Lower Limb Wearable Capacitive Sensing and Its Applications to Recognizing Human Gaits

Sensors

Enhao Zheng¹  Baojun Chen¹  Kunlin Wei² 

[1] Intelligent Control Laboratory, College of Engineering, Peking University, Beijing 100871, China; E-Mails:;Motion Control Laboratory, Department of Psychology, Peking University, Beijing 100871, China; E-Mail:

关键词: wearable gait sensors;    human body capacitance;    capacitive sensing;    muscle shape changes;    human normal gaits;    pattern recognition;   

DOI  :  10.3390/s131013334

来源: mdpi

【 摘 要 】

In this paper, we present an approach to sense human body capacitance and apply it to recognize lower limb locomotion modes. The proposed wearable sensing system includes sensing bands, a signal processing circuit and a gait event detection module. Experiments on long-term working stability, adaptability to disturbance and locomotion mode recognition are carried out to validate the effectiveness of the proposed approach. Twelve able-bodied subjects are recruited, and eleven normal gait modes are investigated. With an event-dependent linear discriminant analysis classifier and feature selection procedure, four time-domain features are used for pattern recognition and satisfactory recognition accuracies (97.3% ± 0.5%, 97.0% ± 0.4%, 95.6% ± 0.9% and 97.0% ± 0.4% for four phases of one gait cycle respectively) are obtained. The accuracies are comparable with that from electromyography-based systems and inertial-based systems. The results validate the effectiveness of the proposed lower limb capacitive sensing approach in recognizing human normal gaits.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.