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迈向使用惯性测量单元对躯干外骨骼进行实际评估。

Toward real-world evaluations of trunk exoskeletons using inertial measurement units.

作者信息

Tran Minh Ha, Kmecl Peter, Regmi Yubi, Dai Boyi, Gorsic Maja, Novak Domen

出版信息

IEEE Int Conf Rehabil Robot. 2019 Jun;2019:483-487. doi: 10.1109/ICORR.2019.8779517.

Abstract

Trunk exoskeletons are an emerging technology that could reduce spinal loading, guide trunk motion, and augment lifting ability. However, while they have achieved promising results in brief laboratory studies, they have not yet been tested in longer-term real-world studies - partially due to reliance on stationary sensors such as cameras. To enable future real-world evaluations of trunk exoskeletons, this paper describes two preliminary studies on using inertial measurement units (IMUs) to collect kinematic data from an exoskeleton wearer. In the first study, a participant performed three activities (walking, sit-to-stand, box lifting) while trunk flexion angle was measured with both IMUs and reference cameras. The mean absolute difference in flexion angle between the two methods was 1.4° during walking, 3.6° during sit-to-stand and 5.2° during box lifting, showing that IMUs can measure trunk flexion with a reasonable accuracy. In the second study, six participants performed five activities (standing, sitting straight, slouching, 'good' lifting, 'bad' lifting), and a naïve Bayes classifier was used to automatically classify the activity from IMU data. The classification accuracy was 92.2%, indicating the feasibility of automated activity classification using IMUs. The IMUs will next be used to obtain longer-term recordings of different activities performed both with and without a trunk exoskeleton to determine how the exoskeleton affects a person's posture and behavior.

摘要

躯干外骨骼是一项新兴技术,它可以减轻脊柱负荷、引导躯干运动并增强举重能力。然而,尽管它们在简短的实验室研究中取得了令人鼓舞的成果,但尚未在长期的实际研究中得到测试——部分原因是依赖于如摄像头等固定传感器。为了实现未来对躯干外骨骼的实际评估,本文描述了两项关于使用惯性测量单元(IMU)从外骨骼穿戴者收集运动学数据的初步研究。在第一项研究中,一名参与者进行了三项活动(行走、从坐姿到站姿、举箱子),同时使用IMU和参考摄像头测量躯干屈曲角度。两种方法在行走过程中屈曲角度的平均绝对差值为1.4°,从坐姿到站姿过程中为3.6°,举箱子过程中为5.2°,这表明IMU能够以合理的精度测量躯干屈曲。在第二项研究中,六名参与者进行了五项活动(站立、挺直坐姿、弯腰驼背、“正确”举重、“错误”举重),并使用朴素贝叶斯分类器根据IMU数据自动对活动进行分类。分类准确率为92.2%,表明使用IMU进行自动活动分类的可行性。接下来,IMU将用于获取在有和没有躯干外骨骼的情况下进行不同活动的长期记录,以确定外骨骼如何影响人的姿势和行为。

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