Introduction: The automatic determination of optimal deep brain stimulation (DBS) parameters is
of great importance to improve the stimulation control of the increasingly popular
segmented DBS leads. For these leads, the parameter space of stimulation settings
is too large to be manually explored to its full extent in clinical practice. Thus,
programming algorithms are necessary to obtain optimal stimulation settings and to
reduce programming times. Recently, several such algorithms have been proposed and
been positively validated in simulation studies. However, few data exist validating
the computationally predicted stimulation settings against patient data.
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© 2018 Published by Elsevier Inc.
