Artificial Intelligence (AI)-Based Intraoperative Visualization is Increasingly Integrated Into Robotic Surgery Platforms; However, Its Impact on Surgeons' Cognitive Workload Remains Unclear. This Study Evaluated Perceived Workload Among Console Surgeons and Bedside Assistants According to Different

Conditions

• Urology

Eligibility Criteria

Sex

ALL

Age

18 Years - N/A

Healthy Volunteers

Accepted

Interventions

• Yolo — OTHER
  The AI system employed in this study was based on a convolutional neural network (CNN) architecture implemented via the YOLO (You Only Look Once) framework, specifically designed for real-time instance segmentation of intraoperative anatomical structures.

Study Details

Robotic surgery is now widely adopted in urology, and the da Vinci Single-Port (SP) platform enables complex procedures through a single multichannel incision, with favorable perioperative and outpatient outcomes in selected patients. However, single-port access and AI implementation also introduce unique ergonomic and cognitive challenges for surgeons and operating room staff. Quantifying intraoperative workload has become crucial to understand how new technologies affect performance, safety and training. The National Aeronautics and Space Administration Task Load Index (NASA-TLX) is a validated multidimensional instrument for subjective workload assessment and has been increasingly applied to surgical and specifically urologic practice. In parallel, augmented reality and artificial intelligence (AI) are emerging as tools to enhance intraoperative visualization and anatomical understanding during robot-assisted urologic procedures. The da Vinci TilePro multi-image display already allows simultaneous viewing of auxiliary imaging, but evidence on how real-time AI overlays integrated via TilePro affect cognitive workload in single-port urologic surgery is lacking. This prospective pilot study evaluates the impact of different TilePro visualization strategies on surgeon and bedside assistant workload, measured by weighted NASA-TLX scores, and explores associations with operative metrics in elective SP urologic procedures.

Key Dates

Start date

Sep 1, 2025

Status verified

Apr 2026

Primary completion

Sep 1, 2027

Completion

Sep 1, 2028

Study Design

Enrollment

90 participants (estimated)

Allocation

NON_RANDOMIZED

Intervention model

PARALLEL

Primary purpose

OTHER

Arms

• Active Comparator: Continuous AI visualization
  the AI overlay was displayed continuously throughout the entire surgical procedure.
• Active Comparator: Intermittent AI visualization
  The operator selectively activated the AI visualization during key surgical phases according to preference
• No Intervention: No AI visualization
  No AI visualization use

Primary Outcome Measure

NASA Task Load Index (NASA-TLX) questionnaire [ Time Frame: 30 minutes after completing the surgey ]

Locations (1)

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