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Multimodal Analysis of Structural Voice Disorders Based on Speech and Stroboscopic Laryngoscope Video

NCT05348031 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 1

Last updated 2022-04-27

No results posted yet for this study

Summary

This study intends to collect clinical data such as strobary laryngoscope images and vowel audio data of patients with structural voice disorders and healthy individuals, and to establish a multimodal voice disorder diagnosis system model by using deep learning algorithms. Multi-classification of diseases that cause voice disorders can be applied to patients with voice disorders but undiagnosed in clinical practice, thereby assisting clinicians in diagnosing diseases and reducing misdiagnosis and missed diagnosis. In addition, some patients with voice disorders can be managed remotely through the audio diagnosis model, and better follow-up and treatment suggestions can be given to them. Remote voice therapy can alleviate the current situation of the shortage of speech therapists in remote areas of our country, and increase the number of patients who need voice therapy. opportunity. Remote voice therapy is more cost-effective, more flexible in time, and more cost-effective.

Conditions

  • Voice Disorders

Sponsors & Collaborators

  • Duke Kunshan University

    collaborator OTHER

  • Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

    lead OTHER

Principal Investigators

  • YueXin Cai · Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Eligibility

Min Age
20 Years
Max Age
80 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2022-05-06
Primary Completion
2025-12-30
Completion
2027-02-20

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05348031 on ClinicalTrials.gov