Multi-gait recognition for a soft ankle exoskeleton with limited sensors

Ma，Liang1,2; Leng，Yuquan2; Zhang，Kuangen2,3; Qian，Yuepeng2; Fu，Chenglong2

10.1109/ICARM52023.2021.9536076

2021-07-03

6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)

978-1-6654-4596-2

2021 6th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2021

566-571

JUL 03-05, 2021

null,Chongqing,PEOPLES R CHINA

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

In order to offer appropriate and reliable assistance to users, wearable robotic devices usually detect human locomotion through multi-sensor fusion system. However, multi-sensor fusion system increased the complexity of the sensor system and the burden of wearing on users for ankle exoskeleton. To optimize the sensor system and recognize multi-gait, we present a multi-gait recognition algorithm for a soft ankle exoskeleton with two IMUs (Inertial Measurement Units) mounted on foot. Five gait features are extracted during swing phase, including mean vertical velocity, mean horizontal velocity, vertical displacement, horizontal displacement, and the inclination angle at foot contact. Then, these gait features are used as the input of BPNN (Back Propagation Neural Network) to recognize five common gait modes (level walking, stair ascent/descent, ramp ascent/descent). The proposed algorithm can provide an accurate automatic recognition result at the early beginning of each stance phase. The results of the experiment shown that the proposed algorithm can distinguish above gait modes with 99.0% success rates.

Mechatronics Measurement units Exoskeletons Neural networks Stairs Robot sensing systems Feature extraction

通讯

英语

CPCI-S ; EI

National Key R&D Program of China["2018YFC2001601","2018YFB1305400"]

Automation & Control Systems ; Engineering ; Robotics

Automation & Control Systems ; Engineering, Electrical & Electronic ; Robotics

WOS:000728141500095

20214010982501

Exoskeleton (Robotics) ; Gait analysis ; Neural networks ; Pattern recognition ; Walking aids ; Wearable sensors

Biomechanics, Bionics and Biomimetics:461.3 ; Rehabilitation Engineering and Assistive Technology:461.5 ; Biomedical Equipment, General:462.1 ; Artificial Intelligence:723.4 ; Robotics:731.5

2-s2.0-85116206286

Scopus

1.The School of Mechanical and Electrical Engineering,Harbin Institute of Technology,Harbin,150001,China
2.The Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems,Guangdong Provincial Key Laboratory of Human Augmentation and Rehabilitation Robotics in Universities,Department of Mechanical and Energy Engineering,Southern University of Science and Technology,Shenzhen,518055,China
3.The Department of Mechanical Engineering,University of British Columbia,Vancouver,V6T 1Z4,Canada

Ma，Liang,Leng，Yuquan,Zhang，Kuangen,et al. Multi-gait recognition for a soft ankle exoskeleton with limited sensors[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2021:566-571.