Automatic Assessment of Procedural Skills Based on the Surgical Workflow Analysis Derived from Speech and Video

Autor: Carmen Guzmán-García, Patricia Sánchez-González, Ignacio Oropesa, Enrique J. Gómez
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Bioengineering, Vol 9, Iss 12, p 753 (2022)
Druh dokumentu: article
ISSN: 2306-5354
95251839
DOI: 10.3390/bioengineering9120753
Popis: Automatic surgical workflow analysis (SWA) plays an important role in the modelling of surgical processes. Current automatic approaches for SWA use videos (with accuracies varying from 0.8 and 0.9), but they do not incorporate speech (inherently linked to the ongoing cognitive process). The approach followed in this study uses both video and speech to classify the phases of laparoscopic cholecystectomy, based on neural networks and machine learning. The automatic application implemented in this study uses this information to calculate the total time spent in surgery, the time spent in each phase, the number of occurrences, the minimal, maximal and average time whenever there is more than one occurrence, the timeline of the surgery and the transition probability between phases. This information can be used as an assessment method for surgical procedural skills.
Databáze: Directory of Open Access Journals
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