Lab versus Field-Based Movement Kinematics

📝 Weekly paper summary

Comparing lab and field agility kinematics in young talented female football players: Implications for ACL injury prevention (Di Paolo et al., 2022)

Category

Cross-Sectional Study

Context

A challenge with any movement assessments is extrapolating how people move in a controlled lab or gym-based environment to sporting contexts. However, given that the sporting environment can influence the coordination patterns that emerge, examining just how much we can extrapolate from lab-based contexts when conducting movement assessments is vital. Therefore, this study aimed to compare lower-limb kinematics in female athletes during cutting tasks in a laboratory, when performing soccer-specific cutting exercises on a field, and when playing a soccer game.

Correctness

Pros

• 28 participants is a good sample size for this type of biomechanical analysis
• Integrating perception and action into these types of research questions is critical given the recent push in the literature to move away from simple drop vertical jump tasks due to the relationships between perceptual-motor skills and ACL injury risk (e.g., April 5th Newsletter)

Cons

• Although there's nothing inherently wrong with using something like an Xsens suit of IMUs to collect motion data, it does create somewhat of a black box regarding how joint kinematics were measured, filtered, and presented. There's some mention of exporting data to a custom script in MatLab, but again it's hard to know exactly how the researchers processed the data.
• Statistical Parametric Mapping is relatively new in the biomechanics literature, and as a result, it's not very "mature" yet. However, I'm unsure about the justification provided for the sample size since the researchers seemed to base it on traditional ANOVAs rather than something specific to these analyses (e.g., PowerMap [paper link])

Contributions

• The researchers found that participants demonstrated less sagittal plane range of motion, greater ankle eversion, and greater pelvic rotations for on-field activities relative to the lab-based movements (i.e., joint motions associated with ACL injury risk were greater in the field-based contexts than in the lab-based contexts).
• Although there were differences in the magnitudes of joint motions between settings, there were still significant (statistically and practically) correlations between the joint motions in different contexts. Therefore, it is still helpful to assess how people move in gym-based contexts to get a general sense of their movement behaviours, but we should expect worse motions in the field.
• NOTE: these findings contrast that of Frost et al. (2015), which may be attributable to the increased perceptual demands in sport-specific contexts versus simulated fireground tasks. Ultimately, though, we need more data to understand how to use data from movement assessments to capture individuals' movement behaviours in other contexts.

🧠 Fun fact of the week

Hearing how many stars there are in the night sky, our galaxy, and our universe elicits awe and insignificance. In some ways, feeling so small in the grand scheme of things makes me feel more connected to the other people I share life with.

That's what makes this following fun fact so crazy- there are more trees on earth than there are stars in the Milky Way Galaxy. There are about 100-400 billion stars in our galaxy, but there are approximately 3 trillion trees. Pretty crazy if you ask me!

🎙 Podcast recommendation

The entire podcast is pretty interesting, but in my opinion, the conversation picks up in the last ~45 minutes. If you're interested in HRV or other recovery metrics (think Oura ring, Whoop, etc.), this podcast is for you!

🗣 Quote of the week

"In this life, we're either getting better or we're getting worse."

- David Goggins

What have you done to get better today (besides reading this newsletter 😊)?