Classifier-based closed-loop deep brain stimulation for essential tremor

Deep brain stimulation (DBS) is a common therapy for the treatment of essential tremor (ET). Currently, this technology continuously delivers stimulation to deep brain regions to mitigate symptoms. Closed-loop DBS aims to deliver stimulation only when symptoms are present, thus improving battery life and decreasing potential side effects. In this study, we used an investigational DBS device implanted with an electrocorticography strip in a subject with essential tremor. Using local field potentials sensed from motor cortex, we built a system of classifiers capable of detecting tremor-inducing movement. These classifiers were incorporated into a closed-loop DBS system which changed stimulation voltage in real time to ameliorate tremor. This is the first time that machine learning has been used in a CLDBS system to detect symptoms and change DBS parameters in real time.