Identification of Vocal Biomarkers to Monitor the Health of People With a Chronic Disease

Chronic Disease Clinical Trial

— CoLive Voice  

Official title:

Identification of Vocal Biomarkers to Monitor the Health of People With a Chronic Disease

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04848623
• Other study ID #: CoLive Voice
• Status: Recruiting
• Start date: June 26, 2021
• Est. completion date: May 1, 2031

Study information

• Verified date: August 2023
• Source: Luxembourg Institute of Health
• Contact: Aurelie Fischer, MSc
• Phone: 00352621328591
• Email: aurelie.fischer[@]lih.lu
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The CoLive Voice research project aims to identify vocal biomarkers of severe conditions and frequent health symptoms. The project is based on digital technologies and statistical algorithms. This is an international anonymous survey where vocal recordings are collected simultaneously with large validated clinical and epidemiological data, in the context of various chronic diseases or frequent health symptoms in the general population.

Description:

With the objective of using vocal biomarkers for diagnosis, risk prediction/stratification and remote monitoring of various clinical outcomes and symptoms, there is a major need to develop surveys where audio data and clinical, epidemiological and patient-reported outcomes data are collected simultaneously. The objectives of CoLive Voice are: - To launch an international anonymized survey where vocal recordings are associated with large validated clinical and epidemiological data, in the context of various chronic diseases or frequent health symptoms in the general population - To extract audio features and train supervised machine learning models to identify key candidate vocal biomarkers of the aforementioned chronic conditions or related symptoms. Participants will be recruited online and will complete the survey using a web application. They will first answer a detailed questionnaire on their health status and then do 5 different voice records: 1. read a 30 sec prespecified text (from the Human Rights Declaration), 2. sustain voicing the vowel /aaaaaa/ as long and as steady as they can at a comfortable loudness 3. cough 3 times 4. breath in and out deeply 3 times 5. Count from 1 to 20 at a normal speed Vocal records will be pre-processed and converted into features, meaning the most dominating and discriminating characteristics of a vocal signal. Following the selection of features, machine or deep learning algorithms will be trained to automatically predict or classify the clinical, medical or epidemiological outcomes of interest, from vocal features alone or in combination with other health-related data.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 50000
• Est. completion date: May 1, 2031
• Est. primary completion date: May 1, 2026
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 15 Years and older

Eligibility

Inclusion Criteria:

• Adolescents and adults > 15 years
• With or without health conditions
• From all countries

Exclusion Criteria:

• Children < 15 years

Related Conditions & MeSH terms

• Chronic Disease

Locations

Country	Name	City	State
Luxembourg	Luxembourg Institute of Health	Luxembourg

Sponsors (1)

Lead Sponsor	Collaborator
Luxembourg Institute of Health

Country where clinical trial is conducted

Luxembourg, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Stress	Patient reported outcome	At baseline
Secondary	Fatigue	Patient reported outcome using the fatigue severity scale (FSS). Minimum value =1, max value = 7 ; 7 is the highest level of fatigue	At baseline
Secondary	Hypertension	Patient reported outcome	At baseline
Secondary	Diabetes	Patient reported outcome	At baseline
Secondary	Migraine	Patient reported outcome	At baseline
Secondary	Covid-19	Patient reported outcome	At baseline
Secondary	Overall pain	Patient reported outcome	At baseline
Secondary	Respiratory problems	Patient reported outcome	At baseline
Secondary	Level of quality of life	Patient reported outcome	At baseline