The concept of running gait analysis is sexy, there I said it! The idea that you can come into a lab with some sports science-y data collection tools on a cool treadmill and get information that could make you a more efficient runner just sounds cool. But in my 5+ years of working with runners and analyzing people’s running gait, it often leaves us with more questions than answers, and can even be kind of frustrating for the runner. Let’s dive into why running gait analysis has left much to be desired over the years, and the big change that has made it actually start living up to the hype.
How could running gait analysis possibly be a waste of time? Think about this. Running is an activity that most people have done for 20+ years before they ever get their gait analyzed. By the time we are analyzing their gait, they have been using their motor plan for running for a very long time, and getting them to change it can be challenging and frustrating for the runner, especially if the things that we change don’t yield the results that the runner is looking for. Take pronation for example. Pronation is the movement of the arch of the foot towards the ground, and is necessary for normal shock absorption. However, it is also a common movement that people try to correct, because it can cause some position faults in the knee and hip. But how much is too much? And if we have a runner work on foot exercises every day for 4 weeks and their pronation isn’t “better”, they might completely lose motivation.
With this information in mind, I’ve been trying to focus on aspects of the running gait that truly make a difference, and that are easier to change. One good example is increasing their steps per minute or cadence to at least 165, which has shown to be an effective way to improve running economy. (1) This is a relatively easy thing to train, because you can listen to a metronome and run to the beat.
Another example is weight acceptance symmetry. This is a visual observation of how well each side absorbs shock. I can usually visualize asymmetries here, but one of the challenges with this metric is that it has always been subjective, which doesn’t give the runner much information about if they are improving over time…
Until now.
Running Gait Analysis With Runeasi
Runeasi is a running gait analysis technology that provides data on dynamic stability, impact magnitude, and impact duration, with symmetry data on each of these parameters. It then compares these metrics to normative data that the company has collected on a wide variety of runners from amateurs to elite. I can honestly say that runeasi has totally changed my approach to running gait analysis, and has allowed me to use objective data to track progress over time of a runners’ gait quality. Here’s what it tells us:
Dynamic stability
This is the amount of movement of your center of gravity side to side vs. forward. A lower percentage indicates better stability in the core muscles.
Impact magnitude
This is the amount of force that your body takes on with each foot fall of the running gait. A higher number indicates more impact taken on by the body and is often found with runners who have a more “bouncy” gait, where a lower number indicates less impact taken on by the body.
Impact duration
This is the amount of time that your body takes to absorb each impact. A longer impact duration means that you are doing a better job of distributing the force of landing throughout your muscles.
This is an absolute game changer for running gait analysis. There are other tools out there that gather objective data about how someone’s body is moving through space, but this tool gathers data about the forces applied to the body, which is really the most important information for determining a runner’s efficiency and injury risk. Here are some examples of runeasi in action:
Case Study
Runner 1 is training for an ultramarathon and has been dealing with some pain in his R arche, L knee, and R hip while running more than 6 miles. His primary sport is weight lifting, specifically olympic lifting, and he came to have a running gait analysis done to see if there is something happening while he is running that is causing his pain. Here are some of his clinical findings:
Decreased standing rotation to the R
Decreased strength and stability with R single leg hop in place
Decreased R lateral hip strength on manual muscle testing
Here is what his score looked like from runeasi:
A couple things to highlight:
Impact duration was shorter on the R side, indicating that his R side is having a more difficult time absorbing and distributing force. This is consistent with what we found on our exam with his single leg hop being limited on the R side.
Dynamic stability was worse on the L side. Often, hip weakness or lack of dynamic stability can contribute to “runner’s knee.” This also correlates with runner 1’s report of L knee pain.
His score at a slower pace was significantly better, indicating that his form breaks down more at higher speeds.
Now let’s take a look at some video of his running gait:
At the end of the session, this client was given an exercise program to work on core/hip stability, and lower leg strength and capacity to improve his dynamic stability and impact tolerance. He was instructed to follow up in a month to see whether the program he was given has achieved the intended results.
At Alterra, we specialize in helping runners resolve any and all of their injuries that limit their running ability or performance. If you're local to Boston's Back Bay area and are interested in learning more about your running gait, we're happy to help! Book a free discovery call to chat with a therapist today.
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Disclaimer: The information in our blog posts is not a substitute for professional medical advice. Consult a healthcare provider before making decisions related to your health. Use our content at your own risk.
Sources
1. Quinn, Timothy J.1; Dempsey, Shauna L.1; LaRoche, Dain P.1; Mackenzie, Allison M.2; Cook, Summer B.1. Step Frequency Training Improves Running Economy in Well-Trained Female Runners. Journal of Strength and Conditioning Research 35(9):p 2511-2517, September 2021. | DOI: 10.1519/JSC.0000000000003206
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