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A Wearable IoT-Based Fall Detection System Using Triaxial Accelerometer and Barometric Pressure Sensor

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Ubiquitous Networking (UNet 2019)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 12293))

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Abstract

The aim of this research work is to develop a wearable and IoT-based fall detection system that can potentially be integrated within a smart home or a community health center to improve the quality of life of the elderly. This system would enable caregivers to remotely monitor the activities of their dependents and to immediately be notified of falls as adverse events. The proposed hardware architecture includes a processor, a triaxial accelerometer, a barometric pressure sensor, a Wi-Fi module, and battery packs. This unobtrusive architecture causes no interference with daily living while monitoring the falls. The output of the fall detection algorithm is a two-state flag, transmitted to a remote server in real-time.

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Author information

Authors and Affiliations

  1. Faculty of Electrical Engineering, K. N. Toosi University of Technology, 1631714191, Tehran, Iran

    Elahe Radmanesh, Mehdi Delrobaei & Somayyeh Chamani

  2. University Limoges, XLIM, UMR 7252, Limoges, France

    Oussama Habachi, Yannis Pousset & Vahid Meghdadi

Authors
  1. Elahe Radmanesh
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  2. Mehdi Delrobaei
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  3. Oussama Habachi
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  4. Somayyeh Chamani
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  5. Yannis Pousset
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  6. Vahid Meghdadi
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Corresponding author

Correspondence to Elahe Radmanesh .

Editor information

Editors and Affiliations

  1. University of Limoges, Limoges, France

    Oussama Habachi

  2. University of Limoges, Limoges, France

    Vahid Meghdadi

  3. Hassan II University, Casablanca, Morocco

    Essaid Sabir

  4. University of Limoges, Limoges, France

    Jean-Pierre Cances

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Radmanesh, E., Delrobaei, M., Habachi, O., Chamani, S., Pousset, Y., Meghdadi, V. (2020). A Wearable IoT-Based Fall Detection System Using Triaxial Accelerometer and Barometric Pressure Sensor. In: Habachi, O., Meghdadi, V., Sabir, E., Cances, JP. (eds) Ubiquitous Networking. UNet 2019. Lecture Notes in Computer Science(), vol 12293. Springer, Cham. https://doi.org/10.1007/978-3-030-58008-7_13

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  • DOI: https://doi.org/10.1007/978-3-030-58008-7_13

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  • Online ISBN: 978-3-030-58008-7

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