Neurological pathologies frequently require continuous and reliable monitoring of patient movements, especially during rehabilitation. This thesis will follow the steps of the development of a firmware for a wearable embedded system that uses Wi-Fi networking to send the motion data that has to be analysed. The Zephyr Real-Time Operating System (RTOS), which was selected for the system due to its robust Internet of Things (IoT) capabilities and modular architecture, serves as its foundation.A low power 9-axis inertial sensor was selected for gathering movements data. The firmware efficiently manages data acquisition, processing, and wireless transmission to external devices or cloud platforms for further analysis.