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地形识别系统的初步设计

Preliminary design of a terrain recognition system.

作者信息

Zhang Fan, Fang Zheng, Liu Ming, Huang He

机构信息

Department of Electrical, Computer, and Biomedical Engineering, University of Rhode Island, Kingston, RI 02881, USA.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:5452-5. doi: 10.1109/IEMBS.2011.6091391.

Abstract

This paper aims to design a wearable terrain recognition system, which might assist the control of powered artificial prosthetic legs. A laser distance sensor and inertial measurement unit (TMU) sensors were mounted on human body. These sensors were used to identify the movement state of the user, reconstruct the geometry of the terrain in front of the user while walking, and recognize the type of terrain before the user stepped on it. Different sensor configurations were investigated and compared. The designed system was evaluated on one healthy human subject when walking on an obstacle course in the laboratory environment. The results showed that the reconstructed terrain height demonstrated clearer pattern difference among studied terrains when the laser was placed on the waist than that when the laser was mounted on the shank. The designed system with the laser on the waist accurately recognized 157 out of 160 tested terrain transitions, 300 ms-2870 ms before the user switched the negotiated terrains. These promising results demonstrated the potential application of the designed terrain recognition system to further improve the control of powered artificial legs.

摘要

本文旨在设计一种可穿戴地形识别系统,该系统可能有助于对动力人工假肢的控制。激光距离传感器和惯性测量单元(IMU)传感器被安装在人体上。这些传感器用于识别用户的运动状态,在行走时重建用户前方地形的几何形状,并在用户踏上之前识别地形类型。研究并比较了不同的传感器配置。在实验室环境中,让一名健康受试者在障碍赛道上行走时对设计的系统进行了评估。结果表明,与将激光安装在小腿上相比,当激光放置在腰部时,重建的地形高度在研究的地形之间显示出更明显的模式差异。腰部安装激光的设计系统在用户切换要通过的地形前300毫秒至2870毫秒内,准确识别了160次测试地形转换中的157次。这些有前景的结果证明了所设计的地形识别系统在进一步改善动力人工腿控制方面的潜在应用。

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本文引用的文献

1
Design and Control of a Powered Transfemoral Prosthesis.
Int J Rob Res. 2008 Feb 1;27(2):263-273. doi: 10.1177/0278364907084588.
2
Multiclass real-time intent recognition of a powered lower limb prosthesis.
IEEE Trans Biomed Eng. 2010 Mar;57(3):542-51. doi: 10.1109/TBME.2009.2034734. Epub 2009 Oct 20.
4
A strategy for identifying locomotion modes using surface electromyography.
IEEE Trans Biomed Eng. 2009 Jan;56(1):65-73. doi: 10.1109/TBME.2008.2003293.
5
Powered ankle-foot prosthesis to assist level-ground and stair-descent gaits.
Neural Netw. 2008 May;21(4):654-66. doi: 10.1016/j.neunet.2008.03.006. Epub 2008 Apr 26.
6
How far ahead do we look when required to step on specific locations in the travel path during locomotion?
Exp Brain Res. 2003 Jan;148(1):133-8. doi: 10.1007/s00221-002-1246-y. Epub 2002 Nov 9.

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