With the widespread proliferation of (miniaturized) sensing facilities and the massive growth
and popularity of the field of machine learning (ML) research, new frontiers in automated …

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 …

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 …

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 …

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 …