DMCA
A Semantically-Adaptive Strategy for Energy- Efficiency in Wireless Medical Monitoring Devices
BibTeX
@MISC{Goudar_asemantically-adaptive,
author = {Vishwa Goudar and Miodrag Potkonjak},
title = {A Semantically-Adaptive Strategy for Energy- Efficiency in Wireless Medical Monitoring Devices},
year = {}
}
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Abstract
Abstract—We propose a novel strategy for energy-efficient operation of wireless monitoring devices under the premise that medical experts are primarily interested in atypical observations- For epilepsy monitoring, EEG data is most valuable at epileptic activity onset. Or, a gait-stability monitoring application is most interested in unusual footsteps. Observations are atypical if application-specific medical metrics and biosignal features are statistical outliers. Our strategy admits energyefficient early-detection of such observations, leading to: (i) an increase in medical information quality by sampling aggressively over semantically important behaviors, and (ii) a savings in energy by precluding communication of typical measurements. From experimentally collected plantar pressure datasets, we show that this can yield up to a 62 % improvement in gait-stability metric evaluation for atypical footsteps and a 10 % energy cost reduction compared to a recently proposed non-adaptive compressive sensing technique. I.
Keyphrases
semantically-adaptive strategy wireless medical monitoring device energy efficiency energyefficient early-detection wireless monitoring device plantar pressure datasets epilepsy monitoring novel strategy energy-efficient operation medical information quality statistical outlier epileptic activity onset typical measurement energy cost reduction medical expert application-specific medical metric gait-stability metric evaluation atypical observation important behavior gait-stability monitoring application eeg data biosignal feature unusual footstep atypical footstep non-adaptive compressive sensing technique
