Deep learning (DL) for sensor-based human activity recognition (HAR) has been a focus of research in recent years. Sensor data stream segmentation is a core element in HAR, which has currently been treated as an independent preprocessing task, usually with a fixed-size window. This has led to two critical problems, namely the multiclass window problem caused by possible multiple activities within a fixed-size window and the fluctuation of prediction results due to noisy data and oversegmentation. To address these research challenges, in this ar...
