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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.
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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
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A Wireless
Body Area Sensor Network for Posture Detection
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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
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Work in progress
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Activity recognition
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Gait Analysis
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