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Development of Voice Biomarkers of Frequent COVID-19 and Long Covid-related Symptoms Based on Data From Users of the Long COVID Companion App

Unravelling Health and Frequent Symptoms and Voice Characteristics Evolution Over Time of Users of the Long COVID Companion Application to Develop Voice Biomarkers of Frequent Long Covid-related Symptoms

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT07156994
Acronym
EVO-LC
Enrollment
300
Registered
2025-09-05
Start date
2025-12-15
Completion date
2028-09-30
Last updated
2026-09-15

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Long COVID

Keywords

Long COVID, Vocal biomarkers, symptoms

Brief summary

The LIH DDP research team focuses its research topics on vocal biomarkers and Long COVID, among others. Voice is indeed a promising tool to monitor health, as it contains many information on our health and is easy to collect. The development of vocal biomarkers of Long COVID-related symptoms could improve the remote monitoring of the health status of people affected by this disease. The LIH developed the Long COVID Companion (LCC) app in collaboration with the ApresJ20 Long COVID patient association in France to support patients in their daily lives. LCC app users will be invited to participate in this study to collect voice recordings at the same time as health-related data. The objectives of this study are: Primary objective: To develop vocal biomarker candidates for the main Long COVID symptoms (fatigue, brain fog, respiratory problems, sleep issues, stress, anxiety,..) in a population of people with Long COVID. Secondary objectives: * to assess the intra-individual longitudinal evolution of voice characteristics of people with LC * to assess app usability and acceptability in the long-term.

Detailed description

Five years after the start of the COVID-19 pandemic, it has been estimated that a mean of 10-20% of COVID-19 patients will develop Long COVID, which represents at least 65 million people worldwide. In Luxembourg, based on the current status of the COVID-19 pandemic and the prevalence of Long COVID in other countries, we estimate that approximately 25,000 individuals may have been affected by Long COVID. People with Long COVID (PWLC) present complaints such as tachycardia, extreme fatigue, dyspnea, and inability to perform daily physical tasks. More than 200 symptoms have been associated with Long COVID, and multiple organs are affected. Our previous work showed that 59% of COVID-19-infected people from the PrediCOVID cohort study reported 1 or more persisting symptom(s) after one year. The number of persisting symptoms increased with the initial disease severity, and the quality of life of those participants was notably impacted by sleep disorders (54%) and compromised respiratory function (12.9%). Nonetheless, individuals with an initially asymptomatic or mild form of COVID-19 infection could also be affected. Long COVID care, as for other chronic diseases, should align with the concept of minimally disruptive medicine, aiming for a reduced burden on patients' lives while maximizing health outcomes. PWLC frequently have several healthcare professionals in charge of different aspects of their care, with many appointments and travels to manage. They are also regularly asked to complete long standardized questionnaires or scales to evaluate their symptoms, which generates an avoidable burden on their lives if care is not coordinated. The development of innovative methods to integrate multiple Patient Report Outcomes in a portable, versatile way, to reduce travels for medical care, and overall for remote health's monitoring is therefore of the highest importance. Few existing apps that could meet the needs of PWLC already exist, such as "Visible" or "Living With". However, these apps are only available in the US and in the UK, respectively. Furthermore, the "Living with" app is available only by invitation. This limits their availability for PWLC in Europe. Some other apps designed for other chronic conditions, like myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) Pacing app, are also used by some PWLC to manage their daily energy levels. However, these apps do not fully meet the specific needs of PWLC, and are only available in specific countries, in English, and some of them only on the iOS operating system, which restricts their potential use. Voice is a promising candidate increasingly used in mobile health (mHealth) interactions in chronic diseases. Voice is an easy and cheap medium to collect and can be easily integrated into a device like a smartphone, now widely used by people of different ages and education levels. It can be used for vocal biomarker assessment as new clinical endpoints for relevant symptoms. Vocal biomarker candidates have already been identified by the Deep Digital Phenotyping (DDP) research team, based on data from the PrediCOVID cohort study, with performances above 80% to detect fatigue, loss of taste and smell, and symptomatic status in COVID-19-infected people. However, further progress is required before these vocal biomarkers can be used in clinical practice. New vocal biomarkers of global health status or of other symptoms need to be developed to allow a more personalized monitoring of PWLC. The LIH developed the Long COVID Companion app based on the results of UpcomingVoice co-design study and in collaboration with the ApresJ20 Long COVID patient association in France. The app is the result of a participative process involving patients and healthcare professionals in charge of PWLC patients. App users can monitor their health and symptoms on a daily basis or at the frequency they want. App also offers the possibility to complete a daily life and a medical diary, a voice journaling, and to generate PDF reports with graphical visualization of symptom evolution. A new module dedicated to research with standardized voice recordings has been integrated in the app for the users who will take part in the present study The app was released in April 2024 and has more than 1700 users as of the end of March 2025. It is of highest importance to assess the evolution of health of PWLC for a better understanding of the disease. Results will allow the development of personalized monitoring strategies by identifying vocal biomarkers of Long COVID symptoms and of the global health of PWLC. As fatigue is the most frequent and impairing symptom of PWLC it is crucial to better understand the drivers of fatigue and to develop monitoring strategies. The objectives of this study are : Primary objective: To develop vocal biomarker candidates for the main Long COVID symptoms (fatigue, brain fog, respiratory problems, sleep issues, stress, anxiety,..) in a population of people with Long COVID. Secondary objectives: * to assess the intra-individual longitudinal evolution of voice characteristics of people with LC * to assess app usability and acceptability in the long-term.

Interventions

OTHERNo Intervention: Observational Cohort

Participants will be followed digitally using the LCC app. They will complete questionnaires about their health status and do voice recordings on their own rhythm during the entire study duration.

Sponsors

Luxembourg Institute of Health
Lead SponsorOTHER_GOV

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

Inclusion criteria

* Adult (≥18 years old) * Male or female * People with persisting symptoms related to COVID-19 (With Long COVID diagnosis or not) * Adequate understanding of one of the study languages (English, French, German) * Electronically signed informed consent form

Exclusion criteria

● No specific

Design outcomes

Primary

MeasureTime frameDescription
Fatigue levelFrom enrollment until 24 months afterLevel of fatigue will be assessed regularly using a 0-5 likert scale. Participants will complete these questionnaires when they want during the follow-up.
Voice featuresFrom inclusion until 24 months after* Source features (e.g., jitter, shimmer) reflecting the origin of voice production * Formant features (e.g., F1, F2, F3 frequencies, bandwidths) representing resonant frequencies of vocal and nasal tracts * Spectral features (e.g., centroid, MFCCs, flatness) capturing frequency distribution at specific moments * Prosody features (e.g., pitch, intensity, speech rate, pause duration) describing rhythm and intonation

Countries

Luxembourg

Contacts

CONTACTAurélie FISCHER, PhD
aurelie.fischer@lih.lu00 352 26970230

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Sep 16, 2026