  Many kinds of lower-limb exoskeletons were developed for walking assistance.
However, when controlling these exoskeletons, time-delay due to the computation
time and the communication delays is still a general problem. In this research,
we propose a novel method to prevent the time-delay when controlling a walking
assist exoskeleton by predicting the future plantar force and walking status.
By using Long Short-Term Memory and a fully-connected network, the plantar
force can be predicted using only data measured by inertial measurement unit
sensors, not only during the walking period but also at the start and end of
walking. From the predicted plantar force, the walking status and the desired
assistance timing can also be determined. By considering the time-delay and
sending the control commands beforehand, the exoskeleton can be moved precisely
on the desired assistance timing. In experiments, the prediction accuracy of
the plantar force and the assistance timing are confirmed. The performance of
the proposed method is also evaluated by using the trained model to control the
exoskeleton.
