低成本嵌入式多模态光惯性人体运动跟踪系统

Mariusz P. Wilk, M. Walsh, B. O’flynn
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引用次数: 1

摘要

人体运动跟踪系统广泛应用于各种应用领域,如运动捕捉、康复或运动。在最先进的(SOA)中存在许多这样的系统,它们在价格、复杂性、准确性和目标应用程序方面各不相同。随着系统集成和小型化的不断发展,可穿戴运动追踪器在研究界越来越受欢迎。采用多模态传感器融合算法的光惯性跟踪器是SOA中常见的一些方法。然而,这些跟踪器往往是昂贵的,有很高的计算需求。在这项工作中,我们展示了我们的光惯性运动跟踪系统的原型版本,提供了一种低成本的替代方案。利用专门设计的数据融合算法,通过融合光学和惯性传感器数据以及关于两个外部参考点的知识来确定三维位置和方向。对该系统的一个用例进行了实验验证,即力量训练中的杠铃深蹲。结果表明,在位置和方向上的总RMSE分别为32.8 mm和0.89°。它以每秒20帧的速度实时运行。
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Low Cost Embedded Multimodal Opto-Inertial Human Motion Tracking System
Human motion tracking systems are widely used in various application spaces, such as motion capture, rehabilitation, or sports. There exists a number of such systems in the State-Of-The-Art (SOA) that vary in price, complexity, accuracy and the target applications. With the continued advances in system integration and miniaturization, wearable motion trackers gain in popularity in the research community. The opto-inertial trackers with multimodal sensor fusion algorithms are some of the common approaches found in SOA. However, these trackers tend to be expensive and have high computational requirements. In this work, we present a prototype version of our opto-inertial, motion tracking system that offers a low-cost alternative. The 3D position and orientation are determined by fusing optical and inertial sensor data together with knowledge about two external reference points using a purpose-designed data fusion algorithm. An experimental validation was carried out on one of the use cases that this system is intended for, i.e. barbell squat in strength training. The results showed that the total RMSE in position and orientation was 32.8 mm and 0.89 degree, respectively. It operated in real-time at 20 frames per second.
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