An automatic and user-driven training method for locomotion mode recognition for artificial leg control

Our previously developed locomotion-mode-recognition (LMR) system has provided a great promise to intuitive control of powered artificial legs. However, the lack of fast, practical training methods is a barrier for clinical use of our LMR system for prosthetic legs. This paper aims to design a new, automatic, and user-driven training method for practical use of LMR system. In this method, a wearable terrain detection interface based on a portable laser distance sensor and an inertial measurement unit (IMU) is applied to detect the terrain change in front of the prosthesis user. The mechanical measurement from the prosthetic pylon is used to detect gait phase. These two streams of information are used to automatically identify the transitions among various locomotion modes, switch the prosthesis control mode, and label the training data with movement class and gait phase in real-time. No external device is required in this training system. In addition, the prosthesis user without assistance from any other experts can do the whole training procedure. The pilot experimental results on an able-bodied subject have demonstrated that our developed new method is accurate and user-friendly, and can significantly simplify the LMR training system and training procedure without sacrificing the system performance. The novel design paves the way for clinical use of our designed LMR system for powered lower limb prosthesis control.