Generalizable Remote Physiological Measurement via Semantic-Sheltered Alignment and Plausible Style Randomization

doi:10.1109/TIM.2024.3497058

	Generalizable Remote Physiological Measurement via Semantic-Sheltered Alignment and Plausible Style Randomization
	Wang, Jiyao 1; Lu, Hao 2; Han, Hu 3,4; Chen, Yingcong 2; He, Dengbo 1; Wu, Kaishun 2
	2025
发表期刊	IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
ISSN	0018-9456
卷号	74 页码:14
摘要	Remote photoplethysmography (rPPG) is a noninvasive technique that measures blood volume changes in the skin using a camera and a light source. Achieving accurate measurements relies on the generalization of models across different individuals and environmental conditions. However, most domain generalization (DG) methods are designed for classification tasks rather than regression tasks, which is a suboptimal solution for the rPPG task. In this work, we propose a novel dual-stream generalization framework (DG-rPPG), which consists of semantic-sheltered alignment (SSA) and plausible attribute randomization (PAR). Specifically, SSA can extract and align domain-agnostic features from different datasets; while maximumly preserving semantic information. PAR can enrich the attribute-related feature of each instance based on the statistical information of all the different domains, ensuring that the augmented features maintain plausibility. The heart rate (HR) and HR variability estimation evaluation with cross-domain protocol across five public datasets illustrated that our proposal significantly (p-value <0.05) outperforms all baselines (e.g., compared to DOHA, DG-rPPG achieves 9.25% and 8.19% improvement on MAE when UBFC and BUAA are target domains). Meanwhile, based on the intra-dataset, computation cost, and out-of-distribution (OOD) assessment, DG-rPPG presents the leading performance in OOD generalization while maintaining relatively good performance in in-distribution estimation and reasonable computational costs. This provides a foundation for real-time monitoring deployments in real environments. The code is available at https://github.com/WJULYW/DG-rPPG.
关键词	Domain generalization (DG) heart rate (HR) estimation invariant risk minimization (IRM) plausible style generation remote photoplethysmography (rPPG) Domain generalization (DG) heart rate (HR) estimation invariant risk minimization (IRM) plausible style generation remote photoplethysmography (rPPG)
DOI	10.1109/TIM.2024.3497058
收录类别	SCI
语种	英语
资助项目	Natural Science Foundation of Guangdong Province of China[2024A1515010392] ; National Natural Science Foundation of China[52202425] ; National Natural Science Foundation of China[62176249] ; Guangzhou Municipal Science and Technology Project[2023A03J0011]
WOS研究方向	Engineering ; Instruments & Instrumentation
WOS类目	Engineering, Electrical & Electronic ; Instruments & Instrumentation
WOS记录号	WOS:001378163300010
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/41063
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	He, Dengbo
作者单位	1.Hong Kong Univ Sci & Technol Guangzhou, Syst Hub, Guangzhou 511455, Peoples R China 2.Hong Kong Univ Sci & Technol Guangzhou, Informat Hub, Guangzhou 511455, Peoples R China 3.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, Beijing 100190, Peoples R China 4.Peng Cheng Lab, Shenzhen 518066, Peoples R China
推荐引用方式 GB/T 7714	Wang, Jiyao,Lu, Hao,Han, Hu,et al. Generalizable Remote Physiological Measurement via Semantic-Sheltered Alignment and Plausible Style Randomization[J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT,2025,74:14.
APA	Wang, Jiyao,Lu, Hao,Han, Hu,Chen, Yingcong,He, Dengbo,&Wu, Kaishun.(2025).Generalizable Remote Physiological Measurement via Semantic-Sheltered Alignment and Plausible Style Randomization.IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT,74,14.
MLA	Wang, Jiyao,et al."Generalizable Remote Physiological Measurement via Semantic-Sheltered Alignment and Plausible Style Randomization".IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 74(2025):14.