SONAR, a nursing activity dataset with inertial sensors.

Journal: Scientific data
Published Date:

Abstract

Accurate and comprehensive nursing documentation is essential to ensure quality patient care. To streamline this process, we present SONAR, a publicly available dataset of nursing activities recorded using inertial sensors in a nursing home. The dataset includes 14 sensor streams, such as acceleration and angular velocity, and 23 activities recorded by 14 caregivers using five sensors for 61.7 hours. The caregivers wore the sensors as they performed their daily tasks, allowing for continuous monitoring of their activities. We additionally provide machine learning models that recognize the nursing activities given the sensor data. In particular, we present benchmarks for three deep learning model architectures and evaluate their performance using different metrics and sensor locations. Our dataset, which can be used for research on sensor-based human activity recognition in real-world settings, has the potential to improve nursing care by providing valuable insights that can identify areas for improvement, facilitate accurate documentation, and tailor care to specific patient conditions.

Authors

  • Orhan Konak
    Digital Health Center, Hasso Plattner Institute, University of Potsdam, 14482 Potsdam, Germany.
  • Valentin Döring
    University of Potsdam, Digital Engineering Faculty, Digital Health - Connected Healthcare of the Hasso Plattner Institute, Potsdam, 14482, Germany.
  • Tobias Fiedler
    University of Potsdam, Digital Engineering Faculty, Digital Health - Connected Healthcare of the Hasso Plattner Institute, Potsdam, 14482, Germany.
  • Lucas Liebe
  • Leander Masopust
    University of Potsdam, Digital Engineering Faculty, Digital Health - Connected Healthcare of the Hasso Plattner Institute, Potsdam, 14482, Germany.
  • Kirill Postnov
  • Franz Sauerwald
  • Felix Treykorn
    University of Potsdam, Digital Engineering Faculty, Digital Health - Connected Healthcare of the Hasso Plattner Institute, Potsdam, 14482, Germany.
  • Alexander Wischmann
    University of Potsdam, Digital Engineering Faculty, Digital Health - Connected Healthcare of the Hasso Plattner Institute, Potsdam, 14482, Germany.
  • Stefan Kalabakov
    Department of Intelligent Systems, Jožef Stefan Institute, 1000 Ljubljana, Slovenia.
  • Hristijan Gjoreski
    Department of Intelligent Systems, Jožef Stefan Institute, Jožef Stefan International Postgraduate School, Jamova cesta 39, Ljubljana, Slovenia. Electronic address: hristijan.gjoreski@ijs.s.
  • Mitja Lustrek
  • Bert Arnrich
    Hasso Plattner Institute, University of Potsdam, Germany.