HARLib: A human activity recognition library on Android
Hua-Cong Yang, Yichao Li, Zhiyu Liu, Jie Qiu · 2014
Current smartphones are integrated with rich sensors, which provides a good opportunity for the smartphone sensor data mining. By mining these data, we are able to analyze the user's behaviors. This paper describes HARLib, a human activity recognition library on the Android operating system. We use accelerometer built-in smartphone to recognize the user's activities, including walking, running, sitting, standing, lying down and stairs. It can be easy embedded into Android applications and provide a good performance of human activity recognition function.