In Shift and In Variance: Assessing the Robustness of HAR Deep Learning Models Against Variability - Khaked, Azhar Ali; Oishi, Nobuyuki; Roggen, Daniel; Lago, Paula (Sensors (Basel, Switzerland), 2025)
Keywords: Accuracy; Automation; Classification; data heterogeneity; Datasets; Deep Learning; distribution shift; Human Activities; human activity recognition; Humans; Machine learning; Measuring instruments; Monitoring, Physiologic - methods; Neural networks; Performance evaluation; real world variability; Sensors; Smartphones; Smartwatches; User behavior; Wearable computers; Wearable Electronic Devices; wearable sensors; deep learning; real world variability; model robustness evaluation; data heterogeneity; human activity recognition; distribution shift; wearable sensors