Evidence map›Paper›PMID 42802294›Full record

ReviewAnnals of biomedical engineering2026

Clinical Readiness of Hemodynamic Estimation from Cardiac Vibration Signals: An Endpoint-Specific Critical Review.

Peshala T Gamage, Yasith Weerasinghe, Prasith Weerasinghe, Mehmet Kaya

Abstract readReview
PubMed Publisher
In one paragraph

Review in Annals of biomedical engineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Peshala T GamageDepartment of Biomedical Engineering and Sciences, Florida Institute of Technology, Melbourne, FL, 32901, USA. pthibbotuwawagam@fit.edu.ORCID http://orcid.org/0000-0002-3317-4811
Yasith WeerasingheDepartment of Biomedical Engineering and Sciences, Florida Institute of Technology, Melbourne, FL, 32901, USA.
Prasith WeerasingheDepartment of Biomedical Engineering and Sciences, Florida Institute of Technology, Melbourne, FL, 32901, USA.
Mehmet KayaDepartment of Biomedical Engineering and Sciences, Florida Institute of Technology, Melbourne, FL, 32901, USA.

Funding

A Novel, Low-Cost, Machine Learning based and Wearable Technology for Monitoring Heart Failure ParametersR15HL175648 · NHLBI · FLORIDA INSTITUTE OF TECHNOLOGY · PI KAYA, MEHMET, THIBBOTUWAWA GAMAGE, PESHALA · 2025 to 2025
$406k
NHLBI NIH HHS R15HL175648
6 · The paper itself

Abstract

purposeCardiac vibration signals have been investigated as unobtrusive surrogates of central hemodynamics, but the literature frequently mixes physiological plausibility, association, and clinically meaningful validation. This review evaluates the validation readiness of vibration-based estimation of central hemodynamic parameters, specifically stroke volume (SV), cardiac output (CO), and arterial blood pressure (BP), including cuffless or central BP claims when explicitly reported. Ejection fraction (EF) and pulmonary capillary wedge pressure (PCWP) are also considered as related endpoints for cardiac function and filling pressure.

methodsA structured narrative review was conducted across studies using seismocardiography, ballistocardiography, gyrocardiography, and kinocardiography. Evidence was appraised by endpoint using reference standard tier, agreement analysis, calibration burden, and population realism, with emphasis on translational interpretability rather than correlation alone.

resultsEvidence maturity differed substantially by endpoint. The strongest support was found for stroke volume and cardiac output. For these endpoints, weighing-scale ballistocardiography and wearable seismocardiography systems validated against catheterization-based Direct Fick and thermodilution measurements provided the clearest agreement-based evidence within the studies reviewed. Clinically meaningful accuracy remains use-case dependent. Ejection fraction studies were dominated by classification and biomarker-style analyses rather than continuous estimation with agreement reporting. Exploratory early diastolic SCG studies remain limited to associations with echocardiographic relaxation indices, such as tissue Doppler e', and preload-perturbation responses, rather than direct preload measurement or validated diastolic-function estimation. Blood pressure studies reported promising calibrated error estimates in small healthy cohorts, but none met the International Organization for Standardization (ISO) 81060-2 requirements.

conclusionCardiac vibration sensing is not uniformly ready for clinical translation. Stroke volume and cardiac output estimation currently have a relatively more developed validation foundation, whereas ejection fraction and cuffless blood pressure remain pre-validation endpoints that require larger, more clinically realistic studies and stronger agreement-based evaluation.

Indexed as

BallistocardiographyCardiac outputHemodynamic monitoringSeismocardiographyValidationWearable sensors

Identifiers

What Socratic holds

Textmetadata
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 Socratic graph.