Establishment of Voice Analysis Cohort for Development of Monitoring Technology for Dysphagia

Deglutition Disorders Clinical Trial

Official title:

Establishment of Voice Analysis Cohort for Development of Monitoring Technology for Dysphagia

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05149976
• Other study ID #: B-2109-707-303
• Status: Recruiting
• Start date: October 7, 2021
• Est. completion date: December 2024

Study information

• Verified date: April 2024
• Source: Seoul National University Hospital
• Contact: Juseok Ryu, M.D. PhD
• Phone: +82-31-787-7739
• Email: jseok337[@]snu.ac.kr
• Is FDA regulated: No
• Study type: Observational [Patient Registry]

Clinical Trial Summary

Collection of basic data to develop a technique for monitoring the state of dysphagia using voice analysis.

Description:

• Design: Prospective study

• Inclusion criteria of the patient group

• Patients scheduled for VFSS examination and normal person (without dysphagia) capable of recording voice (selected as a control group for comparison of voice indicators with patients with dysphagia)

• Patients who can record voices such as "Ah for 5 seconds", "Ah. Ah. Ah.", "umm~~~"

• Inclusion criteria of the control group: Patients unable to speak, Patients who cannot follow along, If the VFSS test is a retest

• Setting: Hospital rehabilitation department

• Intervention: After obtaining the consent form for the patient scheduled for the VFSS test, "Ah for 5 seconds", after clearing the throat, "Ah for 5 seconds", briefly cut with a high-pitched sound, "Ah. Ah. Ah", close your lips lightly and make a "ummm~~~~" sound, and record 2 times each.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 300
• Est. completion date: December 2024
• Est. primary completion date: December 2024
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: N/A and older

Eligibility

Inclusion Criteria:

• Patients with dysphagia and scheduled for VFSS testing

• Patients who can record voice such as "Ah for 5 seconds", "Ah. ah. ah", or "Um~~"

• Normal people (without dysphagia symptoms) who can record voice (additionally recruited for comparison of voice indicators with patients with dysphagia)

Exclusion Criteria:

• Patients who cannot speak.

• Patients who cannot speak according to the researcher's instructions.

• Patients whose VFSS test was reexamined

Related Conditions & MeSH terms

• Deglutition Disorders

Intervention

Diagnostic Test:
• Voice recording before and after dietary intake
A person who is scheduled to undergo a VFSS test, and his/her voice is recorded before and after eating for the VFSS test For general subjects, only voice recordings were conducted before and after food/water intake without a VFSS test.

Locations

Country	Name	City	State
Korea, Republic of	Department of Rehabilitation Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine	Seongnam-si	Gyeonggi-do

Sponsors (1)

Lead Sponsor	Collaborator
Seoul National University Hospital

Country where clinical trial is conducted

Korea, Republic of, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Accuracy of machine learning prediction model using voice change before and after dietary intake	Accuracy measures how well machine learning predicts three groups ('Normal', 'Residue', 'Aspiration') according to voice changes before and after dietary intake.	day 1
Secondary	mAP (mean Average Precision) of machine learning prediction model using voice change before and after dietary intake	mAP measures how well machine learning predicts three groups ('Normal', 'Residue', 'Aspiration') according to voice changes before and after dietary intake.	day 1
Secondary	Recall of machine learning prediction model using voice change before and after dietary intake.	Recall measures how well machine learning predicts three groups ('Normal', 'Residue', 'Aspiration') according to voice changes before and after dietary intake.	day 1
Secondary	AUC (Area Under the ROC curve) of machine learning prediction model using voice change before and after dietary intake.	AUC measures how well machine learning predicts three groups ('Normal', 'Residue', 'Aspiration') according to voice changes before and after dietary intake.	day 1
Secondary	Accuracy of machine learning prediction model using only voice after dietary intake.	Accuracy measures how well machine learning predicts three groups ('Normal', 'Residue', 'Aspiration') according to voice only voice after dietary intake.	day 1
Secondary	mAP (mean Average Precision) of machine learning prediction model using only voice after dietary intake.	mAP measures how well machine learning predicts three groups ('Normal', 'Residue', 'Aspiration') according to voice only voice after dietary intake.	day 1
Secondary	Recall of machine learning prediction model using only voice after dietary intake.	Recall measures how well machine learning predicts three groups ('Normal', 'Residue', 'Aspiration') according to voice only voice after dietary intake.	day 1
Secondary	AUC (Area Under the ROC curve) of machine learning prediction model using only voice after dietary intake.	AUC measures how well machine learning predicts three groups ('Normal', 'Residue', 'Aspiration') according to voice only voice after dietary intake.	day 1