This article presents the development of a system capable of automatically classifying two levels of resting tremor in patients with Parkinson's disease. For this, a wearable device was designed to collect tremor signals, attributes were extracted from these signals and applied in classifier models (KNN and Random Forest). The model results were compared with the labels given by neurologists.