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A hardware implementation of a qEEG-based discriminant function for brain injury detection
Date
2021
Abstract
This paper presents a feature extraction engine based on using Electroencephalogram (EEG) as a tool for Traumatic-Brain-Injury (TBI) detection. The design focuses on the development of hardware accelerator components integrated onto an FPGA platform. Utilizing a combination of four key quantitative-EEG (qEEG) features, the hardware design can perform a discriminant function (DF) based on 20 variables used for predicting TBI. Since the design is intended to operate in real-time and needs to perform intensive EEGprocessing tasks, the emphasis is on the architectural aspects and speed capabilities of the feature extraction work.
Supervisor
Description
peer-reviewed
Publisher
IEEE Computer Society
Citation
2021 IEEE Biomedical Circuits and Systems Conference (BioCAS);
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Files
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BioCAS2021_paper_v3.pdf
Adobe PDF, 516.55 KB
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Funding code
Funding Information
Science Foundation Ireland (SFI)