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Paper ThCT14.2

Jang, Junwon (Samsung Electronics Co., Ltd.), Kim, Kyungrock (Samsung Advanced Institute of Technology (SAIT)), Lee, Jusuk (Samsung Electronics Co., Ltd.), Lim, Bokman (Samsung Advanced Institute of Technology), Shim, Youngbo (Samsung Electronics)

Online Gait Task Recognition Algorithm for Hip Exoskeleton

Scheduled for presentation during the Regular session "Wearable Robots" (ThCT14), Thursday, October 1, 2015, 11:35−11:50, Saal C4

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, Sept 28 - Oct 03, 2015, Congress Center Hamburg, Hamburg, Germany

This information is tentative and subject to change. Compiled on July 19, 2019

Keywords Wearable Robots, Rehabilitation Robotics, Sensor Fusion

Abstract

In this paper, we propose a novel online gait task recognition algorithm for hip exoskeleton. The proposed algorithm provides an automatic and prompt recognition result in just one step based on the relations between both hip joint angles at the moment of foot contact. Gait task recognition is one of the challenges that walking assist devices must address to offer adaptable and reliable assistance to users. However gait task recognition in hip exoskeleton is challenging because the sensors are very limited and fast gait task recognition is required to prevent inadequate assistance and reduce fall risk. Although in general foot contact event can be considered as crucial information during walking, it has not received attention in hip exoskeletons with no sensors corresponding foot force or pressure. In this study, we exploit foot contact event as a critical point to perform gait task recognition in hip exoskeleton. The proposed algorithm suggests a foot contact estimation method without using any foot force or pressure sensors and a rule based inference system to recognize a new gait task in real time. Results presented from experiments will demonstrate the validity and performance of the proposed algorithm.

 

 

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