Evidence map›Paper›PMID 38434334›Full record

ArticleHeliyon2024

Automated extraction of heart rate variability from magnetoencephalography signals.

Ryan C Godwin, William C Flood, Jeremy P Hudson, Marc D Benayoun, Michael E Zapadka, Ryan L Melvin, Christopher T Whitlow

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Ryan C GodwinDepartment of Anesthesiology and Perioperative Medicine, Heersink School of Medicine, University of Alabama, Birmingham, Birmingham, AL, USA.
William C FloodDepartment of Radiology, Wake Forest University School of Medicine, Winston Salem, NC, USA.
Jeremy P HudsonDepartment of Radiology, Wake Forest University School of Medicine, Winston Salem, NC, USA.
Marc D BenayounDepartment of Radiology, Wake Forest University School of Medicine, Winston Salem, NC, USA.
Michael E ZapadkaDepartment of Radiology, Wake Forest University School of Medicine, Winston Salem, NC, USA.
Ryan L MelvinDepartment of Anesthesiology and Perioperative Medicine, Heersink School of Medicine, University of Alabama, Birmingham, Birmingham, AL, USA.
Christopher T WhitlowDepartment of Radiology, Wake Forest University School of Medicine, Winston Salem, NC, USA.

Funding

iTAKL:Imaging Telemetry And Kinematic modeLing in youth football-High SchoolR01NS091602 · NINDS · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI MALDJIAN, JOSEPH A, STITZEL, JOEL DOUGLAS · 2016 to 2020
$3.2M
NINDS NIH HHS R01 NS091602
6 · The paper itself

Abstract

Magnetoencephalography (MEG) measures magnetic fluctuations in the brain generated by neural processes, some of which, such as cardiac signals, are generally removed as artifacts and discarded. However, heart rate variability (HRV) has long been regarded as a biomarker related to autonomic function, suggesting the cardiac signal in MEG contains valuable information that can provide supplemental health information about a patient. To enable access to these ancillary HRV data, we created an automated extraction tool capable of capturing HRV directly from raw MEG data with artificial intelligence. Five scans were conducted with simultaneous MEG and electrocardiogram (ECG) acquisition, which provides a ground truth metric for assessing our algorithms and data processing pipeline. In addition to directly comparing R-peaks between the MEG and ECG signals, this work explores the variation of the corresponding HRV output in time, frequency, and non-linear domains. After removing outlier intervals and aligning the ECG and derived cardiac MEG signals, the RMSE between the RR-intervals of each was

Indexed as

Artificial intelligenceAutonomic nervous systemElectrocardiogramHeart rate variabilityMachine learningMagnetoencephalography

Identifiers

PMID38434334
PMCPMC10907652

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.