Every so often interesting ideas for gait assessment appear in my head. Either by me connecting some metaphorical dots together or because the subject approaches me and by coincidence they also present a unique and intriguing case. If it’s an area that I’ve not had the chance to study before, then my psych level immediately multiplies. This week was one such week. A sudden flash of random thought zipped across my consciousness – the person I am talking to right now, like many women I seem to keep hanging around lately, is pregnant. And she is also a runner. Next thought – Has anyone performed a running gait analysis during a pregnancy before? Well, certainly I’d never heard of anything published so far on the topic.
Luckily there was a crucial piece of additional information to this story. I had already collected data from this runner before the start of her pregnancy, likely 1-2 months before. Hence the idea unfolded and next day she was running and I was collecting data.
To keep the two datasets relatively comparable I used all of the same sensor technology, the recording period was approximately the same and the runner ran at approximately the same pace and on the same surface. In both assessments I also filtered the data to the same portion of the overall workout.
What I present below are snapshots of the high level results from the two assessments. In additional to the tibial sensors that collected this data the runner also wore sensors around the foot/ankle area to ensure that foot and ankle mechanics were roughly consistent across the two tests. In both assessments the foot strike pattern was slightly rearward of the mid-foot, the max pronation angle was approximately 8 degrees and the pronation rate approximately 250-280 deg/s for both feet.
[Data from the assessment just shortly before pregnancy (above). Software: DorsaVi Perform]
[Data from the follow-up assessment 4 and a half months into the pregnancy (above). Software: DorsaVi Perform]
A quick read of the results shows that the average run speed was essentially the same, 6mph. However, the force values are significantly higher in the follow-up ‘pregnancy run’ (approximately let’s say 150N higher). The peak acceleration values are also higher in the pregnancy run at 6g as opposed to 5g (the same bilaterally). The difference in force values between the left and right sides is actually the same in percentage terms in both runs at 5%. What changes though is that the runner goes from higher forces through the right leg to higher forces through the left leg (hence the shift from -5 to 5). Looking at rest of the data we see that the ground contact times reduce in the pregnancy run and the cadence as we would expect, slightly increases.
2 things pop out from this for me:
- Although force increases and ground contact time decrease the runner does not run faster. Thanks to the fact that the runner is approximately 3kg heavier in body mass at the time of the pregnancy run compared to the pre-pregnancy run her force values and acceleration values both increase. This should be good for power generation. However the negative consequence of the extra mass, particularly as it sits in a part of the body that creates significant imbalance/instability, is that the runner now has to move that larger mass. Hence she cannot turn the extra input power into extra output propulsion and stride length.
- There are is an extremely marked shift in her asymmetry from right side dominance to left side dominance at the same magnitude. Given that I know from previous testing that her status quo is normally to be lower body right side dominant this second dataset really stands out. Could it be a new internal compensation for the baby bump? Could the baby be hanging out more on her left side?
Sometimes on this site I will post data that presents quite a clear result or a distinct learning and sometimes I will just post interesting data and ideas for no other reason than to provoke thought and more ideas. This is a case that certainly falls into the latter category. There are definitely no earth shattering conclusions from this but it could be an area for further future study. As my ex-NASA high school physics teacher used to say in class: ‘you don’t know what you don’t know, so collect some data’. Thanks Dr Lindley, your teachings were not lost on me.