Preliminary study of online gait recognizer for lower limb exoskeletons

We propose a novel two-tier gait recognizer using a minimal number of mechanical sensors built into a lower limb exoskeleton. The aim of this recognizer is to offer one-step selection of one of the actions ascending, descending, and level walking during five gaits (stair ascent/descent, slope ascent/descent, level walking). The proposed recognizer is executed at the moment of foot contact as estimated by an inertial measurement unit (IMU) on the pelvis without using direct foot sensors. The proposed recognizer selects the gait by using the relations between the angles formed by the hip and knee joints during the last step. As this study constitutes preliminary work for lower limb exoskeletons, we used a hip exoskeleton integrated with two wireless IMUs on the shank to set up the lower limb exoskeleton sensor configuration. Experiments were used to evaluate IMU-based foot contact estimation with respect to a foot sensor based on a force-sensitive resistor (FSR) for stairs, slopes, and level ground. In addition, we evaluated the performance of the proposed two-tier gait recognizer by using two healthy male subjects in various gait environments.

[1]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[2]  Robert Riener,et al.  Control strategies for active lower extremity prosthetics and orthotics: a review , 2015, Journal of NeuroEngineering and Rehabilitation.

[3]  Junwon Jang,et al.  Assistance strategy for stair ascent with a robotic hip exoskeleton , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[4]  Michael Goldfarb,et al.  Control and implementation of a powered lower limb orthosis to aid walking in paraplegic individuals , 2011, 2011 IEEE International Conference on Rehabilitation Robotics.

[5]  R. Riener,et al.  Stair ascent and descent at different inclinations. , 2002, Gait & posture.

[6]  H. Kazerooni,et al.  Biomechanical design of the Berkeley lower extremity exoskeleton (BLEEX) , 2006, IEEE/ASME Transactions on Mechatronics.

[7]  Robert Riener,et al.  A survey of sensor fusion methods in wearable robotics , 2015, Robotics Auton. Syst..

[8]  A. Esquenazi,et al.  The ReWalk Powered Exoskeleton to Restore Ambulatory Function to Individuals with Thoracic-Level Motor-Complete Spinal Cord Injury , 2012, American journal of physical medicine & rehabilitation.

[9]  Hugh M. Herr,et al.  Powered ankle-foot prosthesis to assist level-ground and stair-descent gaits , 2008, Neural Networks.

[10]  Ann M. Simon,et al.  A Training Method for Locomotion Mode Prediction Using Powered Lower Limb Prostheses , 2014, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[11]  Michael Goldfarb,et al.  Multiclass Real-Time Intent Recognition of a Powered Lower Limb Prosthesis , 2010, IEEE Transactions on Biomedical Engineering.

[12]  Nello Cristianini,et al.  An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .

[13]  Jichuan Zhang,et al.  Terrain Identification for Prosthetic Knees Based on Electromyographic Signal Features , 2006 .

[14]  Fan Zhang,et al.  Preliminary design of a terrain recognition system , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[15]  Junwon Jang,et al.  Online gait task recognition algorithm for hip exoskeleton , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[16]  Junwon Jang,et al.  An event-driven control to achieve adaptive walking assist with gait primitives , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[17]  Atilla Kilicarslan,et al.  High accuracy decoding of user intentions using EEG to control a lower-body exoskeleton , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[18]  He Huang,et al.  A Strategy for Identifying Locomotion Modes Using Surface Electromyography , 2009, IEEE Transactions on Biomedical Engineering.

[19]  Yasuhisa Hasegawa,et al.  Intention-based walking support for paraplegia patients with Robot Suit HAL , 2007, Adv. Robotics.