Human activity recognition (HAR) from wearable motion sensor data is a promising research
field due to its applications in healthcare, athletics, lifestyle monitoring, and computer–
human interaction. Smartphones are an obvious platform for the deployment of HAR
algorithms. This paper provides an overview of the state-of-the-art when it comes to the
following aspects: relevant signals, data capture and preprocessing, ways to deal with
unknown on-body locations and orientations, selecting the right features, activity models and …