MER Classification for Deep Brain Stimulation

Deep brain stimulation (DBS) of the subthalamic nu-cleus (STN) has become a common procedure to alle-viate the symptoms of advanced Parkinson’s disease. To estimate the optimal site for placement of the defi-nite electrode, up to five microelectrodes are inserted at first and the neuronal activity at the electrode tip is recorded. These microelectrode recordings (MER) are classified to STN or non-STN signals manually by the surgeon, which requires experience and time. A system has been developed for automatic clas-sification of MER signals. The classifier consists of three levels, each of which using a specific criterion to decide whether a MER is STN signal or not. In the first level, the background activity is examined and those recordings showing increased activity are marked. The second level uses the bursty or irreg-ular behavior of typical STN single cell activity for taking decisions. In the last level, the spike rate of duplicated intervals resulting from level 1 and 2 is examined. Results from all levels are combined and thus STN signals are identified. To enhance the evaluation of the different charac-teristics, signal preprocessing is performed in level 2 and level 3. Wavelet transformation is used to re-move background activity (noise) and a multilevel 1