It is undeniable that mobile devices have become an inseparable part of human's daily
routines due to the persistent growth of high-quality sensor devices, powerful computational
resources and massive storage capacity nowadays. Similarly, the fast development of
Internet of Things technology has motivated people into the research and wide applications
of sensors, such as the human activity recognition system. This results in substantial existing
works that have utilized wearable sensors to identify human activities with a variety of …

Human activity recognition (HAR) can be exploited to great benefits in many applications,
including elder care, health care, rehabilitation, entertainment, and monitoring. Many
existing techniques, such as deep learning, have been developed for specific activity
recognition, but little for the recognition of the transitions between activities. This work
proposes a deep learning based scheme that can recognize both specific activities and the
transitions between two different activities of short duration and low frequency for health care …