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arXiv · 2210.00864

quEEGNet: Quantum AI for Biosignal Processing

Toshiaki Koike-Akino·Ye Wang
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Abstract

In this paper, we introduce an emerging quantum machine learning (QML) framework to assist classical deep learning methods for biosignal processing applications. Specifically, we propose a hybrid quantum-classical neural network model that integrates a variational quantum circuit (VQC) into a deep neural network (DNN) for electroencephalogram (EEG), electromyogram (EMG), and electrocorticogram (ECoG) analysis. We demonstrate that the proposed quantum neural network (QNN) achieves state-of-the-art performance while the number of trainable parameters is kept small for VQC.

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BibTeXRIS

Toshiaki Koike-Akino, Ye Wang. 2022-09-29. quEEGNet: Quantum AI for Biosignal Processing. https://arxiv.org/abs/2210.00864

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