# A comprehensive electrooculography measurement system and protocols for screening myasthenia gravis

## TL;DR

This paper introduces a non-invasive EOG-based system for screening myasthenia gravis using eye movement signals.

## Contribution

A novel non-invasive method using electrooculography (EOG) and standardized protocols for MG screening is proposed.

## Key findings

- EOG signals can effectively detect and quantify myasthenia gravis through eye movement patterns.
- Standardized data collection protocols for EOG-based MG screening were developed and tested.
- Novel biomarkers based on eye movement signals were identified for MG quantification.

## Abstract

Myasthenia gravis (MG) is a neuromuscular disorder that can precipitate serious and fatal complications, especially when respiratory muscles are affected. Current electrodiagnostic methods, such as Single Fiber Electromyography (SFEMG) and Repetitive Nerve Stimulation (RNS), have notable limitations. While SFEMG is sensitive to neuromuscular abnormalities rather than being specific for MG, it is also a semi-invasive procedure that requires supervision by specialist clinicians and an expensive clinical setup. Conversely, RNS is highly specific for MG, but its sensitivity decreases in cases of low severity. Prior studies, including our previous work, have demonstrated that the manifestation of MG in affecting eye movements can be indirectly quantified using electrooculography (EOG) signals. This non-invasive method could develop into a widely used and easily deployed screening method, especially for early detection of MG using readily obtainable biomarkers. With this goal in mind, our research team developed data collection protocols using a standardized eye movement protocol that could be implemented in a standard clinical setting to acquire EOG data. In this article, we present the experimental setup, test protocols, sample outcomes, and preliminary analysis approaches. Common artifacts encountered, as well as technical and logistical challenges associated with such a setup, are also discussed.1.An approach to non-invasively detect and quantify MG using eye movement signals.2.Data collection protocols for acquiring eye movement signals designed for MG quantification3.Novel eye movement-based biomarkers in quantifying MG.

An approach to non-invasively detect and quantify MG using eye movement signals.

Data collection protocols for acquiring eye movement signals designed for MG quantification

Novel eye movement-based biomarkers in quantifying MG.

Image, graphical abstract