Vital Sign Signal Extraction Method Based on Permutation Entropy and EEMD Algorithm for Ultra-Wideband Radar
The noncontact measurement of vital sign signals is useful for medical care, rescuing disaster survivors from ruins and public safety. In this paper, a novel vital sign signal extraction method based on permutation entropy (PE) and ensemble empirical mode decomposition (EEMD) algorithm is proposed....
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8930533/ |
| _version_ | 1818410934782132224 |
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| author | Degui Yang Zhengliang Zhu Buge Liang |
| author_facet | Degui Yang Zhengliang Zhu Buge Liang |
| author_sort | Degui Yang |
| collection | DOAJ |
| description | The noncontact measurement of vital sign signals is useful for medical care, rescuing disaster survivors from ruins and public safety. In this paper, a novel vital sign signal extraction method based on permutation entropy (PE) and ensemble empirical mode decomposition (EEMD) algorithm is proposed. The proposed algorithm analyzes the permutation entropy of radar-received pulses; the range between a human target and ultra-wideband (UWB) radar can be obtained by permutation entropy. Permutation entropy represents the complexity of signals, so we can use PE to select and recombine human life signals that are distributed in the adjacent distance gate. Moreover, EEMD algorithm is adopted to decompose the combined signal into intrinsic mode functions (IMF), and both the respiration and the heartbeat signals are reconstructed by IMF via reaching the energy threshold in the time domain. Experiments are carried out using UWB radar. Compared with traditional algorithms, the proposed algorithm can be used to extract the range and frequency information of human targets efficiently and accurately. |
| first_indexed | 2024-12-14T10:23:25Z |
| format | Article |
| id | doaj.art-0ea9dec0e82f4165991ae961c7f5a4c7 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-14T10:23:25Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-0ea9dec0e82f4165991ae961c7f5a4c72022-12-21T23:06:28ZengIEEEIEEE Access2169-35362019-01-01717887917889010.1109/ACCESS.2019.29586008930533Vital Sign Signal Extraction Method Based on Permutation Entropy and EEMD Algorithm for Ultra-Wideband RadarDegui Yang0https://orcid.org/0000-0003-1604-9792Zhengliang Zhu1https://orcid.org/0000-0001-7445-8223Buge Liang2https://orcid.org/0000-0002-5344-2799School of Aeronautics and Astronautics, Central South University, Changsha, ChinaSchool of Aeronautics and Astronautics, Central South University, Changsha, ChinaSchool of Aeronautics and Astronautics, Central South University, Changsha, ChinaThe noncontact measurement of vital sign signals is useful for medical care, rescuing disaster survivors from ruins and public safety. In this paper, a novel vital sign signal extraction method based on permutation entropy (PE) and ensemble empirical mode decomposition (EEMD) algorithm is proposed. The proposed algorithm analyzes the permutation entropy of radar-received pulses; the range between a human target and ultra-wideband (UWB) radar can be obtained by permutation entropy. Permutation entropy represents the complexity of signals, so we can use PE to select and recombine human life signals that are distributed in the adjacent distance gate. Moreover, EEMD algorithm is adopted to decompose the combined signal into intrinsic mode functions (IMF), and both the respiration and the heartbeat signals are reconstructed by IMF via reaching the energy threshold in the time domain. Experiments are carried out using UWB radar. Compared with traditional algorithms, the proposed algorithm can be used to extract the range and frequency information of human targets efficiently and accurately.https://ieeexplore.ieee.org/document/8930533/Vital sign signalultra-wideband (UWB) radarensemble empirical mode decomposition (EEMD)permutation entropy (PE) |
| spellingShingle | Degui Yang Zhengliang Zhu Buge Liang Vital Sign Signal Extraction Method Based on Permutation Entropy and EEMD Algorithm for Ultra-Wideband Radar IEEE Access Vital sign signal ultra-wideband (UWB) radar ensemble empirical mode decomposition (EEMD) permutation entropy (PE) |
| title | Vital Sign Signal Extraction Method Based on Permutation Entropy and EEMD Algorithm for Ultra-Wideband Radar |
| title_full | Vital Sign Signal Extraction Method Based on Permutation Entropy and EEMD Algorithm for Ultra-Wideband Radar |
| title_fullStr | Vital Sign Signal Extraction Method Based on Permutation Entropy and EEMD Algorithm for Ultra-Wideband Radar |
| title_full_unstemmed | Vital Sign Signal Extraction Method Based on Permutation Entropy and EEMD Algorithm for Ultra-Wideband Radar |
| title_short | Vital Sign Signal Extraction Method Based on Permutation Entropy and EEMD Algorithm for Ultra-Wideband Radar |
| title_sort | vital sign signal extraction method based on permutation entropy and eemd algorithm for ultra wideband radar |
| topic | Vital sign signal ultra-wideband (UWB) radar ensemble empirical mode decomposition (EEMD) permutation entropy (PE) |
| url | https://ieeexplore.ieee.org/document/8930533/ |
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