Abstract. In this paper, we propose a two-layered classification approach to effectively recognize the physical activities while the smartphone is placed at any four common positions on the body. Then we implement a Life Record app on smartphone that automatically classifies physical activities and records them as the personal life logs. For assisting users in comprehending their daily activities, the system also provides the visualization interface that shows the brief descriptions of their life logs.We demonstrate that the system possesses less limitation to monitor daily activities that the users are not restricted to carry their smartphones in specific positions. Another major benefit of our system is to provide a complete overview of personal activities, which enhances the self-awareness of physical activity in our daily life through an intuitive visualization interface. Furthermore, analysis of life logs can also be applied in specific services or recommendation applications in the future.
Keywords: Activity monitoring · Life record · Physical inactivity · Pattern recognition · Data visualization
IntroductionPhysical inactivity is one of the most important modifiable risk factors, and it causes unhealthy life habits such that most people spend their leisure time involved in sedentary pursuits. Due to this lack of physical activity, more and more people have become overweight (body mass index ≥25 kg/m 2 ) and even have become obese (body mass index ≥30 kg/m 2 ). Globally, in 2005, it was estimated that over 1 billion people were overweight, including 805 million women, and that over 300 million people were obese. By 2015, it has been estimated that over 1.5 billion people will be overweight [1]. Overweight and obesity, moreover, will cause increasing risk for various chronic diseases, such as diabetes, cardiovascular diseases, hypertension and cancer.