学术动态：Biomechanical Modeling and Analysis of the Lower-Limb Musculoskeletal System for Hemiplegia: A Pilot Study
MDPI Sensors 论文摘要：Preliminary estimation of lower-limb motor function is important in rehabilitation research, especially for biomechanical assessment of post-stroke hemiplegic gait. However, subject-specific musculoskel
论文标题：Biomechanical Modeling and Analysis of the Lower-Limb Musculoskeletal System for Hemiplegia: A Pilot Study
发布日期：2026-05-25
作者：Kexiang Li, Ye Sun, Chuang Li, Tongzan Guo, Hui Li
DOI：10.3390/s26113353
论文摘要：Preliminary estimation of lower-limb motor function is important in rehabilitation research, especially for biomechanical assessment of post-stroke hemiplegic gait. However, subject-specific musculoskeletal modeling in this population is challenging because standard maximum voluntary contraction (MVC) testing is often unsafe or unreliable for normalizing surface electromyography (sEMG) signals. To address this limitation, a normalized correction coefficient was introduced for pathological sEMG preprocessing, and an improved Hill-type muscle model (iHMM) was established to account for submaximal activation conditions. By combining inverse dynamics, static optimization, and a subject-specific lower-limb dynamic model, the proposed framework was used to estimate musculotendon force, knee joint torque, knee joint kinematics, and shank center-of-mass trajectory. In a preliminary validation involving six hemiplegic subjects, the predicted knee joint torques showed moderate to good agreement with the reference results, with correlation coefficients ranging from 0.724 to 0.807 and RMSE values ranging from 3.872 to 7.814 Nm. These preliminary results support the feasibility of the proposed framework for subject-specific biomechanical analysis of the hemiplegic lower extremity and suggest its potential utility in individualized rehabilitation assessment.
元数据：Crossref 收录的 MDPI Sensors 论文。 DOI: 10.3390/s26113353. Vol. 26, Issue 11. Authors: Kexiang Li, Ye Sun, Chuang Li, Tongzan Guo, Hui Li.
开放许可： https://creativecommons.org/licenses/by/4.0/
原文链接： https://doi.org/10.3390/s26113353
PDF 链接： https://www.mdpi.com/1424-8220/26/11/3353/pdf
来源： MDPI Sensors via Crossref
