Evidence map›Paper›PMID 32524032›Full record

ArticlePerspectives of the ASHA special interest groups2019

Tongue Part Movement Trajectories for /r/ Using Ultrasound.

Sarah Dugan, Sarah R Li, Jack Masterson, Hannah Woeste, Neeraja Mahalingam, Caroline Spencer, T Douglas Mast, Michael A Riley, Suzanne E Boyce

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Perspectives of the ASHA special interest groups, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.8field-weighted citation impact, top 23% 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

8 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Classification of accurate and misarticulated /Clinical linguistics & phonetics · 2023
    Article
  7. Neuroimaging of the Syllable Repetition Task in Children With Residual Speech Sound Disorder.Journal of speech, language, and hearing research : JSLHR · 2021
    Article
  8. 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

9 authors at 1 institution in 1 country.

Sarah DuganDepartment of Psychology, University of Cincinnati, OH.
Sarah R LiDepartment of Biomedical Engineering, University of Cincinnati, OH.
Jack MastersonDepartment of Biomedical Engineering, University of Cincinnati, OH.
Hannah WoesteDepartment of Biomedical Engineering, University of Cincinnati, OH.
Neeraja MahalingamDepartment of Biomedical Engineering, University of Cincinnati, OH.
Caroline SpencerDepartment of Communication Sciences and Disorders, University of Cincinnati, OH.
T Douglas MastDepartment of Biomedical Engineering, University of Cincinnati, OH.
Michael A RileyDepartment of Psychology, University of Cincinnati, OH.
Suzanne E BoyceDepartment of Communication Sciences and Disorders, University of Cincinnati, OH.
University of Cincinnati · US

Funding

Improving clinical speech remediation with ultrasound technologyR01DC013668 · NIDCD · CUNY GRADUATE SCH AND UNIV CTR · PI BOYCE, SUZANNE ELIZABETH, WHALEN, DOUGLAS H · 2014 to 2018
$3.4M
Simplified Ultrasound Biofeedback for Speech RemediationR01DC017301 · NIDCD · UNIVERSITY OF CINCINNATI · PI BOYCE, SUZANNE ELIZABETH, MAST, T DOUGLAS · 2018 to 2022
$2.6M
NIDCD NIH HHS R01 DC013668NIDCD NIH HHS R01 DC017301
6 · The paper itself

Abstract

purposeBecause it shows the movement of different parts of the tongue in real time, ultrasound biofeedback therapy is a promising technology for speech research and remediation. One limitation is the difficulty of interpreting real-time ultrasound images of tongue motion. Our image processing system, TonguePART, tracks the tongue surface and allows for the acquisition of quantitative tongue part trajectories.

methodTonguePART automatically identifies the tongue contour based on ultrasound image brightness and tracks motion of the tongue root, dorsum, and blade in real time. We present tongue part trajectory data from 2 children with residual sound errors on /r/ and 2 children with typical speech, focusing on /r/ (International Phonetic Alphabet ɹ) in the phonetic context /ɑr/. We compared the tongue trajectories to magnetic resonance images of sustained vowel /ɑ/ and /r/.

resultsMeasured trajectories show larger overall displacement and greater differentiation of tongue part movements for children with typical speech during the production of /ɑr/, compared to children with residual speech sound disorders.

conclusionTonguePART is a fast, reliable method of tracking articulatory movement of tongue parts for syllables such as /ɑr/. It is extensible to other sounds and phonetic contexts. By tracking tongue parts, clinical researchers can investigate lingual coordination. TonguePART is suitable for real-time data collection and biofeedback. Ultrasound biofeedback therapy users may make more progress using simplified biofeedback of tongue movement.

Identifiers

PMID32524032
PMCPMC7286630
OpenAlexW2996222982

What OpenQuestion holds

Textmetadata
LicenceTDM
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.