A marker-less technique for measuring kinematics in the operating room
| Autor: | Caprice C. Greenberg, Carla M. Pugh, Yue Ma, David P. Azari, Thomas Y. Yen, Sudha R. Pavuluri Quamme, Robert G. Radwin, Lane L. Frasier, Chia-Hsiung Chen |
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| Rok vydání: | 2016 |
| Předmět: |
Male
Operating Rooms medicine.medical_specialty Video Recording Kinematics behavioral disciplines and activities Article Standard deviation Task (project management) 03 medical and health sciences 0302 clinical medicine Physical medicine and rehabilitation Region of interest Task Performance and Analysis medicine Humans Bowel anastomosis 030212 general & internal medicine Experience level Technical skills CLIPS computer.programming_language business.industry Suture Techniques Internship and Residency Biomechanical Phenomena Surgery Surgical Procedures Operative Time and Motion Studies 030220 oncology & carcinogenesis Female Clinical Competence business computer |
| Zdroj: | Surgery. 160:1400-1413 |
| ISSN: | 0039-6060 |
| DOI: | 10.1016/j.surg.2016.05.004 |
| Popis: | Background Often in simulated settings, quantitative analysis of technical skill relies largely on specially tagged instruments or tracers on surgeons’ hands. We investigated a novel, marker-less technique for evaluating technical skill during open operations and for differentiating tasks and surgeon experience level. Methods We recorded the operative field via in-light camera for open operations. Sixteen cases yielded 138 video clips of suturing and tying tasks ≥5 seconds in duration. Video clips were categorized based on surgeon role (attending, resident) and task subtype (suturing tasks: body wall, bowel anastomosis, complex anastomosis; tying tasks: body wall, superficial tying, deep tying). We tracked a region of interest on the hand to generate kinematic data. Nested, multilevel modeling addressed the nonindependence of clips obtained from the same surgeon. Results Interaction effects for suturing tasks were seen between role and task categories for average speed ( P = .04), standard deviation of speed ( P = .05), and average acceleration ( P = .03). There were significant differences across task categories for standard deviation of acceleration ( P = .02). Significant differences for tying tasks across task categories were observed for maximum speed ( P = .02); standard deviation of speed ( P = .04); and average ( P = .02), maximum ( P P = .03) of acceleration. Conclusion We demonstrated the ability to detect kinematic differences in performance using marker-less tracking during open operative cases. Suturing task evaluation was most sensitive to differences in surgeon role and task category and may represent a scalable approach for providing quantitative feedback to surgeons about technical skill. |
| Databáze: | OpenAIRE |
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