Background: Acute ankle sprain may affect ankle function during sport and daily activities. This study aimed to use vector coding technique to analyze the difference over time between injured and healthy lower limb during the first week of acute ankle sprain phase (P1) and post a 1-month recovery phase (P2) to understand the return-to-play coordination strategy in the lower extremity. Methods: Six females attended the gait experiments with attached 40 reflective markers using eight camera Vicon motion capture system. All participants walked barefoot while turning in four directions (T0°, T45°, T90°, T135°) at their self-selected speed. Coordination patterns were classified as in-phase, anti-phase, proximal or distal dominancy between lower limb joints involving hip, knee, ankle, subtalar, metatarsophalangeal (MTP) joint and tarsometatarsal (TMT) joint. Results: P1 showed more proximal joint dominant in Hip-Knee coupling angles but P2 displayed more distal joint dominant in Knee-Ankle joint coordination pattern and mainly distal joint dominant in Ankle-MTP coupling angle mapping. The Ankle-TMT1 and Ankle-TMT5 coordination patterns matched best in straight walking but worst in T135 walking. Conclusions: Investigating inter-segmental coordination in different turning movements could provide insights into gait changes from acute ankle sprain from one-month return-to-play recovery. Knowledge of lower limb coordination pattern may provide clinical implications to improve dynamic balance and gait stability for individuals with acute ankle sprain.
Foot pronation is not an isolated factor influencing lower limb functions. Exploring gait variability and impact loading associated with the foot posture are crucial for understanding foot pronation-related injury mechanisms. This study aimed to evaluate how foot posture affects impact loading and running variability during running. Methods: Twenty-five male participants were recruited into this study. Pressure under the foot arch, acceleration and marker trajectory were recorded in the right limb for each runner after 1, 4, 7 and 10 km running, respectively. Linear mixed effects models were used to analyze the statistical difference of the data. Results: FPI-6 has significantly increased after the 10 km running ( p < 0.01). For the tibial acceleration, peak resultant acceleration after 10 km running was significantly increased than after 4 km running ( p = 0.02). At the dorsum of the foot, the short-time largest Lyapunov exponent (LyE) after 10 km running decreased 0.28 bit/s compared with LyE after 7 km running ( p = 0.03). In the tibia, LyE after 4 km and 10 km running was decreased significantly ( p < 0.01 and p = 0.01). Conclusions: The foot was significantly pronated at the middle and at the end of running. Foot pronation during distance running increased the distal tibia peak impact acceleration but did not increase running instability.
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