RAGT was performed with the Lokomat System (for details
see references). However, in the present study,
we used customized software that, besides the positioncontrolled
mode (standard Lokomat software), had 2 additional
modes. In position-controlled mode, the end point
of the robotic leg is exactly defined for each particular
time point during the gait cycle. In path control mode,
however, there is a virtual tunnel around the preprogrammed
gait trajectory and within this tunnel, the participant
can freely move his leg. If the participant’s leg
deviates from this virtual tunnel, the Lokomat pushes the
leg back into the tunnel. With this control mode,
the participant trains a more functional gait pattern that
better represents “over ground walking” compared to the
standard position-controlled mode. Path control mode
allows individual variability within the gait cycle, which is relevant for motor learning. For the most difficult training
mode, we added treadmill speed control to the path control
mode. Here, participants additionally could control
the speed of the belt with their body posture.