Automatic Voice Analysis for Dysphagia Screening in Neurological Patients

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Conditions studied: Deglutition Disorders, Neurological Disorder

In brief

The proposed study suggests using automatic voice analysis and machine learning algorithms to develop a dysphagia screening tool for neurological patients. The research involves patients with Parkinson's disease, stroke, and amyotrophic lateral sclerosis, both with and without dysphagia, along with healthy individuals. Participants perform various vocal tasks during a single recording session. Voice signals are analysed and used as input for machine learning classification algorithms. The significance of this study is that oropharyngeal dysphagia, a condition involving swallowing difficulties in the transit of food or liquids from the mouth to the esophagus, generates malnutrition, dehydration, and pneumonia, significantly contributing to management costs and hospitalization durations. Currently, there is a lack of rapid and effective dysphagia screening methods for healthcare personnel, with only expensive invasive tests and clinical scales in use.

Key facts

Study ID
NCT06219200
Run by
Istituti Clinici Scientifici Maugeri SpA
People needed
400
Starts
2023-10-11
Expected to finish
2025-12-01
Last updated by the study team
2025-02-20

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

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