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

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 695)

Abstract

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.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.School of Computer EngineeringKIIT UniversityBhubaneswarIndia
  2. 2.Department of Computer Science and EngineeringJadavpur UniversityKolkataIndia

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