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Ambient Intelligence
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Wireless Sensor Network Group @ Micrel Lab

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WiMoCa: a Wireless Sensor Node for Body Area Networks

This work is about the design and implementation of a wireless sensor node for a Motion Capture system with Accelerometers (WiMoCA). It is composed by a tri-axial integrated
accelerometer, a microcontroller and a wireless transceiver. The use of a single integrated tri-axial accelerometer allows to overcome inaccuracies of orthogonally mounted biaxial accelerometers and to build a smaller device compared to other sensors presented in literature. WiMoCA nodes have been exploited to build a Wireless Body Area Sensor Network (WBASN), that allows to implement a wireless/ wearable distributed gesture recognition system where nodes are mounted on many parts of the human body. We describe the hardware architecture and all the software layers supporting the recognition system. We also show characterization experiments on WiMoCA nodes that highlight how their performance and power consumption levels make them suitable to HCI applications.

E.Farella, A.Pieracci, D.Brunelli, A.Acquaviva, L.Benini, B.Ricco' "Design and Implementation of WiMoCA Node for a Body Area Wireless Sensor Network", to be published in Proc. of SENET 05

Resources:

Video

A Wireless Body Area Sensor Network for Posture Detection

Body Area Sensor Networks (BASN) are an emerging technology enabling the design of natural Human Computer Interfaces (HCI) in the context of Ambient Intelligence. This class of interactive applications poses new challenges on sensor network design that are hard to be faced using traditional solutions optimized for environmental monitoring-like applications. We are working on a novel solution for wireless and wearable posture recognition based on a custom-designed wireless body area sensor network, called WiMoCA. Nodes of the network, mounted on different parts of the human body, exploit tri-axial accelerometers to detect body postures. In this paper we first describe a complete posture recognition system developed on top of WiMoCA, then we discuss results of interactive performance and power consumption optimizations required to match application constraints.

Resources:

video posture

Work in progress
Activity recognition
Gait Analysis

 

 

 


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