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成像式光体积描记术信号去噪

李文通 张起起 刘隆鑫 马真龙 孙运杰 嵇晓强

中国光学(中英文)2026,Vol.19Issue(1):96-108,13.
中国光学(中英文)2026,Vol.19Issue(1):96-108,13.DOI:10.37188/CO.2025-0103

成像式光体积描记术信号去噪

Denoising of imaging photoplethysmography signals

李文通 1张起起 1刘隆鑫 1马真龙 1孙运杰 1嵇晓强1

作者信息

  • 1. 长春理工大学生命科学技术学院,吉林长春 130022
  • 折叠

摘要

Abstract

Image Photoplethysmography(IPPG)signals are easily disturbed by noise during acquisition.To address the issue,this study proposes a denoising diffusion probability model for IPPG(DDPM-IPPG).This model eliminates baseline drift and noise through diffusion and reverse diffusion stages,and improves the signal-to-noise ratio and heart rate accuracy.First,Gaussian noise is gradually added to the photoplethysmo-graphy(PPG)signal during the diffusion phase to create a noise sequence.A noise predictor based on a non-linear fusion module and a bridging module is trained.Subsequently,in the reverse diffusion phase,the well-trained noise predictor is employed to perform step-by-step denoising on the initially extracted IPPG signal.Through this denoising,a signal with high signal-to-noise ratio is recovered.The model proposed in this pa-per is validated and compared with current mainstream algorithms on the PURE,UBFC-IPPG,UBFC-Phys,and MMPD datasets.The experimental results show that DDPM-IPPG improves the signal-to-noise ratio by 1.06 dB on the PURE dataset comparing with the existing highest-precision extraction method.The mean absolute error of heart rate decreases by 0.24 bpm.The root mean square error of heart rate decreases by 0.41 bpm.On the UBFC-IPPG dataset,the signal-to-noise ratio is improved by 1.50 dB.The proposed DDPM-IPPG model has achieved the current advanced level in eliminating baseline drift and noise from IP-PG signals,enabling a more precise approximation of the true signals and providing a more reliable data foundation for physiological health assessment and telemedicine monitoring.

关键词

成像式光体积描记术/信号去噪/扩散模型/注意力机制

Key words

imaging photoplethysmography/signal denoising/diffusion model/attention mechanism

分类

信息技术与安全科学

引用本文复制引用

李文通,张起起,刘隆鑫,马真龙,孙运杰,嵇晓强..成像式光体积描记术信号去噪[J].中国光学(中英文),2026,19(1):96-108,13.

基金项目

吉林省科技发展计划项目(No.20240101339JC)Supported by Science and Technology Development Plan Project of Jilin Province(No.20240101339JC) (No.20240101339JC)

中国光学(中英文)

2095-1531

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