Despite the exponential growth in using inertial measurement units (IMUs) for biomechanical studies, future growth in “inertial motion capture” is stymied by a fundamental challenge - how to estimate the orientation of underlying bony anatomy using skin-mounted IMUs. This challenge is of paramount importance given the need to deduce the orientation of the bony anatomy to estimate joint angles. This paper systematically surveys a large number (N = 112) of studies from 2000 to 2018 that employ four broad categories of methods to address this challenge across a range of body segments and joints. We categorize these methods as: (1) Assumed Alignment methods, (2) Functional Alignment methods, (3) Model Based methods, and (4) Augmented Data methods. Assumed Alignment methods, which are simple and commonly used, require the researcher to visually align the IMU sense axes with the underlying anatomical axes. Functional Alignment methods, also commonly used, relax the need for visual alignment but require the subject to complete prescribed movements. Model Based methods further relax the need for prescribed movements but instead assume a model for the joint. Finally, Augmented Data methods shed all of the above assumptions, but require data from additional sensors. Significantly different estimates of the underlying anatomical axes arise both across and within these categories, and to a degree that renders it difficult, if not impossible, to compare results across studies. Consequently, a significant future need remains for creating and adopting a standard for defining anatomical axes via inertial motion capture to fully realize this technology’s potential for biomechanical studies.

尽管在生物力学研究中使用惯性测量单元（IMU）呈指数级增长，但“惯性运动捕获”的未来增长仍受到一个基本挑战的困扰-如何使用皮肤固定式IMU估算潜在的骨骼解剖学方向。鉴于需要推断骨骼解剖的方向以估算关节角度，这一挑战至关重要。本文系统地调查了2000年至2018年的大量研究（N = 112），这些研究采用了四大类方法来应对一系列身体部位和关节的挑战。我们将这些方法分类为：（1）假定对齐方法，（2）功能对齐方法，（3）基于模型的方法和（4）增强数据方法。假定的对准方法是简单且常用的，要求研究人员在视觉上将IMU感应轴与基础解剖轴对齐。功能对齐方法（通常也使用）减轻了视觉对齐的需要，但要求对象完成规定的运动。基于模型的方法进一步放松了对规定运动的需求，而是采用了关节模型。最后，增强数据方法摆脱了所有上述假设，但需要来自其他传感器的数据。在这些类别之间和之内，都对基础解剖轴产生了明显不同的估计，并且在某种程度上使得很难（即使不是不可能）比较研究之间的结果。所以，