平均女性头颈部有限元模型颈部肌肉控制策略之比较。

PubMed ID
G H
发表日期 2019年月

原始出处 交通伤害预防
Traffic injury prevention
作者 Putra  I Putu A  Iraeus  Johan  Thomson  Robert  Svensson  Mats Y  Linder  Astrid  Sato  Fusako 

文献标题 平均女性头颈部有限元模型颈部肌肉控制策略之比较。
Comparison of control strategies for the cervical muscles of an average female head-neck finite element model.
Comparison of control strategies for the cervical muscles of an average female head-neck finite element model.

文献摘要

目的:vivaopenhbm是第一个用于碰撞安全评估的开源人体模型(HBM)。它代表女性的平均尺寸(第50百分位),用于评估汽车中的挥鞭样保护系统。为了提高当前模型的生物逼真度,在低速追尾碰撞中,由于颈部肌肉改变了乘员的头部和颈部运动学,因此正在通过实施肌肉反射响应能力来进一步增强。本研究的目的是评估不同的颈部肌肉激活控制策略对低速后方头颈部运动学的影响影响。方法:本研究采用先前根据PMHS数据验证的VIVA OpenHBM头颈模型。采用129个Hill型材料模型梁单元来代表34块颈部肌肉。采用两种不同的肌肉激活控制策略:模拟前庭系统神经反馈的控制策略和表示肌肉纺锤位移反馈的控制策略。为了确定这些控制器策略的控制增益值,使用最优化方法进行参数校准。这些优化的目的是匹配志愿者测得的头部线性和角位移测试结果:与未激活肌肉的模型相比,肌肉激活通过减少峰值线性位移来改变头部运动学。对于模拟人类前庭系统的肌肉激活模型,观察到头部水平平移的一致性。然而,在垂直方向上,颈椎屈曲引起的头部运动反应存在差异。在具有代表肌梭反馈的控制策略的模型中,观察到头部平移运动学的改善,并观察到较少的颈椎屈曲。虽然,总体运动学反应在第一阶段更好策略。结论与被动模型相比,两种肌肉控制策略都改善了头部运动学,与志愿者的运动学响应相比,模型与模拟人类前庭系统的主动肌肉模型取得了更好的一致性。


Objective: ViVA OpenHBM is the first open source Human Body Model (HBM) for crash safety assessment. It represents an average size (50th percentile) female and was created to assess whiplash protection systems in a car. To increase the biofidelity of the current model, further enhancements are being made by implementing muscle reflex response capabilities as cervical muscles alter the head and neck kinematics of the occupant during low-speed rear crashes. The objective of this study was to assess how different neck muscle activation control strategies affect head-neck kinematics in low speed rear impacts.Methods: The VIVA OpenHBM head-neck model, previously validated to PMHS data, was used for this study. To represent the 34 cervical muscles, 129 beam elements with Hill-type material models were used. Two different muscle activation control strategies were implemented: a control strategy to mimic neural feedback from the vestibular system and a control strategy to represent displacement feedback from muscle spindles. To identify control gain values for these controller strategies, parameter calibrations were conducted using optimization. The objective of these optimizations was to match the head linear and angular displacements measured in volunteer tests.Results: Muscle activation changed the head kinematics by reducing the peak linear displacements, as compared to the model without muscle activation. For the muscle activation model mimicking the human vestibular system, a good agreement was observed for the horizontal head translation. However, in the vertical direction there was a discrepancy of head kinematic response caused by buckling of the cervical spine. In the model with a control strategy that represents muscle spindle feedback, improvements in translational head kinematics were observed and less cervical spine buckling was observed. Although, the overall kinematic responses were better in the first strategy.Conclusions: Both muscle control strategies improved the head kinematics compared to the passive model and comparable to the volunteer kinematics responses with overall better agreement achieved by the model with active muscles mimicking the human vestibular system.

Objective: ViVA OpenHBM is the first open source Human Body Model (HBM) for crash safety assessment. It represents an average size (50th percentile) female and was created to assess whiplash protection systems in a car. To increase the biofidelity of the current model, further enhancements are being made by implementing muscle reflex response capabilities as cervical muscles alter the head and neck kinematics of the occupant during low-speed rear crashes. The objective of this study was to assess how different neck muscle activation control strategies affect head-neck kinematics in low speed rear impacts.Methods: The VIVA OpenHBM head-neck model, previously validated to PMHS data, was used for this study. To represent the 34 cervical muscles, 129 beam elements with Hill-type material models were used. Two different muscle activation control strategies were implemented: a control strategy to mimic neural feedback from the vestibular system and a control strategy to represent displacement feedback from muscle spindles. To identify control gain values for these controller strategies, parameter calibrations were conducted using optimization. The objective of these optimizations was to match the head linear and angular displacements measured in volunteer tests.Results: Muscle activation changed the head kinematics by reducing the peak linear displacements, as compared to the model without muscle activation. For the muscle activation model mimicking the human vestibular system, a good agreement was observed for the horizontal head translation. However, in the vertical direction there was a discrepancy of head kinematic response caused by buckling of the cervical spine. In the model with a control strategy that represents muscle spindle feedback, improvements in translational head kinematics were observed and less cervical spine buckling was observed. Although, the overall kinematic responses were better in the first strategy.Conclusions: Both muscle control strategies improved the head kinematics compared to the passive model and comparable to the volunteer kinematics responses with overall better agreement achieved by the model with active muscles mimicking the human vestibular system.


获取全文 10.1080/15389588.2019.1670818