Artificial Intelligence in Diagnosing Dysphagia Patients

Stroke Clinical Trial

Official title:

Classification of Dysphagia Patients at Risk of Aspiration Pneumonia Using Machine Learning Algorithms Incorporating Acoustic Features From Phonetic Evaluation

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT05098808
• Other study ID #: HC19EESE0060
• Status: Completed
• Start date: September 1, 2019
• Est. completion date: October 1, 2021

Study information

• Verified date: October 2021
• Source: The Catholic University of Korea
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational [Patient Registry]

Clinical Trial 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.

Description:

This study was prospective study, and patients who visited the department of rehabilitation medicine in a single university-affiliated tertiary hospital with dysphagic symptoms from September 2019 to March 2021 were included.Voice recording was performed at the enrollment with blinded assessment, where the participants first visited the rehabilitation department with chief complaints of dysphagia. The cough sounds were recorded with an iPad (Apple, Cupertino, CA, USA) through an embedded microphone.

From the acoustic files we extracted fourteen voice parameters that include the average value and standard deviation of the fundamental frequency (f0), harmonic-to-noise ratio (HNR), the jitter that refers to frequency instability, and the shimmer that represents the amplitude instability of the sound signal.

Machine learning algorithms and sophisticated deep neural network analysis will be performed.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 449
• Est. completion date: October 1, 2021
• Est. primary completion date: September 1, 2021
• Gender: All
• Age group: 19 Years to 90 Years

Eligibility

Inclusion Criteria:

• Inclusion criteria

1. Suspected swallowing disorder who were referred for swallowing assessment

2. Dysphagia attributable to brain lesion including stroke

Exclusion Criteria:

1. Participants who were unable to perform phonation

2. Participants who had no VFSS or standardized swallowing assessment results

3. Participants with no spirometric measurements

Related Conditions & MeSH terms

• Aspiration Pneumonia
• Aspiration; Liquids
• Deglutition Disorders
• Disease
• Dysphonia
• Phonation Disorder
• Pneumonia
• Pneumonia, Aspiration
• Respiration Disorders
• Stroke
• Swallowing Disorder
• Voice Disorders

Intervention

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

Locations

Country	Name	City	State
Korea, Republic of	Department of Rehabilitation Medicine Bucheon St Mary's Hospital, Catholic University of Korea, College of Medicine	Bucheon	Kyounggido

Sponsors (1)

Lead Sponsor	Collaborator
The Catholic University of Korea

Country where clinical trial is conducted

Korea, Republic of, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Functional Oral Intake Scale	Dysphagia severity as measured by the the Functional Oral Intake Scale obtained from standardized swallowing tests	during the intervention
Primary	Cough strength	Spirometry values : cough strength as measured by the spirometric values during voluntary cough	during the intervention