Evidence map›Paper›PMID 39860838›Full record

ArticleSensors (Basel, Switzerland)2025

Design of a Cost-Effective Ultrasound Force Sensor and Force Control System for Robotic Extra-Body Ultrasound Imaging.

Yixuan Zheng, Hongyuan Ning, Eason Rangarajan, Aban Merali, Adam Geale, Lukas Lindenroth, Zhouyang Xu, Weizhao Wang, Philipp Kruse, Steven Morris and 4 more

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. 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

14 authors.

Yixuan ZhengSchool of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK.ORCID 0009-0004-8798-407X
Hongyuan NingSchool of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK.
Eason RangarajanSchool of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK.ORCID 0000-0001-5853-058X
Aban MeraliSchool of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK.ORCID 0009-0002-5093-5421
Adam GealeSchool of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK.ORCID 0009-0009-5903-9237
Lukas LindenrothSchool of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK.ORCID 0000-0002-9108-4574
Zhouyang XuSchool of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK.ORCID 0009-0004-9611-6514
Weizhao WangSchool of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK.ORCID 0009-0002-0643-1496
Philipp KruseSchool of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK.
Steven MorrisSchool of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK.
Liang YeSchool of Medicine, Southern University of Science and Technology, Shenzhen 518055, China.
Xinyi FuSchool of Medicine, Southern University of Science and Technology, Shenzhen 518055, China.
Kawal RhodeSchool of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK.ORCID 0000-0002-4707-7318
Richard James HousdenSchool of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK.ORCID 0000-0002-1673-5728

Funding

King's-China Scholarship Council PhD Scholarship Program (K-CSC) 202208060358Wellcome/EPSRC Centre for Medical Engineering WT203148/Z/16/ZWellcome Trust
6 · The paper itself

Abstract

Ultrasound imaging is widely valued for its safety, non-invasiveness, and real-time capabilities but is often limited by operator variability, affecting image quality and reproducibility. Robot-assisted ultrasound may provide a solution by delivering more consistent, precise, and faster scans, potentially reducing human error and healthcare costs. Effective force control is crucial in robotic ultrasound scanning to ensure consistent image quality and patient safety. However, existing robotic ultrasound systems rely heavily on expensive commercial force sensors or the integrated sensors of commercial robotic arms, limiting their accessibility. To address these challenges, we developed a cost-effective, lightweight, 3D-printed force sensor and a hybrid position-force control strategy tailored for robotic ultrasound scanning. The system integrates patient-to-robot registration, automated scanning path planning, and multi-sensor data fusion, allowing the robot to autonomously locate the patient, target the region of interest, and maintain optimal contact force during scanning. Validation was conducted using an ultrasound-compatible abdominal aortic aneurysm (AAA) phantom created from patient CT data and healthy volunteer testing. For the volunteer testing, during a 1-min scan, 65% of the forces were within the good image range. Both volunteers reported no discomfort or pain during the whole procedure. These results demonstrate the potential of the system to provide safe, precise, and autonomous robotic ultrasound imaging in real-world conditions.

Indexed as

RoboticsAortic Aneurysm, AbdominalCost-Benefit AnalysisEquipment DesignHumansPhantoms, ImagingUltrasonographyforce control for robotic systemsforce sensor designmedical roboticsmulti-sensor fusionrobot-assisted ultrasound imagingultrasound-compatible phantom design

Identifiers

PMID39860838
PMCPMC11769168

What OpenQuestion holds

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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.