Improving neuroimaging headgear placement robustness using facial-landmark-guided augmented reality.

ABSTRACT:

Significance

Accurate and consistent probe placement is crucial in functional near-infrared spectroscopy (fNIRS) and electroencephalogram (EEG) experiments, especially in longitudinal and group-based studies. Both operator experience and subject head shape variability can affect placement accuracy.

Aim

We aim to develop an easy-to-use software, NeuroNavigatAR (NNAR), utilizing augmented reality (AR) and machine learning to estimate and display in real-time the subject's cranial and head landmarks to guide consistent headgear placement.

Approach

By applying a facial recognition toolbox to the image frames extracted from a video camera, we can obtain and continuously track subject-specific three-dimensional facial landmarks. Separately, we have precomputed a robust line

SUBMITTER: Yen FY 

PROVIDER: S-EPMC12546995 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature