Characterization of a low consumption wireless sensor node for the intensive transmission of physiological signals

Ricardo Yauri, Santiago Rubiños, Juan Grados, Mario Chauca

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


This paper describes the development and implementation of low power consumption wireless sensor nodes for the periodic monitoring of physiological signals with intensive data transmission, using Wi-Fi and ZigBee wireless communication modules, obtaining operation characteristics from the energy point of view that allow to increase the life time of the sensor node. The sensor nodes are designed and built using low energy consumption electronic devices to evaluate their energy performance using current data, transmission time, data transmission period and the relationship with the sensor node's lifetime when transmitting electrocardiographic (ECG), temperature and pulse type physiological signals. The development of this work generates recommendations for the design, development and construction of sensor nodes where the energy consumption of the wireless communication modules is evaluated. In this way, results are obtained that can allow the data transmission period, current consumption and size of data sent to be related to the operating time, defining the operating conditions and wireless technologies that allow the optimization of energy consumption when data is sent to Internet monitoring applications.

Original languageEnglish
Pages (from-to)957-965
Number of pages9
JournalIndonesian Journal of Electrical Engineering and Computer Science
Issue number2
StatePublished - May 2019
Externally publishedYes

Bibliographical note

Funding Information:
This paper was developed in the Faculty of Electrical and Electronic Engineering, National University of Callao and the laboratories of INICTEL-UNI (National Institute of Research and Training in Telecommunications-National University of Engineering).

Publisher Copyright:
© 2019 Institute of Advanced Engineering and Science. All rights reserved.

Copyright 2019 Elsevier B.V., All rights reserved.


  • BAN
  • GPRS
  • Sensors
  • WSN
  • Wi-Fi
  • ZigBee


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