Evidence map›Paper›PMID 36421112›Full record

ArticleBioengineering (Basel, Switzerland)2022

Heart and Breathing Rate Variations as Biomarkers for Anxiety Detection.

Florian Ritsert, Mohamed Elgendi, Valeria Galli, Carlo Menon

Open access · goldAbstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
5.7field-weighted citation impact, top 3% 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

18 citing papers in PubMed, 38 citations in OpenAlex.

  1. Article
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  4. α2δ-1-NMDAR1 complex in the hypothalamic paraventricular nucleus mediates anxiety-induced sympathetic hyperactivity.Clinical autonomic research : official journal of the Clinical Autonomic Research Society · 2026
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  11. Review
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  14. Article
  15. Prediction of Impulsive Aggression Based on Video Images.Bioengineering (Basel, Switzerland) · 2023
    Article
  16. Article
  17. Article
  18. 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

4 authors at 2 institutions in 2 countries.

Florian RitsertBiomedical and Mobile Health Technology Lab, ETH Zurich, 8008 Zurich, Switzerland.ORCID 0000-0002-3927-8873
Mohamed ElgendiBiomedical and Mobile Health Technology Lab, ETH Zurich, 8008 Zurich, Switzerland.ORCID 0000-0003-1831-0202
Valeria GalliBiomedical and Mobile Health Technology Lab, ETH Zurich, 8008 Zurich, Switzerland.ORCID 0000-0001-8522-3251
Carlo MenonBiomedical and Mobile Health Technology Lab, ETH Zurich, 8008 Zurich, Switzerland.ORCID 0000-0002-2309-9977
ETH Zurich · CHSimon Fraser University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With advances in portable and wearable devices, it should be possible to analyze and interpret the collected biosignals from those devices to tailor a psychological intervention to help patients. This study focuses on detecting anxiety by using a portable device that collects electrocardiogram (ECG) and respiration (RSP) signals. The feature extraction focused on heart-rate variability (HRV) and breathing-rate variability (BRV). We show that a significant change in these signals occurred between the non-anxiety-induced and anxiety-induced states. The HRV biomarkers were the mean heart rate (MHR; p¯ = 0.04), the standard deviation of the heart rate (SD; p¯ = 0.01), and the standard deviation of NN intervals (SDNN; p¯ = 0.03) for ECG signals, and the mean breath rate (MBR; p¯ = 0.002), the standard deviation of the breath rate (SD; p¯ < 0.0001), the root mean square of successive differences (RMSSD; p¯ < 0.0001) and SDNN (p¯ < 0.0001) for RSP signals. This work extends the existing literature on the relationship between stress and HRV/BRV by being the first to introduce a transitional phase. It contributes to systematically processing mental and emotional impulse data in humans measured via ECG and RSP signals. On the basis of these identified biomarkers, artificial-intelligence or machine-learning algorithms, and rule-based classification, the automated biosignal-based psychological assessment of patients could be within reach. This creates a broad basis for detecting and evaluating psychological abnormalities in individuals upon which future psychological treatment methods could be built using portable and wearable devices.

Indexed as

anxiety assessmentbreathing rate variabilitydigital healthheart rate variabilitymental health monitoringreal-time anxiety detectionrespiration rate variabilitywearable technology

Identifiers

PMID36421112
PMCPMC9687500
OpenAlexW4309705193

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.