• motion capture
• kinect
• imu
• sensor fusion
• Rehubility
• teleriabilitazione

Thesis tele-rehabilitation field, with the development of the Rehubility system for the remote support of rehabilitation activities, mainly aimed at the elderly. It describes the hardware actively used, namely IMU, DCF and 3D Azure Kinect camera, characterizing the components and focusing in detail on the camera (its operations for the extraction of the patient's Skeleton from the Kinect's Point Cloud). Then, the analysis of the Rehubility software Workflow is presented for the execution of an exergame, the reception of data through the UDP protocol, their time synchronization, filtering and sending to the UI for viewing the movements carried out on an avatar. Subsequently, we focus on the Sensor Fusion techniques analyzed in the literature to allow the merging of IMU and Azure Kinect data and describe the Kalman Filter, used for this purpose, reporting the underlying theory and the specific implementation used in this project. Finally, the preliminary tests carried out on the entire Rehubility software are reported, demonstrating its operation for each available exercise. In conclusion, observations on the project and its future developments are reported.