Elevation of Spectral Components of Electrodermal Activity Precedes Central Nervous System Oxygen Toxicity Symptoms in Divers

Overview

Journal Commun Med (Lond)

Publisher Nature Portfolio

Specialty General Medicine

Date 2024 Dec 20

PMID 39702758

Authors

Hugo F Posada-Quintero

Bruce J Derrick

M Claire Ellis

Michael J Natoli

Christopher Winstead-Derlega

Sara I Gonzalez

Christopher M Allen

Matthew S Makowski

Brian M Keuski

Richard E Moon

John J Freiberger

Ki H Chon

Affiliations

Soon will be listed here.

Abstract

Background: Oxygen-rich breathing mixtures up to 100% are used in some underwater diving operations for several reasons. Breathing elevated oxygen partial pressures (PO) increases the risk of developing central nervous system oxygen toxicity (CNS-OT) which could impair performance or result in a seizure and subsequent drowning. We aimed to study the dynamics of the electrodermal activity (EDA) and heart rate (HR) while breathing elevated PO in the hyperbaric environment (HBO) as a possible means to predict impending CNS-OT.

Methods: EDA is recorded during 50 subject exposures (26 subjects) to evaluate CNS-OT in immersed (head out of water) exercising divers in a hyperbaric chamber breathing 100% O at 35 feet of seawater (FSW), (PO = 2.06 ATA) for up to 120 min.

Results: 32 subject exposures exhibit symptoms "definitely" or "probably" due to CNS-OT before the end of the exposure, whereas 18 do not. We obtain traditional and time-varying spectral indices (TVSymp) of EDA to determine its utility as predictive physio markers. Variations in EDA and heart rate (HR) for the last 5 min of the experiment are compared to baseline values prior to breathing O. In the subset of experiments where "definite" CNS-OT symptoms developed, we find a significant elevation in the mean ± standard deviation TVSymp value 57 ± 79 s and median of 10 s, prior to symptoms.

Conclusions: In this retrospective analysis, TVSymp may have predictive value for CNS-OT with high sensitivity (1.0) but lower specificity (0.48). Additional work is being undertaken to improve the detection algorithm.

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