The aim of this work is to implement and validate an automated method for the localization of body-worn inertial sensors. Often, body-sensor networks with inertial measurement units (IMU) used in rehabilitation and ambient monitoring of patients with movement disorders, require specific markings or labels for the correct body placement. This introduces a burden, which, especially for ambient monitoring, could lead to errors or reduced adherence. We propose a method to automatically identify sensors attached on a predefined set of body placements, namely, wrists, shanks and torso. The method was used in a multi-site clinical trial with Parkinson's disease patients and in 45 sessions it identified sensor placement on torso, wrists and shanks with 100% accuracy, discriminated between left and right shank with 100% accuracy and between left and right wrist with 98% accuracy. This is remarkable, considering the presence of parkinsonian motor symptoms causing abnormal movement patterns, such as dyskinesia.Clinical Relevance- This method can facilitate home monitoring of patients with movement disorders.