ECSS Paris 2023: CP-BM09
INTRODUCTION: The foot arch is a mechanically important structure for human locomotion, and higher arch stiffness allows more efficient utilization of the mechanical energy generated by the ankle joint during the pushing-off. Therefore, understanding the characteristics of the foot arch can provide important insights into human locomotor performance. Among the foot arch, medial longitudinal arch (MLA) has been extensively studied, whereas research focusing on the transverse tarsal arch (TTA) remains limited. However, recent study has reported that, in terms of contributions to foot arch stiffness, MLA curvature accounts for approximately 25%, whereas TTA curvature accounts for approximately 50% (Venkadesan et al., 2020). It was suggested that the morphology of the TTA during running may be an important factor associated with running performance and running-related injuries. Accordingly, the purpose of this study was to clarify the morphology of the foot arch in long-distance runners and its relationship with running performance, with a focus on both the MLA and TTA. METHODS: Thirty-nine male middle- and long-distance runners participated in this study. Magnetic resonance (MR) images of the dominant foot were acquired at 0.3 T. From the obtained foot MR images, MLA height and TTA curvature, estimated from the torsion of the fourth metatarsal and foot morphology. To account for potential changes in the foot morphology by training, relationships between MLA and TTA morphology and performance were examined using 5,000-m personal best times recorded within ±1 month of the MR measurement date. Statistical analyses included Pearson’s correlation analysis, simple linear regression analysis, and multiple regression analysis incorporating polynomial terms. The contribution of each explanatory variable to the 5,000-m performance was evaluated using the change in the coefficient of determination (ΔR²). The level of statistical significance was set at 0.05. RESULTS: Simple regression analysis revealed a significant U-shaped relationship between the 5,000-m performance and TTA curvature (R² = 0.23, p = 0.040). Furthermore, a multiple regression model incorporating polynomial terms was constructed with TTA curvature and MLA height as explanatory variables, which explained 21% of the variance in 5,000-m performance time (p = 0.049). Block-wise analysis demonstrated that TTA curvature provided an additional explanation for 16.5% of the variance in performance, while MLA height also contributed 13.2% to the explained variance. CONCLUSION: Among the foot arch morphology of long-distance runners, the TTA showed a greater contribution to competitive performance than the MLA, explaining 16.5% and 13.2% of the variance, respectively. In addition, a U-shaped relationship was observed between competitive performance and TTA curvature, indicating the existence of an optimal curvature value (estimated at approximately 24.3 m⁻¹).
Read CV Keiichiro HataECSS Paris 2023: CP-BM09
INTRODUCTION: Recent advances in pose estimation AI enable quantitative movement analysis, but field-based analysis of children’s running remains technically challenging due to occlusions, tracking instability, and environmental noise. Raw AI outputs often lack sufficient reliability for direct movement evaluation. This study aimed to develop and validate a foundational technical pipeline to stably extract evaluation features from children’s running videos recorded in field settings, with particular emphasis on robustness under real-world conditions. METHODS: A total of 59 image sequences (118 runners) were analyzed. Person detection utilized a retrained YOLOv11 model (Precision = 1.000, Recall = 0.994, mAP@0.5 = 0.995), ensuring stable lower-limb detection. Pose estimation was performed with RTMPose to obtain frame-wise joint coordinates. A custom algorithm corrected tracking interruptions, joint outliers, and left–right swaps by applying temporal continuity constraints alongside joint-angle and segment-length consistency checks. To represent key components of overall running movement quality, five categories of evaluation features were extracted: thigh/knee angles at maximal knee lift; trunk inclination from shoulder–hip midpoint slope; maximal forward, upward, and backward elbow positions; peak swing-leg ankle height; and running cycle temporal durations defined by phase transitions in joint trajectories. RESULTS: Complete body overlap in six sequences prevented reliable identification of two runners. In five cases involving limb crossing, pose estimation remained accurate after applying the correction algorithm. Right-ankle estimation deteriorated in eight runners under shadow conditions; however, these misestimations occurred outside the specific evaluation frames and therefore had minimal impact on feature extraction. Overall, the system demonstrated robustness under partial occlusion, whereas complete body overlap remained a primary constraint. CONCLUSION: The findings indicate that performance limitations arise mainly under severe occlusion rather than moderate limb interaction. Integration of detection refinement, temporal correction, and biomechanically informed filtering substantially improved stability compared to raw pose estimation outputs. The proposed framework mitigated common field-based errors, enabling consistent extraction of running-related features in most real-world conditions. This technical foundation represents a critical step toward the development of an automated digital coaching system capable of assessing movement quality and providing structured feedback in natural training environments. Future work will focus on environment-specific correction strategies, including shadow compensation, occlusion-aware modeling, and real-time implementation to further enhance robustness and scalability.
Read CV Shohei KokudoECSS Paris 2023: CP-BM09
INTRODUCTION: Ultra-trail running is characterized by prolonged duration, repeated downhill sections, and substantial cumulative eccentric loading on the knee extensor complex and surrounding connective tissues (1). Although physiological and performance responses to ultra-endurance running have been widely investigated, mechanical adaptations of knee muscles and connective tissues remain unclear. The aim of this study was to compare the mechanical properties of Quadriceps, knee exstensor and flexor muscle strength, and dynamic balance between ultra-trail runners and age- and sex-matched healthy controls. METHODS: A total of 36 participants (3 Female and 15 Male for each group) were included in this cross-sectional study, consisting of 18 ultra-trail runners (mean age 42.00±7.03 years; mean BMI 24.26±2.06 kg/m²) and 18 age- and sex-matched controls (mean age 42.33±6.93 years; mean BMI 25.59±3.85 kg/m²). Among the ultra-trail runners, the mean longest completed race distance was 76.61±30.96 km.The mechanical properties (tone (F), stiffness (S) and creep (C)) of the quadriceps muscle were assessed using a MyotonPRO device. Measurements were obtained from the rectus femoris, vastus lateralis, and vastus medialis obliquus components of the quadriceps muscle, as well as the iliotibial band and the patellar tendon. Knee extensor and flexor muscle strength were evaluated with a handheld dynamometer. Dynamic balance was assessed using the Y Balance Test, and a composite score was calculated from anterior, posterolateral, and posteromedial reach distances.All measurements were performed both the dominant and non-dominant lower extremity. RESULTS: Significant between-group differences were observed in the dominant lower extremity for vastus medialis F (p=0.038) and C (p=0.006), as well as for iliotibial band S (p=0.019) and C (p = 0.021). However, no significant differences were found in the rectus femoris, vastus lateralis, or patellar tendon in the dominant limb (all p>0.05). Furthermore, no significant between-group differences were observed in the non-dominant limb for F, S, or C values of the rectus femoris, vastus lateralis, vastus medialis, iliotibial band, or patellar tendon (all p>0.05). Significant between-group differences were observed in the Y Balance composite scores for both the dominant (p=0.004) and non-dominant limbs (p=0.001). Knee extensor muscle strength demonstrated significant between-group differences in both the dominant and non-dominant limbs, favoring the ultra-trail group (both p<0.001). Likewise, knee flexor muscle strength was significantly greater in the ultra-trail group in the dominant (p<0.001) and non-dominant limbs (p=0.001). CONCLUSION: The findings indicate that chronic exposure to ultra-trail running may induce side-specific mechanical adaptations in periarticular soft tissues, accompanied by enhanced strength and dynamic balance capacity, potentially reflecting sport-specific neuromuscular conditioning.
Read CV Ezgi CelebiECSS Paris 2023: CP-BM09