A Novel Lower-Limb Coordination Assessment Scheme Using Multi-Scale Nonlinear Coupling Characteristics with sEMG

• Published in: IEEE transactions on instrumentation and measurement Vol. 72; p. 1
• Main Authors: Tu, Pengjia, Li, Junhuai, Wang, Huaijun, Li, Yuxin, Xiang, Wei
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.01.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Coherence; Coordination; Coupling; Couplings; Decomposition; differential evolution algorithm; Electromyography; Evolutionary algorithms; Evolutionary computation; Feature extraction; Females; Global optimization; intermuscular coherence; Legged locomotion; Lower-limb coordination; Males; Muscles; Optimization; Provisioning; surface electromyography; Time-frequency analysis; variational mode decomposition
• ISSN: 0018-9456; 1557-9662
• DOI: 10.1109/TIM.2023.3246490

Motor dysfunction (e.g., incoordination of upper or lower limb) significantly limits the individuals' ability of daily living, and thus the provisioning of a motion coordination assessment method becomes of vital importance. As a quantitative indicator, inter-muscular coupling strength could assess limb coordination. Since surface electromyography (sEMG) signals cover nonlinear coupling characteristics, in this paper, a lower-limb motion coordination assessment scheme with intermuscular coherence (IMC) analysis and optimization variational mode decomposition (VMD) is proposed. First, sEMG signals are decomposed into several intrinsic mode functions (IMFs) using optimized VMD. Then, the nonlinear coupling feature vector in the beta-band frequency domian (15-35Hz) is extracted by the G-P algorithm from optimal IMF, thereby estimating intermuscular coupling strength by IMC. In particular, differential evolution (DE) algorithm's global optimization capability and envelope entropy (EE)'s sparsity are adopted to provide the basis for optimization VMD and screening optimal IMF, respectively. Finally, signals are collected from four muscle pairs of the 12 male and 12 female subjects to assess lower-limb motions coordination. Simultaneously, the independent sample T test is leveraged to compare the effects of gender on groups' characteristics (e.g., age, height, and body mass). Results demonstrate not only the effectiveness of the proposed approach (i.e., p < 0.01 with both "S-walking" and "Running" motions, p < 0.05 with "Q-walking"), but also the difference of motion coordination relationship between male and female adults as well as the significance of muscle selection.