Dataset Information

Head orientation and electrode placement potentially influence fetal scalp ECG waveform.

ABSTRACT:

Background

Fetal monitoring based on electrocardiographic (ECG) morphology is obtained from a single unipolar fetal scalp electrode. Ideally, it should be obtained from multiple leads, as ECG waveform depends on alignment between electrode and electrical heart axis. This alignment is unknown in fetuses. Besides, fetuses are surrounded by conductive media, which may influence ECG waveform. We explored the influence of electrode position and head orientation on ECG waveforms of unipolar and bipolar scalp ECGs recorded in air and in conductive medium.

Methods

We recorded ECGs in one adult subject at five different scalp positions in five different head orientations both in dry and immersed conditions. The ratio between T-amplitude and QRS-amplitude (T/QRS ratio) of unipolar and bipolar scalp ECGs was determined and compared between all conditions.

Results

In the dry condition, we observed in the unipolar leads little to no difference between different electrode positions (maximal T/QRS difference 0.00-0.01) and minor differences between head orientations (0.02-0.03), whereas bipolar leads showed no recognizable ECG signal at all. During the immersed condition, we found variation in the unipolar leads, both between electrode positions (maximal T/QRS difference 0.02-0.05) and between head orientations (0.03-0.06). Bipolar leads showed different ECG signals in contrasting head orientations.

Conclusions

Both unipolar and bipolar scalp lead-derived ECG waveforms are influenced by electrode position and head orientation when the subject is submerged in a conductive medium. Fetal monitoring based on single scalp lead ECG waveform might be suboptimal, as it lacks correction for fetal head orientation and electrode position.

SUBMITTER: Hulsenboom ADJ

PROVIDER: S-EPMC6786568 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Publications

Head orientation and electrode placement potentially influence fetal scalp ECG waveform.

Hulsenboom Alexandra D J ADJ Warmerdam Guy J J GJJ Weijers Janna J Blijham Paul J PJ Oei S Guid SG van Laar Judith O E H JOEH Vullings Rik R Delhaas Tammo T

PloS one 20191010 10

<h4>Background</h4>Fetal monitoring based on electrocardiographic (ECG) morphology is obtained from a single unipolar fetal scalp electrode. Ideally, it should be obtained from multiple leads, as ECG waveform depends on alignment between electrode and electrical heart axis. This alignment is unknown in fetuses. Besides, fetuses are surrounded by conductive media, which may influence ECG waveform. We explored the influence of electrode position and head orientation on ECG waveforms of unipolar an ...[more]

PMID: 31600255

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Project description:The detection of psychological stress using the electrocardiogram (ECG) signal is most commonly based on the detection of the R peak-the most prominent part of the ECG waveform-and the heart rate variability (HRV) measurements derived from it. For stress detection algorithms focused on short-duration time windows, there is potential benefit in including HRV features derived from the detection of smaller peaks within the ECG waveform: the P, Q, S, and T waves. However, the potential drawback of using these small peaks is their smaller magnitude and subsequent susceptibility to noise, making them more difficult to reliably detect. In this work, we demonstrate the potential benefits of including smaller waves within binary stress classification using a pre-existing data set of ECG recordings from 57 participants (aged 18-40) with a self-reported fear of spiders during exposure to videos of spiders. We also present an analysis of the performance of an automated peak detection algorithm and the reliability of detection for each of the smaller parts of the ECG waveform. We compared two models, one with only R peak features and one with small peak features. They were similar in precision, recall, F1, area under ROC curve (AUC), and accuracy, with the greatest differences less than the standard deviations of each metric. There was a significant difference in the Akaike Information Criterion (AIC), which represented the information loss of the model. The inclusion of novel small peak features made the model 4.29×1028 times more probable to minimize the information loss, and the small peak features showed higher regression coefficients than the R peak features, indicating a stronger relationship with acute psychological stress. This difference and further analysis of the novel features suggest that small peak intervals could be indicative of independent processes within the heart, reflecting a psychophysiological response to stress that has not yet been leveraged in stress detection algorithms.

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Dataset Information

Head orientation and electrode placement potentially influence fetal scalp ECG waveform.

Background

Methods

Results

Conclusions

Publications

Head orientation and electrode placement potentially influence fetal scalp ECG waveform.

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