A Multi-Sensor Fusion Scheme to Increase Life Autonomy of Elderly People With Cognitive Problems

Abstract

Elderly people care is a major challenge for the smart-cities of future. This represents a valuable opportunity to develop scalable applications to cover the special needs in terms of health monitoring and accessibility for people with cognitive impairments. In this paper, a complete system to support daily activities of elderly people based on a multi-sensor scheme is presented. This system is intended to be deployed not only at home, but also at crowded places, such as daily care centers. A multi-layer architecture is drawn to ensure system modularity and interoperability of heterogeneous data with concurrent services. The proposed system includes a set of algorithms for data gathering and processing to detect abnormal events in the considered scenarios. The experiments performed in real scenarios have led to a good performance of the algorithms proposed as well as high accuracy in event detection for both environments.

Keywords

• Abnormal behavior detection
• healthcare
• WSN
• multi-modal fusion
• depth sensors