Evidence map›Paper›PMID 37447668›Full record

ArticleSensors (Basel, Switzerland)2023

Signal Quality Analysis of Single-Arm Electrocardiography.

Jia-Jung Wang, Shing-Hong Liu, Cheng-Hsien Tsai, Ioannis Manousakas, Xin Zhu, Thung-Lip Lee

Open access · goldAbstract 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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 20% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
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

6 authors at 4 institutions in 2 countries.

Jia-Jung WangDepartment of Biomedical Engineering, I-Shou University, Kaohsiung 84001, Taiwan.
Shing-Hong LiuDepartment of Computer Science and Information Engineering, Chaoyang University of Technology, Taichung 413310, Taiwan.ORCID 0000-0002-3923-4387
Cheng-Hsien TsaiDepartment of Biomedical Engineering, I-Shou University, Kaohsiung 84001, Taiwan.
Ioannis ManousakasDepartment of Biomedical Engineering, I-Shou University, Kaohsiung 84001, Taiwan.ORCID 0000-0003-2295-1096
Xin ZhuDivision of Information Systems, School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu City 965-8580, Japan.ORCID 0000-0002-4376-0806
Thung-Lip LeeDepartment of Cardiology, E-Da Hospital, Kaohsiung 84001, Taiwan.
I-Shou University · TWChaoyang University of Technology · TWE-Da Hospital · TWUniversity of Aizu · JP

Funding

National Science and Technology Council, Taiwan NSTC 111-2221-E-324 -003 -MY3National Science and Technology Council, Taiwan NSTC NSTC 111-2221-E-214 -003
6 · The paper itself

Abstract

The number of people experiencing mental stress or emotional dysfunction has increased since the onset of the COVID-19 pandemic, as many individuals have had to adapt their daily lives. Numerous studies have demonstrated that mental health disorders can pose a risk for certain diseases, and they are also closely associated with the problem of mental workload. Now, wearable devices and mobile health applications are being utilized to monitor and assess individuals' mental health conditions on a daily basis using heart rate variability (HRV), typically measured by the R-to-R wave interval (RRI) of an electrocardiogram (ECG). However, portable or wearable ECG devices generally require two electrodes to perform bipolar limb leads, such as the Einthoven triangle. This study aims to develop a single-arm ECG measurement method, with lead I ECG serving as the gold standard. We conducted static and dynamic experiments to analyze the morphological performance and signal-to-noise ratio (SNR) of the single-arm ECG. Three morphological features were defined, RRI, the duration of the QRS complex wave, and the amplitude of the R wave. Thirty subjects participated in this study. The results indicated that RRI exhibited the highest cross-correlation (R = 0.9942) between the single-arm ECG and lead I ECG, while the duration of the QRS complex wave showed the weakest cross-correlation (R = 0.2201). The best SNR obtained was 26.1 ± 5.9 dB during the resting experiment, whereas the worst SNR was 12.5 ± 5.1 dB during the raising and lowering of the arm along the z-axis. This single-arm ECG measurement method offers easier operation compared to traditional ECG measurement techniques, making it applicable for HRV measurement and the detection of an irregular RRI.

Indexed as

COVID-19Wearable Electronic DevicesElectrocardiographyHeart RateHumansPandemicselectrocardiogram (ECG)heart rate variability (HRV)R-to-R wave interval (RRI)signal-to-noise ratio (SNR)single-arm ECG

Identifiers

PMID37447668
PMCPMC10346735
OpenAlexW4381799442

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.