Slajpah S, Kamnik R, Munih M
University of Ljubljana, Faculty of Electrical Engineering, Tržaška cesta 25, 1000 Ljubljana, Slovenia.
Comput Methods Programs Biomed. 2014 Sep;116(2):131-44. doi: 10.1016/j.cmpb.2013.11.012. Epub 2013 Dec 4.
Measuring the kinematic parameters in unconstrained human motion is becoming crucial for providing feedback information in wearable robotics and sports monitoring. This paper presents a novel sensory fusion algorithm for assessing the orientations of human body segments in long-term human walking based on signals from wearable sensors. The basic idea of the proposed algorithm is to constantly fuse the measured segment's angular velocity and linear acceleration via known kinematic relations between segments. The wearable sensory system incorporates seven inertial measurement units attached to the human body segments and two instrumented shoe insoles. The proposed system was experimentally validated in a long-term walking on a treadmill and on a polygon with stairs simulating different activities in everyday life. The outputs were compared to the reference parameters measured by a stationary optical system. Results show accurate joint angle measurements (error median below 5°) in all evaluated walking conditions with no expressed drift over time.
测量无约束人体运动中的运动学参数对于在可穿戴机器人技术和运动监测中提供反馈信息变得至关重要。本文提出了一种新颖的传感融合算法，用于基于可穿戴传感器的信号评估长期人类行走中人体各节段的方位。该算法的基本思想是通过节段之间已知的运动学关系不断融合测量节段的角速度和线性加速度。可穿戴传感系统包括七个附着在人体节段上的惯性测量单元和两个装有仪器的鞋垫。所提出的系统在跑步机上以及在模拟日常生活中不同活动的带楼梯的多边形上进行的长期行走实验中得到了验证。将输出结果与由固定光学系统测量的参考参数进行了比较。结果表明，在所有评估的行走条件下，关节角度测量准确（误差中位数低于5°），且未表现出随时间的漂移。
