20.500.12556/DiRROS-17496 HARE unifying the human activity recognition engineering workflow HARE: unifying the human activity recognition engineering workflow Sensor-based human activity recognition is becoming ever more prevalent. The increasing importance of distinguishing human movements, particularly in healthcare, coincides with the advent of increasingly compact sensors. A complex sequence of individual steps currently characterizes the activity recognition pipeline. It involves separate data collection, preparation, and processing steps, resulting in a heterogeneous and fragmented process. To address these challenges, we present a comprehensive framework, HARE, which seamlessly integrates all necessary steps. HARE offers synchronized data collection and labeling, integrated pose estimation for data anonymization, a multimodal classification approach, and a novel method for determining optimal sensor placement to enhance classification results. Additionally, our framework incorporates real-time activity recognition with on-device model adaptation capabilities. To validate the effectiveness of our framework, we conducted extensive evaluations using diverse datasets, including our own collected dataset focusing on nursing activities. Our results show that HARE’s multimodal and on-device trained model outperforms conventional single-modal and offline variants. Furthermore, our vision-based approach for optimal sensor placement yields comparable results to the trained model. Our work advances the field of sensor-based human activity recognition by introducing a comprehensive framework that streamlines data collection and classification while offering a novel method for determining optimal sensor placement. human activity recognition multimodal classification privacy preservation real-time classification sensor placement nosljivi senzorji fizična aktivnost zdravstvo true false true MDPI Švica Angleški jezik Slovenski jezik © 2023 by the authors Neznano 2023-12-11 11:14:03 2023-12-11 11:14:04 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. 1-23 iss. 23, [article no.] 9571 Vol. 23 Dec. 2023 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2023-10-13 2023-11-29 2023-12-02 681.5 1424-8220 10.3390/s23239571 174721027 https://www.mdpi.com/1424-8220/23/23/9571 1 a4c10c3e-9805-11ee-9ccb-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=23763 RAZ_Konak_Orhan_2023.pdf RAZ_Konak_Orhan_2023.pdf 1 77022A9114AE9FB2ACB53384AF973E4A 4ccc9cd4a6b66b8bc0fffd95e4d246ce05d378d3c0ac2260efa6675307fbb426 2d968759-9807-11ee-9ccb-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=23764 Institut Jožef Stefan 0 0 0