Université Paris Cité, Inserm, System Engineering and Evolution Dynamics, F-75004 Paris, France.
Learning Planet Institute, F-75004 Paris, France.
J Exp Biol. 2023 Apr 25;226(Suppl_1). doi: 10.1242/jeb.245138. Epub 2023 Feb 8.
Deconstructing motion to better understand it is a key prerequisite in the field of comparative biomechanics. Since Marey and Muybridge's work, technical constraints have been the largest limitation to motion capture and analysis, which, in turn, limited what kinds of questions biologists could ask or answer. Throughout the history of our field, conceptual leaps and significant technical advances have generally worked hand in hand. Recently, high-resolution, three-dimensional (3D) motion data have become easier to acquire, providing new opportunities for comparative biomechanics. We describe how adding a third dimension of information has fuelled major paradigm shifts, not only leading to a reinterpretation of long-standing scientific questions but also allowing new questions to be asked. In this paper, we highlight recent work published in Journal of Experimental Biology and influenced by these studies, demonstrating the biological breakthroughs made with 3D data. Although amazing opportunities emerge from these technical and conceptual advances, high-resolution data often come with a price. Here, we discuss challenges of 3D data, including low-throughput methodology, costly equipment, low sample sizes, and complex analyses and presentation. Therefore, we propose guidelines for how and when to pursue 3D high-resolution data. We also suggest research areas that are poised for major new biological advances through emerging 3D data collection.
对运动进行解构以更好地理解它是比较生物力学领域的一个关键前提。自 Marey 和 Muybridge 的工作以来,技术限制一直是运动捕捉和分析的最大限制,这反过来又限制了生物学家可以提出或回答什么样的问题。纵观我们领域的历史,概念上的飞跃和重大的技术进步通常是齐头并进的。最近,高分辨率的三维(3D)运动数据变得更容易获取,为比较生物力学提供了新的机会。我们描述了如何添加第三个维度的信息来推动主要的范式转变,不仅导致对长期存在的科学问题的重新解释,而且还允许提出新的问题。在本文中,我们强调了最近发表在《实验生物学杂志》上并受到这些研究影响的工作,展示了使用 3D 数据取得的生物学突破。尽管这些技术和概念上的进步带来了令人惊叹的机会,但高分辨率数据通常需要付出代价。在这里,我们讨论了 3D 数据面临的挑战,包括低通量方法、昂贵的设备、小样本量以及复杂的分析和呈现。因此,我们提出了如何以及何时追求 3D 高分辨率数据的指导方针。我们还建议了一些研究领域,这些领域通过新兴的 3D 数据收集有望取得重大的新生物学进展。