Zambalde Ellen Pereira, Germer Carina Marconi, Molinari Ricardo Gonçalves, Negro Francesco, Dideriksen Jakob, Elias Leonardo Abdala
Department of Electronics and Biomedical Engineering, School of Electrical and Computer Engineering, University of Campinas, Campinas, SP, Brazil.
Neural Engineering Research Laboratory, Center for Biomedical Engineering, University of Campinas, Campinas, SP, Brazil.
Eur J Appl Physiol. 2025 Jul 1. doi: 10.1007/s00421-025-05880-5.
We employed an optimization method for the approximate entropy (ApEn) parameters ( , ) to evaluate the influence of changes in contraction intensity, visual feedback conditions, and joint angles in force ApEn during an isometric force-matching task.
Seventeen participants performed an index finger abduction isometric force task in six contraction intensities (5-75% of maximum voluntary contraction, MVC), with and without visual feedback of the force, and in three different metacarpophalangeal (MCP) joint angles. Force variability, complexity (ApEn), and power spectrum density (PSD) were assessed, and a correlation analysis was performed between these variables.
The best ApEn ( , ) pair for muscle force analysis was and force standard deviation (SD). Visual feedback influenced the ApEn; however, the comparison between experimental conditions (force intensity and joint angle) was similar. Both the force ApEn and the coefficient of variation (CoV) were reduced as a function of contraction intensity and without visual feedback. Conversely, the force SD and the PSD in the low-frequency band increased with contraction intensity and the absence of visual feedback. The changes in the MCP joint angle affected the MVC values and force CoV, with no significant effect on the force ApEn. The PSD in the low-frequency band (< 5 Hz) showed a strong negative correlation with force ApEn in both visual feedback conditions.
ApEn is influenced by force level and visual feedback, and it is strongly correlated with low-frequency force oscillations, which are related to the muscle's common drive.
我们采用一种优化方法来确定近似熵（ApEn）参数（ ， ），以评估在等长力匹配任务中，收缩强度、视觉反馈条件和关节角度变化对力ApEn的影响。
17名参与者进行食指外展等长力任务，收缩强度分为六种（最大自主收缩的5 - 75%，MVC），分别在有和没有力的视觉反馈的情况下，以及在三个不同的掌指（MCP）关节角度下进行。评估了力的变异性、复杂性（ApEn）和功率谱密度（PSD），并对这些变量进行了相关性分析。
用于肌肉力分析的最佳ApEn（ ， ）参数对是 和力标准差（SD）。视觉反馈影响ApEn；然而，实验条件（力强度和关节角度）之间的比较是相似的。随着收缩强度增加且无视觉反馈时，力ApEn和变异系数（CoV）均降低。相反，力SD和低频带的PSD随着收缩强度增加且无视觉反馈时而增加。MCP关节角度的变化影响MVC值和力CoV，对力ApEn无显著影响。在两种视觉反馈条件下，低频带（< 5 Hz）的PSD与力ApEn均呈强负相关。
ApEn受力水平和视觉反馈影响，且与低频力振荡密切相关，而低频力振荡与肌肉的共同驱动有关。
