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EEG electrode localization with 3D iPhone scanning using point-cloud electrode selection (PC-ES).

Alicia Everitt¹, Haley Richards¹, Yinchen Song^2,3

¹Thayer School of Engineering, Dartmouth College, Hanover, NH 03755, United States of America.

Journal of Neural Engineering

|December 6, 2023

Summary

This summary is machine-generated.

A new iPhone-based method for digitizing electroencephalography (EEG) electrode positions offers a portable and affordable solution. This technique provides accuracy comparable to existing systems, improving access to EEG source imaging (ESI) for epilepsy evaluation.

Keywords:

3D scanning EEG source imaging (ESI)electrode localization electroencephalography (EEG)open-source software

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Area of Science:

Medical Imaging
Neuroscience
Biomedical Engineering

Background:

Electroencephalography source imaging (ESI) is crucial for epilepsy evaluation but limited by anatomical modeling errors.
Accurate scalp electrode localization is essential for ESI, yet current devices are costly and lack portability.
Accessibility of ESI is hindered, especially in critical care settings, due to electrode localization challenges.

Purpose of the Study:

To develop a portable and affordable method for digitizing electroencephalography electrode positions.
To utilize iPhone 3D scanning technology combined with custom image processing for electrode localization.
To compare the accuracy of the novel iPhone-based method against state-of-the-art photogrammetry.

Main Methods:

A portable electrode digitization technique using iPhone 3D scanning and a custom MATLAB application (PC-ES) was developed.
Over 6000 electrodes were labeled using both the iPhone/PC-ES method and photogrammetry in a human study.
Performance was characterized by head location and algorithm parameter impact.

Main Results:

The iPhone/PC-ES method showed a median electrode position variation of 1.50 mm across reviewers.
Photogrammetry yielded a median variation of 0.53 mm, with an average median distance of 3.4 mm between methods.
These results indicate comparable performance and sufficient accuracy for ESI.

Conclusions:

Low-cost, portable electrode localization using iPhone scanning significantly reduces barriers to ESI in various clinical settings.
This technology enhances accessibility for inpatient, outpatient, and remote epilepsy evaluations.
Future software automation and advancements in 3D scanning technology are expected to further improve PC-ES.