Human-Robot Interaction: Does Robotic Guidance Force Affect Gait-Related Brain Dynamics during Robot-Assisted Treadmill Walking?
In order to determine optimal training parameters for robot-assisted treadmill walking, it is essential to understand how a robotic device interacts with its wearer, and thus, how parameter settings of the device affect locomotor control. The aim of this study was to assess the effect of different levels of guidance force during robot-assisted treadmill walking on cortical activity. Eighteen healthy subjects walked at 2 km.h-1 on a treadmill with and without assistance of the Lokomat robotic gait orthosis. Event-related spectral perturbations and changes in power spectral density were investigated during unassisted treadmill walking as well as during robot-assisted treadmill walking at 30%, 60% and 100% guidance force (with 0% body weight support). Clustering of independent components revealed three clusters of activity in the sensorimotor cortex during treadmill walking and robot-assisted treadmill walking in healthy subjects. These clusters demonstrated gait-related spectral modulations in the mu, beta and low gamma bands over the sensorimotor cortex related to specific phases of the gait cycle. Moreover, mu and beta rhythms were suppressed in the right primary sensory cortex during treadmill walking compared to robot-assisted treadmill walking with 100% guidance force, indicating significantly larger involvement of the sensorimotor area during treadmill walking compared to robot-assisted treadmill walking. Only marginal differences in the spectral power of the mu, beta and low gamma bands could be identified between robot-assisted treadmill walking with different levels of guidance force. From these results it can be concluded that a high level of guidance force (i.e., 100% guidance force) and thus a less active participation during locomotion should be avoided during robot-assisted treadmill walking. This will optimize the involvement of the sensorimotor cortex which is known to be crucial for motor learning.
Human Physiology Research Group, Vrije Universiteit Brussel, Brussels, Belgium.
Kristel
K
Knaepen
Institute of Movement and Neurosciences, German Sport University, Cologne, Germany.
Andreas
A
Mierau
Center for Neurosciences, Vrije Universiteit Brussel, Brussels, Belgium; Department of Rehabilitation Research, Vrije Universiteit Brussel, Brussels, Belgium.
Eva
E
Swinnen
Human Physiology Research Group, Vrije Universiteit Brussel, Brussels, Belgium; Center for Neurosciences, Vrije Universiteit Brussel, Brussels, Belgium.
Helio
H
Fernandez Tellez
Jessa Hospital, Rehabilitation Center Sint-Ursula, Herk-de-Stad, Belgium.
Marc
M
Michielsen
Center for Neurosciences, Vrije Universiteit Brussel, Brussels, Belgium; Department of Rehabilitation Research, Vrije Universiteit Brussel, Brussels, Belgium.
Eric
E
Kerckhofs
Robotics and Multibody Mechanics Research Group, Vrije Universiteit Brussel, Brussels, Belgium.
Dirk
D
Lefeber
Human Physiology Research Group, Vrije Universiteit Brussel, Brussels, Belgium; School of Public Health, Tropical Medicine and Rehabilitation Sciences, James Cook University, Queensland, Australia.
Romain
R
Meeusen
D000328:Adult; D001696:Biomechanical Phenomena / Q000502:physiology; D001921:Brain / Q000502:physiology*; D005260:Female; D005684:Gait / Q000502:physiology*; D006801:Humans; D008297:Male; D012371:Robotics / Q000379:methods*; D014584:User-Computer Interface; D016138:Walking / Q000502:physiology*; D055815:Young Adult