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Artificial Intelligence in Diagnosing Dysphagia Patients

NCT05098808 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 449

Last updated 2021-10-28

No results posted yet for this study

Summary

In this prospective study we extracted acoustic parameters using PRAAT from patient's attempt to phonate during the clinical evaluation using a digital smart device. From these parameters we attempted (1) to define which of the PRAAT acoustic features best help to discriminate patients with dysphagia (2) to develop algorithms using sophisticated ML techniques that best classify those i) with dysphagia and those ii ) at high risk of respiratory complications due to poor cough force.

Conditions

  • Respiration Disorders
  • Swallowing Disorder
  • Phonation Disorder
  • Stroke
  • Aspiration Pneumonia
  • Aspiration; Liquids

Interventions

OTHER

Acoustic features (from signals obtained during phonation)

Acoustic features will be obtained via phonation files. A voice recorder application provided by Apple was used, and the sampling frequency of the sound was 44,100 Hz. The digitized cough sound signals were band-pass-filtered between 20 to 16,000 Hz to use data from the whole frequency band gathered by the iPad. In each case, the smart device was positioned 20cm from the patient

Sponsors & Collaborators

  • The Catholic University of Korea

    lead OTHER

Principal Investigators

  • Sun Im, MD PhD · The Catholic University of Korea

Eligibility

Min Age
19 Years
Max Age
90 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2019-09-01
Primary Completion
2021-09-01
Completion
2021-10-01

Countries

  • South Korea

Study Locations

More Related Trials

Entities

Diseases

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 NCT05098808 on ClinicalTrials.gov