The Real Time Gait Phase Detection Based on Long Short-Term Memory

Multiple sensors system has been adopted in most existing gait phase research. In this paper, we present a novel method to detect and discriminate gait phase based on single Inertial Measurement Unit (IMU). At first, we built a data acquisition system consisting of single IMU measuring the kinematic data of shank and foot switches labeling the data to collect the gait samples. And then we developed a gait phase recognition algorithm based on long short-term memory (LSTM) and trained it with phase-labeled data. The experimental results show that the algorithm has 91.4% accuracy on the testing set. Compared with existing approaches, the proposed method ensures the accuracy of gait phase detection and avoids the complex sensor system.