Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland.
Institute of Mathematics, Silesian University of Technology, 44-100 Gliwice, Poland.
Sensors (Basel). 2017 Mar 17;17(3):612. doi: 10.3390/s17030612.
The paper describes a scalable, wearable multi-sensor system for motion capture based on inertial measurement units (IMUs). Such a unit is composed of accelerometer, gyroscope and magnetometer. The final quality of an obtained motion arises from all the individual parts of the described system. The proposed system is a sequence of the following stages: sensor data acquisition, sensor orientation estimation, system calibration, pose estimation and data visualisation. The construction of the system's architecture with the dataflow programming paradigm makes it easy to add, remove and replace the data processing steps. The modular architecture of the system allows an effortless introduction of a new sensor orientation estimation algorithms. The original contribution of the paper is the design study of the individual components used in the motion capture system. The two key steps of the system design are explored in this paper: the evaluation of sensors and algorithms for the orientation estimation. The three chosen algorithms have been implemented and investigated as part of the experiment. Due to the fact that the selection of the sensor has a significant impact on the final result, the sensor evaluation process is also explained and tested. The experimental results confirmed that the choice of sensor and orientation estimation algorithm affect the quality of the final results.
本文描述了一种基于惯性测量单元(IMU)的可扩展、可穿戴多传感器运动捕捉系统。这样的单元由加速度计、陀螺仪和磁力计组成。所获得的运动的最终质量取决于描述系统的所有单个部分。所提出的系统是以下阶段的序列:传感器数据采集、传感器方向估计、系统校准、姿势估计和数据可视化。系统架构的构建采用数据流编程范例,使得添加、删除和替换数据处理步骤变得容易。系统的模块化架构允许轻松引入新的传感器方向估计算法。本文的原创贡献是对运动捕捉系统中使用的各个组件的设计研究。本文探讨了系统设计的两个关键步骤:传感器和方向估计算法的评估。这三个选择的算法已被实现并作为实验的一部分进行了研究。由于传感器的选择对最终结果有重大影响,因此还解释和测试了传感器评估过程。实验结果证实,传感器和方向估计算法的选择会影响最终结果的质量。