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Objective: Closed-loop deep brain stimulation (DBS) may improve currentclinical DBS treatment for neurological movement disorders, but controlalgorithms may perform differently across patients. New metrics are needed forcomparing and evaluating closed-loop algorithm performance that address thespecific needs of closed-loop neuromodulation controllers. Approach: A metricis proposed for system performance that includes normalized terms that can beused to compare algorithm performance for a patient. This metric was evaluatedusing two closed-loop control algorithms that were tested in patients withParkinson's Disease (PD) who experience rest tremor. Main Results: The metric'sresulting balance between tremor treatment and power savings varied on a perpatient and algorithm basis. This was expected given how each trial resulted ina variable reduction in stimulation power at the cost of additional tremor forthe patient when compared to open-loop stimulation. Significance: The proposedmetric will aid in clinical evaluation of new algorithms and provide abenchmark for future system designers. This will be important given the growingpotential applications of dynamically adjusted neural stimulation.ClinicalTrials.gov Identifier: NCT02384421.

A Metric for Evaluating and Comparing Closed-Loop Deep Brain Stimulation Algorithms