CSI-based Indoor Fall Detection And Application Research

In nowadays social, the population aging process is accelerating. The elders require more and more home care. Fall, which is one of the major health threats to independent living of elders, will attract the health-care organization's attention. Thus, automatic fall detection is highly in need. Current proposed fall detection systems either need hardware installation or disrupt people's daily life. These limitations make it hard to widely deploy fall detection systems in residential settings. In this work, we analyze the wireless signal to detect fall action, apply the character of CSI to solve these problems.This paper introduce our preliminary study and analysis on the CSI-based indoor fall detection. The major job is building the fine-grained CSI environment perception fingerprint database and the CSI-based fall detection system.The main contribution of this paper can be summarized as follows:(1) Building the fine-grained CSI perception fingerprint database: By analysis of amplitude and phase of CSI, we find the influence mechanism of those. Focusing on the action section, this paper get a high robustness and high sensitivity database.(2) Designing a action fingerprint database-based fall detection method. We use the MIMO and space diversity to achieve the weight voting fusion and combine the CSI database and classification method to design the fall detection system.(3) We test the features of CSI-based environmental perception and the fall detection in different environments. Based on the providing information, we provide the improved scheme.Through this research, we reveal the potential of CSI and MIMO which can be applied in environmental perception and feasibility of CSI-based indoor fall detection. In the paper, we build a fall detection system with high availability.