Simar P. Singh;Amir Mehdi Shayan;Jianxin Gao;Joseph Bible;Richard E. Groff;Ravikiran Singapogu
{"title":"开放式手术缝合技能评估中器械操作的客观和自动量化:基于模拟的研究","authors":"Simar P. Singh;Amir Mehdi Shayan;Jianxin Gao;Joseph Bible;Richard E. Groff;Ravikiran Singapogu","doi":"10.1109/OJEMB.2024.3402393","DOIUrl":null,"url":null,"abstract":"<italic>Goal:</i>\n Vascular surgical procedures are challenging and require proficient suturing skills. To develop these skills, medical training simulators with objective feedback for formative assessment are gaining popularity. As hardware advancements offer more complex, unique sensors, determining effective task performance measures becomes imperative for efficient suturing training. \n<italic>Methods:</i>\n 97 subjects of varying clinical expertise completed four trials on a suturing skills measurement and feedback platform (SutureCoach). Instrument handling metrics were calculated from electromagnetic motion trackers affixed to the needle driver. \n<italic>Results:</i>\n The results of the study showed that all metrics significantly differentiated between novices (no medical experience) from both experts (attending surgeons/fellows) and intermediates (residents). Rotational motion metrics were more consistent in differentiating experts and intermediates over traditionally used tooltip motion metrics. \n<italic>Conclusions:</i>\n Our work emphasizes the importance of tool motion metrics for open suturing skills assessment and establishes groundwork to explore rotational motion for quantifying a critical facet of surgical performance.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2024-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10533671","citationCount":"0","resultStr":"{\"title\":\"Objective and Automated Quantification of Instrument Handling for Open Surgical Suturing Skill Assessment: A Simulation-Based Study\",\"authors\":\"Simar P. Singh;Amir Mehdi Shayan;Jianxin Gao;Joseph Bible;Richard E. Groff;Ravikiran Singapogu\",\"doi\":\"10.1109/OJEMB.2024.3402393\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<italic>Goal:</i>\\n Vascular surgical procedures are challenging and require proficient suturing skills. To develop these skills, medical training simulators with objective feedback for formative assessment are gaining popularity. As hardware advancements offer more complex, unique sensors, determining effective task performance measures becomes imperative for efficient suturing training. \\n<italic>Methods:</i>\\n 97 subjects of varying clinical expertise completed four trials on a suturing skills measurement and feedback platform (SutureCoach). Instrument handling metrics were calculated from electromagnetic motion trackers affixed to the needle driver. \\n<italic>Results:</i>\\n The results of the study showed that all metrics significantly differentiated between novices (no medical experience) from both experts (attending surgeons/fellows) and intermediates (residents). Rotational motion metrics were more consistent in differentiating experts and intermediates over traditionally used tooltip motion metrics. \\n<italic>Conclusions:</i>\\n Our work emphasizes the importance of tool motion metrics for open suturing skills assessment and establishes groundwork to explore rotational motion for quantifying a critical facet of surgical performance.\",\"PeriodicalId\":33825,\"journal\":{\"name\":\"IEEE Open Journal of Engineering in Medicine and Biology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2024-03-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10533671\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Open Journal of Engineering in Medicine and Biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10533671/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, BIOMEDICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Open Journal of Engineering in Medicine and Biology","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10533671/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
Objective and Automated Quantification of Instrument Handling for Open Surgical Suturing Skill Assessment: A Simulation-Based Study
Goal:
Vascular surgical procedures are challenging and require proficient suturing skills. To develop these skills, medical training simulators with objective feedback for formative assessment are gaining popularity. As hardware advancements offer more complex, unique sensors, determining effective task performance measures becomes imperative for efficient suturing training.
Methods:
97 subjects of varying clinical expertise completed four trials on a suturing skills measurement and feedback platform (SutureCoach). Instrument handling metrics were calculated from electromagnetic motion trackers affixed to the needle driver.
Results:
The results of the study showed that all metrics significantly differentiated between novices (no medical experience) from both experts (attending surgeons/fellows) and intermediates (residents). Rotational motion metrics were more consistent in differentiating experts and intermediates over traditionally used tooltip motion metrics.
Conclusions:
Our work emphasizes the importance of tool motion metrics for open suturing skills assessment and establishes groundwork to explore rotational motion for quantifying a critical facet of surgical performance.
期刊介绍:
The IEEE Open Journal of Engineering in Medicine and Biology (IEEE OJEMB) is dedicated to serving the community of innovators in medicine, technology, and the sciences, with the core goal of advancing the highest-quality interdisciplinary research between these disciplines. The journal firmly believes that the future of medicine depends on close collaboration between biology and technology, and that fostering interaction between these fields is an important way to advance key discoveries that can improve clinical care.IEEE OJEMB is a gold open access journal in which the authors retain the copyright to their papers and readers have free access to the full text and PDFs on the IEEE Xplore® Digital Library. However, authors are required to pay an article processing fee at the time their paper is accepted for publication, using to cover the cost of publication.