生理信号的深度生成模型:一个系统的文献综述
Nour Neifar1, Afef Mdhaffar1, Achraf Ben-Hamadou2
1ReDCAD Lab, ENIS, University of Sfax, Tunisia.
Artificial intelligence in medicine
|April 24, 2025
概括
本综述涵盖了心电图和脑电图等生理信号的深度生成模型. 它总结了这个快速发展的领域的最新进展,应用和挑战.
科学领域:
- 生物医学工程 生物医学工程
- 人工智能的人工智能
- 信号处理 信号处理
背景情况:
- 生理信号 (ECG,EEG,PPG,EMG) 对于健康监测至关重要.
- 深度生成模型为分析和合成这些信号提供了新的方法.
- 现有的评论缺乏对该领域最先进的深度生成模型的全面摘要.
研究的目的:
- 提供对生理信号深度生成模型的系统文献综述.
- 要总结最近最先进的深度生成模型.
- 分析应用程序,挑战和评估方法.
主要方法:
- 系统的文献搜索和审查.
- 对ECG,EEG,PPG和EMG深度生成模型的最新研究进行分析.
- 基于架构,应用程序和数据集的模型的分类.
主要成果:
- 识别和总结用于生理信号分析的领先深度生成模型.
- 关键应用的概述,包括信号合成,异常检测和数据增强.
- 分析常见挑战,如数据稀缺性和模型可解释性.
结论:
- 深度生成模型对推进生理信号分析有显著的前景.
- 标准化的评估协议和基准数据集对于未来的研究至关重要.
- 本综述为该领域的研究人员和从业人员提供了基础资源.
关键词:
深度生成模型深度生成模型这是一个ECGECGECGECGECG.这是一个EEGEEGEEGEEGEEGEEGEEG.在EMGEMGEMGEMGEMGEMGEMGEMGEMGEM这是一个PPGPPG.更多相关视频
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