부산대학교 도서관

Screen time analytics on smartphones have become a topic of interest. The digital well-being framework in Android and iOS devices present statistics on phone usage and time spent on apps. However, these tools provide the data on only an hourly basis, so we cannot utilize it in any form for long-term behavioral analysis of smartphone users. Several academic works have studied smartphone user behaviors by developing and installing custom mobile apps that record mobile app usage and built-in sensor data. The studies reveal that prolonged smartphone usage negatively impacts users' physical and mental health. However, these apps are available upon request and may sometimes crash due to operating system versions. Despite hundreds of screen time and sensor data apps on Google PlayStore, they are available separately and not as a single all-in-one app. In this work, we present a unified mobile application that collects phone usage and sensor data with minute-by-minute levels of granularity and infers human physical activity, sleep, and unlock duration. All three metrics are vital to identifying symptoms of mental health disorders such as depression and anxiety. The app has several benefits to various stakeholders, including industry-level app developers and organizations focusing on mental health.