TY  - JOUR
A1  - Konak, Orhan
A1  - van de Water, Robin
A1  - Döring, Valentin
A1  - Fiedler, Tobias
A1  - Liebe, Lucas
A1  - Masopust, Leander
A1  - Postnov, Kirill
A1  - Sauerwald, Franz
A1  - Treykorn, Felix
A1  - Wischmann, Alexander
A1  - Gjoreski, Hristijan
A1  - Luštrek, Mitja
A1  - Arnrich, Bert
T1  - HARE
T2  - Sensors
N2  - 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.
KW  - human activity recognition
KW  - multimodal classification
KW  - privacy preservation
KW  - real-time classification
KW  - sensor placement
Y1  - 2023
UR  - https://publishup.uni-potsdam.de/frontdoor/index/index/docId/64952
SN  - 1424-8220
VL  - 23
IS  - 23
PB  - MDPI
CY  - Basel
ER  -