Implementation of a Wearable Feedback System Monitoring the Activities of Upper-extremities

In the previous work done by ZG.Xiao and C.Menon, the novel idea of using a strap with 8 Force Sensing Resistor (FSR) sensors for monitoring activities of upper-extremities was proposed. The goal of my research is to implement such a system for a low-cost, low power embedded system, a band module, together with a hand-held user interface for rehabilitation related application. For hand gesture classification, the Linear Discriminate Analysis (LDA) method is used. The training and predicting can be done on either a band module or a hand-held user interface. Two system configurations are proposed: real-time band module data sampling and hand-held user interface data analysis, or real-time band module data sampling and analysis. On top of this, the LDA algorithm in C language used in our system has been profiled on an Intel Galileo Gen2 board in order to evaluate its performance on 32-bit embedded platforms for the next generation of our system.