The Walk of Life
You’re a pedestrian during the downtown rush hour. As you make your way down the sidewalk and approach the curb, you see the white walk sign change to a flashing red hand. In a rush, you step foot onto the asphalt and traverse the pedestrian-flooded crosswalk. You make it across the street, catch your bus and arrive home in time for dinner. Simple. Or is it?
During the process of walking, more than 1000 muscles work together to move over 200 bones around 100 moveable joints. We often don’t give it a second thought when it comes to performing seemingly simple tasks, like crossing the street. However, how we walk and how fast we do it has, in recent years, become of great interest, especially when we consider older adults, and their ability to safely navigate their neighbourhoods and communities.
Although for many people the time to walk across the street may seem adequate, these times are based on a walking speed of 1.2 m/s which surpasses the normal walking speed of 0.86 m/s of many older adults. This finding can be quite troubling, as the ability to engage with the built environment (including crossing the street) is an important part of independence and mobility for older adults.
However, limited time to cross the street isn’t the only concern to the safety of older adults in the community; the way we walk is equally important. Many existing studies evaluate street crossing behaviour in terms of gait or walking speed, but overlook other important issues. Factors such as step length, step time and step variability are critical to better understand how a person crosses the street, but these can be difficult to measure in practice. That’s where computerized walkways come in.
An example of such a computerized walkway is GAITRite, a specialized mat that contains over 18,000 pressure sensors and software to measure walking patterns in terms of both time and space. The software can convert this walking information into foot placement patterns; the distance and time between steps, pressure applied by different areas of the foot, and variation in direction are all captured by the mat and software.
So why is such detailed information important? Emerging evidence shows that increased step-to-step changes can affect balance when walking and could lead to increased risk for falls. To further investigate these findings, we used the specialized mat to explore the way that older adults change their walking during a crosswalk simulation, compared to their normal walking patterns. Existing evidence shows that multitasking while walking can significantly increase step variability, further spurring our research into walking in crosswalk scenarios. That being said, our investigations are often limited to a controlled lab environment, so how does our walking and our risk of falling change when we add factors like other pedestrians into the mix? How about turning cars? Uneven walking surfaces? The list goes on. Certainly, as technology continues to advance, we will have more insight into changes in walking in different environments. For now, these are just some things to think about the next time you find yourself crossing the road.
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- Menz HB et al. Reliability of the GAITRite walkway system for the quantification of temporo-spatial parameters of gait in young and older people. Gait and Posture. 2011; 40(4):481-7.
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- Springer S et al. Dual tasking effects on walking variability: The role of aging, falls, and executive function. Movement Disorders. 2006;21(4):950-7.