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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

NCT06985862 · Status: SUSPENDED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 35

Last updated 2026-05-08

No results posted yet for this study

Summary

Stress refers to all the reactions of an organism subjected to exogenous or endogenous stress. In the context of diabetes, stress plays a critical role. There are two forms of stress: acute and chronic, both of which can have a significant impact on patients' glycaemic control. Acute stress, if repeated, can cause rapid increases in blood glucose levels, while chronic stress can lead to insulin resistance. It is therefore essential to develop tools for recognising and quantifying stress states specific to patients with diabetes. These tools would provide a better understanding of the role of stress in diabetes management, paving the way for more targeted therapeutic interventions and improving patients' quality of life.

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.

Conditions

  • Diabetes Type 1

Interventions

OTHER

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.

Sponsors & Collaborators

  • Centre d'Etudes et de Recherche pour l'Intensification du Traitement du Diabète

    lead OTHER

Principal Investigators

  • Pierre-Yves Benhamou, Pr · University Hospital, Grenoble

Study Design

Allocation
NA
Purpose
PREVENTION
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-09-03
Primary Completion
2026-12-31
Completion
2026-12-31

Countries

  • France

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06985862 on ClinicalTrials.gov