Fusion-Based Approach for Respiratory Rate Recognition From Facial Video Images
The respiratory rate is an important vital parameter that provides information about persons' physical condition. In clinical practice it is currently only monitored using contact-based techniques, which can have negative effects on patients. In this study, a new algorithm for remote respirator...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9139240/ |
| _version_ | 1818351365456396288 |
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| author | Marc-Andre Fiedler Micha Rapczynski Ayoub Al-Hamadi |
| author_facet | Marc-Andre Fiedler Micha Rapczynski Ayoub Al-Hamadi |
| author_sort | Marc-Andre Fiedler |
| collection | DOAJ |
| description | The respiratory rate is an important vital parameter that provides information about persons' physical condition. In clinical practice it is currently only monitored using contact-based techniques, which can have negative effects on patients. In this study, a new algorithm for remote respiratory rate recognition is presented using photoplethysmographic signals derived from facial video images in the visible light spectrum. The effects of different implementation steps in the presented algorithm are investigated in order to optimize the approach and gain new findings in this research field. In addition, a detailed examination of already implemented procedures is performed and the results are compared on two different databases. We show that by fusing the results of seven different respiratory-induced modulations in combination with other processing steps, very good estimates for the respiratory rate on both moving and non-moving data are achieved. The obtained detection rates of 72.16 % and 87.68 % are significantly higher than those of the best comparison algorithm with 37.37 % and 59.13 %. The comparison algorithms developed so far are not competitive with the newly designed method, especially for video recordings involving persons in motion. This paper provides important new findings in the field of facial video-based respiratory rate recognition for the research community. A new method has been created that delivers significantly better estimates of the respiratory rate than previously developed techniques. |
| first_indexed | 2024-12-13T18:36:35Z |
| format | Article |
| id | doaj.art-56b89cf3d51d47adb81997bd76931dcc |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-13T18:36:35Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-56b89cf3d51d47adb81997bd76931dcc2022-12-21T23:35:21ZengIEEEIEEE Access2169-35362020-01-01813003613004710.1109/ACCESS.2020.30086879139240Fusion-Based Approach for Respiratory Rate Recognition From Facial Video ImagesMarc-Andre Fiedler0https://orcid.org/0000-0002-5606-4033Micha Rapczynski1https://orcid.org/0000-0003-4430-6952Ayoub Al-Hamadi2Neuro-Information Technology Group, Institute for Information Technology and Communications, Otto von Guericke University Magdeburg, Magdeburg, GermanyNeuro-Information Technology Group, Institute for Information Technology and Communications, Otto von Guericke University Magdeburg, Magdeburg, GermanyNeuro-Information Technology Group, Institute for Information Technology and Communications, Otto von Guericke University Magdeburg, Magdeburg, GermanyThe respiratory rate is an important vital parameter that provides information about persons' physical condition. In clinical practice it is currently only monitored using contact-based techniques, which can have negative effects on patients. In this study, a new algorithm for remote respiratory rate recognition is presented using photoplethysmographic signals derived from facial video images in the visible light spectrum. The effects of different implementation steps in the presented algorithm are investigated in order to optimize the approach and gain new findings in this research field. In addition, a detailed examination of already implemented procedures is performed and the results are compared on two different databases. We show that by fusing the results of seven different respiratory-induced modulations in combination with other processing steps, very good estimates for the respiratory rate on both moving and non-moving data are achieved. The obtained detection rates of 72.16 % and 87.68 % are significantly higher than those of the best comparison algorithm with 37.37 % and 59.13 %. The comparison algorithms developed so far are not competitive with the newly designed method, especially for video recordings involving persons in motion. This paper provides important new findings in the field of facial video-based respiratory rate recognition for the research community. A new method has been created that delivers significantly better estimates of the respiratory rate than previously developed techniques.https://ieeexplore.ieee.org/document/9139240/Facial videosnon-contact monitoringremote photoplethysmographyremote PPGrespiratory ratevisible light spectrum |
| spellingShingle | Marc-Andre Fiedler Micha Rapczynski Ayoub Al-Hamadi Fusion-Based Approach for Respiratory Rate Recognition From Facial Video Images IEEE Access Facial videos non-contact monitoring remote photoplethysmography remote PPG respiratory rate visible light spectrum |
| title | Fusion-Based Approach for Respiratory Rate Recognition From Facial Video Images |
| title_full | Fusion-Based Approach for Respiratory Rate Recognition From Facial Video Images |
| title_fullStr | Fusion-Based Approach for Respiratory Rate Recognition From Facial Video Images |
| title_full_unstemmed | Fusion-Based Approach for Respiratory Rate Recognition From Facial Video Images |
| title_short | Fusion-Based Approach for Respiratory Rate Recognition From Facial Video Images |
| title_sort | fusion based approach for respiratory rate recognition from facial video images |
| topic | Facial videos non-contact monitoring remote photoplethysmography remote PPG respiratory rate visible light spectrum |
| url | https://ieeexplore.ieee.org/document/9139240/ |
| work_keys_str_mv | AT marcandrefiedler fusionbasedapproachforrespiratoryraterecognitionfromfacialvideoimages AT micharapczynski fusionbasedapproachforrespiratoryraterecognitionfromfacialvideoimages AT ayoubalhamadi fusionbasedapproachforrespiratoryraterecognitionfromfacialvideoimages |