Aoki Takashi, Lin Jonathan Feng-Shun, Kulic Dana, Venture Gentiane
Annu Int Conf IEEE Eng Med Biol Soc. 2016 Aug;2016:3163-3166. doi: 10.1109/EMBC.2016.7591400.
This paper proposes an approach for the segmentation of human body movements measured by inertial measurement unit sensors. Using the angular velocity and linear acceleration measurements directly, without converting to joint angles, we perform segmentation by formulating the problem as a classification problem, and training a classifier to differentiate between motion end-point and within-motion points. The proposed approach is validated with experiments measuring the upper body movement during reaching tasks, demonstrating classification accuracy of over 85.8%.
本文提出了一种用于分割由惯性测量单元传感器测量的人体运动的方法。我们直接使用角速度和线性加速度测量值，无需转换为关节角度，通过将问题表述为分类问题并训练分类器来区分运动端点和运动中的点，从而进行分割。通过测量伸手任务期间上半身运动的实验对所提出的方法进行了验证，结果表明分类准确率超过85.8%。
