Sleep quality monitoring with ambient and mobile sensing

Evaluating daily life quality is important in ambient intelligence applications targeted for health status monitoring. When we consider the fact that people approximately spend one-third of their lives sleeping, we need to monitor the sleep quality as well as the activities of daily living in order to be able to provide a seamless health monitoring system. In this paper, a seamless activity recognition system that makes use of multi-modal wireless sensor networks (WSNs) and mobile phones is proposed. The proposed system is then used to collect life-log and sleep behavior data from actual users. In the lights of this information, important factors affecting the sleep quality of a person is extracted.