Gait Phase Detection Based on LSTM-CRF for Stair Ambulation

Congratulations to Haochen for publishing her work "Gait Phase Detection Based on LSTM-CRF for Stair Ambulation" in the IEEE Robotics and Automation Letters (RA-L)! In this study, we developed an LSTM-CRF model to detect five gait sub-phases during stair ambulation. The proposed method shows stable and high accuracy among different subphases and subjects. The proposed method was validated on data from ten healthy subjects and improved the prediction performance of gait phase detection during stair ambulance from other machine learning methods.