3 papers
cs.LG2025
Physically Plausible Data Augmentations for Wearable IMU-based Human Activity Recognition Using Physics Simulation
Nobuyuki Oishi, Philip Birch, Daniel Roggen +1
The scarcity of high-quality labeled data in sensor-based Human Activity Recognition (HAR) hinders model performance and limits generalization across real-world scenarios. Data aug…
cs.HC2025
In Shift and In Variance: Assessing the Robustness of HAR Deep Learning Models against Variability
Azhar Ali Khaked, Nobuyuki Oishi, Daniel Roggen +1
Human Activity Recognition (HAR) using wearable inertial measurement unit (IMU) sensors can revolutionize healthcare by enabling continual health monitoring, disease prediction, an…
cs.HC2024
A State-of-the-Art Review of Computational Models for Analyzing Longitudinal Wearable Sensor Data in Healthcare
Paula Lago
Wearable devices are increasingly used as tools for biomedical research, as the continuous stream of behavioral and physiological data they collect can provide insights about our h…