The book reports on the author¿s original work to address the use of today¿s state-of-the-art
smartphones for human physical activity recognition. By exploiting the sensing computing and
communication capabilities currently available in these devices the author developed a novel
smartphone-based activity-recognition system which takes into consideration all aspects of
online human activity recognition from experimental data collection to machine learning
algorithms and hardware implementation. The book also discusses and describes solutions to some
of the challenges that arose during the development of this approach such as real-time
operation high accuracy low battery consumption and unobtrusiveness. It clearly shows that it
is possible to perform real-time recognition of activities with high accuracy using current
smartphone technologies. As well as a detailed description of the methods this book also
provides readers with a comprehensive review of the fundamental concepts in human activity
recognition. It also gives an accurate analysis of the most influential works in the field and
discusses them in detail. This thesis was supervised by both the Universitat Politècnica de
Catalunya (primary institution) and University of Genoa (secondary institution) as part of the
Erasmus Mundus Joint Doctorate in Interactive and Cognitive Environments.
