Evidence map›Paper›PMID 33542260›Full record

ArticleScientific reports2021

Contactless analysis of heart rate variability during cold pressor test using radar interferometry and bidirectional LSTM networks.

Kilin Shi, Tobias Steigleder, Sven Schellenberger, Fabian Michler, Anke Malessa, Fabian Lurz, Nicolas Rohleder, Christoph Ostgathe, Robert Weigel, Alexander Koelpin

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
2.9field-weighted citation impact, top 9% of its field
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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 43 citations in OpenAlex.

  1. Pooled it
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  3. Review
  4. Review
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  7. Article
  8. A Review and Tutorial on Machine Learning-Enabled Radar-Based Biomedical Monitoring.IEEE open journal of engineering in medicine and biology · 2024
    Article
  9. EmRad: Ubiquitous Vital Sign Sensing Using Compact Continuous-Wave Radars.IEEE open journal of engineering in medicine and biology · 2024
    Article
  10. Review
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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

10 authors at 5 institutions in 1 country.

Kilin Shi *Institute for Electronics Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91058, Erlangen, Germany. kilin.shi@fau.de.
Tobias Steigleder *Department of Palliative Medicine, Universitätsklinikum Erlangen, Comprehensive Cancer Center CCC Erlangen-EMN, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054, Erlangen, Germany.
Sven SchellenbergerHamburg University of Technology, Institute of High-Frequency Technology, 21073, Hamburg, Germany.
Fabian MichlerInstitute for Electronics Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91058, Erlangen, Germany.
Anke MalessaDepartment of Palliative Medicine, Universitätsklinikum Erlangen, Comprehensive Cancer Center CCC Erlangen-EMN, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054, Erlangen, Germany.
Fabian LurzHamburg University of Technology, Institute of High-Frequency Technology, 21073, Hamburg, Germany.
Nicolas RohlederChair of Health Psychology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91052, Erlangen, Germany.
Christoph OstgatheDepartment of Palliative Medicine, Universitätsklinikum Erlangen, Comprehensive Cancer Center CCC Erlangen-EMN, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91054, Erlangen, Germany.
Robert WeigelInstitute for Electronics Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91058, Erlangen, Germany.
Alexander KoelpinHamburg University of Technology, Institute of High-Frequency Technology, 21073, Hamburg, Germany.
Friedrich-Alexander-Universität Erlangen-Nürnberg · DEHamburg University of Technology · DEComprehensive Cancer Center Erlangen · DEUniversität Hamburg · DEUniversitätsklinikum Erlangen · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Contactless measurement of heart rate variability (HRV), which reflects changes of the autonomic nervous system (ANS) and provides crucial information on the health status of a person, would provide great benefits for both patients and doctors during prevention and aftercare. However, gold standard devices to record the HRV, such as the electrocardiograph, have the common disadvantage that they need permanent skin contact with the patient. Being connected to a monitoring device by cable reduces the mobility, comfort, and compliance by patients. Here, we present a contactless approach using a 24 GHz Six-Port-based radar system and an LSTM network for radar heart sound segmentation. The best scores are obtained using a two-layer bidirectional LSTM architecture. To verify the performance of the proposed system not only in a static measurement scenario but also during a dynamic change of HRV parameters, a stimulation of the ANS through a cold pressor test is integrated in the study design. A total of 638 minutes of data is gathered from 25 test subjects and is analysed extensively. High F-scores of over 95% are achieved for heartbeat detection. HRV indices such as HF norm are extracted with relative errors around 5%. Our proposed approach is capable to perform contactless and convenient HRV monitoring and is therefore suitable for long-term recordings in clinical environments and home-care scenarios.

Indexed as

AdultAutonomic Nervous SystemElectrocardiographyFemaleHeart RateHeart SoundsHumansInterferometryMaleMonitoring, PhysiologicRadar

Identifiers

PMID33542260
PMCPMC7862409
OpenAlexW3128216532

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.