Adaptive Deep Brain Stimulation

The objective of improving deep brain stimulation for the treatment of movement disorders in an automated and closed-loop context, such as through adaptive deep brain stimulation, represents a substantial evolution. Realizing this technological advance would considerably alleviate clinical resources, provide optimal therapeutic intervention in essentially real-time, and conserve deep brain stimulation battery usage. An inherent aspect of adaptive deep brain stimulation is the requirement for realistic feedback of the symptomatic response. Two proposed strategies are neurophysiological and kinematic in concept. One approach would utilize electrodes to ascertain local field potential activity, such as beta oscillation, which would require deep brain stimulation electrodes with sensing capability. The other approach would be to apply extrinsically through a wearable and wireless inertial sensor system to quantify the tremor. Using quantified feedback, the optimal parameter configuration would be specified through algorithms, such as incorporating machine learning. An assortment of adaptive deep brain stimulation strategies are reviewed.