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

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...

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Bibliographic Details
Published in:Bioengineering (Basel) 2022-12, Vol.9 (12), p.753
Main Authors: Guzmán-García, Carmen, Sánchez-González, Patricia, Oropesa, Ignacio, Gómez, Enrique J
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Artificial intelligence
Bioengineering
Cholecystectomy
Cognition & reasoning
Cognitive ability
Datasets
Decision making
Educational films
Endoscopy
Laparoscopy
Machine learning
Neural networks
Performance evaluation
procedural skills
Skills
skills’ assessment
Speech
Surgery
surgical training
Technology application
Training
Transition probabilities
Workflow
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Summary: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.
ISSN:2306-5354
2306-5354
DOI:10.3390/bioengineering9120753