20.500.12556/DiRROS-17497 SONAR, a nursing activity dataset with inertial sensors 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. nursing documentation nursing activities SONAR sensors negovalna dokumentacija aktivnosti zdravstvene nege SONAR senzorji true false true Springer Nature Švica Angleški jezik Slovenski jezik © The Author(s) 2023 Neznano 2023-12-11 11:28:52 2023-12-11 11:28:53 2023-12-12 03:38:37 0000-00-00 00:00:00 2023 0 0 Nasl. z nasl. zaslona; Soavtor iz Slovenije: Mitja Luštrek; Opis vira z dne 4. 12. 2023; str. 1-12 Vol. 10, article no. 727 2023 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2023-05-02 2023-10-05 2023-10-20 681.5 2052-4463 10.1038/s41597-023-02620-2 174723075 https://www.nature.com/articles/s41597-023-02620-2#article-info 1 b0b51a37-9807-11ee-9ccb-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=23765 RAZ_Konak_Orhan_2023.pdf RAZ_Konak_Orhan_2023.pdf 1 F277E14245FB7A592D370FB8C0D9297D 67811bfc6f72f3e5f4fdc70a09ed2621924bd9a5a9818f23672793dc7d1145fe 985897df-9808-11ee-9ccb-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=23766 Institut Jožef Stefan 0 0 0