This study presents an approach to real-time data acquisition and processing using Inertial Measurement Units (IMUs) in a System-on-Chip (SoC) based on Field-Programmable Gate Array (FPGA). By leveraging the parallel processing capabilities of FPGAs, the system achieves a low latency, essential for real-time applications where accurate orientation estimation, such as in neurorehabilitation. In this context, the use of IMUs and FPGAs can be particularly beneficial for movement assessment, biofeedback, and the control of assistive devices, which are fundamental in rehabilitation. The experimental results demonstrate the effectiveness of this approach, with minimal latency, which is critical for therapies that depend on the patient’s rapid response to stimuli. This paper discusses the materials and methods used, including the SoC architecture for data processing, showing the potential of FPGA-based SoCs to enhance performance in rehabilitation-focused applications, offering significant improvements in the precision and efficiency of monitoring and control systems in this field.