Adaptive deep brain stimulation (DBS) is expected to improve Parkinson’s disease (PD) symptoms. This advance in neurostimulation strategy requires to interact with pathological electrical signaling from basal ganglia circuitry and to use this continuous feedback for controlling therapeutic DBS. Further knowledge about how such signals change in terms of clinical phenotypes and rest/movement states is necessary to optimize this adaptive method and to bridge the clinical needs with daily activities. This work assessed the differences in local field potentials (LFP) spectrum recorded from the subthalamic nucleus (STN) in rest and active arm movement and classified these conditions for the different PD clinical subtypes seeking to estimate the cost underlying the early movement detection. Our results suggest there is a tradeoff between the signal length and accuracy, in which the subtypes play an important role in this performance. These findings may define a crucial design variable for real-time applications and allow future perspectives for tailored DBS design.

XII SIMPÓSIO DE ENGENHARIA BIOMÉDICA - IX SIMPÓSIO DE INSTRUMENTAÇÃO E IMAGENS MÉDICAS