BLE Embedded Solution for Gait Analysis on Subjects Affected by Multiple Sclerosis

Multiple sclerosis (MS), also known al encephalomyelitis disseminata, is a demyelinating disease in which the insulating covers of nerve cells in the brain and spinal cord are damaged. The majority of patients either present with or transition into a progressive course, characterised by the gradual accumulation of disability independent of clinical relapses, which usually significantly affect their ability to walk. This thesis follows the development of a low power embedded device for activity recognition and gait assessment. The Bluetooth Low Energy protocol is studied and applied for wireless communication between the device and a smartphone. A machine learning approach is implemented to detect walking-related activities during the day. Then, data analysis extracts the mobility-related data and uses it to compute gait-related information.