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1%, comparable with the use of the full set of features. In the same conditions, the spike-dependent features provided the lowest accuracy (86.8%), while a power density-based index was shown to be a good indicator of STN activity (92.3%). Results suggest that a small and simple set of features can be used for an efficient classification of microelectrode recordings to implement an intraoperative support for clinical decision during deep brain stimulation surgery. Results suggest that a small and simple set of features can be used for an