App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 10

PPG-ECG signal conversion based on MPST-UNet generative adversarial network

Sun Chaolia
Wang Yongkanga
Zhang Pengyunb
a. School of Computer Science & Technology, b. School of Electronic Information Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China
DOI: 10.19734/j.issn.1001-3695.2025.12.0544

Abstract

To address the issues of insufficient frequency-domain feature utilization, difficulties in long-term signal modeling, lack of dynamic feature importance adjustment, and poor robustness in low signal-to-noise ratio scenarios during the cross-modal conversion between Photoplethysmography (PPG) and Electrocardiogram (ECG) physiological signals, this study proposes an improved model based on Generative Adversarial Network (GAN) . It employs multi-phase Patch encoding to strengthen global temporal modeling, integrates a frequency-domain feature enhancement module to improve multi-domain information fusion capability, adopts a dynamic component routing fusion mechanism to optimize feature weighting and detail restoration, and combines multi-dimensional loss collaborative constraints to ensure waveform fidelity and parameter consistency. Experimental results demonstrate that the model outperforms existing methods in signal morphological similarity, physiological parameter consistency, and clinical interpretability across multiple datasets. Compared with the latest 2025 method ECG-QGAN, its RMSE decreases by 4.3% and ρ value increases by 0.9%. This research provides effective technical support for cardiovascular disease auxiliary diagnosis and wearable health monitoring, adapting to diverse clinical scenarios and on-device real-time inference requirements.

Foundation Support

国家自然科学基金项目(62372319)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.12.0544
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 10

Publish History

[2026-07-03] Accepted Paper

Cite This Article

孙超利, 王永康, 张鹏云. 基于MPST-UNet生成对抗网络的PPG与ECG信号转换方法 [J]. 计算机应用研究, 2026, 43 (10). (2026-07-30). https://doi.org/10.19734/j.issn.1001-3695.2025.12.0544. (Sun Chaoli, Wang Yongkang, Zhang Pengyun. PPG-ECG signal conversion based on MPST-UNet generative adversarial network [J]. Application Research of Computers, 2026, 43 (10). (2026-07-30). https://doi.org/10.19734/j.issn.1001-3695.2025.12.0544. )

About the Journal

  • Application Research of Computers Monthly Journal
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    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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