RSSI-Based Posture Identification for Repeated and Continuous Motions in Body Area Network
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.
- 1.Maitra, T., Mallick, P., Roy, S.: LD-MAC: A load-distributed data transmission in body area network. In: IEEE SENSORS, Orlando, FL, pp. 1–3. (2016)Google Scholar
- 4.Castalia: Wireless Sensor Networks and BAN Simulator. http://castalia.npc.nicta.com.au
- 5.Mukherjee, N., Neogy, S., Roy, S.: Building Wireless Sensor Networks: Theoretical and Practical Perspectives. CRC Press, London (2015)Google Scholar