Background and Purpose
Because robotic devices record the kinematics and kinetics of human
movements with high resolution, we hypothesized that robotic measures
collected longitudinally in patients after stroke would bear a significant
relationship to standard clinical outcome measures and, therefore, might
provide superior biomarkers.
Methods
In patients with moderate-to-severe acute ischemic stroke, we used
clinical scales and robotic devices to measure arm movement 7, 14, 21, 30,
and 90 days after the event at 2 clinical sites. The robots are interactive
devices that measure speed, position, and force so that calculated kinematic
and kinetic parameters could be compared with clinical assessments.
Results
Among 208 patients, robotic measures predicted well the clinical
measures (cross-validated R2 of modified Rankin
scale=0.60; National Institutes of Health Stroke Scale=0.63;
Fugl-Meyer=0.73; Motor Power=0.75). When suitably scaled and combined by an
artificial neural network, the robotic measures demonstrated greater
sensitivity in measuring the recovery of patients from day 7 to day 90
(increased standardized effect=1.47).
Conclusions
These results demonstrate that robotic measures of motor performance
will more than adequately capture outcome, and the altered effect size will
reduce the required sample size. Reducing sample size will likely improve
study efficiency.
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