Trading Detection Accuracy For Battery Autonomy In A Wearable Seizure-detection Device

Abstract (2015)

Authors

C. Strydis Erasmus MC
R.M. Seepers Erasmus MC
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External organisation
Energy Epilepsy Wavelet Approximate computing Seizure suppression FIR filter coefficients Battery autonomy
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Published Date

2015

Language

English

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Abstract

Experimental devices aiming at real-time detection and suppression of epileptic-seizure events in live subjects already exist. However, to guarantee high detection accuracy, existing approaches employ high-accuracy detection filters that overlook the incurred energy costs, thus leading to unrealistic solutions for low-power implementations. In this short paper, we capitalize on the approximate nature of the seizure-detection phenomenon and propose an energy-efficient scheme for embedded, seizure-detection devices with trivial impact on detection accuracy. For a 1% reduction in filter detection accuracy we achieve a 3.7x increase in device-battery lifetime.