{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T15:38:13Z","timestamp":1789659493442,"version":"4.0.1"},"reference-count":20,"publisher":"Oxford University Press (OUP)","issue":"Supplement_2","license":[{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/100020785","name":"U.S. Army Futures Command","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100020785","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Combat Capabilities Development Command Soldier Center STTC","award":["W912CG-21-2-0001"],"award-info":[{"award-number":["W912CG-21-2-0001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,9,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Introduction<\/jats:title>\n                  <jats:p>Endotracheal intubation (ETI) is a critical procedure that requires effective training and assessment to ensure successful oxygen delivery. Traditional training methods, such as observation and checklist-based assessments, are resource-intensive and heavily reliant on expert supervision. This study evaluates provider posture during ETI and explores the use of video-based posture analysis and machine learning to classify successful intubation attempts.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Materials and Methods<\/jats:title>\n                  <jats:p>Eighteen novice participants performed ETI on a manikin for 30 repetitions over 3 visits (10 per visit) within 1 week. Videos of the third visit were cropped to the final 5 seconds of the task and processed at 4 frames per second. Provider posture points were extracted using a pose detection network, and relative distances between points were calculated as features across a dataset of 2,429 frames. After filtering out incomplete data, the 922-frame dataset was split for 10-fold cross-validation in an XGBoost model.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>The model achieved an average test performance of 77.8% accuracy, 76.9% sensitivity, and 78.7% specificity on average across folds in classifying successful and unsuccessful intubations. Feature analysis identified key spatial relationships, such as the relative positions of elbows and wrists, as significant predictors of success.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Discussion<\/jats:title>\n                  <jats:p>This study demonstrates the potential of video-based posture analysis in objectively evaluating ETI performance. The approach minimizes the need for expert oversight and offers a scalable solution for training in resource-constrained settings. Although additional validation is needed, this method could enhance training effectiveness in environments such as military healthcare.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>Integrating posture analysis and machine learning provides a practical, scalable framework for assessing ETI performance. Future research should focus on refining this methodology and exploring its integration into current training programs.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/milmed\/usaf296","type":"journal-article","created":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T22:24:04Z","timestamp":1758320644000},"page":"656-661","source":"Crossref","is-referenced-by-count":1,"title":["Video-Based Posture Analysis for Evaluating Endotracheal Intubation Performance"],"prefix":"10.1093","volume":"190","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1412-0922","authenticated-orcid":false,"given":"Gabriel","family":"Gazetta","sequence":"first","affiliation":[{"name":"Department of Industrial and Systems Engineering, University at Buffalo , Buffalo, NY 14260,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chloe","family":"Miller","sequence":"additional","affiliation":[{"name":"Department of Industrial and Systems Engineering, University at Buffalo , Buffalo, NY 14260,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brian","family":"Clemency","sequence":"additional","affiliation":[{"name":"Department of Emergency Medicine, University at Buffalo , Buffalo, NY 14203,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaori","family":"Tanaka","sequence":"additional","affiliation":[{"name":"Department of Emergency Medicine, University at Buffalo , Buffalo, NY 14203,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4807-4784","authenticated-orcid":false,"given":"Matthew","family":"Hackett","sequence":"additional","affiliation":[{"name":"United States Army Combat Capabilities Development Command\u2014Soldier Center , Orlando, FL 32826,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jack","family":"Norfleet","sequence":"additional","affiliation":[{"name":"United States Army Combat Capabilities Development Command\u2014Soldier Center , Orlando, FL 32826,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Steven D","family":"Schwaitzberg","sequence":"additional","affiliation":[{"name":"Department of Surgery, University at Buffalo , Buffalo, NY 14203,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Suvranu","family":"De","sequence":"additional","affiliation":[{"name":"FAMU-FSU College of Engineering, Tallahassee , FL 32310,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4717-8378","authenticated-orcid":false,"given":"Lora","family":"Cavuoto","sequence":"additional","affiliation":[{"name":"Department of Industrial and Systems Engineering, University at Buffalo , Buffalo, NY 14260,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2025,9,16]]},"reference":[{"key":"2025091919354063400_usaf296-B1","doi-asserted-by":"publisher","first-page":"e352","DOI":"10.1093\/milmed\/usz34931865392","article-title":"Outcomes of Casualties Without Airway Trauma Undergoing Prehospital Airway Interventions: A Department of Defense Trauma Registry Study","volume":"185","author":"Schauer","year":"2020","journal-title":"Mil Med"},{"key":"2025091919354063400_usaf296-B2","doi-asserted-by":"publisher","first-page":"S333","DOI":"10.1097\/TA.0b013e31827018a523114490","article-title":"Emergency tracheal intubation immediately following traumatic injury: an Eastern Association for the Surgery of Trauma practice management guideline","volume":"73","author":"Mayglothling","year":"2012","journal-title":"J Trauma Acute Care Surg"},{"key":"2025091919354063400_usaf296-B3","doi-asserted-by":"publisher","first-page":"156","DOI":"10.4187\/respcare.0503727999151","article-title":"Endotracheal Intubation Training and Skill Maintenance for Respiratory Therapists","volume":"62","author":"Miller","year":"2017","journal-title":"Respir Care"},{"key":"2025091919354063400_usaf296-B4","doi-asserted-by":"publisher","first-page":"e209278","DOI":"10.1001\/jamanetworkopen.2020.9278","article-title":"Association of Checklist Use in Endotracheal Intubation With Clinically Important Outcomes: A Systematic Review and Meta-analysis","volume":"3","author":"Turner","year":"2020","journal-title":"JAMA Netw Open"},{"key":"2025091919354063400_usaf296-B5","doi-asserted-by":"publisher","first-page":"42","DOI":"10.7205\/MILMED-D-13-0024724402984","article-title":"Reliability and validity of a test designed to assess combat medics\u2019 readiness to perform life-saving procedures","volume":"179","author":"Schmitz","year":"2014","journal-title":"Mil Med"},{"key":"2025091919354063400_usaf296-B6","doi-asserted-by":"publisher","first-page":"e1484","DOI":"10.7205\/MILMED-D-15-00570","article-title":"Validation of an Assessment Tool for Field Endotracheal Intubation","volume":"181","author":"Hart","year":"2016","journal-title":"Mil Med"},{"key":"2025091919354063400_usaf296-B7","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1093\/milmed\/usab18534724056","article-title":"Perseverance: An Essential Trait of Military Interprofessional Healthcare Teams","volume":"186","author":"Meyer","year":"2021","journal-title":"Mil Med"},{"key":"2025091919354063400_usaf296-B8","doi-asserted-by":"publisher","first-page":"2870","DOI":"10.3390\/healthcare11212870","article-title":"Supporting the Frontlines: A Scoping Review Addressing the Health Challenges of Military Personnel and Veterans","volume":"11","author":"Alruwaili","year":"2023","journal-title":"Healthcare"},{"key":"2025091919354063400_usaf296-B9","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1186\/s12909-022-03256-3","article-title":"When medical trainees encountering a performance difficulty: evidence from pupillary responses","volume":"22","author":"Liu","year":"2022","journal-title":"Med Educ"},{"key":"2025091919354063400_usaf296-B10","doi-asserted-by":"publisher","first-page":"705238","DOI":"10.3389\/fnhum.2022.705238","article-title":"Neuromonitoring correlates of expertise level in surgical performers: a systematic review","volume":"16","author":"Hannah","year":"2022","journal-title":"Front Hum Neurosci"},{"key":"2025091919354063400_usaf296-B11","doi-asserted-by":"publisher","first-page":"574","DOI":"10.1177\/21695067231199681","article-title":"Evaluating Workload Indicators for Learning During Stress Exposure Training of Endotracheal Intubation","volume":"67","author":"Gazetta","year":"2023","journal-title":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting"},{"key":"2025091919354063400_usaf296-B12","doi-asserted-by":"publisher","first-page":"1645","DOI":"10.1016\/j.jsurg.2019.05.01331175065","article-title":"Video-Based Assessment in Surgical Education: A Scoping Review","volume":"76","author":"McQueen","year":"2019","journal-title":"J Surg Educ"},{"key":"2025091919354063400_usaf296-B13","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1016\/j.amjsurg.2020.06.02732665080","article-title":"The what? How? And Who? Of video based assessment","volume":"221","author":"Pugh","year":"2021","journal-title":"Am J Surg"},{"key":"2025091919354063400_usaf296-B14","doi-asserted-by":"publisher","first-page":"482","DOI":"10.1016\/j.echo.2023.01.01536754100","article-title":"Video-Based Deep Learning for Automated Assessment of Left Ventricular Ejection Fraction in Pediatric Patients","volume":"36","author":"Reddy","year":"2023","journal-title":"J Am Soc Echocardiogr"},{"key":"2025091919354063400_usaf296-B15","doi-asserted-by":"publisher","first-page":"e2120786","DOI":"10.1001\/jamanetworkopen.2021.20786","article-title":"Development and Validation of a 3-Dimensional Convolutional Neural Network for Automatic Surgical Skill Assessment Based on Spatiotemporal Video Analysis","volume":"4","author":"Kitaguchi","year":"2021","journal-title":"JAMA Netw Open"},{"key":"2025091919354063400_usaf296-B16","doi-asserted-by":"publisher","first-page":"239","DOI":"10.3109\/10903127.2013.864352","article-title":"Paramedic intubation: patient position might matter","volume":"18","author":"Clemency","year":"2014","journal-title":"Prehosp Emerg Care"},{"key":"2025091919354063400_usaf296-B17","doi-asserted-by":"publisher","first-page":"1101","DOI":"10.1213\/ANE.0000000000001184","article-title":"Head-Elevated Patient Positioning Decreases Complications of Emergent Tracheal Intubation in the Ward and Intensive Care Unit","volume":"122","author":"Khandelwal","year":"2016","journal-title":"Anesth Analg"},{"key":"2025091919354063400_usaf296-B18","doi-asserted-by":"publisher","author":"Kendall","year":"2015","DOI":"10.48550\/arXiv.1505.07427"},{"key":"2025091919354063400_usaf296-B19","doi-asserted-by":"publisher","first-page":"2131","DOI":"10.1109\/TCBB.2019.291107130998478","article-title":"XGBoost Model for Chronic Kidney Disease Diagnosis","volume":"17","author":"Ogunleye","year":"2020","journal-title":"IEEE\/ACM Trans Comput Biol Bioinform"},{"key":"2025091919354063400_usaf296-B20","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1007\/978-3-030-80421-3_37","volume-title":"Intelligent Tutoring Systems","author":"Giannakas","year":"2021"}],"container-title":["Military Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/milmed\/article-pdf\/190\/Supplement_2\/656\/64288076\/usaf296.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/milmed\/article-pdf\/190\/Supplement_2\/656\/64288076\/usaf296.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T23:35:50Z","timestamp":1758324950000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/milmed\/article\/190\/Supplement_2\/656\/8256287"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,1]]},"references-count":20,"journal-issue":{"issue":"Supplement_2","published-online":{"date-parts":[[2025,9,16]]},"published-print":{"date-parts":[[2025,9,1]]}},"URL":"https:\/\/doi.org\/10.1093\/milmed\/usaf296","relation":{},"ISSN":["0026-4075","1930-613X"],"issn-type":[{"value":"0026-4075","type":"print"},{"value":"1930-613X","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2025,9]]},"published":{"date-parts":[[2025,9,1]]}}}