Creating and benchmarking a new dataset for physical activity monitoring

Physical activity monitoring has recently become an important field in wearable computing research. However, there is a lack of a commonly used, standard dataset and established benchmarking problems. In this work, a new dataset for physical activity monitoring --- recorded from 9 subjects, wearing 3 inertial measurement units and a heart rate monitor, and performing 18 different activities --- is created and made publicly available. Moreover, 4 classification problems are benchmarked on the dataset, using a standard data processing chain and 5 different classifiers. The benchmark shows the difficulty of the classification tasks and exposes some challenges, defined by e.g. a high number of activities and personalization.