Evidence map›Paper›PMID 41909777›Full record

ArticleExperimental mechanics2026

Image-based Evaluation of Cutting Forces During Ultrasonic Cutting of Bone.

A Marek, X Li, M Lucas, F Pierron

Abstract read
In one paragraph

Article in Experimental mechanics, 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
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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.

A MarekFaculty of Engineering and Physical Sciences, University of Southampton, University Road, Southampton, SO17 1BJ United Kingdom.
X LiFaculty of Engineering and Physical Sciences, University of Southampton, University Road, Southampton, SO17 1BJ United Kingdom.
M LucasCentre for Medical and Industrial Ultrasonics, James Watt School of Engineering, University of Glasgow, Glasgow, G12 8QQ United Kingdom.
F PierronFaculty of Engineering and Physical Sciences, University of Southampton, University Road, Southampton, SO17 1BJ United Kingdom.ORCID 0000-0003-2813-4994

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Ultrasonic surgical cutting tools are an appealing alternative to traditional devices. The measurement of time-resolved ultrasonic cutting forces is important to understand the material removal process but a challenge because of inertial effects affecting the results of traditional load cells. Objective: The present work details an attempt to resolve the cutting force of an ultrasonically powered surgical tool at the time scale of the 25 kHz ultrasonic excitation, by using the tool tip itself as the load cell. Methods: Ultra-high speed imaging is used in conjunction with Digital Image Correlation to measure strain and acceleration in the cutting blade. Dynamic equilibrium is then leveraged to identify the cutting force at the tool tip within a single cutting cycle of the tool. The methodology is first verified on simulated data before being applied to experiments on cortical bovine bone (free vibrations and cutting). Results: The force detection threshold was evaluated on the order of 5 N, recorded at 1 Mfps with a Shimadzu HPV-X camera. A particular difficulty was that the blade exhibited some out-of-plane bending which created a bias on the identified cutting force. Finally, it was possible to detect that when the blade engaged in the workpiece, a compressive force acted on the tool while during the disengagement part of the cycle, the force was null. Conclusions: It was shown that it was possible to use the thin flat blade of an in-house developed ultrasonic surgical tool to measure time-resolved cutting forces.

Indexed as

Digital image correlationForce identificationUltrasonic cuttingVirtual fields method

Identifiers

PMID41909777
PMCPMC13021876

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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.