EKGNet: A 10.96μW Fully Analog Neural Network for Intra-Patient Arrhythmia Classification

Benyamin Allahgholizadeh Haghi, Lin Ma, Sahin Lale, Anima Anandkumar, Azita Emami. EKGNet: A 10.96μW Fully Analog Neural Network for Intra-Patient Arrhythmia Classification. In IEEE Biomedical Circuits and Systems Conference, BioCAS 2023, Toronto, ON, Canada, October 19-21, 2023. pages 1-5, IEEE, 2023. [doi]

Abstract

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