The proverb "Actions speak louder than words” contains plenty of truth:
Knowing what activities someone has been performing in the past will divulge a lot of information on the behavior, the aims, and the habits of the person, often more detailed than what this person would tell you. This talk will present a body-worn sensor system for recognizing physical activity based on initial sensors that is currently used in several trials in sleep study and psychiatry. The core of this research is the integration of novel signal processing and machine learning techniques to handle incoming sensor data streams as efficiently as possible, and to make the wearable system run as long as possible on a single battery charge.
Kristof Van Laerhoven obtained his Ph.D. at Lancaster University (UK) and his M.Sc. degree at the University of Brussels (Belgium). He heads the Embedded Sensing Systems lab at the TU Darmstadt (Germany), funded by the Emmy Noether Programme of the German research foundation DFG. His research combines sensing systems with pattern recognition and machine learning, to obtain adaptive and power-efficient systems. These are especially applied in the challenging scenarios of wearable systems and wirelessly connected networks. More information can be found on http://www.ess.tu-darmstadt.de
