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RECRUITING
NCT06219200

Automatic Voice Analysis for Dysphagia Screening in Neurological Patients

Sponsor: Istituti Clinici Scientifici Maugeri SpA

View on ClinicalTrials.gov

Summary

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 Details

Gender

All

Age Range

18 Years - Any

Study Type

OBSERVATIONAL

Enrollment

400

Start Date

2023-10-11

Completion Date

2025-12

Last Updated

2025-02-20

Healthy Volunteers

Yes

Locations (2)

Istituti Clinici Scientifici Maugeri

Lissone, Lombardy, Italy

Istituti Clinici Scientifici Maugeri

Milan, Lombardy, Italy