Abstract
Anterior knee pain (AKP) is one of the most prevalent musculoskeletal conditions and significantly affects the adolescents’ age group. Modern methods of diagnosis frequently depend on subjective evaluation, which may result in misdiagnoses and suboptimal clinical care. This study aims to investigate, efficacy of accelerometry technology in evaluating knee mechanics and pronated foot posture in subjects with anterior knee pain. To investigate the efficacy of accelerometry technology in routine clinical practice for patients with AKP, find the correlation between accelerometry-derived metrics and traditional clinical measures of knee pain and function, and explore biomechanical impact of pronated foot posture on knee mechanics. This cross-sectional study recruits 20 participants aged 18–45 years with anterior knee pain. Participants undergone baseline evaluation followed that, The ActiGraph GT9X Link accelerometer was used to measure stride length, cadence, acceleration peaks, and movement variability during standardized activities. Data were analyzed using SPSS version 27.0 and MATLAB R2021b, with correlations and multiple regression analyses performed to explore relationships between variables. The results support that, significant correlations were found between accelerometry data and traditional clinical measures of knee outcome measures. Cadence (r = −0.42), Stride length (r = −0.45), and acceleration peaks (r = −0.38) were inversely correlated with VAS pain scores, while movement variability (r = 0.40) was positively correlated. Pronated foot posture was a significant factor of abnormal knee mechanics, with stride length (β = −0.32, p < 0.01), cadence (β = −0.28, p < 0.01), and acceleration peaks (β = −0.30, p < 0.01) affected. Accelerometry is an efficient tool for assessing knee mechanics in patients with AKP, providing objective data that correlates with clinical outcome measures of pain and function. Pronated foot posture significantly influences knee mechanics, emphasizing the need for targeted interventions.
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Kumar, A.A.U., Ramalingam, V., Selvam, S. (2026). Efficacy of Accelerometry Technology in Evaluating Knee Mechanics and Pronated Foot Posture in Subjects with Anterior Knee Pain. In: Kumar, A., Gunjan, V.K., Senatore, S., Hu, YC. (eds) Proceedings of the 6th International Conference on Data Science, Machine Learning and Applications, Volume 2. ICDSMLA2024 2024. Lecture Notes in Electrical Engineering, vol 1529. Springer, Singapore. https://doi.org/10.1007/978-981-95-5835-3_121
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