unlike other possible determinants of preferred walking speed, which become less favorable at higher speeds, time to destination becomes more favorable (less time spent walking) with increasing speed. Value of time therefore likely represents a key factor influencing preferred walking speed. Levine and Norenzayan (1999) demonstrated that preferred walking speed is positively correlated with per capita GDP and with purchasing power parity. People living in more affluent places and therefore with higher economic values to their time generally walk more quickly. In the other direction, individuals suffering from major depression may ascribe lower values to their own time and correspondingly prefer to walk significantly slower than healthy controls.

This idea is broadly consistent with common intuition. Everyday situations often change the value of time. For example, when walking to catch a bus, arriving marginally after the bus has left may result in a relatively long wait. Here, the value of the one minute immediately before the bus has departed may be worth 30 minutes of time (the time saved not waiting for the next bus). The idea of walking or running to catch a bus has become almost cliché. Supporting this idea, Darley and Bateson show that individuals who are “hurried” under experimental conditions are less likely to stop in response to a distraction and arrive at their destination sooner.

Energetics
Energy minimization is widely considered a primary goal of the central nervous system. The rate at which a human expends metabolic energy while walking (gross metabolic rate) increases curvilinearly with increasing speed. However, humans also require a continuous basal metabolic rate to maintain normal function. The energetic cost of walking itself is therefore best understood by subtracting basal metabolic rate from gross metabolic rate, yielding net metabolic rate. In human walking, net metabolic rate also increases curvilinearly with speed. These measures of walking energetics are based on how much oxygen people consume per unit time. Many locomotion tasks, however, require walking a fixed distance rather than for a set time. Dividing gross metabolic rate by walking speed results in gross cost of transport. For human Walking, gross cost of transport is U-shaped. Similarly, dividing net metabolic rate by walking speed yields a U-shaped net cost of transport. These curves reflect the cost of moving a given distance at a given speed and may better reflect the energetic cost associated with walking.

Ralston (1958) showed that humans tend to walk at or near the speed that minimizes gross cost of transport. He showed that gross cost of transport is minimized at approximately 1.23 m/s (2.75 MPH), which corresponded to the preferred speed of his subjects. Supporting this, Wickler et al (2000) showed that the preferred speed of horses both uphill and on the level corresponds closely to the speed that minimizes their gross cost of transport. Among other gait costs that human walkers choose to minimize, this observation has led many to suggest that people minimize cost and maximize efficiency during locomotion (Alexander 2002). Because gross cost of transport includes velocity, gross cost of transport includes an inherent value of time. Subsequent research suggests that individuals may walk marginally faster than the speed that minimizes gross cost of transport under some experimental setups, although this may be due to how preferred walking speed was measured. In contrast, other researchers have suggested that gross cost of transport may not represent the metabolic cost of walking. People must continue to expend their basal metabolic rate regardless of whether or not they are walking, suggesting that the metabolic cost of walking should not include basal metabolic rate. Some researchers have therefore used net metabolic rate instead of gross metabolic rate to characterize the cost of locomotion. Net cost of transport reaches a minimum at approximately 1.05 m/s (2.35 MPH). Healthy pedestrians walk faster than this under many situations.

Gross metabolic rate may also directly limit preferred walking speed. Aging is associated with reduced aerobic capacity (reduced VO2 max). For example 80-year-old individuals are walking at 60% of their VO2 max even when walking at speeds significantly slower those observed in younger individuals. Malatesta et al. (2004) suggests that walking speed in elderly individuals is limited by aerobic capacity; elderly individuals are unable to walk faster because they cannot sustain that level of activity.

Biomechanics
Biomechanical factors such as mechanical work, stability, and joint or muscle forces may also influence human walking speed. Walking faster requires additional external mechanical work per step. Similarly, swinging the legs relative to the center of mass requires some internal mechanical work. As faster walking is accomplished with both longer and faster steps, internal mechanical work also increases with increasing walking speed. Therefore, both internal and external mechanical work per step increases with increasing speed. Individuals may try to reduce either external or internal mechanical work by walking more slowly, or may select a speed at which mechanical energy recovery is at a maximum.

Stability may be another factor influencing speed selection. Hunter et al.(2010) showed that individuals use energetically suboptimal gaits when walking downhill. He suggests that people may instead be choosing gait parameters that maximize stability while walking downhill. This suggests that under adverse conditions such as down hills, gait patterns may favor stability over speed.

Individual joint and muscle biomechanics also directly affect walking speed. Norris showed that elderly individuals walked faster when their ankle extensors were augmented by an external pneumatic muscle. Muscle force, specifically in the gastrocnemius and/or soleus may limit walking speed in certain populations and lead to slower preferred speeds. Similarly, patients with ankle osteoarthritis walked faster after a complete ankle replacement then before. This suggests that reducing joint reaction forces or joint pain may factor into speed selection.

Visual Flow
The rate at which the environment flows past the eyes seems to be a mechanism for regulating walking speed. In virtual environments, the gain on visual flow can be decoupled from a person’s actual walking speed, much as one might experience when walking on a conveyor belt. There, the environment flows past an individual more quickly than their walking speed would predict (higher than normal visual gain). At higher virtual than normal visual gains, individuals prefer to walk more slowly, while at lower than normal visual gains, individuals prefer to walk more quickly (Mohler 2007).