A Novel Nonlinear Method for Cardiovascular Data Synchronization
This study introduces and evaluates a novel nonlinear technique for synchronizing electrocardiogram (ECG) and photoplethysmogram (PPG) signals by embracing the intrinsic relationship between heart rate variability (HRV) and pulse rate variability (PRV). The proposed method utilizes normalized mutual...
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| Format: | Article |
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2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/11006692/ |
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| author | Daniele Padovano Arturo Martinez-Rodrigo Norbert Marwan Santiago Mula Munoz Jose J. Rieta Raul Alcaraz |
| author_facet | Daniele Padovano Arturo Martinez-Rodrigo Norbert Marwan Santiago Mula Munoz Jose J. Rieta Raul Alcaraz |
| author_sort | Daniele Padovano |
| collection | DOAJ |
| description | This study introduces and evaluates a novel nonlinear technique for synchronizing electrocardiogram (ECG) and photoplethysmogram (PPG) signals by embracing the intrinsic relationship between heart rate variability (HRV) and pulse rate variability (PRV). The proposed method utilizes normalized mutual information (NMI) derived from cross-distance matrices (CDM) of HRV and PRV, alongside the distance matrix of a reference HRV extract. We tested the methodology on two databases containing simultaneous ECG and PPG signals, including one publicly available on Physionet, and benchmarked it against various synchronization techniques, both linear (Pearson coefficient, dynamic time warping) and nonlinear (conventional mutual information, NMI with recurrence plots, cross-recurrence plot, and determinism). Results showed that the proposed method (NMI of CDM) outperformed all others, achieving synchronization rates near 50% within a 1.2-second lag threshold. This study also comprehensively examines how signal quality and recording methodology variations affect synchronization outcomes, confirming the importance of lag threshold adjustment for real accuracy assessment. However, some limitations must be kept in mind: the proposed approach is not suited for blood pressure estimation based on HRV-PRV differences, nonlinear methods generally require higher computational resources than linear ones, and further validation is needed with additional databases from real-world scenarios similar to those used in this study. |
| format | Article |
| id | doaj-art-b42a9d6df57f4d2d9f3b7d69149a1beb |
| institution | OA Journals |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
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| series | IEEE Access |
| spelling | doaj-art-b42a9d6df57f4d2d9f3b7d69149a1beb2025-08-20T01:56:48ZengIEEEIEEE Access2169-35362025-01-0113893148933110.1109/ACCESS.2025.357107011006692A Novel Nonlinear Method for Cardiovascular Data SynchronizationDaniele Padovano0https://orcid.org/0000-0003-3838-1438Arturo Martinez-Rodrigo1https://orcid.org/0000-0003-2343-3186Norbert Marwan2https://orcid.org/0000-0003-1437-7039Santiago Mula Munoz3Jose J. Rieta4https://orcid.org/0000-0002-3364-6380Raul Alcaraz5https://orcid.org/0000-0002-0942-3638Research Group in Electronic, Biomedical and Telecommunications Engineering, University of Castilla–La Mancha, Cuenca, SpainResearch Group in Electronic, Biomedical and Telecommunications Engineering, University of Castilla–La Mancha, Cuenca, SpainNonlinear Dynamics Group, Institute of Physics, University of Potsdam, Potsdam, GermanyResearch Group in Electronic, Biomedical and Telecommunications Engineering, University of Castilla–La Mancha, Cuenca, SpainElectronic Engineering Department, BioMIT.org, Universitat Politecnica de Valencia, Valencia, SpainResearch Group in Electronic, Biomedical and Telecommunications Engineering, University of Castilla–La Mancha, Cuenca, SpainThis study introduces and evaluates a novel nonlinear technique for synchronizing electrocardiogram (ECG) and photoplethysmogram (PPG) signals by embracing the intrinsic relationship between heart rate variability (HRV) and pulse rate variability (PRV). The proposed method utilizes normalized mutual information (NMI) derived from cross-distance matrices (CDM) of HRV and PRV, alongside the distance matrix of a reference HRV extract. We tested the methodology on two databases containing simultaneous ECG and PPG signals, including one publicly available on Physionet, and benchmarked it against various synchronization techniques, both linear (Pearson coefficient, dynamic time warping) and nonlinear (conventional mutual information, NMI with recurrence plots, cross-recurrence plot, and determinism). Results showed that the proposed method (NMI of CDM) outperformed all others, achieving synchronization rates near 50% within a 1.2-second lag threshold. This study also comprehensively examines how signal quality and recording methodology variations affect synchronization outcomes, confirming the importance of lag threshold adjustment for real accuracy assessment. However, some limitations must be kept in mind: the proposed approach is not suited for blood pressure estimation based on HRV-PRV differences, nonlinear methods generally require higher computational resources than linear ones, and further validation is needed with additional databases from real-world scenarios similar to those used in this study.https://ieeexplore.ieee.org/document/11006692/Electrocardiographyphotoplethysmographysignal synchronizationrecurrence analysis |
| spellingShingle | Daniele Padovano Arturo Martinez-Rodrigo Norbert Marwan Santiago Mula Munoz Jose J. Rieta Raul Alcaraz A Novel Nonlinear Method for Cardiovascular Data Synchronization IEEE Access Electrocardiography photoplethysmography signal synchronization recurrence analysis |
| title | A Novel Nonlinear Method for Cardiovascular Data Synchronization |
| title_full | A Novel Nonlinear Method for Cardiovascular Data Synchronization |
| title_fullStr | A Novel Nonlinear Method for Cardiovascular Data Synchronization |
| title_full_unstemmed | A Novel Nonlinear Method for Cardiovascular Data Synchronization |
| title_short | A Novel Nonlinear Method for Cardiovascular Data Synchronization |
| title_sort | novel nonlinear method for cardiovascular data synchronization |
| topic | Electrocardiography photoplethysmography signal synchronization recurrence analysis |
| url | https://ieeexplore.ieee.org/document/11006692/ |
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