A Real-Time Digital Twin Synchronization Framework for Multi-Sensor Cardiopulmonary Resuscitation Measurement.

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 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

3 authors.

Kai-Chao YaoDepartment of Electrical and Mechanical Technology, College of Technology, National Changhua University of Education, Bao-Shan Campus, No. 2, Shi-Da Rd., Changhua City 500208, Taiwan.ORCID 0000-0002-5975-2392

Feng-Yu LinDepartment of Electrical and Mechanical Technology, College of Technology, National Changhua University of Education, Bao-Shan Campus, No. 2, Shi-Da Rd., Changhua City 500208, Taiwan.ORCID 0009-0002-2826-2865

Sumei ChiangDepartment of Electrical and Mechanical Technology, College of Technology, National Changhua University of Education, Bao-Shan Campus, No. 2, Shi-Da Rd., Changhua City 500208, Taiwan.ORCID 0009-0006-4125-7680

Funding

National Science and Technology Council, Taiwan NSTC 112-2410-H-018-030-MY3

6 · The paper itself

Abstract

This study proposes a digital twin-based CPR compression measurement system (DTCMS) architecture for real-time monitoring of CPR compression. The system combines a load cell, an inertial measurement unit (IMU), a LabVIEW acquisition platform, and a CNN module to capture multi-modal motion characteristics during CPR repetitive compression training. A calibration-aware sensor fusion framework synchronizes heterogeneous signals, reduces drift, and enhances robustness under high-frequency operation. Real-time data acquisition, latency-controlled transmission, and digital twin visualization enable synchronized physical-virtual interaction. Experimental results demonstrate high accuracy (

Indexed as

Cardiopulmonary ResuscitationDigital TechnologyAlgorithmsCalibrationCompression AlgorithmsHumansSignal Processing, Computer-AssistedCPR compression measurementdigital twinIoT sensingLabVIEWmulti-sensor integrationreal-time feedback

Identifiers

PMID42280975

DOI10.3390/s26113459

PMCPMC13258877

What Socratic 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 Socratic graph.