Neonatal Neurological Observation With Video AI

Part of paid clinical trials in New York, New York.

Sponsor
Artemis AI Labs
Study ID
NCT07628829
Status
Recruiting
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Conditions

  • Hypoxic-Ischemic Encephalopathy
  • Neonatal Encephalopathy
  • Sedation
  • Sleep

Eligibility Criteria

Sex
ALL
Age
N/A - N/A
Healthy Volunteers
Accepted

Interventions

  • Continuous bedside video monitoring with AI anatomic landmark tracking for neurologic monitoring — DEVICE
    A non-contact, passive bedside video recording system is mounted adjacent to the infant's crib or incubator. The device continuously captures video data from enrollment to hospital discharge or withdrawal. The device runs AI models to track infant anatomic landmarks and calculate a continuous movement index. The trial runs in "silent mode," where AI outputs are not shown to the patient's clinical team and do not influence care.

Study Details

NeoNOVA is a multi-site, prospective, single-arm, silent observational study to determine: among (Population) infants admitted to newborn services during their inpatient hospital stay, whether (Intervention) continuous bedside non-contact high definition video running real-time AI analysis of anatomic landmarks and movement, (Comparison) compared against human-labeled video frames and standardized clinical exams, will (Outcome) accurately localize infant anatomic landmarks (primary objective; outcome median position error in pixels) and demonstrate a statistically significant association between a video-derived movement index and clinical measures of patient neurological exams (secondary objective; outcomes N-PASS and modified Sarnat exams).

Key Dates

First listed
Jun 5, 2026
Start date
Jul 13, 2026
Status verified
Jul 2026
Primary completion
Jul 12, 2027
Completion
Jul 12, 2029

Study Design

Enrollment
200 participants (estimated)

Arms

  • Arm: NICU-Admitted Infants Undergoing Continuous Video Monitoring
    Infants admitted to newborn services, including the neonatal intensive care unit (NICU), who meet eligibility criteria and undergo continuous, non-contact bedside video monitoring from enrollment until hospital discharge.

Primary Outcome Measure

AI Anatomic Landmark Tracking Accuracy [ Time Frame: At study completion, an average of 1 week. ]

Central Contacts

Locations (2)

FacilityCityStateZIPSite coordinators
Mount Sinai HospitalNew YorkNew York10029
Klaren Ng
[email protected]
347-525-8336
Rachelle Weisman, MPH
[email protected]
Benjamin Glicksberg, PhD (PRINCIPAL_INVESTIGATOR)
Weill Cornell Medicine / NewYork-Presbyterian HospitalNew YorkNew York10065
Martha Liu
[email protected]
646-697-6428
Sushma Krishna, MD (PRINCIPAL_INVESTIGATOR)

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By research site
Mount Sinai Hospital· New York, NYWeill Cornell Medicine / NewYork-Presbyterian Hospital· New York, NY

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