Article

Recovery of upper extremity function is particularly recalcitrant to
successful rehabilitation. Robotic-assisted arm training devices integrated with
virtual targets or complex virtual reality gaming simulations are being developed
to deal with this problem. Neural control mechanisms indicate that reaching and
hand-object manipulation are interdependent, suggesting that training on tasks
requiring coordinated effort of both the upper arm and hand may be a more
effective method for improving recovery of real world function. However, most
robotic therapies have focused on training the proximal, rather than distal
effectors of the upper extremity. This paper describes the effects of
robotically-assisted, integrated upper extremity training. METHODS: Twelve
subjects post-stroke were trained for eight days on four upper extremity gaming
simulations using adaptive robots during 2-3 hour sessions. RESULTS: The subjects
demonstrated improved proximal stability, smoothness and efficiency of the
movement path. This was in concert with improvement in the distal kinematic
measures of finger individuation and improved speed. Importantly, these changes
were accompanied by a robust 16-second decrease in overall time in the Wolf Motor
Function Test and a 24-second decrease in the Jebsen Test of Hand Function.
CONCLUSIONS: Complex gaming simulations interfaced with adaptive robots requiring
integrated control of shoulder, elbow, forearm, wrist and finger movements appear
to have a substantial effect on improving hemiparetic hand function. We believe
that the magnitude of the changes and the stability of the patient's function
prior to training, along with maintenance of several aspects of the gains
demonstrated at retention make a compelling argument for this approach to training.

Langue : ANGLAIS