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

Study Overview
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Brief Summary
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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.

Detailed Description
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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: read a 30 sec prespecified text (from the Human Rights Declaration), sustain voicing the vowel /aaaaaa/ as long and as steady as they can at a comfortable loudness cough 3 times breath in and out deeply 3 times 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.

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

Conditions
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Chronic Disease

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Adolescents and adults > 15 years With or without health conditions From all countries Exclusion Criteria: Children < 15 years

Ages Eligible for Study
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Minimum Age: 15 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Stress | Patient reported outcome | At baseline | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| 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 | 
| Hypertension | Patient reported outcome | At baseline | 
| Diabetes | Patient reported outcome | At baseline | 
| Migraine | Patient reported outcome | At baseline | 
| Covid-19 | Patient reported outcome | At baseline | 
| Overall pain | Patient reported outcome | At baseline | 
| Respiratory problems | Patient reported outcome | At baseline | 
| Level of quality of life | Patient reported outcome | At baseline | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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vocal biomarker, digital biomarker, digital health, artificial intelligence, telemonitoring, medical devices, precision health digital biomarker