Evidence map›Paper›PMID 40387564›Full record

ReviewInternational journal for numerical methods in biomedical engineering2025

Computational Modeling of Cardiovascular-Induced Chest Vibrations: A Review and Practical Guide for Seismocardiography Simulation.

Mohammadali Monfared, Peshala T Gamage, Ali Loghmani, Amirtahà Taebi

Abstract readReview
In one paragraph

Review in International journal for numerical methods in biomedical engineering, 2025. 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. Wearable Flexible Sensors for Cardiovascular Disease Monitoring.Advanced materials (Deerfield Beach, Fla.) · 2026
    Review
  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

4 authors.

Mohammadali MonfaredDepartment of Bioengineering, Lehigh University, Bethlehem, Pennsylvania, USA.ORCID https://orcid.org/0000-0002-3900-6704
Peshala T GamageDepartment of Biomedical Engineering and Science, Florida Institute of Technology, Melbourne, Florida, USA.
Ali LoghmaniDepartment of Mechanical Engineering, Isfahan University of Technology, Esfahan, Isfahan, Iran.ORCID https://orcid.org/0000-0001-6900-7129
Amirtahà TaebiDepartment of Bioengineering, Lehigh University, Bethlehem, Pennsylvania, USA.ORCID https://orcid.org/0000-0002-5962-186X

Funding

National Science Foundation 2340020
6 · The paper itself

Abstract

This paper presents a comprehensive examination of finite element modeling (FEM) approaches for seismocardiography (SCG), a non-invasive method for assessing cardiac function through chest surface vibrations. The paper provides a comparative analysis of existing FEM approaches, exploring the strengths and challenges of various modeling choices in the literature. Additionally, we introduce a sample framework for developing FEM models of SCG, detailing key methodologies from governing equations and meshing techniques to boundary conditions and material property selection. This framework serves as a guide for researchers aiming to create accurate models of SCG signal propagation and offers insights into capturing complex cardiac mechanics and their transmission to the chest surface. By consolidating the current methodologies, this paper aims to establish a reference point for advancing FEM-based SCG modeling, ultimately improving our understanding of SCG waveforms and enhancing their reliability and applicability in cardiovascular health assessment.

Indexed as

Computer SimulationModels, CardiovascularThoraxVibrationFinite Element AnalysisHumanscomputational modelingfinite element modelingheart vibrationsseismocardiography

Identifiers

PMID40387564
PMCPMC12087531

What OpenQuestion holds

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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.