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Evaluating and Classifying Gentleness in VR-Based Surgical Simulation: A VR + fNIRS Study.

Suveyda Sanli¹, Hasan Onur Keles^1,2,3

¹Department of Biomedical Engineering, Ankara University, Ankara 06560, Turkey.

Sensors (Basel, Switzerland)

|May 4, 2026

Summary

Assessing surgical gentleness in virtual reality training is crucial. Functional near-infrared spectroscopy (fNIRS) successfully classified performance levels, showing potential for automated skill assessment.

Keywords:

fNIRS gentleness skill assessment virtual reality

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Area of Science:

Neurosurgery
Medical Simulation
Biomedical Engineering

Background:

Surgical gentleness is a key skill, difficult to objectively measure during training.
Virtual reality (VR) offers a controlled environment for surgical skill acquisition.
Real-time feedback on surgical gentleness can enhance psychomotor and cognitive learning.

Purpose of the Study:

To evaluate the use of functional near-infrared spectroscopy (fNIRS) for classifying surgical gentleness in VR training.
To identify hemodynamic features indicative of different performance levels.
To assess the efficacy of machine learning models in automated performance evaluation.

Main Methods:

Twenty-three novices performed a VR laparoscopic task while fNIRS recorded brain activity.
Hemodynamic features (slope, RMS, std dev) were extracted from fNIRS signals.
Machine learning classifiers were trained to differentiate between low and high gentleness performance scores.

Main Results:

Lower gentleness performance correlated with increased right-frontal oxygenated hemoglobin (HbO) and left-motor deoxygenated hemoglobin (HbR) activity.
Slope-based fNIRS features outperformed other metrics for classification.
Random Forest models using HbR slope achieved high accuracy (≈0.85) and AUC (up to 0.93).

Conclusions:

fNIRS-derived hemodynamic metrics show promise for objective, real-time assessment of surgical gentleness in VR.
This technology can provide valuable feedback for surgical trainees.
Automated assessment using fNIRS can improve the efficiency and effectiveness of VR surgical training.