Abstract

Wireless body area networks (WBANs) present unique challenges due to their specific characteristics of mobility and over-the-body radio propagation. A huge amount of factors—both internal and external to the network—affect WBAN channel conditions, so a reliable and comprehensive theoretical model of these communications is unfeasible and impractical in real scenarios. Thus, an empirical performance analysis of several WBAN channels is presented in this work, based on the receiver signal strength indicator (RSSI) and packet reception rate (PRR) metrics. Four different static and dynamic activities have been characterized: standing, sitting, cycling and walking. This analysis confirms the theoretical notions of path attenuation due to body parts obstructing the signal path, while serving as a benchmark for the design of future algorithms. The experiments have been carried out with real hardware nodes with wireless interfaces in three ISM bands: 433 MHz, 868 MHz and 2.4 GHz, evaluating the effect of the transmit power and node placement for different subjects. In all scenarios, the PRR metric reaches its maximum of 100% for both sub-GHz bands. Finally, our study concludes that the RSSI metric is sufficient to exploit the periodicity of dynamic activities, without the need for any extra hardware resources.

Highlights

  • IntroductionWireless body area networks (WBANs) are primarily applied to healthcare and the biomedical field, but they have potential for use in several other areas, such as enhancing the human experience, sport training or even entertainment

  • An empirical performance analysis of several Wireless body area networks (WBANs) channels is presented in this work, based on the receiver signal strength indicator (RSSI) and packet reception rate (PRR) metrics

  • These networks are a subset of Wireless Sensor Networks (WSNs) and consist of low-power and lightweight sensor nodes placed along the human body to monitor its vital functions and other relevant data [1]

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Summary

Introduction

WBANs are primarily applied to healthcare and the biomedical field, but they have potential for use in several other areas, such as enhancing the human experience, sport training or even entertainment

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