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The Measurement of Cognitive Workload in Surgery Using Pupil Metrics: A Systematic Review and Narrative Analysis.
Ravi Naik1, Alexandros Kogkas1, Hutan Ashrafian2
1Department of Surgery and Cancer, St Mary's Hospital, Imperial College London, London, UK; Hamlyn Centre for Robotic Surgery, Institute of Global Health Innovation, Imperial College London, London, UK.
The Journal of Surgical Research
|August 28, 2022
Summary
Pupil and gaze tracking can objectively measure cognitive workload (CWL) in surgery. This review synthesizes evidence on eye-tracking metrics for assessing surgical performance and expertise.
Area of Science:
- Ophthalmology
- Surgical Education
- Human Factors Engineering
Background:
- Increased cognitive workload (CWL) negatively impacts surgical performance and safety.
- Objective measurement of CWL in surgery is crucial for training and error reduction.
- Pupil and gaze tracking offer promising avenues for quantifying CWL.
Approach:
- Systematic review adhering to PRISMA guidelines.
- Comprehensive literature search across multiple databases (MEDLINE, IEEE Xplore, Web of Science, etc.) from 1990 to January 2021.
- Narrative analysis of 32 selected full-text articles due to study heterogeneity.
Key Points:
- Seventy-eight percent of reviewed studies were high quality.
- Surgical simulation and laparoscopic skills were the most studied areas (75% and 56%, respectively).
- Eye-tracking metrics are categorized into direct CWL measurement, expertise determination, and performance prediction.
Conclusions:
- Eye-tracking data, particularly pupil diameter and gaze entropy, show potential for CWL assessment.
- Significant study heterogeneity exists, necessitating further research.
- Future directions include integrating artificial intelligence (deep learning) and multisensor platforms for enhanced CWL measurement.
