What can data analysis recommend on design of wearable sensors?

The paper aims at developing recommendations on the design and use of human activity recognition systems based on wearable sensors and their applications. Both the system structure and the application design challenges are addressed. Various design problems are investigated such as the selection of a number and types of sensors, amount of samples used for recognition, choice of machine learning techniques and the features set for a classifier design as well as the type of a training model employed. The design is implemented on the Android smartphone sensors platform and tested by conducting an empirical study in a real-life environment. The study results are provided and discussed. The recommendations on the sensor systems design are derived.