A Respiration-Derived Posture Method Based on Dual-Channel Respiration Impedance Signals
Sleep posture has been used as a sleep assessment indicator in home health monitoring and clinical monitoring in recent years. Considering comfort and usability, unobtrusive sleep posture detection is needed. In this paper, we proposed a novel sleep respiration-derived posture (RDP) method based on...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2017-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8004417/ |
| _version_ | 1819168429063536640 |
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| author | Guanzheng Liu Kunyang Li Lianrong Zheng Wen-Hui Chen Guangmin Zhou Qing Jiang |
| author_facet | Guanzheng Liu Kunyang Li Lianrong Zheng Wen-Hui Chen Guangmin Zhou Qing Jiang |
| author_sort | Guanzheng Liu |
| collection | DOAJ |
| description | Sleep posture has been used as a sleep assessment indicator in home health monitoring and clinical monitoring in recent years. Considering comfort and usability, unobtrusive sleep posture detection is needed. In this paper, we proposed a novel sleep respiration-derived posture (RDP) method based on left and right lung respiration impedance signals. We developed a dual-channel respiratory impedance acquisition system with wireless transmission. Then, support vector machine using radial basis function kernel was applied to recognize four typical sleep postures. Moreover, the performance of the SVM classifier was improved by using backward elimination. In-situ experiments with 16 subjects indicated that the RDP method reached an accuracy of 99.67%. Thus, our method is reliable in sleep posture recognition. Furthermore, a whole-night monitoring system based on respiration impedance can be conducted for sleep quality assessment. |
| first_indexed | 2024-12-22T19:03:27Z |
| format | Article |
| id | doaj.art-d0b0ce4a1c63471c955f372acf0a08a9 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-22T19:03:27Z |
| publishDate | 2017-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-d0b0ce4a1c63471c955f372acf0a08a92022-12-21T18:15:52ZengIEEEIEEE Access2169-35362017-01-015175141752410.1109/ACCESS.2017.27374618004417A Respiration-Derived Posture Method Based on Dual-Channel Respiration Impedance SignalsGuanzheng Liu0https://orcid.org/0000-0002-1208-7479Kunyang Li1Lianrong Zheng2Wen-Hui Chen3Guangmin Zhou4Qing Jiang5Biomedical Engineering, School of Engineering, Sun Yat-sen University, Guangzhou, ChinaBiomedical Engineering, School of Engineering, Sun Yat-sen University, Guangzhou, ChinaBiomedical Engineering, School of Engineering, Sun Yat-sen University, Guangzhou, ChinaBiomedical Engineering, School of Engineering, Sun Yat-sen University, Guangzhou, ChinaBiomedical Engineering, School of Engineering, Sun Yat-sen University, Guangzhou, ChinaBiomedical Engineering, School of Engineering, Sun Yat-sen University, Guangzhou, ChinaSleep posture has been used as a sleep assessment indicator in home health monitoring and clinical monitoring in recent years. Considering comfort and usability, unobtrusive sleep posture detection is needed. In this paper, we proposed a novel sleep respiration-derived posture (RDP) method based on left and right lung respiration impedance signals. We developed a dual-channel respiratory impedance acquisition system with wireless transmission. Then, support vector machine using radial basis function kernel was applied to recognize four typical sleep postures. Moreover, the performance of the SVM classifier was improved by using backward elimination. In-situ experiments with 16 subjects indicated that the RDP method reached an accuracy of 99.67%. Thus, our method is reliable in sleep posture recognition. Furthermore, a whole-night monitoring system based on respiration impedance can be conducted for sleep quality assessment.https://ieeexplore.ieee.org/document/8004417/Respiration derived posture (RDP)respiratory impedancebackward elimination (BE)support vector machine (SVM)radial basis function (RBF) |
| spellingShingle | Guanzheng Liu Kunyang Li Lianrong Zheng Wen-Hui Chen Guangmin Zhou Qing Jiang A Respiration-Derived Posture Method Based on Dual-Channel Respiration Impedance Signals IEEE Access Respiration derived posture (RDP) respiratory impedance backward elimination (BE) support vector machine (SVM) radial basis function (RBF) |
| title | A Respiration-Derived Posture Method Based on Dual-Channel Respiration Impedance Signals |
| title_full | A Respiration-Derived Posture Method Based on Dual-Channel Respiration Impedance Signals |
| title_fullStr | A Respiration-Derived Posture Method Based on Dual-Channel Respiration Impedance Signals |
| title_full_unstemmed | A Respiration-Derived Posture Method Based on Dual-Channel Respiration Impedance Signals |
| title_short | A Respiration-Derived Posture Method Based on Dual-Channel Respiration Impedance Signals |
| title_sort | respiration derived posture method based on dual channel respiration impedance signals |
| topic | Respiration derived posture (RDP) respiratory impedance backward elimination (BE) support vector machine (SVM) radial basis function (RBF) |
| url | https://ieeexplore.ieee.org/document/8004417/ |
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