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Standardizing Ankle Position During the Active Straight Leg Raise: Effects on Lateral Abdominal Muscle Thickness and Pressure Biofeedback in Healthy Young Adults

Aug 2026 · Journal of Functional Morphology and Kinesiology · Vol 11 · 0 citations · 20 references
Medicine

Abstract

Background and Objectives: Ankle instructions during the active straight leg raise (ASLR) are not consistently standardized and may alter lumbopelvic measurements. This study tested whether a relaxed ankle, maximal active dorsiflexion (DF), and maximal active plantarflexion (PF) changed lateral abdominal muscle thickness and pressure biofeedback unit (PBU) responses during a standardized supine ASLR performed at 30° of hip flexion. Methods: Thirty-three healthy adults completed three trials per condition according to a pre-specified schedule containing all six possible condition orders. B-mode rehabilitative ultrasound imaging (RUSI) measured transversus abdominis (TrA), internal oblique (IO), and external oblique (EO) thickness at rest and during ASLR. Three end-expiratory images were acquired for each participant, condition, and state; each image was measured three times, and the three image means were averaged. Rest-to-ASLR changes yielded 99 participant-condition values. Pressure biofeedback unit (PBU) pressure was recorded at four prespecified events and analyzed at the trial level. Results: Across participant-condition means, TrA thickness was 2.44 ± 0.59 mm at rest and 2.66 ± 0.70 mm during ASLR; the largest observed mean was 4.46 mm under the study task, not a physiological maximum. DF increased the change in transversus abdominis thickness (ΔTrA) versus the relaxed ankle by 0.172 mm (95% CI, 0.077–0.267; p < 0.001) and total lateral abdominal wall change by 0.672 mm (95% CI, 0.413–0.931; p < 0.001). PF increased signed image-moment pressure deviation by 1.505 mmHg (95% CI, 0.985–2.025; p < 0.001). Conclusions: Ankle-position instructions changed ultrasound and PBU outcomes during ASLR. Standardizing ankle positioning instructions and image aggregation may improve measurement reproducibility.

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