Learning to Detect User Activity and Availability from a Variety of Sensor Data
PERCOM '04 Proceedings of the Second IEEE International Conference on Pervasive Computing and Communications (PerCom'04)
ICHIT '06 Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 02
Validation of a remote monitoring system for the elderly: Application to mobility measurements
Technology and Health Care
Evidential fusion of sensor data for activity recognition in smart homes
Pervasive and Mobile Computing
Movement Activity Monitoring of Elderly People
ICCEA '10 Proceedings of the 2010 Second International Conference on Computer Engineering and Applications - Volume 02
The role of prediction algorithms in the MavHome smart home architecture
IEEE Wireless Communications
A model for the measurement of patient activity in a hospital suite
IEEE Transactions on Information Technology in Biomedicine
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A research and development innovation project partly funded by the French company EDF was conducted for the advancement of smart homes. The aim is to help elderly to live at home in safe conditions. The experiments were carried out in a long-term setting in Orléans (France). As part of the project, the monitoring system aims to assess daily activity habits or lifestyle at home (fall, restlessness, fainting, running away....) through individual mobility data collection and analysis. This paper describes the architecture of the multisensor monitoring system used to collect individual mobility data, and presents the software used to assess the daily activity habits or lifestyle. Some preliminary results are given.