Deglutition DisordersVOICEDNCT06219200
Automatic Voice Analysis for Dysphagia Screening in Neurological Patients
An observational study of Deglutition Disorders and Neurological Disorder, run by Istituti Clinici Scientifici Maugeri SpA at 2 sites in Italy.
Trial 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… Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Deglutition Disorders, Neurological Disorder
- How many people
- 400 participants
- Where
- 2 sitesItaly
- Study dates
- 11 Oct 2023to Dec 2025
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: The study population included a group of patients with Parkinson's disease, a group of post-stroke patients, a group of patients with amyotrophic lateral sclerosis, and a group of healthy individuals
Who may be able to join
- Patients with a diagnosis of stroke, Parkinson's disease, or amyotrophic lateral sclerosis, or healthy individuals.
- Age higher than 18 years old.
Who cannot join
- 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.
Trial locations and contacts
2 sites in 1 country. Contact the study team or a site near you to ask about taking part.
Italy2 sites, 2 recruiting
- Recruiting
Istituti Clinici Scientifici Maugeri
Lissone, Lombardy
Beatrice De Maria
- Recruiting
Istituti Clinici Scientifici Maugeri
Milan, Lombardy
Beatrice De Maria, PhD
About this study
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.
Read the detailed description
Background:
Oropharyngeal dysphagia, defined as any alterations in swallowing abilities during the transit of food or liquids from the oral cavity to the esophagus, is an insidious complication of many neurological diseases. This condition can seriously lead to severe complications such as malnutrition, dehydration, and pneumonia, which overall has a huge impact on management costs and the number of hospitalization days. In this context, it is essential to immediately recognize the risk factors and the first signs of dysphagia to take prompt adequate actions and request further clinical and instrumental evaluations. Rapid, quantitative, and effective dysphagia screening methods are not currently available to support healthcare personnel. To date, only clinical rating scales or expensive invasive tests that require specialized personnel are adopted in clinical scenarios, whereas no objective tools are still available in extra-hospital contexts to alert patients of risk situations.
Current Gaps in Knowledge and Aim:
Since oropharyngeal dysphagia is caused by an impaired coordination control of the swallowing muscles and these muscles play also an important role in the phonation process, investigating voice alterations could be a screening option to recognize dysphagia in patients with neurological diseases. In the current literature, automatic voice analysis and the use of machine learning algorithms have given relevant findings in the discrimination between neurological diseases and healthy subjects, and there are also interesting preliminary data on dysphagia. The goal of this study is to the development a machine learning classification algorithm for dysphagia screening in neurological patients using automatic voice analysis.
Study Involvement:
The study involves patients with neurological diseases (Parkinson's disease, stroke, amyotrophic lateral Sclerosis) with or without dysphagia and healthy individuals. The participants are asked to perform some vocal tasks (sustained vocal phonation, diadochokinetic tasks, production of standardized sentences, free speech) in a single experimental session at the enrolment. Voice recordings will be automatically proceeded to derive acoustic voice features, used as input for the machine learning classification algorithm. The evaluation of the participants to characterize the studied sample is carried out with the collection of anamnestic and clinical data.
- Conditions
- Deglutition Disorders, Neurological Disorder
- Medical subject headings
- Deglutition Disorders, Nervous System Diseases
What is being measured
The primary outcome is the main question the study is designed to answer.
A classification algorithm to screen swallowing disorders in neurological patients
Development of a classification algorithm for dysphagia screening in neurological patients using voice analysis
Measured: Baseline
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted23 Jan 2024
- Study start11 Oct 2023
- Primary completionDec 2025 (estimated)
- Study completionDec 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Deglutition DisordersStudies of the same condition, open and under way.
- More trials run by Istituti Clinici Scientifici Maugeri SpAThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case only
- Time perspective
- Prospective
- Enrolment
- 400 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Istituti Clinici Scientifici Maugeri SpA
- Sponsor type
- University, hospital or other
- Collaborators
- Politecnico di Milano
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06219200
- Sponsor's protocol ID
- CE2708
- Acronym
- VOICED
- Status last verified
- Feb 2025
- First submitted
- 12 Jan 2024
- Last updated
- 20 Feb 2025
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 20 Feb 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Automatic Voice Analysis for Dysphagia Screening in Neurological Patients
- ClinicalTrials.gov ID
- NCT06219200
- Acronym / sponsor ID
- VOICED / CE2708
- Conditions
- Deglutition Disorders, Neurological Disorder
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 400 participants (estimated)
- Lead sponsor
- Istituti Clinici Scientifici Maugeri SpAUniversity, hospital or other
- Collaborators
- Politecnico di Milano
- Study start
- 11 Oct 2023 (actual)
- Primary completion
- Dec 2025 (estimated)
- Study completion
- Dec 2025 (estimated)
- First posted
- 23 Jan 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
Background:
Oropharyngeal dysphagia, defined as any alterations in swallowing abilities during the transit of food or liquids from the oral cavity to the esophagus, is an insidious complication of many neurological diseases. This condition can seriously lead to severe complications such as malnutrition, dehydration, and pneumonia, which overall has a huge impact on management costs and the number of hospitalization days. In this context, it is essential to immediately recognize the risk factors and the first signs of dysphagia to take prompt adequate actions and request further clinical and instrumental evaluations. Rapid, quantitative, and effective dysphagia screening methods are not currently available to support healthcare personnel. To date, only clinical rating scales or expensive invasive tests that require specialized personnel are adopted in clinical scenarios, whereas no objective tools are still available in extra-hospital contexts to alert patients of risk situations.
Current Gaps in Knowledge and Aim:
Since oropharyngeal dysphagia is caused by an impaired coordination control of the swallowing muscles and these muscles play also an important role in the phonation process, investigating voice alterations could be a screening option to recognize dysphagia in patients with neurological diseases. In the current literature, automatic voice analysis and the use of machine learning algorithms have given relevant findings in the discrimination between neurological diseases and healthy subjects, and there are also interesting preliminary data on dysphagia. The goal of this study is to the development a machine learning classification algorithm for dysphagia screening in neurological patients using automatic voice analysis.
Study Involvement:
The study involves patients with neurological diseases (Parkinson's disease, stroke, amyotrophic lateral Sclerosis) with or without dysphagia and healthy individuals. The participants are asked to perform some vocal tasks (sustained vocal phonation, diadochokinetic tasks, production of standardized sentences, free speech) in a single experimental session at the enrolment. Voice recordings will be automatically proceeded to derive acoustic voice features, used as input for the machine learning classification algorithm. The evaluation of the participants to characterize the studied sample is carried out with the collection of anamnestic and clinical data.
Study design
- Observational model
- Case only
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- The study population included a group of patients with Parkinson's disease, a group of post-stroke patients, a group of patients with amyotrophic lateral sclerosis, and a group of healthy individuals
Key inclusion criteria (2 listed)
- Patients with a diagnosis of stroke, Parkinson's disease, or amyotrophic lateral sclerosis, or healthy individuals.
- Age higher than 18 years old.
Key exclusion criteria (2 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
A classification algorithm to screen swallowing disorders in neurological patients
Time frame: Baseline
Development of a classification algorithm for dysphagia screening in neurological patients using voice analysis
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 20 Feb 2025.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Deglutition Disorders and Neurological Disorder, run by Istituti Clinici Scientifici Maugeri SpA at 2 sites in Italy.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 20 Feb 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in Italy. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Beatrice De Maria, PhD (0250725 ext. +39, beatrice.demaria@icsmaugeri.it), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
A classification algorithm to screen swallowing disorders in neurological patients (time frame: Baseline). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 20 Feb 2025.