Evidence map›Paper›PMID 39247094›Full record

ArticleDigital health

Solving variability: Accurately extracting feature components from ballistocardiograms.

Tianyi Yang, Haihang Yuan, Junqi Yang, Zhongchao Zhou, Masayuki Abe, Yoshitake Nakayama, Shao Ying Huang, Wenwei Yu

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Observational
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.

Tianyi YangDepartment of Medical Engineering, Chiba University, Chiba City, Chiba Prefecture, Japan.ORCID https://orcid.org/0000-0002-0711-919X
Haihang YuanDepartment of Medical Engineering, Chiba University, Chiba City, Chiba Prefecture, Japan.
Junqi YangDepartment of Medical Engineering, Chiba University, Chiba City, Chiba Prefecture, Japan.
Zhongchao ZhouDepartment of Medical Engineering, Chiba University, Chiba City, Chiba Prefecture, Japan.
Masayuki AbeNanayume Co. Ltd, Chiba City, Chiba Prefecture, Japan.
Yoshitake NakayamaCenter for Preventive Medical Sciences, Chiba University, Chiba City, Chiba Prefecture, Japan.
Shao Ying HuangEngineering Product Development, Singapore University of Technology and Design, Singapore, Singapore.
Wenwei YuDepartment of Medical Engineering, Chiba University, Chiba City, Chiba Prefecture, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: A ballistocardiogram (BCG) is a vibration signal generated by the ejection of the blood in each cardiac cycle. The BCG has significant variability in amplitude, temporal aspects, and the deficiency of waveform components, attributed to individual differences, instantaneous heart rate, and the posture of the person being measured. This variability may make methods of extracting J-waves, the most distinct components of BCG less generalizable so that the J-waves could not be precisely localized, and further analysis is difficult. This study is dedicated to solving the variability of BCG to achieve accurate feature extraction. Methods: Inspired by the generation mechanism of the BCG, we proposed an original method based on a profile of second-order derivative of BCG waveform (2ndD-P) to capture the nature of vibration and solve the variability, thereby accurately localizing the components especially when the J-wave is not prominent. Results: In this study, 51 recordings of resting state and 11 recordings of high-heart-rate from 24 participants were used to validate the algorithm. Each recording lasts about 3 min. For resting state data, the sensitivity and positive predictivity of proposed method are: 98.29% and 98.64%, respectively. For high-heart-rate data, the proposed method achieved a performance comparable to those of low-heart-rate: 97.14% and 99.01% for sensitivity and positive predictivity, respectively. Conclusion: Our proposed method can detect the peaks of the J-wave more accurately than conventional extraction methods, under the presence of different types of variability. Higher performance was achieved for BCG with non-prominent J-waves, in both low- and high-heart-rate cases.

Indexed as

Ballistocardiogramcomponent extractiondynamic time warpingJ-wavesecond-order derivate

Identifiers

PMID39247094
PMCPMC11378244

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.