Clinical Trials Logo

Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT04848623
Other study ID # CoLive Voice
Secondary ID
Status Recruiting
Phase
First received
Last updated
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
Health authority
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

Study Design


Related Conditions & MeSH terms


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
See also
  Status Clinical Trial Phase
Completed NCT03153644 - Improving Contraceptive Care for Women With Medical Conditions
Recruiting NCT06058754 - Group-based [ADAPT] Versus One-to-one [Usual] Occupational Therapy (Go:OT Trial) N/A
Completed NCT04082585 - Total Health Improvement Program Research Project
Recruiting NCT05558085 - Biomarker Cost-Benefit Analysis of EFNEP N/A
Completed NCT04037436 - Functional Exercise and Nutrition Education Program for Older Adults N/A
Not yet recruiting NCT05622422 - A Chronic Disease Self Care Management Pilot Study N/A
Not yet recruiting NCT06016101 - Usefulness of the Medissimo Nurse Application for Supporting Medication Compliance in Elderly People With Chronic Polypathologies
Not yet recruiting NCT04954209 - Comparative Study in Long-term Commitment to Physical Activity After Two Different Resumption Programs
Not yet recruiting NCT04090593 - Chronic Disease Mobile Educational Experience N/A
Not yet recruiting NCT03628963 - Optimizing Patient Usability Experience for Chronic Care N/A
Completed NCT02390570 - Incorporating Patient Capacity Into the Clinical Landscape N/A
Completed NCT02072941 - Preparing Spanish-speaking Older Adults for Advance Care Planning and Medical Decision Making (PREPARE) N/A
Completed NCT02017262 - Group Self-Management of Depression and Medical Illness N/A
Terminated NCT02115971 - Jumping Exercises Approach in Individuals With Chronic Ankle Instability N/A
Completed NCT01933789 - Improving Communication About Serious Illness N/A
Completed NCT02292940 - Consumer Health IT Tools: Impact on Experience, Access, and Outcomes for Patients With Complex Chronic Conditions
Completed NCT02307929 - Evaluation of Quality of Care - Nurse Allied Health Clinic Programme, HA N/A
Completed NCT01458184 - Study of PhoneCare System to Treat Patients With Chronic Diseases N/A
Completed NCT00380536 - Medical Self-Management for Improving Health Behavior Among Individuals in Community Mental Health Settings N/A
Completed NCT00333710 - Evaluating a Telehealth Treatment for Veterans With Hepatitis C and PTSD N/A