Estimation of Heart Rate and Respiratory Rate from PPG Signal Using Complementary Ensemble Empirical Mode Decomposition with both Independent Component Analysis and Non-Negative Matrix Factorization
This paper proposes a framework combining the complementary ensemble empirical mode decomposition with both the independent component analysis and the non-negative matrix factorization for estimating both the heart rate and the respiratory rate from the photoplethysmography (PPG) signal. After perfo...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-06-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/20/11/3238 |
| _version_ | 1797565974267822080 |
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| author | Ruisheng Lei Bingo Wing-Kuen Ling Peihua Feng Jinrong Chen |
| author_facet | Ruisheng Lei Bingo Wing-Kuen Ling Peihua Feng Jinrong Chen |
| author_sort | Ruisheng Lei |
| collection | DOAJ |
| description | This paper proposes a framework combining the complementary ensemble empirical mode decomposition with both the independent component analysis and the non-negative matrix factorization for estimating both the heart rate and the respiratory rate from the photoplethysmography (PPG) signal. After performing the complementary ensemble empirical mode decomposition on the PPG signal, a finite number of intrinsic mode functions are obtained. Then, these intrinsic mode functions are divided into two groups to perform the further analysis via both the independent component analysis and the non-negative matrix factorization. The surrogate cardiac signal related to the heart activity and another surrogate respiratory signal related to the respiratory activity are reconstructed to estimate the heart rate and the respiratory rate, respectively. Finally, different records of signals acquired from the Medical Information Mart for Intensive Care database downloaded from the Physionet Automated Teller Machine (ATM) data bank are employed for demonstrating the outperformance of our proposed method. The results show that our proposed method outperforms both the digital filtering approach and the conventional empirical mode decomposition based methods in terms of reconstructing both the surrogate cardiac signal and the respiratory signal from the PPG signal as well as both achieving the higher accuracy and the higher reliability for estimating both the heart rate and the respiratory rate. |
| first_indexed | 2024-03-10T19:20:15Z |
| format | Article |
| id | doaj.art-cad12fec533847bea0e8df3b14ecfa53 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T19:20:15Z |
| publishDate | 2020-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-cad12fec533847bea0e8df3b14ecfa532023-11-20T03:04:17ZengMDPI AGSensors1424-82202020-06-012011323810.3390/s20113238Estimation of Heart Rate and Respiratory Rate from PPG Signal Using Complementary Ensemble Empirical Mode Decomposition with both Independent Component Analysis and Non-Negative Matrix FactorizationRuisheng Lei0Bingo Wing-Kuen Ling1Peihua Feng2Jinrong Chen3School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, ChinaSchool of Information Engineering, Guangdong University of Technology, Guangzhou 510006, ChinaSchool of Information Engineering, Guangdong University of Technology, Guangzhou 510006, ChinaSchool of Information Engineering, Guangdong University of Technology, Guangzhou 510006, ChinaThis paper proposes a framework combining the complementary ensemble empirical mode decomposition with both the independent component analysis and the non-negative matrix factorization for estimating both the heart rate and the respiratory rate from the photoplethysmography (PPG) signal. After performing the complementary ensemble empirical mode decomposition on the PPG signal, a finite number of intrinsic mode functions are obtained. Then, these intrinsic mode functions are divided into two groups to perform the further analysis via both the independent component analysis and the non-negative matrix factorization. The surrogate cardiac signal related to the heart activity and another surrogate respiratory signal related to the respiratory activity are reconstructed to estimate the heart rate and the respiratory rate, respectively. Finally, different records of signals acquired from the Medical Information Mart for Intensive Care database downloaded from the Physionet Automated Teller Machine (ATM) data bank are employed for demonstrating the outperformance of our proposed method. The results show that our proposed method outperforms both the digital filtering approach and the conventional empirical mode decomposition based methods in terms of reconstructing both the surrogate cardiac signal and the respiratory signal from the PPG signal as well as both achieving the higher accuracy and the higher reliability for estimating both the heart rate and the respiratory rate.https://www.mdpi.com/1424-8220/20/11/3238photoplethysmographyheart raterespiratory ratecomplementary ensemble empirical mode decompositionmode mixingindependent component analysis |
| spellingShingle | Ruisheng Lei Bingo Wing-Kuen Ling Peihua Feng Jinrong Chen Estimation of Heart Rate and Respiratory Rate from PPG Signal Using Complementary Ensemble Empirical Mode Decomposition with both Independent Component Analysis and Non-Negative Matrix Factorization Sensors photoplethysmography heart rate respiratory rate complementary ensemble empirical mode decomposition mode mixing independent component analysis |
| title | Estimation of Heart Rate and Respiratory Rate from PPG Signal Using Complementary Ensemble Empirical Mode Decomposition with both Independent Component Analysis and Non-Negative Matrix Factorization |
| title_full | Estimation of Heart Rate and Respiratory Rate from PPG Signal Using Complementary Ensemble Empirical Mode Decomposition with both Independent Component Analysis and Non-Negative Matrix Factorization |
| title_fullStr | Estimation of Heart Rate and Respiratory Rate from PPG Signal Using Complementary Ensemble Empirical Mode Decomposition with both Independent Component Analysis and Non-Negative Matrix Factorization |
| title_full_unstemmed | Estimation of Heart Rate and Respiratory Rate from PPG Signal Using Complementary Ensemble Empirical Mode Decomposition with both Independent Component Analysis and Non-Negative Matrix Factorization |
| title_short | Estimation of Heart Rate and Respiratory Rate from PPG Signal Using Complementary Ensemble Empirical Mode Decomposition with both Independent Component Analysis and Non-Negative Matrix Factorization |
| title_sort | estimation of heart rate and respiratory rate from ppg signal using complementary ensemble empirical mode decomposition with both independent component analysis and non negative matrix factorization |
| topic | photoplethysmography heart rate respiratory rate complementary ensemble empirical mode decomposition mode mixing independent component analysis |
| url | https://www.mdpi.com/1424-8220/20/11/3238 |
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