Voice Analysis in Patients With Neurologic Diseases

NCT ID: NCT04846413

Last Updated: 2023-03-22

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Total Enrollment

100 participants

Study Classification

OBSERVATIONAL

Study Start Date

2021-09-01

Study Completion Date

2023-07-31

Brief Summary

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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

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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

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Voice Disorders Neurologic Disorder

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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Patients

Patients affected by neurologic disorders showing a prominent voice impairment.

Speech task

Intervention Type OTHER

Speech task which consists of a sustained emission of the vowel /e/.

Interventions

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Speech task

Speech task which consists of a sustained emission of the vowel /e/.

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* Clinical diagnosis of neurologic disorders

Exclusion Criteria

* smoking
* bilateral/unilateral hearing loss
* respiratory disorders
* conditions affecting the vocal cords, including nodules.
Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Neuromed IRCCS

OTHER

Sponsor Role lead

Responsible Party

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Antonio Suppa

Principal Investigator

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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Antonio Suppa

Pozzilli, , Italy

Site Status RECRUITING

Countries

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Italy

Central Contacts

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Antonio Suppa, MD, PhD

Role: CONTACT

3494940365 ext. +0039

Facility Contacts

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Antonio Suppa

Role: primary

+00393494940365

Other Identifiers

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DIPNEUROSCI_01

Identifier Type: -

Identifier Source: org_study_id

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