可穿戴无线体域网中异质传感器数据融合算法研究

摘要

为构建一个高精度稳定的可穿戴老年人健康监测系统，提出基于可穿戴无线体域网技术的异质传感器数据融合算法。选择人体血压、指脉、皮肤电阻、呼吸和姿态等5个体征参数采集节点对老年人进行监测，并采用蓝牙将异质传感器采集的数据传输到智能手机，通过手机通信网络与服务中心、用户家人等进行交互，组成以可穿戴技术为主的无线体域网。该系统的核心是姿态计算，以Kalman滤波算法为基础进行数据融合，降低系统噪声，提高系统稳定性。%A data fusion algorithm based on wearable wireless body area network technology is proposed to construct a high precision and stable monitoring system for the elderly. We chose human blood pressure, refers to the veins, skin resistance, breathing and posture parameters levy collected five individual nodes to monitor the elderly, and uses Bluetooth to transmit data collected by heterogeneous sensors to smartphones,and interact via mobile communications network and service centers, family and other users, composition with wearable technology based wireless body area network. The core of the system is the attitude calculation, and the data fusion based on Kalman filtering algorithm is proposed to reduce the system noise and improve the stability of the system.