Voice DisordersNCT04846413
Voice Analysis in Patients With Neurologic Diseases
An observational study of Voice Disorders and Neurologic Disorder, run by Neuromed IRCCS at 1 site in Italy.
Trial summary
In this observational pilot study, the investigators will record and assess voice samples from healthy participants and those participants affected by neurologic diseases to evaluate possible differences in voice features. Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- Voice Disorders, Neurologic Disorder
- What is being tested?
- Speech task
- How many people
- 100 participants
- Where
- 1 siteItaly
- Study dates
- 1 Sep 2021to 31 Jul 2023
- Phase
- Observational
- Are there results?
- None posted in the registry
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 Any age
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Study population: We will recruit neurologic patients not taking any oral medications or alcohol and any drugs acting on the central nervous system at the time of the study.
Who may be able to join
- Clinical diagnosis of neurologic disorders
Who cannot join
- smoking
- bilateral/unilateral hearing loss
- respiratory disorders
- conditions affecting the vocal cords, including nodules.
Trial locations and contacts
1 site in 1 country.
Italy1 site, 1 recruiting
- Recruiting
Antonio Suppa
Pozzilli, 86077
Antonio Suppa, +00393494940365, antonio.suppa@uniroma1.it
About this study
Official title: Advanced Voice Analysis With Machine Learning Algorithms in Patients With Neurologic Diseases
In this observational pilot study, the investigators will record and assess voice samples from healthy participants and those participants affected by neurologic diseases to evaluate possible differences in voice features.
Read the detailed description
In this study, the investigators will evaluate the clinical features of healthy participants and those participants with neurologic disorders by applying dedicated clinical scales. Also, the investigators will assess voice impairment by using perceptual examination tools. Then, the investigators will apply spectral analysis to assess the main frequency components of voice in healthy participants and in patients affected by neurologic disorders with a prominent voice impairment. To distinguish between healthy participants and patients affected by various neurologic diseases, the investigators will apply a voice analysis based on support vector machine (SVM) classifier that included a large number of features in addition to the main frequency components of voice.
For these purposes, the investigators will assess in detail the sensitivity, specificity, positive predictive value, and negative predictive value and accuracy of all diagnostic tests. Furthermore, the investigators will calculate the area under the receiver operating characteristic (ROC) curves to verify the optimal diagnostic threshold as reflected by the associated criterion (Ass. Crit.) and Youden Index (YI). To assess possible clinical-instrumental correlations, the investigators will also use a modified algorithm of SVM analysis to calculate a continuous numerical value (the likelihood ratio [LR]) providing a measure of voice impairment severity for each participant.
Voice recordings will be performed by asking participants to produce a specific speech task with their usual voice intensity, pitch, and quality. The speech task will consist of a sustained emission of a close mid-front unrounded vowel /e/ for at least 5 seconds. Voice recordings will be collected by using a high-definition audio-recorder placed at a distance of 5 cm from the mouth. Voice samples will be recorded in linear PCM format (.wav) at a sampling rate of 44.1 kHz, with 24-bit sample size. Voice analysis will consist of three separate processes: feature extraction, selection and classification. For feature extraction, the investigators will use the OpenSMILE (audEERING GmbH, Germany), dedicated software. Then, the investigators will select and classify voice feature by using SVM algorithm included in Weka.
- Conditions
- Voice Disorders, Neurologic Disorder
- Being tested
- Speech task
- Keywords
- voice analysis, machine learning, neurologic disorders
- Medical subject headings
- Voice Disorders, Nervous System Diseases
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Speech taskOther
Speech task which consists of a sustained emission of the vowel /e/.
| Study group | Role | What they receive |
|---|---|---|
| Patients | Patients affected by neurologic disorders showing a prominent voice impairment. Receives: Other: Speech task |
What is being measured
The primary outcome is the main question the study is designed to answer.
Voice analysis
Voice features obtained by using Support Vector Machine algorithm
Measured: Voice analysis with machine learning algorithms will be implemented immediately after voice recording, during the clinical evaluation of each participant.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted15 Apr 2021
- Study start1 Sep 2021
- Primary completion31 Jul 2022
- Study completion31 Jul 2023 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Voice DisordersStudies of the same condition, open and under way.
- 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
- Cohort
- Time perspective
- Prospective
- Enrolment
- 100 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Neuromed IRCCS
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Antonio Suppa, Neuromed IRCCS
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04846413
- Sponsor's protocol ID
- DIPNEUROSCI_01
- Status last verified
- Mar 2023
- First submitted
- 12 Apr 2021
- Last updated
- 22 Mar 2023
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 22 Mar 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Advanced Voice Analysis With Machine Learning Algorithms in Patients With Neurologic Diseases
- ClinicalTrials.gov ID
- NCT04846413
- Acronym / sponsor ID
- DIPNEUROSCI_01
- Conditions
- Voice Disorders, Neurologic Disorder
- Keywords
- voice analysis, machine learning, neurologic disorders
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 100 participants (estimated)
- Lead sponsor
- Neuromed IRCCSUniversity, hospital or other
- Study start
- 1 Sep 2021 (actual)
- Primary completion
- 31 Jul 2022 (actual)
- Study completion
- 31 Jul 2023 (estimated)
- First posted
- 15 Apr 2021 (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.
In this observational pilot study, the investigators will record and assess voice samples from healthy participants and those participants affected by neurologic diseases to evaluate possible differences in voice features.
Detailed description
In this study, the investigators will evaluate the clinical features of healthy participants and those participants with neurologic disorders by applying dedicated clinical scales. Also, the investigators will assess voice impairment by using perceptual examination tools. Then, the investigators will apply spectral analysis to assess the main frequency components of voice in healthy participants and in patients affected by neurologic disorders with a prominent voice impairment. To distinguish between healthy participants and patients affected by various neurologic diseases, the investigators will apply a voice analysis based on support vector machine (SVM) classifier that included a large number of features in addition to the main frequency components of voice.
For these purposes, the investigators will assess in detail the sensitivity, specificity, positive predictive value, and negative predictive value and accuracy of all diagnostic tests. Furthermore, the investigators will calculate the area under the receiver operating characteristic (ROC) curves to verify the optimal diagnostic threshold as reflected by the associated criterion (Ass. Crit.) and Youden Index (YI). To assess possible clinical-instrumental correlations, the investigators will also use a modified algorithm of SVM analysis to calculate a continuous numerical value (the likelihood ratio [LR]) providing a measure of voice impairment severity for each participant.
Voice recordings will be performed by asking participants to produce a specific speech task with their usual voice intensity, pitch, and quality. The speech task will consist of a sustained emission of a close mid-front unrounded vowel /e/ for at least 5 seconds. Voice recordings will be collected by using a high-definition audio-recorder placed at a distance of 5 cm from the mouth. Voice samples will be recorded in linear PCM format (.wav) at a sampling rate of 44.1 kHz, with 24-bit sample size. Voice analysis will consist of three separate processes: feature extraction, selection and classification. For feature extraction, the investigators will use the OpenSMILE (audEERING GmbH, Germany), dedicated software. Then, the investigators will select and classify voice feature by using SVM algorithm included in Weka.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Patients | – | Other: Speech taskPatients affected by neurologic disorders showing a prominent voice impairment. |
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
- Study population
- We will recruit neurologic patients not taking any oral medications or alcohol and any drugs acting on the central nervous system at the time of the study.
Key inclusion criteria (1 listed)
- Clinical diagnosis of neurologic disorders
Key exclusion criteria (4 listed)
- smoking
- bilateral/unilateral hearing loss
- respiratory disorders
- conditions affecting the vocal cords, including nodules.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Speech taskSpeech task which consists of a sustained emission of the vowel /e/. | Other | Patients |
Primary outcome
Voice analysis
Time frame: Voice analysis with machine learning algorithms will be implemented immediately after voice recording, during the clinical evaluation of each participant.
Voice features obtained by using Support Vector Machine algorithm
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 22 Mar 2023.
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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. This study is not recruiting at the moment.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Voice Disorders and Neurologic Disorder, run by Neuromed IRCCS at 1 site 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 1 inclusion and 4 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: status not confirmed, as of the sponsor's last update on 22 Mar 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site 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?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Antonio Suppa, MD, PhD (3494940365 ext. +0039, antonio.suppa@uniroma1.it), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Voice analysis (time frame: Voice analysis with machine learning algorithms will be implemented immediately after voice recording, during the clinical evaluation of each participant.). 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 22 Mar 2023.