Department of Engineering, University of Hull, Hull HU67RX, United Kingdom.
J Biomech. 2010 Oct 19;43(14):2804-9. doi: 10.1016/j.jbiomech.2010.05.037. Epub 2010 Jul 31.
In biomechanical investigations, geometrically accurate computer models of anatomical structures can be created readily using computed-tomography scan images. However, representation of soft tissue structures is more challenging, relying on approximations to predict the muscle loading conditions that are essential in detailed functional analyses. Here, using a sophisticated multi-body computer model of a reptile skull (the rhynchocephalian Sphenodon), we assess the accuracy of muscle force predictions by comparing predicted bite forces against in vivo data. The model predicts a bite force almost three times lower than that measured experimentally. Peak muscle force estimates are highly sensitive to fibre length, muscle stress, and pennation where the angle is large, and variation in these parameters can generate substantial differences in predicted bite forces. A review of theoretical bite predictions amongst lizards reveals that bite forces are consistently underestimated, possibly because of high levels of muscle pennation in these animals. To generate realistic bites during theoretical analyses in Sphenodon, lizards, and related groups we suggest that standard muscle force calculations should be multiplied by a factor of up to three. We show that bite forces increase and joint forces decrease as the bite point shifts posteriorly within the jaw, with the most posterior bite location generating a bite force almost double that of the most anterior bite. Unilateral and bilateral bites produced similar total bite forces; however, the pressure exerted by the teeth is double during unilateral biting as the tooth contact area is reduced by half.
在生物力学研究中,可以使用计算机断层扫描图像轻松创建解剖结构的几何精确计算机模型。然而,软组织结构的表示形式更具挑战性,需要进行近似处理以预测肌肉加载条件,这对于详细的功能分析至关重要。在这里,我们使用爬行动物头骨(喙头蜥形目 Sphenodon)的复杂多体计算机模型来评估肌肉力预测的准确性,方法是将预测的咬合力与体内数据进行比较。该模型预测的咬合力比实验测量的低近三倍。峰值肌肉力估计对纤维长度、肌肉应力和角度较大的羽毛角度非常敏感,这些参数的变化会导致预测的咬合力产生很大差异。对蜥蜴类动物的理论咬合力预测进行回顾后发现,咬合力一直被低估,可能是因为这些动物的肌肉羽毛角度较高。为了在喙头蜥形目、蜥蜴类和相关群体的理论分析中生成逼真的咬合,我们建议将标准肌肉力计算乘以高达 3 倍的系数。我们表明,随着咬合点在颌骨内向后移动,咬合力增加,关节力减小,最靠后的咬合位置产生的咬合力几乎是最靠前的咬合位置的两倍。单侧和双侧咬合产生的总咬合力相似;然而,由于牙齿接触面积减少了一半,单侧咬合时施加的压力是双侧咬合的两倍。