Evidence map›Paper›PMID 37420560›Full record

ArticleSensors (Basel, Switzerland)2023

Non-Contact Assessment of Swallowing Dysfunction Using Smartphone Captured Skin Displacements.

Nikyta Chesney, Prashanna Khwaounjoo, Maggie-Lee Huckabee, Yusuf Ozgur Cakmak

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. 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
0.5field-weighted citation impact, top 33% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Review
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 3 institutions in 1 country.

Nikyta ChesneyDepartment of Anatomy, University of Otago, Dunedin 9016, New Zealand.
Prashanna KhwaounjooAuckland Bioengineering Institute, University of Auckland, Auckland 1010, New Zealand.
Maggie-Lee HuckabeeRose Centre for Stroke Recovery and Research, University of Canterbury, Christchurch 8140, New Zealand.
Yusuf Ozgur CakmakDepartment of Anatomy, University of Otago, Dunedin 9016, New Zealand.ORCID 0000-0003-4884-0714
University of Canterbury · NZUniversity of Auckland · NZUniversity of Otago · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Early and accurate dysphagia diagnosis is essential for reducing the risk of associated co-morbidities and mortalities. Barriers to current evaluation methods may alter the effectiveness of identifying at-risk patients. This preliminary study evaluates the feasibility of using iPhone X-captured videos of swallowing as a non-contact dysphagia screening tool. Video recordings of the anterior and lateral necks were captured simultaneously with videofluoroscopy in dysphagic patients. Videos were analyzed using an image registration algorithm (phase-based Savitzky-Golay gradient correlation (P-SG-GC)) to determine skin displacements over hyolaryngeal regions. Biomechanical swallowing parameters of hyolaryngeal displacement and velocity were also measured. Swallowing safety and efficiency were assessed by the Penetration Aspiration Scale (PAS), Residue Severity Ratings (RSR), and the Normalized Residue Ratio Scale (NRRS). Anterior hyoid excursion and horizontal skin displacements were strongly correlated with swallows of a 20 mL bolus (r

Indexed as

DeglutitionDeglutition DisordersHumansHyoid BoneSmartphoneVideo Recordingdysphagiaimage registration algorithmlarynxmobile healthmobile phonenon-contactpenetration aspirationphase-based Savitzky–Golay gradient correlationremote monitorizationresidue

Identifiers

PMID37420560
PMCPMC10302948
OpenAlexW4380049599

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.