Vital Signs Telemonitoring by Using Smart Body Area Networks, Mobile Devices and Advanced Signal Processing

  • Hariton CostinEmail author
  • Cristian Rotariu
Part of the Intelligent Systems Reference Library book series (ISRL, volume 137)


In the last years the demographic changes and ageing of population increase health care demand. The growing number of chronic patients and elders requires close attention to their health conditions. In this paper we present the realization of a wireless remote monitoring system, based on body area network of medical sensors, capable to measure process and transmit patient’s physiologic signals (electrocardiogram, respiratory rhythm, saturation of arterial oxygen, blood pressure and body temperature) to a central medical server. The use of system is suitable for continuous long-time monitoring, as a part of a diagnostic procedure or can achieve medical assistance of a chronic condition. We used custom developed and commercially available devices, low power microcontrollers and RF transceivers that perform measurements and transmit the corresponding numerical values to the Personal Server. The Personal Server, in the form of a personal digital assistant (PDA) or a smartphone, runs a monitor application, receives the physiological signals from the monitoring devices, activates the alarms when the monitored parameters exceed the preset limits, and communicates periodically to the central server by using WiFi or GSM/GPRS connections. The application programs are complemented by automatic atrial fibrillation detection through some advanced signal processing techniques, as well as by patient localization on different maps by means of GPS methodology. Thus, by adding capability of automatic detection of certain heart diseases (for instance), the telemonitoring process becomes “smarter” and more efficient than the traditional approaches based on visualization of raw data.


Advanced signal processing Body area networks Mobile devices Vital signs telemonitoring GPS localization Wireless sensor networks 


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Faculty of Medical BioengineeringGrigore T, Popa University of Medicine and PharmacyIasiRomania
  2. 2.Institute of Computer Science of Romanian AcademyIași BranchRomania

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