  Gait adaptation is an important part of gait analysis and its neuronal origin
and dynamics has been studied extensively. In neurorehabilitation, it is
important as it perturbs neuronal dynamics and allows patients to restore some
of their motor function. Exoskeletons and robotics of the lower limbs are
increasingly used to facilitate rehabilitation as well as supporting daily
function. Their efficiency and safety depends on how well can sense the human
intention to move and adapt the gait accordingly. This paper presents a gait
adaptation scheme in natural settings. It allows monitoring of subjects in more
realistic environment without the requirement of specialized equipment such as
treadmill and foot pressure sensors. We extract gait characteristics based on a
single RBG camera whereas wireless EEG signals are monitored simultaneously. We
demonstrate that the method can not only successfully detect adaptation steps
but also detect efficiently whether the subject adjust their pace to higher or
lower speed.
