A systematic review of approaches to modelling lower limb muscle forces during gait: Applicability to clinical gait analyses

步态 物理医学与康复 步态周期 计算机科学 步态分析 航程(航空) 生物力学 医学 工程类 运动学 解剖 经典力学 物理 航空航天工程
作者
Ursula Trinler,Kristen Hollands,Richard Jones,Richard Baker
出处
期刊:Gait & Posture [Elsevier BV]
卷期号:61: 353-361 被引量:31
标识
DOI:10.1016/j.gaitpost.2018.02.005
摘要

Computational methods to estimate muscle forces during walking are becoming more common in biomechanical research but not yet in clinical gait analysis. This systematic review aims to identify the current state-of-the-art, examine the differences between approaches, and consider applicability of the current approaches in clinical gait analysis. A systematic database search identified studies including estimated muscle force profiles of the lower limb during healthy walking. These were rated for quality and the muscle force profiles digitised for comparison. From 13.449 identified studies, 22 were finally included which used four modelling approaches: static optimisation, enhanced static optimisation, forward dynamics and EMG-driven. These used a range of different musculoskeletal models, muscle-tendon characteristics and cost functions. There is visually broad agreement between and within approaches about when muscles are active throughout the gait cycle. There remain, considerable differences (CV 7%–151%, range of timing of peak forces in gait cycle 1%–31%) in patterns and magnitudes of force between and within modelling approaches. The main source of this variability is not clear. Different musculoskeletal models, experimental protocols, and modelling approaches will clearly have an effect as will the variability of joint kinetics between healthy individuals. Limited validation of modelling approaches, particularly at the level of individual participants, makes it difficult to conclude if any of the approaches give consistently better estimates than others. While muscle force modelling has clear potential to enhance clinical gait analyses future research is needed to improve validation, accuracy and feasibility of implementation in clinical practice.

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