Video-Based Physiologic Monitoring During an Acute Hypoxic Challenge: Heart Rate, Respiratory Rate, and Oxygen Saturation
BACKGROUND:The physiologic information contained in the video photoplethysmogram is well documented. However, extracting this information during challenging conditions requires new analysis techniques to capture and process the video image streams to extract clinically useful physiologic parameters....
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Veröffentlicht in: | Anesthesia and analgesia 2017-09, Vol.125 (3), p.860-873 |
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description | BACKGROUND:The physiologic information contained in the video photoplethysmogram is well documented. However, extracting this information during challenging conditions requires new analysis techniques to capture and process the video image streams to extract clinically useful physiologic parameters. We hypothesized that heart rate, respiratory rate, and oxygen saturation trending can be evaluated accurately from video information during acute hypoxia.
METHOD:Video footage was acquired from multiple desaturation episodes during a porcine model of acute hypoxia using a standard visible light camera. A novel in-house algorithm was used to extract photoplethysmographic cardiac pulse and respiratory information from the video image streams and process it to extract a continuously reported video-based heart rate (HRvid), respiratory rate (RRvid), and oxygen saturation (SvidO2). This information was then compared with HR and oxygen saturation references from commercial pulse oximetry and the known rate of respiration from the ventilator.
RESULTS:Eighty-eight minutes of data were acquired during 16 hypoxic episodes in 8 animals. A linear mixed-effects regression showed excellent responses relative to a nonhypoxic reference signal with slopes of 0.976 (95% confidence interval [CI], 0.973–0.979) for HRvid; 1.135 (95% CI, 1.101–1.168) for RRvid, and 0.913 (95% CI, 0.905–0.920) for video-based oxygen saturation. These results were obtained while maintaining continuous uninterrupted vital sign monitoring for the entire study period.
CONCLUSIONS:Video-based monitoring of HR, RR, and oxygen saturation may be performed with reasonable accuracy during acute hypoxic conditions in an anesthetized porcine hypoxia model using standard visible light camera equipment. However, the study was conducted during relatively low motion. A better understanding of the effect of motion and the effect of ambient light on the video photoplethysmogram may help refine this monitoring technology for use in the clinical environment.This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
doi_str_mv | 10.1213/ANE.0000000000001989 |
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METHOD:Video footage was acquired from multiple desaturation episodes during a porcine model of acute hypoxia using a standard visible light camera. A novel in-house algorithm was used to extract photoplethysmographic cardiac pulse and respiratory information from the video image streams and process it to extract a continuously reported video-based heart rate (HRvid), respiratory rate (RRvid), and oxygen saturation (SvidO2). This information was then compared with HR and oxygen saturation references from commercial pulse oximetry and the known rate of respiration from the ventilator.
RESULTS:Eighty-eight minutes of data were acquired during 16 hypoxic episodes in 8 animals. A linear mixed-effects regression showed excellent responses relative to a nonhypoxic reference signal with slopes of 0.976 (95% confidence interval [CI], 0.973–0.979) for HRvid; 1.135 (95% CI, 1.101–1.168) for RRvid, and 0.913 (95% CI, 0.905–0.920) for video-based oxygen saturation. These results were obtained while maintaining continuous uninterrupted vital sign monitoring for the entire study period.
CONCLUSIONS:Video-based monitoring of HR, RR, and oxygen saturation may be performed with reasonable accuracy during acute hypoxic conditions in an anesthetized porcine hypoxia model using standard visible light camera equipment. However, the study was conducted during relatively low motion. A better understanding of the effect of motion and the effect of ambient light on the video photoplethysmogram may help refine this monitoring technology for use in the clinical environment.This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</description><identifier>ISSN: 0003-2999</identifier><identifier>EISSN: 1526-7598</identifier><identifier>DOI: 10.1213/ANE.0000000000001989</identifier><identifier>PMID: 28333706</identifier><language>eng</language><publisher>United States: The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the International Anesthesia Research Society</publisher><subject>Animals ; Heart Rate - physiology ; Hypoxia - physiopathology ; Monitoring, Physiologic - methods ; Oximetry - methods ; Oxygen Consumption - physiology ; Respiratory Rate - physiology ; Swine ; Video Recording - methods</subject><ispartof>Anesthesia and analgesia, 2017-09, Vol.125 (3), p.860-873</ispartof><rights>The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the International Anesthesia Research Society.</rights><rights>2017 International Anesthesia Research Society</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4019-1f1dc133dd177c91ce2932d71855be467c6c5599fff9292bb67fbd774380e40a3</citedby><cites>FETCH-LOGICAL-c4019-1f1dc133dd177c91ce2932d71855be467c6c5599fff9292bb67fbd774380e40a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf><![CDATA[$$Uhttp://ovidsp.ovid.com/ovidweb.cgi?T=JS&CSC=Y&NEWS=N&PAGE=fulltext&PDF=y&D=ovft&AN=00000539-201709000-00024$$EPDF$$P50$$Gwolterskluwer$$H]]></linktopdf><linktohtml>$$Uhttp://ovidsp.ovid.com/ovidweb.cgi?T=JS&NEWS=n&CSC=Y&PAGE=fulltext&D=ovft&AN=00000539-201709000-00024$$EHTML$$P50$$Gwolterskluwer$$H</linktohtml><link.rule.ids>314,780,784,4609,27924,27925,64666,65461</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28333706$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Addison, Paul S.</creatorcontrib><creatorcontrib>Jacquel, Dominique</creatorcontrib><creatorcontrib>Foo, David M. H.</creatorcontrib><creatorcontrib>Antunes, André</creatorcontrib><creatorcontrib>Borg, Ulf R.</creatorcontrib><title>Video-Based Physiologic Monitoring During an Acute Hypoxic Challenge: Heart Rate, Respiratory Rate, and Oxygen Saturation</title><title>Anesthesia and analgesia</title><addtitle>Anesth Analg</addtitle><description>BACKGROUND:The physiologic information contained in the video photoplethysmogram is well documented. However, extracting this information during challenging conditions requires new analysis techniques to capture and process the video image streams to extract clinically useful physiologic parameters. We hypothesized that heart rate, respiratory rate, and oxygen saturation trending can be evaluated accurately from video information during acute hypoxia.
METHOD:Video footage was acquired from multiple desaturation episodes during a porcine model of acute hypoxia using a standard visible light camera. A novel in-house algorithm was used to extract photoplethysmographic cardiac pulse and respiratory information from the video image streams and process it to extract a continuously reported video-based heart rate (HRvid), respiratory rate (RRvid), and oxygen saturation (SvidO2). This information was then compared with HR and oxygen saturation references from commercial pulse oximetry and the known rate of respiration from the ventilator.
RESULTS:Eighty-eight minutes of data were acquired during 16 hypoxic episodes in 8 animals. A linear mixed-effects regression showed excellent responses relative to a nonhypoxic reference signal with slopes of 0.976 (95% confidence interval [CI], 0.973–0.979) for HRvid; 1.135 (95% CI, 1.101–1.168) for RRvid, and 0.913 (95% CI, 0.905–0.920) for video-based oxygen saturation. These results were obtained while maintaining continuous uninterrupted vital sign monitoring for the entire study period.
CONCLUSIONS:Video-based monitoring of HR, RR, and oxygen saturation may be performed with reasonable accuracy during acute hypoxic conditions in an anesthetized porcine hypoxia model using standard visible light camera equipment. However, the study was conducted during relatively low motion. A better understanding of the effect of motion and the effect of ambient light on the video photoplethysmogram may help refine this monitoring technology for use in the clinical environment.This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</description><subject>Animals</subject><subject>Heart Rate - physiology</subject><subject>Hypoxia - physiopathology</subject><subject>Monitoring, Physiologic - methods</subject><subject>Oximetry - methods</subject><subject>Oxygen Consumption - physiology</subject><subject>Respiratory Rate - physiology</subject><subject>Swine</subject><subject>Video Recording - methods</subject><issn>0003-2999</issn><issn>1526-7598</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkE9v1DAQxS0EokvLN0DIRw6k-E8S29y2S8siFVq1wDVy7MmuwRsvdqI2375ud0GIA7VkjWb8e2_kh9ArSo4po_zd_MvpMfnrUCXVEzSjFasLUSn5FM3ylBdMKXWAXqT04x4isn6ODpjknAtSz9D03VkIxYlOYPHlekou-LByBn8OvRtCdP0Kfxgfiu7x3IwD4OW0DbcZWay199Cv4D1ego4DvtIDvMVXkLYu6iye9hPdW3xxO62gx9d6GPObC_0RetZpn-Dlvh6ib2enXxfL4vzi46fF_LwwZf5TQTtqDeXcWiqEUdQAU5xZQWVVtVDWwtSmqpTquk4xxdq2Fl1rhSi5JFASzQ_Rm53vNoZfI6Sh2bhkwHvdQxhTQ6WkrOY1Zxktd6iJIaUIXbONbqPj1FDS3Ife5NCbf0PPstf7DWO7AftH9DvlDMgdcBP8ADH99OMNxGYN2g_rx7zL_0gfuIqrghEqiMpNkS8r-R2L_p18</recordid><startdate>20170901</startdate><enddate>20170901</enddate><creator>Addison, Paul S.</creator><creator>Jacquel, Dominique</creator><creator>Foo, David M. H.</creator><creator>Antunes, André</creator><creator>Borg, Ulf R.</creator><general>The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the International Anesthesia Research Society</general><general>International Anesthesia Research Society</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20170901</creationdate><title>Video-Based Physiologic Monitoring During an Acute Hypoxic Challenge: Heart Rate, Respiratory Rate, and Oxygen Saturation</title><author>Addison, Paul S. ; Jacquel, Dominique ; Foo, David M. H. ; Antunes, André ; Borg, Ulf R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4019-1f1dc133dd177c91ce2932d71855be467c6c5599fff9292bb67fbd774380e40a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Animals</topic><topic>Heart Rate - physiology</topic><topic>Hypoxia - physiopathology</topic><topic>Monitoring, Physiologic - methods</topic><topic>Oximetry - methods</topic><topic>Oxygen Consumption - physiology</topic><topic>Respiratory Rate - physiology</topic><topic>Swine</topic><topic>Video Recording - methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Addison, Paul S.</creatorcontrib><creatorcontrib>Jacquel, Dominique</creatorcontrib><creatorcontrib>Foo, David M. H.</creatorcontrib><creatorcontrib>Antunes, André</creatorcontrib><creatorcontrib>Borg, Ulf R.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Anesthesia and analgesia</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Addison, Paul S.</au><au>Jacquel, Dominique</au><au>Foo, David M. H.</au><au>Antunes, André</au><au>Borg, Ulf R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Video-Based Physiologic Monitoring During an Acute Hypoxic Challenge: Heart Rate, Respiratory Rate, and Oxygen Saturation</atitle><jtitle>Anesthesia and analgesia</jtitle><addtitle>Anesth Analg</addtitle><date>2017-09-01</date><risdate>2017</risdate><volume>125</volume><issue>3</issue><spage>860</spage><epage>873</epage><pages>860-873</pages><issn>0003-2999</issn><eissn>1526-7598</eissn><abstract>BACKGROUND:The physiologic information contained in the video photoplethysmogram is well documented. However, extracting this information during challenging conditions requires new analysis techniques to capture and process the video image streams to extract clinically useful physiologic parameters. We hypothesized that heart rate, respiratory rate, and oxygen saturation trending can be evaluated accurately from video information during acute hypoxia.
METHOD:Video footage was acquired from multiple desaturation episodes during a porcine model of acute hypoxia using a standard visible light camera. A novel in-house algorithm was used to extract photoplethysmographic cardiac pulse and respiratory information from the video image streams and process it to extract a continuously reported video-based heart rate (HRvid), respiratory rate (RRvid), and oxygen saturation (SvidO2). This information was then compared with HR and oxygen saturation references from commercial pulse oximetry and the known rate of respiration from the ventilator.
RESULTS:Eighty-eight minutes of data were acquired during 16 hypoxic episodes in 8 animals. A linear mixed-effects regression showed excellent responses relative to a nonhypoxic reference signal with slopes of 0.976 (95% confidence interval [CI], 0.973–0.979) for HRvid; 1.135 (95% CI, 1.101–1.168) for RRvid, and 0.913 (95% CI, 0.905–0.920) for video-based oxygen saturation. These results were obtained while maintaining continuous uninterrupted vital sign monitoring for the entire study period.
CONCLUSIONS:Video-based monitoring of HR, RR, and oxygen saturation may be performed with reasonable accuracy during acute hypoxic conditions in an anesthetized porcine hypoxia model using standard visible light camera equipment. However, the study was conducted during relatively low motion. A better understanding of the effect of motion and the effect of ambient light on the video photoplethysmogram may help refine this monitoring technology for use in the clinical environment.This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</abstract><cop>United States</cop><pub>The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the International Anesthesia Research Society</pub><pmid>28333706</pmid><doi>10.1213/ANE.0000000000001989</doi><tpages>14</tpages></addata></record> |
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subjects | Animals Heart Rate - physiology Hypoxia - physiopathology Monitoring, Physiologic - methods Oximetry - methods Oxygen Consumption - physiology Respiratory Rate - physiology Swine Video Recording - methods |
title | Video-Based Physiologic Monitoring During an Acute Hypoxic Challenge: Heart Rate, Respiratory Rate, and Oxygen Saturation |
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