Activity classification using a single tri-axial accelerometer of smartphone

Abstract

Activity recognition and classification is very useful filed. In this paper, we present the activity classification using a single tri-axial accelerometer of smartphone. Smartphones have a lot of sensors and a powerful performance, and many researchers study using smartphone sensors. Especially, utilization with the accelerometer is very large. The topic of the activity classification can be used as many parts, such as health-care part, medical part, and emergency part. We want to make the activity predictive model in everyday life using the activity classification. To make this model, user's activity should be classified and recorded. In order to classify the daily activity, some elements should be considered. In this paper, we analyze to find the optimized environments for activity classification. © 2012 Springer Science+Business Media.