Evidence map›Paper›PMID 39943416›Full record

ArticleSensors (Basel, Switzerland)2025

Smart Force Sensing in Robot Surgery Utilising the Back Electromotive Force.

Storm Chabot, Koen Schouten, Bart Van Straten, Stefano Pomati, Andres Hunt, Jenny Dankelman, Tim Horeman

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 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

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

1 citing paper in PubMed.

  1. 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

7 authors.

Storm ChabotDepartment of BioMechanical Engineering, Delft University of Technology, 2628 CD Delft, The Netherlands.
Koen SchoutenDepartment of BioMechanical Engineering, Delft University of Technology, 2628 CD Delft, The Netherlands.
Bart Van StratenDepartment of BioMechanical Engineering, Delft University of Technology, 2628 CD Delft, The Netherlands.ORCID 0000-0003-0269-6593
Stefano PomatiAsensus Surgical, Durham, NC 27703, USA.
Andres HuntDepartment of Precision and Microsystems Engineering, Delft University of Technology, 2628 CD Delft, The Netherlands.
Jenny DankelmanDepartment of BioMechanical Engineering, Delft University of Technology, 2628 CD Delft, The Netherlands.ORCID 0000-0003-3951-2129
Tim HoremanDepartment of BioMechanical Engineering, Delft University of Technology, 2628 CD Delft, The Netherlands.ORCID 0000-0002-8527-4486

Funding

Netherlands Organisation for Health Research and Development KICH1.ST03.21.002
6 · The paper itself

Abstract

Since the introduction of robot-assisted laparoscopic surgery, efforts have been made to incorporate force sensing technologies to monitor critical components and to provide force feedback. The advanced laparoscopic robotic system (AdLap RS) is a robotic platform that aims to make robot technology more sustainable through the use of the fully reusable shaft-actuated tip-articulating (SATA) instruments. The SATA instrument driver features electronics and sensors exposed to the sterile environment, which complicate the sterilisation process. The aim of this study was to develop and validate smart sensing in stepper motors using the back electromotive force in a newly developed Smart SATA Driver (SSD), eliminating the need for sensors in the sterile environment.

methodsThe stepper drivers were equipped with TMC2209 ICs featuring StallGuard technology to measure back EMF. The tip was actuated up until a set StallGuard threshold value was reached, at which the resulting tip force was measured. This cycle was repeated ten times for a range of threshold levels. A regression analysis with a power series model was used to determine the quality of the fit.

resultsThe SSD is capable of exerting tip forces between 2.4 and 8.2 N. The back EMF force test demonstrated a strong correlation between obtained StallGuard values and measured tip forces. The regression analysis showed an R-squared of 0.95 and a root Mean squared error of 0.4 N. DISCUSSION: The back EMF force test shows promise for force feedback, but its accuracy limits real-time use due to back EMF fluctuations. Future improvements in motor stability and refining the back EMF model are needed to enable real-time feedback.

conclusionThe strong correlation during the back EMF force test shows its potential as a low-budget method for detecting motor stalls and estimating tool-tissue forces without the need for sensors in laparoscopic instruments.

Indexed as

RoboticsRobotic Surgical ProceduresEquipment DesignHumansLaparoscopyback electromotive forceforce feedbacklaparoscopyrobotic surgerysmart force sensing

Identifiers

PMID39943416
PMCPMC11820894

What OpenQuestion holds

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Registered trials

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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.