Koopman Axel S, Kingma Idsart, Faber Gert S, Bornmann Jonas, van Dieën Jaap H
Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, The Netherlands.
Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, The Netherlands.
J Biomech. 2018 Mar 21;70:242-248. doi: 10.1016/j.jbiomech.2017.10.001. Epub 2017 Oct 12.
Mechanical loading of the spine has been shown to be an important risk factor for the development of low-back pain. Inertial motion capture (IMC) systems might allow measuring lumbar moments in realistic working conditions, and thus support evaluation of measures to reduce mechanical loading. As the number of sensors limits applicability, the objective of this study was to investigate the effect of the number of sensors on estimates of L5S1 moments. Hand forces, ground reaction forces (GRF) and full-body kinematics were measured using a gold standard (GS) laboratory setup. In the ambulatory setup, hand forces were estimated based on the force plates measured GRF and body kinematics that were measured using (subsets of) an IMC system. Using top-down inverse dynamics, L5S1 flexion/extension moments were calculated. RMSerrors (Nm) were lowest (16.6) with the full set of 17 sensors and increased to 20.5, 22 and 30.6, for 8, 6 and 4 sensors. Absolute errors in peak moments (Nm) ranged from 17.7 to 16.4, 16.9 and 49.3 Nm, for IMC setup's with 17, 8, 6 and 4 sensors, respectively. When horizontal GRF were neglected for 6 sensors, RMSerrors and peak moment errors decreased from 22 to 17.3 and from 16.9 to 13 Nm, respectively. In conclusion, while reasonable moment estimates can be obtained with 6 sensors, omitting the forearm sensors led to unacceptable errors. Furthermore, vertical GRF information is sufficient to estimate L5S1 moments in lifting.
脊柱的机械负荷已被证明是下腰痛发生的一个重要风险因素。惯性运动捕捉(IMC)系统可能允许在实际工作条件下测量腰椎力矩,从而支持对减少机械负荷措施的评估。由于传感器数量限制了其适用性,本研究的目的是调查传感器数量对L5S1力矩估计的影响。使用金标准(GS)实验室设置测量手部力量、地面反作用力(GRF)和全身运动学。在动态设置中,基于测力板测量的GRF和使用IMC系统(子集)测量的身体运动学来估计手部力量。使用自上而下的逆动力学计算L5S1屈伸力矩。对于17个传感器的完整集合,RMS误差(Nm)最低(16.6),对于8、6和4个传感器,RMS误差分别增加到20.5、22和30.6。对于分别具有17、8、6和4个传感器的IMC设置,峰值力矩(Nm)的绝对误差范围为17.7至16.4、16.9和49.3 Nm。当忽略6个传感器的水平GRF时,RMS误差和峰值力矩误差分别从22降至17.3,从16.9降至13 Nm。总之,虽然使用6个传感器可以获得合理的力矩估计,但省略前臂传感器会导致不可接受的误差。此外,垂直GRF信息足以估计举重时的L5S1力矩。