LAUSR

To control an exoskeleton robot, gait event (phase) of the robot needs to be identified. This paper presents a novel gait event detection method for a lower extremity exoskeleton robot based on an intelligent inertial measurement unit (iIMU). The iIMU is designed as a gait monitor to independently accomplish data sampling, data processing, and wireless transmission. It also has good portability that can be easily attached on the surface of a shoe. Moreover, an online detection algorithm is proposed to detect the gait events by local search windows and fixed thresholds, resulting in a minimal time delay and small computational burden. The accuracy and detection rate of the iIMU are experimentally verified by 10 healthy subjects walking on a force plate and treadmill. The mean time errors of heel-strike and toe-off detection are −10 and 19 ms when compared to the force plate. Gait events of a total 478 steps, collected from a treadmill with various walking speeds, are all detected. When applied to a lower extremity exoskeleton robot, the iIMU successfully detects the gait events of the human–robot synchronous walk.