Kim Wangdo, Vela Emir A, Kohles Sean S, Huayamave Victor, Gonzalez Oscar
Ingeniería Mecánica, Universidad de Ingenieria y Tecnologia-UTEC, Lima 15063, Peru.
Research Center in Bioengineering, Ingeniería Mecánica, Universidad de Ingenieria y Tecnologia-UTEC, Lima 15063, Peru.
Electronics (Basel). 2023 Sep 1;12(17). doi: 10.3390/electronics12173694. Epub 2023 Aug 31.
Inertial kinetics and kinematics have substantial influences on human biomechanical function. A new algorithm for Inertial Measurement Unit (IMU)-based motion tracking is presented in this work. The primary aims of this paper are to combine recent developments in improved biosensor technology with mainstream motion-tracking hardware to measure the overall performance of human movement based on joint axis-angle representations of limb rotation. This work describes an alternative approach to representing three-dimensional rotations using a normalized vector around which an identified joint angle defines the overall rotation, rather than a traditional Euler angle approach. Furthermore, IMUs allow for the direct measurement of joint angular velocities, offering the opportunity to increase the accuracy of instantaneous axis of rotation estimations. Although the axis-angle representation requires vector quotient algebra (quaternions) to define rotation, this approach may be preferred for many graphics, vision, and virtual reality software applications. The analytical method was validated with laboratory data gathered from an infant dummy leg's flexion and extension knee movements and applied to a living subject's upper limb movement. The results showed that the novel approach could reasonably handle a simple case and provide a detailed analysis of axis-angle migration. The described algorithm could play a notable role in the biomechanical analysis of human joints and offers a harbinger of IMU-based biosensors that may detect pathological patterns of joint disease and injury.
惯性动力学和运动学对人体生物力学功能有重大影响。本文提出了一种基于惯性测量单元(IMU)的运动跟踪新算法。本文的主要目的是将改进的生物传感器技术的最新进展与主流运动跟踪硬件相结合,以基于肢体旋转的关节轴角表示来测量人体运动的整体性能。这项工作描述了一种替代方法,即使用归一化向量来表示三维旋转,围绕该向量确定的关节角定义整体旋转,而不是传统的欧拉角方法。此外,IMU允许直接测量关节角速度,这为提高瞬时旋转轴估计的准确性提供了机会。尽管轴角表示需要向量商代数(四元数)来定义旋转,但这种方法可能更适用于许多图形、视觉和虚拟现实软件应用。该分析方法通过从婴儿假人腿部膝关节屈伸运动收集的实验室数据进行了验证,并应用于活体受试者的上肢运动。结果表明,该新方法能够合理处理简单情况,并提供轴角迁移的详细分析。所描述的算法在人体关节的生物力学分析中可能发挥显著作用,并为基于IMU的生物传感器提供了一个先兆,这种传感器可能检测关节疾病和损伤的病理模式。