计算机应用研究2024，Vol.41Issue(4)：1123-1130,8.DOI:10.19734/j.issn.1001-3695.2023.07.0354
基于对比学习的心电信号情绪识别方法
ECG-based emotion recognition based on contrastive learning
摘要
Abstract
The majority of current machine learning and deep learning solutions for ECG-based emotion recognition utilize fully-supervised learning methods.Several limitations of this approach are that large human-annotated datasets and computing resources are required.Furthermore,the feature representations learned by fully supervised methods tend to be task-specific with limited generalization capability.In response to these issues,this paper proposed an approach based on contrastive lear-ning for ECG-based emotion recognition,which consisted of two steps,such as pre-training and fine-tuning.The goal of pre-training was to learn representations from unlabeled EGG data through contrastive learning.Specifically,it designed two sim-ple and efficient ECG signal augmentation methods,and used these two views to learn robust temporal representations in the time contrastive module,followed by learning discriminative feature representations in the context contrastive module.Fine-tuning used labelled data to learn emotion recognition.Experiments show that the proposed method has reached the maximum accuracy on three public ECG-based emotion recognition datasets.Additionally,the proposed method shows high efficiency under the semi-supervised settings.关键词
心电信号/情绪识别/对比学习/自监督学习/深度学习/生理信号/数据增强/自注意力机制Key words
electrocardiogram signal/emotion recognition/contrastive learning/self-supervised learning/deep learning/physiological signals/data augmentation/self-attention mechanism分类
信息技术与安全科学引用本文复制引用
龙锦益,方景龙,刘斯为,吴汉瑞,张佳..基于对比学习的心电信号情绪识别方法[J].计算机应用研究,2024,41(4):1123-1130,8.基金项目
国家自然科学基金资助项目(62276115) （62276115）
广东省中医药信息化重点实验室资助项目(2021B1212040007) （2021B1212040007）
