Abstract Locomotion mode recognition is one of the key aspects of control of intelligent prostheses. This paper presents a wireless wearable multi-sensor system for locomotion mode recognition. The sensor suit of the system includes three inertial measurement units (IMUs) and eight force sensors. The system was built to measure both kinematic (tilt angles) and dynamic (ground contact forces) signals of human gaits. To evaluate the recognition performance of the system, seven motion modes and sit-to-stand transition were monitored. With a linear discriminant analysis (LDA) classifier, the proposed system can accurately classify the current states. The overall motion mode recognition accuracy was 99.9% during the stance phase and 98.5% during the swing phase. For sit-to-stand transition recognition, the average accuracy was 99.9%. These promising results show the potential of the designed system for the control of intelligent prostheses.
Zheng et al. REF created a wireless wearable multi-sensor system for locomotion mode recognition, with three inertial measurement units (IMUs) and eight force sensors, measuring both kinematic and dynamic signals of human gait, using a linear discriminant analysis (LDA) classifier.
On the Design of a Wearable Multi-sensor System for Recognizing Motion Modes and Sit-to-stand Transition
International Journal of Advanced Robotic Systems
Computer Science