Feature extraction is crucial for human activity recognition (HAR) using body-worn movement sensors. Recently, learned representations have been used successfully, offering …
Recent improvements in deep learning and hardware support offer a new breakthrough in mobile sensing; we could enjoy context-aware services and mobile healthcare on a mobile …
Traditionally, the sliding window based activity recognition chain (ARC) has been dominating practical applications, in which features are carefully optimized towards scenario …
Z Leng, H Kwon, T Plötz - Proceedings of the 2023 ACM International …, 2023 - dl.acm.org
The development of robust, generalized models for human activity recognition (HAR) has been hindered by the scarcity of large-scale, labeled data sets. Recent work has shown that …
F Duan, T Zhu, J Wang, L Chen… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
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 …
Perinatal stroke (PS) is a serious condition that, if undetected and thus untreated, often leads to life-long disability, in particular Cerebral Palsy (CP). In clinical settings, Prechtl's General …
With the growing interest in smart home environments and in providing seamless interactions with various smart devices, robust and reliable human activity recognition (HAR) …
Multiresident activity recognition (AR), which has become a popular research field in smart environments, aims to recognize the activities of multiple residents based on data collected …
SK Hiremath, T Plötz - Proceedings of the ACM on Interactive, Mobile …, 2020 - dl.acm.org
Research in sensor based human activity recognition (HAR) has been a core concern of the mobile and ubiquitous computing community. Sophisticated systems have been developed …