Real-time arm movement recognition using FPGA

In this paper we present a FPGA-based system to detect three elementary arm movements in real-time (reach and retrieve, lift cup to mouth, rotation of the arm) using data from a wrist-worn accelerometer. Recognition is carried out by accurately mapping transitions of predefined, standard orientations of an accelerometer to the corresponding arm movements. The algorithm is coded in HDL and synthesized on the Altera DE2-115 FPGA board. For real-time operation, interfacing between the streaming sensor unit, host PC and the FPGA was achieved through a combination of Bluetooth, RS232 and an application software developed in C# using the .NET framework to facilitate serial port controls. The synthesized design used 1804 logic elements and recognised the performed arm movement in 41.2 μs, @50 MHz clock on the FPGA. Our experimental results show that the system can recognise all three arm movements with accuracies ranging 85%-96% for healthy subjects and 63%-75% for stroke survivors involved in `making-a-cup-of-tea', typical of an activity of daily living (ADL).