RSSI-Based Posture Identification for Repeated and Continuous Motions in Body Area Network

摘要

Node-wise suitable posture-based data transmission reduces the energy consumption and prolongs the network lifetime. But, the challenging task is to classify and identify the posture sequence for a repeated activity such as walk, freehand exercise, and run in body area network (BAN) with low-cost (without using motion-detecting sensors like accelerometer) solution. This study proposes a solution to identify and classify the posture-based movements in repeated activity like a freehand exercise in BAN after observing the variation of received signal strength indicator (RSSI) over time. Analysis through simulation results shows that proposed solution can achieve the goal.