A radar-based terrain mapping approach for stair detection towards enhanced prosthetic foot control

Current developments in ankle prosthetics are focusing on integrated actuators to fully control torques and angles. This enables terrain adaptive strategies e.g. for stairs and ramps. EMG and motion sensor input are state of the art approaches to classify different terrain or terrain changes, but these approaches have limited capabilities and detection accuracy. We present a novel approach for the detection of obstacles using a wearable Frequency-Modulated Continuous Wave (FMCW) radar integrated into a lower limb prosthetic device. With the continuous rotational motion of the tibia during the swing and stance phase, the radar scans the profile of the terrain in sagittal plane in front of the prosthesis. Gait phases are detected using a neural network classifiers based on inertial sensor data. Performance of the system is demonstrated in a single stair detection scenario.