Recognizing Breathing Rate and Movement While Sleeping in Home Environment

  • Maksym GaidukEmail author
  • Ralf Seepold
  • Natividad Martínez Madrid
  • Simone Orcioni
  • Massimo Conti
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 627)


The recovery of our body and brain from fatigue directly depends on the quality of sleep, which can be determined from the results of a sleep study. The classification of sleep stages is the first step of this study and includes the measurement of vital data and their further processing. The non-invasive sleep analysis system is based on a hardware sensor network of 24 pressure sensors providing sleep phase detection. The pressure sensors are connected to an energy-efficient microcontroller via a system-wide bus. A significant difference between this system and other approaches is the innovative way in which the sensors are placed under the mattress. This feature facilitates the continuous use of the system without any noticeable influence on the sleeping person. The system was tested by conducting experiments that recorded the sleep of various healthy young people. Results indicate the potential to capture respiratory rate and body movement.



This research was partially funded by the EU Interreg V-Program “Alpenrhein-Bodensee-Hochrhein”: Project “IBH Living Lab Active and Assisted Living”, grants ABH040, ABH041 and ABH066.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Maksym Gaiduk
    • 1
    • 2
    Email author
  • Ralf Seepold
    • 1
    • 3
  • Natividad Martínez Madrid
    • 3
    • 4
  • Simone Orcioni
    • 5
  • Massimo Conti
    • 5
  1. 1.HTWG KonstanzKonstanzGermany
  2. 2.University of SevilleSevilleSpain
  3. 3.Department of Information and Internet TechnologySechenov UniversityMoscowRussian Federation
  4. 4.Reutlingen UniversityReutlingenGermany
  5. 5.Department of Information EngineeringUniversità Politecnica delle MarcheAnconaItaly

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