quEEGNet: Quantum AI for Biosignal Processing

Toshiaki Koike–Akino, Ye Wang

20222022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)11 citationsDOI

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.

Topics & Concepts

BiosignalArtificial neural networkComputer scienceArtificial intelligenceQuantumDeep learningPattern recognition (psychology)Computer visionPhysicsFilter (signal processing)Quantum mechanicsEEG and Brain-Computer InterfacesAdvanced Memory and Neural ComputingQuantum Computing Algorithms and Architecture