DexterNet: An Open Platform for Heterogeneous Body Sensor Networks and Its Applications

摘要

In this paper, we present an open-source platform for wireless body sensor networks called DexterNet. The system is motivated by shifting research paradigms to support real-time, persistent human monitoring in both indoor and outdoor environments. The platform utilizes a three-layer architecture to control heterogeneous body sensors. The first layer, called the body sensor layer (BSL), deals with design of different wireless body sensors and their instrumentation on the body. We detail two custom-built body sensors: one measuring body motions and the other measuring the ECG and respiratory patterns. At the second layer, called the personal network layer (PNL), the wireless body sensors on a single subject communicate with a mobile base station, which supports Linux OS and the IEEE 802.15.4 protocol. The BSL and PNL functions are abstracted and implemented as an open-source software library, called Signal Processing In Node Environment (SPINE). A DexterNet network is scalable, and can be reconfigured on-the-fly via SPINE. At the third layer, called the global network layer (GNL), multiple PNLs communicate with a remote Internet server to permanently log the sensor data and support higher-level applications. We demonstrate the versatility of the DexterNet platform via three applications: avatar visualization, human activity recognition, and integration of DexterNet with global positioning sensors and air pollution sensors for asthma studies.