Evidence map›Paper›PMID 22033532›Full record

ArticleJournal of applied physiology (Bethesda, Md. : 1985)2012

Automated regional analysis of B-mode ultrasound images of skeletal muscle movement.

John Darby, Emma F Hodson-Tole, Nicholas Costen, Ian D Loram

Open access · greenAbstract read
In one paragraph

Article in Journal of applied physiology (Bethesda, Md. : 1985), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
2.6field-weighted citation impact, top 11% of its field
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

20 citing papers in PubMed, 53 citations in OpenAlex.

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  6. Automated semi-real-time detection of muscle activity with ultrasound imaging.Medical & biological engineering & computing · 2021
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  17. Investigation of different stimulation patterns with doublet pulses to reduce muscle fatigue.Journal of rehabilitation and assistive technologies engineering
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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 at 1 institution in 1 country.

John DarbySchool of Computing, Mathematics and Digital Technology, Manchester Metropolitan University, UK.
Emma F Hodson-Tole
Nicholas Costen
Ian D Loram
Manchester Metropolitan University · GB

Funding

Wellcome Trust EP/H000291/1
6 · The paper itself

Abstract

To understand the functional significance of skeletal muscle anatomy, a method of quantifying local shape changes in different tissue structures during dynamic tasks is required. Taking advantage of the good spatial and temporal resolution of B-mode ultrasound imaging, we describe a method of automatically segmenting images into fascicle and aponeurosis regions and tracking movement of features, independently, in localized portions of each tissue. Ultrasound images (25 Hz) of the medial gastrocnemius muscle were collected from eight participants during ankle joint rotation (2° and 20°), isometric contractions (1, 5, and 50 Nm), and deep knee bends. A Kanade-Lucas-Tomasi feature tracker was used to identify and track any distinctive and persistent features within the image sequences. A velocity field representation of local movement was then found and subdivided between fascicle and aponeurosis regions using segmentations from a multiresolution active shape model (ASM). Movement in each region was quantified by interpolating the effect of the fields on a set of probes. ASM segmentation results were compared with hand-labeled data, while aponeurosis and fascicle movement were compared with results from a previously documented cross-correlation approach. ASM provided good image segmentations (<1 mm average error), with fully automatic initialization possible in sequences from seven participants. Feature tracking provided similar length change results to the cross-correlation approach for small movements, while outperforming it in larger movements. The proposed method provides the potential to distinguish between active and passive changes in muscle shape and model strain distributions during different movements/conditions and quantify nonhomogeneous strain along aponeuroses.

Indexed as

Ankle JointExerciseExercise TestHumansImage Processing, Computer-AssistedMotor ActivityMuscle ContractionMuscle, SkeletalRange of Motion, ArticularUltrasonography

Identifiers

PMID22033532
PMCPMC3349610
OpenAlexW2031595164

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.