Data flow-driven BAN: Architecture and algorithms

Abstract

This chapter refl ects the objectives and the design of the StrokeBack Body Area Network (BAN) with respect to the requirements given by the application scenarios of clinical assessment and recognition of daily activities, as well as the user feedback from patients and therapists. The StrokeBack sensor platform, called GHOST, is designed to provide smaller size, more effi cient power consumption, stronger security means and much better usability than the currently available state-of-the-art sensing devices. The GHOST platform is a tiny sensor platform with inertial sensors, Qi compliant wireless power transfer and an embedded Bluetooth Low-Energy (Bluetooth 4.0) front end. In a full package, the complete GHOST sensor platform is of matchbox size only, including a Lithium cell battery pack and a receiver coil for wireless power transfer. Two versions of the StrokeBack sensor nodes have been assembled. The fi rst sensor node design uses the shelf components while the second variant of the sensor nodes incorporates a customised cryptomicrocontroller providing enhanced security options. This platform is used for detection of Activities of Daily Living (ADL) within the StrokeBack project, where the patient wears the platform at the affected limb. The daily data fl ow principle is described in detail. The platform collects movement data from accelerometer, gyroscope and magnetometer throughout the day, which are uploaded and analysed during the night when the sensor resides in the wireless charging station.