Haraguchi Naoto, Hase Kazunori
Department of Mechanical Systems Engineering, Tokyo Metropolitan University, Tokyo 191-0065, Japan.
Sensors (Basel). 2024 Apr 27;24(9):2792. doi: 10.3390/s24092792.
The biomechanical-model-based approach with a contact model offers advantages in estimating ground reaction forces (GRFs) and ground reaction moments (GRMs), as it does not rely on the need for training data and gait assumptions. However, this approach faces the challenge of long computational times due to the inclusion of optimization processes. To address this challenge, the present study developed a new optical motion capture (OMC)-based method to estimate GRFs, GRMs, and joint torques without prolonged computational times. The proposed approach performs the estimation process by distributing external forces, as determined by a multibody model, between the left and right feet based on foot deformations, thereby predicting the GRFs and GRMs without relying on optimization techniques. In this study, prediction accuracies during level walking were confirmed by comparing a general analysis using a force plate with the estimation results. The comparison revealed excellent or strong correlations between the prediction and the measurements for all GRFs, GRMs, and lower-limb-joint torques. The proposed method, which provides practical estimation with low computational cost, facilitates efficient biomechanical analysis and rapid feedback of analysis results, contributing to its increased applicability in clinical settings.
基于生物力学模型并带有接触模型的方法在估计地面反作用力(GRF)和地面反作用力矩(GRM)方面具有优势,因为它不依赖于训练数据和步态假设。然而,由于包含优化过程,这种方法面临计算时间长的挑战。为应对这一挑战,本研究开发了一种基于新型光学运动捕捉(OMC)的方法,无需长时间计算就能估计GRF、GRM和关节扭矩。所提出的方法通过根据足部变形在左右脚之间分配由多体模型确定的外力来执行估计过程,从而无需依赖优化技术即可预测GRF和GRM。在本研究中,通过将使用测力台的常规分析与估计结果进行比较,证实了平地上行走时的预测准确性。比较结果显示,所有GRF、GRM和下肢关节扭矩的预测值与测量值之间存在极好或很强的相关性。所提出的方法以低计算成本提供实际估计,便于进行高效的生物力学分析和快速反馈分析结果,有助于其在临床环境中的适用性提高。