Evidence map›Paper›PMID 41219390›Full record

ArticleCommunications medicine2025

Multi-view ultrasound for diaphragm monitoring and cough strength estimation.

Zhen Song, Yu Sun, Vaheh Nazari, Yihao Zhou, Yongping Zheng

Abstract read
In one paragraph

Article in Communications medicine, 2025. 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

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

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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

5 authors.

Zhen SongDepartment of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China.ORCID http://orcid.org/0000-0002-2035-2420
Yu SunDepartment of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China.
Vaheh NazariDepartment of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China.
Yihao ZhouDepartment of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China.
Yongping ZhengDepartment of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China. yongping.zheng@polyu.edu.hk.ORCID http://orcid.org/0000-0002-3407-9226

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe current extubation process for mechanical ventilation is subjective and imprecise, as it lacks insight into respiratory muscle function. Ultrasound imaging has become an insightful technique to investigate diaphragmatic function, but common techniques have limitations in terms of repeatability and automation. We aim to develop a wearable ultrasound system to automatically quantify diaphragm movement from intercostal and subcostal views. We focus on diaphragm monitoring and cough strength estimation.

methodsThe proposed system consists of angle-free probes, a tracking algorithm, and a downstream algorithm. The probe allows for rapid setup and automatic diaphragm positioning. To provide real-time monitoring, we proposed a diaphragm tracking algorithm, which is automated and applicable for multiple ultrasound views. Sixty healthy participants (29 males and 31 females) were recruited to assess the system's accuracy and feasibility. In our validity study, we compared our measurements with those from a commercially available ultrasound scanner. Using sonomyographic techniques and machine learning regressors, we evaluated the system's potential for diaphragm monitoring and cough strength estimation in ICU applications.

resultsHere, we show that our tracking algorithm exhibits strong resistance to motion interference, achieving a Jaccard index of 73.6% and a boundary accuracy of 84.8%. In the validity study, the wearable probes demonstrate minimal measurement error. Additionally, the system enables the implementation of monitoring and cough strength estimation, achieving an error of less than 50 L/min.

conclusionsUsing our advanced sonomyographic techniques, we observe distinct patterns of muscle activation and demonstrate the feasibility of analyzing the underlying mechanisms of complex respiratory movements. The results show the potential for these methods to serve as standard practice in the ICU for various applications during and after extubation.

Identifiers

PMID41219390
PMCPMC12606270

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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.