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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

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

Status
Suspended
Phases
Unknown
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT06985862
Acronym
SMART-T1D
Enrollment
35
Registered
2025-05-22
Start date
2025-09-03
Completion date
2026-12-01
Last updated
2026-05-08

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

Conditions

Diabetes Type 1

Keywords

stress, voice markers, glycemic control

Brief 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.

Interventions

OTHERVoice 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

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

Study design

Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
PREVENTION
Masking
NONE

Eligibility

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

Inclusion criteria

* Patient who has signed the SMART-T1D free and informed consent form * Patient able to speak and read French

Exclusion criteria

* Mute patient. * Patient with severe speech problems that may prevent voice recordings from being made.

Design outcomes

Primary

MeasureTime frameDescription
Voice recording of participants14 daysDaily voice recordings

Secondary

MeasureTime frameDescription
Diabetes-related distress in the test populationat inclusion and after 14 daysDDS T1 is an indicator of overall diabetes distress (average of 17 items, rated 1 to 6 on a scale). A higher score indicates higher distress.

Countries

France

Contacts

PRINCIPAL_INVESTIGATORPierre-Yves Benhamou, Pr

University Hospital, Grenoble

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: May 9, 2026