Most fish swim with body undulations that result from fluid–structure interactions between the fish’s internal tissues and the surrounding water. Gaining insight into these complex fluid–structure interactions is essential to understand how fish swim. To this end, we developed a dedicated experimental–numerical inverse dynamics approach to calculate the lateral bending moment distributions for a large-amplitude undulatory swimmer that moves freely in three-dimensional space. We combined automated motion tracking from multiple synchronised high-speed video sequences, computation of fluid dynamic stresses on the swimmer’s body from computational fluid dynamics, and bending moment calculations using these stresses as input for a novel beam model of the body. The bending moment, which represent the system’s net actuation, varies over time and along the fish’s central axis due to muscle actions, passive tissues, inertia, and fluid dynamics. Our three-dimensional analysis of 113 swimming events of zebrafish larvae ranging in age from 3 to 12 days after fertilisation shows that these bending moment patterns are not only relatively simple but also strikingly similar throughout early development and from fast starts to periodic swimming. This suggests that fish larvae may produce and adjust swimming movements relatively simply, yet effectively, while restructuring their neuromuscular control system throughout their rapid development.

大多数鱼在游泳时身体都会波动，这是由于鱼的内部组织与周围水之间的流体结构相互作用造成的。深入了解这些复杂的流体-结构相互作用对于理解鱼类如何游泳至关重要。为此，我们开发了一种专用的实验数值逆动力学方法来计算在三维空间中自由移动的大振幅波动游泳者的横向弯矩分布。我们结合了来自多个同步高速视频序列的自动运动跟踪、根据计算流体动力学计算游泳者身体上的流体动态应力，以及使用这些应力作为新型身体梁模型的输入进行弯矩计算。由于肌肉动作、被动组织、惯性和流体动力学，代表系统净驱动的弯矩会随着时间并沿着鱼的中心轴而变化。我们对受精后 3 至 12 天的斑马鱼幼鱼的 113 个游泳事件进行了三维分析，结果表明这些弯矩模式不仅相对简单，而且在整个早期发育过程中以及从快速开始到周期性游泳的过程中惊人地相似。这表明鱼类幼虫可以相对简单而有效地产生和调整游泳运动，同时在其快速发育过程中重组其神经肌肉控制系统。