Article

Robot-assisted therapy has become increasingly common in neurorehabilitation.
Sophisticated controllers have been developed for robots to assist and cooperate
with the patient. It is difficult for the patient to judge to what extent the
robot contributes to the execution of a movement. Therefore, methods to
comprehensively quantify the patient's contribution and provide feedback are of
key importance. We developed a method comprehensively to estimate the patient's
contribution by combining kinematic measures and the motor assistance applied.
Inverse dynamic models of the robot and the passive human arm calculate the
required torques to move the robot and the arm and build, together with the
recorded motor torque, a metric (in percentage) that represents the patient's
contribution to the movement. To evaluate the developed metric, 12 nondisabled
subjects and 7 patients with neurological problems simulated instructed movement
contributions. The results are compared with a common performance metric. The
estimation shows very satisfying results for both groups, even though the arm
model used was strongly simplified. Displaying this metric to patients during
therapy can potentially motivate them to actively participate in the training.

Langue : ANGLAIS