Dysphagia detection using near-ear sensors and machine learning

Research question: Swallowing disorders affect approximately 600 million individuals globally and are a major risk factor for aspiration pneumonia. Current diagnostic methods, including FEES (Fiberoptic Endoscopic Evaluation of Swallowing) and VFSS (Videofluoroscopic Swallowing Study), are highly accurate [for full text, please go to the a.m. URL]

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Publication Details

Journal
German Medical Science (German Research Foundation)
Published
2026-03-02
DOI
https://doi.org/10.3205/26dga116
Primary Topic
Dysphagia Assessment and Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Dysphagia detection using near-ear sensors and machine learning

Andreas Radeloff, Tanja Schultz, Aditya Mehra
German Medical Science (German Research Foundation)
Dysphagia Assessment and Management
article

Dysphagia detection using near-ear sensors and machine learning

Andreas Radeloff, Tanja Schultz, Aditya Mehra
article en

Abstract

Research question: Swallowing disorders affect approximately 600 million individuals globally and are a major risk factor for aspiration pneumonia. Current diagnostic methods, including FEES (Fiberoptic Endoscopic Evaluation of Swallowing) and VFSS (Videofluoroscopic Swallowing Study), are highly accurate [for full text, please go to the a.m. URL]

German Medical Science (German Research Foundation)
Carl von Ossietzky Universität Oldenburg (DE)
Openalex Percentile: Top 36%
Dysphagia Assessment and Management
DOIOpen Access PDFOpenAlex
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Dysphagia detection using near-ear sensors and machine learning — Andreas Radeloff, Tanja Schultz, et al. · German Medical Science (German Research Foundation) (2026) | TGRS Research Map | TGRS