Automatic Voice Analysis for Dysphagia Screening in Neurological Patients
Recruiting now
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…
- Patients with a diagnosis of stroke, Parkinson's disease, or amyotrophic lateral sclerosis, or healthy individuals.
- Age higher than 18 years old.
You may not qualify if…
- Cognitive impairment that do not allow participants to understand the requested vocal tasks.
- Ear, nose,throat diseases and other disorders able to affect voice quality.
Where it is running
- Istituti Clinici Scientifici Maugeri — Lissone, Lombardy, Italy (enrolling)
- Istituti Clinici Scientifici Maugeri — Milan, Lombardy, Italy (enrolling)
Full record on ClinicalTrials.gov
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