Establishment of Voice Analysis Cohort for Development of Monitoring Technology for Dysphagia
- Conditions
- Deglutition Disorders
- Interventions
- Diagnostic Test: Voice recording before and after dietary intake
- Registration Number
- NCT05149976
- Lead Sponsor
- Seoul National University Hospital
- Brief Summary
Collection of basic data to develop a technique for monitoring the state of dysphagia using voice analysis.
- Detailed 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 & Eligibility
- Status
- RECRUITING
- Sex
- All
- Target Recruitment
- 300
- 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)
- Patients who cannot speak.
- Patients who cannot speak according to the researcher's instructions.
- Patients whose VFSS test was reexamined
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Arm && Interventions
Group Intervention Description Residue Group Voice recording before and after dietary intake - As a result of VFSS (video fluoroscopic swallowing study), the subjects who have residues left around the pharynx or airway Normal group Voice recording before and after dietary intake * A person judged normal among VFSS (video fluoroscopic swallowing study) examiners * Normal subjects without symptoms of dysphagia Aspiration Group Voice recording before and after dietary intake - VFSS (video fluoroscopic swallowing study) test result, the subjects who have aspiration in the airway
- Primary Outcome Measures
Name Time Method Accuracy of machine learning prediction model using voice change before and after dietary intake day 1 Accuracy measures how well machine learning predicts three groups ('Normal', 'Residue', 'Aspiration') according to voice changes before and after dietary intake.
- Secondary Outcome Measures
Name Time Method AUC (Area Under the ROC curve) of machine learning prediction model using voice change before and after dietary intake. day 1 AUC measures how well machine learning predicts three groups ('Normal', 'Residue', 'Aspiration') according to voice changes before and after dietary intake.
mAP (mean Average Precision) of machine learning prediction model using voice change before and after dietary intake day 1 mAP measures how well machine learning predicts three groups ('Normal', 'Residue', 'Aspiration') according to voice changes before and after dietary intake.
Recall of machine learning prediction model using voice change before and after dietary intake. day 1 Recall measures how well machine learning predicts three groups ('Normal', 'Residue', 'Aspiration') according to voice changes before and after dietary intake.
Accuracy of machine learning prediction model using only voice after dietary intake. day 1 Accuracy measures how well machine learning predicts three groups ('Normal', 'Residue', 'Aspiration') according to voice only voice after dietary intake.
mAP (mean Average Precision) of machine learning prediction model using only voice after dietary intake. day 1 mAP measures how well machine learning predicts three groups ('Normal', 'Residue', 'Aspiration') according to voice only voice after dietary intake.
AUC (Area Under the ROC curve) of machine learning prediction model using only voice after dietary intake. day 1 AUC measures how well machine learning predicts three groups ('Normal', 'Residue', 'Aspiration') according to voice only voice after dietary intake.
Recall of machine learning prediction model using only voice after dietary intake. day 1 Recall measures how well machine learning predicts three groups ('Normal', 'Residue', 'Aspiration') according to voice only voice after dietary intake.
Trial Locations
- Locations (1)
Department of Rehabilitation Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine
🇰🇷Seongnam-si, Gyeonggi-do, Korea, Republic of