Development of Artificial Intelligence Tools for the Detection of Stress Markers and Consideration of Stress States in the Monitoring of Subjects With Type 1 Diabetes
NCT ID: NCT06985862
Last Updated: 2025-10-01
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
NA
35 participants
INTERVENTIONAL
2025-09-03
2026-02-28
Brief Summary
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We are currently training algorithms using advanced machine learning and artificial intelligence techniques to recognise and quantify stress states using existing databases, including voice and physiological data. These technological advances will make it possible to identify moments of stress more accurately and provide appropriate responses, thereby contributing to better diabetes management.
The SMART-T1D study is an ancillary study of the EVASTRESS study.
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Detailed Description
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Conditions
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Study Design
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NA
SINGLE_GROUP
PREVENTION
NONE
Study Groups
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Voice recording 4 days a day
* Morning (first recording): Text reading (article 25.1 of the Declaration of Human Rights).
* Noon (second recording): Counting from 1 to 20 at normal speed
* Evening (third recording): Prolonged phonation of the vowel 'a' without catching your breath.
* Bedtime (fourth recording): Free expression describing stressful moments of the day and their impact on diabetes management, for at least 30 seconds.
Voice recording 4 times a day
* Morning (first recording): Text reading (article 25.1 of the Declaration of Human Rights).
* Noon (second recording): Counting from 1 to 20 at normal speed
* Evening (third recording): Prolonged phonation of the vowel 'a' without catching your breath.
* Bedtime (fourth recording): Free expression describing stressful moments of the day and their impact on diabetes management, for at least 30 seconds.
Interventions
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Voice recording 4 times a day
* Morning (first recording): Text reading (article 25.1 of the Declaration of Human Rights).
* Noon (second recording): Counting from 1 to 20 at normal speed
* Evening (third recording): Prolonged phonation of the vowel 'a' without catching your breath.
* Bedtime (fourth recording): Free expression describing stressful moments of the day and their impact on diabetes management, for at least 30 seconds.
Eligibility Criteria
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Inclusion Criteria
* Patient able to speak and read French
Exclusion Criteria
* Patient with severe speech problems that may prevent voice recordings from being made.
18 Years
ALL
No
Sponsors
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Centre d'Etudes et de Recherche pour l'Intensification du Traitement du Diabète
OTHER
Responsible Party
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Principal Investigators
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Pierre-Yves Benhamou, Pr
Role: PRINCIPAL_INVESTIGATOR
University Hospital, Grenoble
Locations
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CERITD (Centre d'Etudes et de Recherches pour l'Intensification du Traitement du Diabète)
Évry, , France
Grenoble University Hospital
Grenoble, , France
Countries
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Central Contacts
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Facility Contacts
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Other Identifiers
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2024-A02431-46
Identifier Type: -
Identifier Source: org_study_id
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