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BLE-GSpeed: A New BLE-Based Dataset to Estimate User Gait Speed

Author

Listed:
  • Emilio Sansano-Sansano

    (Institute of New Imaging Technologies, Universitat Jaume I, Avda. Vicente Sos Baynat S/N, 12071 Castellón, Spain)

  • Fernando J. Aranda

    (Sensory Systems Research Group, University of Extremadura, 06006 Badajoz, Spain)

  • Raúl Montoliu

    (Institute of New Imaging Technologies, Universitat Jaume I, Avda. Vicente Sos Baynat S/N, 12071 Castellón, Spain)

  • Fernando J. Álvarez

    (Sensory Systems Research Group, University of Extremadura, 06006 Badajoz, Spain)

Abstract

To estimate the user gait speed can be crucial in many topics, such as health care systems, since the presence of difficulties in walking is a core indicator of health and function in aging and disease. Methods for non-invasive and continuous assessment of the gait speed may be key to enable early detection of cognitive diseases such as dementia or Alzheimer’s disease. Wearable technologies can provide innovative solutions for healthcare problems. Bluetooth Low Energy (BLE) technology is excellent for wearables because it is very energy efficient, secure, and inexpensive. In this paper, the BLE-GSpeed database is presented. The dataset is composed of several BLE RSSI measurements obtained while users were walking at a constant speed along a corridor. Moreover, a set of experiments using a baseline algorithm to estimate the gait speed are also presented to provide baseline results to the research community.

Suggested Citation

  • Emilio Sansano-Sansano & Fernando J. Aranda & Raúl Montoliu & Fernando J. Álvarez, 2020. "BLE-GSpeed: A New BLE-Based Dataset to Estimate User Gait Speed," Data, MDPI, vol. 5(4), pages 1-15, December.
    • Handle: RePEc:gam:jdataj:v:5:y:2020:i:4:p:115-:d:457911
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    References listed on IDEAS

    as
    1. Fernando J. Aranda & Felipe Parralejo & Fernando J. Álvarez & Joaquín Torres-Sospedra, 2020. "Multi-Slot BLE Raw Database for Accurate Positioning in Mixed Indoor/Outdoor Environments," Data, MDPI, vol. 5(3), pages 1-20, July.
    2. Germán Martín Mendoza-Silva & Miguel Matey-Sanz & Joaquín Torres-Sospedra & Joaquín Huerta, 2019. "BLE RSS Measurements Dataset for Research on Accurate Indoor Positioning," Data, MDPI, vol. 4(1), pages 1-17, January.
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    Cited by:

    1. Joaquín Torres-Sospedra & Aleksandr Ometov, 2021. "Data from Smartphones and Wearables," Data, MDPI, vol. 6(5), pages 1-3, April.

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