title: Adaptation to constant-magnitude assistive forces: kinematic and neural correlates.
abstract: In many robot-assisted rehabilitation and motor skill learning applications, robots generate forces that facilitate movement performance. While there is some evidence that assistance is beneficial, the underlying mechanisms of action are largely unknown, and it is unclear what force patterns are more effective. Here, we investigate how reaching movements (and their neural correlates) are altered by 'assistive' forces. Subjects performed center-out reaching movements, under the influence of a robot-generated force, constant in magnitude and always directed toward the target. The experimental protocol included three phases: (1) baseline (no forces), (2) force field (with two different force levels, 3 N and 6 N, applied in random order), and (3) after-effect (no forces). EEG activity was recorded from motor and frontal cortical areas. In both movement kinematics and EEG activity, we looked at the effects of forces, of adaptation to such forces and at the aftereffects of such adaptation. Assistive forces initially induced a degraded performance and in general alterations in movement kinematics. However, subjects quickly adapted to the perturbation by improving their performance. With regard to EEG activity, we found (1) an increased beta band synchronization just before movements and an alpha band synchronization in the ipsilateral hemisphere, both proportional to force magnitude; (2) a gradual decrease in alpha band synchronization with practice in the contralateral hemisphere; (3) an increase in theta band synchronization in the later stage of the force epochs; and (4) an ipsilateral to contralateral shift (from baseline to aftereffect) of theta band synchronization. These results point to the need for a careful design of assistive forces to effectively facilitate motor performance and motor learning. Moreover, EEG signals exhibit distinct features related to force and adaptation. Therefore, at least in principle, the latter might be used to monitor the learning process and/or to regulate the amount of assistance.
authors.affiliation: Department of Informatics, Systems and Telematics, University of Genoa, Via Opera Pia 13, 16145 Genoa, Italy. vladimir.novakovic@unige.it
authors.forename: Vladimir
authors.initials: V
authors.lastname: Novakovic
authors.forename: Vittorio
authors.initials: V
authors.lastname: Sanguineti
mesh_terms: D000222:Adaptation, Physiological / Q000502:physiology*; D000328:Adult; D000704:Analysis of Variance; D001696:Biomechanical Phenomena; D001931:Brain Mapping; D004569:Electroencephalography / Q000379:methods; D004576:Electromyography / Q000379:methods; D019054:Evoked Potentials, Motor / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009068:Movement / Q000502:physiology*; D018482:Muscle, Skeletal / Q000294:innervation / Q000502:physiology; D011597:Psychomotor Performance / Q000502:physiology*; D011930:Reaction Time / Q000502:physiology; D050781:Transcranial Magnetic Stimulation / Q000379:methods