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Using a New Light-Based Sensor and Artificial Intelligence to Monitor the Baby During Labour and Improve Pregnancy Outcomes

Advancing multimodal fetal monitoring during labour to improve pregnancy outcomes using a novel optical sensor and artificial intelligence - MERIT

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2026/02/104620
Enrollment
181
Registered
2026-02-24
Start date
Unknown
Completion date
Unknown
Last updated
2026-03-02

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

Conditions

Health Condition 1: O09- Supervision of high risk pregnancy

Interventions

Intervention1: Nil: Nil

Sponsors

All India Institute of Medical Sciences
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: 1. Pregnant women with fetal gestation of 36-42 weeks or above with: Normal or low risk pregnancy OR high-risk pregnancy (hypertensive disorders (including preeclampsia (PE) pregnancy induced hypertension and essential hypertension) pre-existing or gestational diabetes mellitus (GDM) and reactive hypoglycemia (a condition with outcomes similar to GDM according to UCLH research) Small for Gestational Age (SGA) Fetal Growth Restriction (FGR) and postdates (40weeks) with suspected or evidence of infection or inflammation) 2. Singleton pregnancy 3. Participants aged 18 years or over

Exclusion criteria

Exclusion criteria: 1. Fetal malformation 2. Fetal genetic and structural abnormalities 3. Participants unable to read and respond to questionnaires in English or Hindi (India)

Design outcomes

Primary

MeasureTime frame
validation of the NIRS sensor in the pregnant females of POG 36-42 weeks.Timepoint: validation of the NIRS sensor in the pregnant females of POG 36-42 weeks during 24 months

Secondary

MeasureTime frame
1. To evaluate whether FetalSense can improve the current clinical understanding of fetal wellbeing and aid timely clinical decision-making to reduce adverse outcomes. 2. To compare the sensitivity and specificity of FetalSense with standard cardiotocography (CTG) in predicting adverse intrapartum outcomes. 3. To collect qualitative feedback from patients and healthcare providers regarding the usability, comfort, and acceptability of FetalSense during labour. 4. To develop and validate a machine learning/artificial intelligence model that integrates FetalSense data with CTG parameters for prediction of neonatal outcomes. 5. To explore the hallmark changes in optical variables during acute fetal compromise. Timepoint: these will be analysed during 24 months.

Countries

India

Contacts

Public ContactDr K Aparna Sharma

All India Institute of Medical Sciences

kaparnasharma@gmail.com09711824415

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Mar 14, 2026