Evidence map›Paper›PMID 36904896›Full record

ArticleSensors (Basel, Switzerland)2023

Effects of Ballistocardiogram Peak Detection Jitters on the Quality of Heart Rate Variability Features: A Simulation-Based Case Study in the Context of Sleep Staging.

Ahmad Suliman, Md Rakibul Mowla, Alaleh Alivar, Charles Carlson, Punit Prakash, Balasubramaniam Natarajan, Steve Warren, David E Thompson

Full text read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. 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. Article
  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

8 authors.

Ahmad SulimanMike Wiegers Department of Electrical & Computer Engineering, Kansas State University, Manhattan, KS 66506, USA.ORCID 0000-0002-4688-7976
Md Rakibul MowlaMike Wiegers Department of Electrical & Computer Engineering, Kansas State University, Manhattan, KS 66506, USA.ORCID 0000-0001-5765-8856
Alaleh AlivarMike Wiegers Department of Electrical & Computer Engineering, Kansas State University, Manhattan, KS 66506, USA.ORCID 0000-0002-9123-1079
Charles CarlsonMike Wiegers Department of Electrical & Computer Engineering, Kansas State University, Manhattan, KS 66506, USA.ORCID 0000-0002-4293-3090
Punit PrakashMike Wiegers Department of Electrical & Computer Engineering, Kansas State University, Manhattan, KS 66506, USA.ORCID 0000-0001-6467-722X
Balasubramaniam NatarajanMike Wiegers Department of Electrical & Computer Engineering, Kansas State University, Manhattan, KS 66506, USA.
Steve WarrenMike Wiegers Department of Electrical & Computer Engineering, Kansas State University, Manhattan, KS 66506, USA.ORCID 0000-0002-9811-2267
David E ThompsonMike Wiegers Department of Electrical & Computer Engineering, Kansas State University, Manhattan, KS 66506, USA.

Funding

Kansas State University Faculty Startup FundsNational Science Foundation CBET-1067740National Science Foundation CHS-1910526National Science Foundation UNS-1512564
6 · The paper itself

Abstract

Heart rate variability (HRV) features support several clinical applications, including sleep staging, and ballistocardiograms (BCGs) can be used to unobtrusively estimate these features. Electrocardiography is the traditional clinical standard for HRV estimation, but BCGs and electrocardiograms (ECGs) yield different estimates for heartbeat intervals (HBIs), leading to differences in calculated HRV parameters. This study examines the viability of using BCG-based HRV features for sleep staging by quantifying the impact of these timing differences on the resulting parameters of interest. We introduced a range of synthetic time offsets to simulate the differences between BCG- and ECG-based heartbeat intervals, and the resulting HRV features are used to perform sleep staging. Subsequently, we draw a relationship between the mean absolute error in HBIs and the resulting sleep-staging performances. We also extend our previous work in heartbeat interval identification algorithms to demonstrate that our simulated timing jitters are close representatives of errors between heartbeat interval measurements. This work indicates that BCG-based sleep staging can produce accuracies comparable to ECG-based techniques such that at an HBI error range of up to 60 ms, the sleep-scoring error could increase from 17% to 25% based on one of the scenarios we examined.

Indexed as

BallistocardiographyBCG VaccineAlgorithmsElectrocardiographyHeart RateSleep StagesBCG VaccineballistocardiogramBayes errorclassifierelectrocardiogramheartbeat intervalk-nearest neighborR-J intervalR-R intervalsupport vector machine

Identifiers

PMID36904896
PMCPMC10007206

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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.