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Neonatal Neurological Observation With Video AI (NeoNOVA)

1. Juni 2026 aktualisiert von: Artemis AI Labs
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).

Studienübersicht

Status

Noch keine Rekrutierung

Bedingungen

Intervention / Behandlung

Detaillierte Beschreibung

Over 1.3 million infants are admitted to Neonatal Intensive Care Units (NICUs) in OECD countries every year. All NICU infants undergo cardiorespiratory monitoring allowing for expedient hemodynamic management. However, there is no analogous clinical decision support for neurologic monitoring, despite neurologic injury having the highest impact on long-term neurodevelopmental outcome. Neonatal encephalopathy (NE) is a leading cause of neurodevelopmental impairment (NDI) and death, occurring in 3 per 1000 live births; inadequate pain control and sedation is a leading risk factor for many complications in the NICU including unplanned extubation (UE), occurring at rates 1-5 UEs per 100 intubation days. Currently, neurologic changes such as NE, pain control, and sedation are primarily assessed by physical examination. However, this approach is deeply flawed since physical examination is performed at set time intervals, is highly subjective, and may not discern subtle or subacute changes.

To fill this critical gap in neonatal care, we developed and validated NeoPose, a low-cost, non-invasive, computer vision digital health tool to continuously monitor infants using real time video streams. NeoPose uses Pose Artificial Intelligence (AI) for an explainable approach to measure, quantify, and analyze infant movement. From the vectorized movement, we can accurately confirm the presence of encephalopathy and quantify the degree of sedation. Our explainable AI platform enables continuous neuromonitoring with AI-driven alerts, suspicious event replay, movement comparisons, and training on a vast dataset of normal and abnormal infant movements far beyond what any provider could witness.

The Neonatal Neurological Observation with Video AI (NeoNOVA) study is a multi-site, prospective, single-arm, pragmatic, silent observational study to evaluate the performance of NeoPose and AI-derived insights in real world settings. NeoNOVA will deploy a bedside video monitoring system (ArtemisAI Platform) that continuously, passively video records the subject from enrollment to discharge. The study will prospectively validate the AI system's tracking accuracy against ground-truth human-labeled video frames (primary objective; outcome median position error in pixels), will evaluate the association between a video-derived movement index and standardized bedside assessments of encephalopathy, pain, and sedation (secondary objective; outcomes N-PASS and modified Sarnat scales), and will support hypothesis-generating research on novel video prediction algorithms for outcomes like sepsis and need for respiratory support (tertiary objective). The study operates in "silent mode," where AI outputs are not shown to the patient's clinical team. Findings are intended to support a structured clinical evidence generation plan for a Software as a Medical Device (SaMD) designed for continuous, non-contact neurological monitoring in the NICU.

Studientyp

Beobachtungs

Einschreibung (Geschätzt)

200

Kontakte und Standorte

Dieser Abschnitt enthält die Kontaktdaten derjenigen, die die Studie durchführen, und Informationen darüber, wo diese Studie durchgeführt wird.

Studienkontakt

Studieren Sie die Kontaktsicherung

Studienorte

  • Vereinigte Staaten
    • New York
      • New York, New York, Vereinigte Staaten, 10029
      • New York, New York, Vereinigte Staaten, 10065
        • Weill Cornell Medicine / NewYork-Presbyterian Hospital
        • Kontakt:
        • Hauptermittler:
          • Sushma Krishna, MD

Teilnahmekriterien

Forscher suchen nach Personen, die einer bestimmten Beschreibung entsprechen, die als Auswahlkriterien bezeichnet werden. Einige Beispiele für diese Kriterien sind der allgemeine Gesundheitszustand einer Person oder frühere Behandlungen.

Zulassungskriterien

Studienberechtigtes Alter

  • Kind
  • Erwachsene
  • Älterer Erwachsener

Akzeptiert gesunde Freiwillige

Ja

Probenahmeverfahren

Nicht-Wahrscheinlichkeitsprobe

Studienpopulation

Neonates of any sex, gestational age, demographic background, or health status admitted to newborn services, including the NICU, at a participating hospital. No diagnosis-specific criteria apply. Consent is provided by at least one parent or legally authorized representative aged 18 or older. Sites will make reasonable efforts to enroll a demographically diverse sample reflective of their local NICU populations, supporting prespecified subgroup analyses of AI performance consistency across gestational age, race/ethnicity, sex, and clinical condition. The first five participants at each site are excluded from primary and secondary endpoint analyses and serve as a technology familiarization cohort.

Beschreibung

Inclusion Criteria:

  • Signed and dated informed consent from at least one parent or legally authorized representative (LAR) who is at least 18 years old.
  • Parent/LAR expresses willingness to comply with study procedures for the duration of the infant's hospital stay.
  • Infant of any sex (including intersex/undetermined) admitted to newborn services (including the NICU) at a participating hospital.

Exclusion Criteria:

  • Parents or LAR unable to provide informed consent or are under the age of 18.
  • Non-viable neonates

Studienplan

Dieser Abschnitt enthält Einzelheiten zum Studienplan, einschließlich des Studiendesigns und der Messung der Studieninhalte.

Wie ist die Studie aufgebaut?

Designdetails

Kohorten und Interventionen

Gruppe / Kohorte
Intervention / Behandlung
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.
Gerät: Continuous bedside video monitoring with AI anatomic landmark tracking for neurologic monitoring
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.

Was misst die Studie?

Primäre Ergebnismessungen

Ergebnis Maßnahme
Maßnahmenbeschreibung
Zeitfenster
AI Anatomic Landmark Tracking Accuracy
Zeitfenster: At study completion, an average of 1 week.
The primary endpoint is analytical performance of the AI pose estimation system, quantified as median position error (in pixels) between AI-predicted and human-labeled anatomic landmark positions extracted from continuous bedside video. Success is defined as median position error less than typical human inter-rater variability.
At study completion, an average of 1 week.

Sekundäre Ergebnismessungen

Ergebnis Maßnahme
Maßnahmenbeschreibung
Zeitfenster
Movement Index - Encephalopathy measured by modified Sarnat exam
Zeitfenster: Through study completion, an average of 1 week.
Association between a video-derived movement index and encephalopathy classification of severity from the modified Sarnat exam score, a bedside neurological exam assessed by trained clinical staff.
Through study completion, an average of 1 week.
Movement Index - N-PASS
Zeitfenster: Through study completion, an average of 1 week.
Association between a video-derived movement index and Neonatal Pain, Agitation, and Sedation Scale (N-PASS) score (ordinal outcome), a bedside neurological exam measuring pain/sedation and assessed by trained clinical staff.
Through study completion, an average of 1 week.
Movement Index - Sedative Exposure
Zeitfenster: Through study completion, an average of 1 week.
Association between movement index and sedative exposure, a routinely collected clinical variable that influences neonatal arousal.
Through study completion, an average of 1 week.
Movement Index - Chronological Age at Video
Zeitfenster: Through study completion, an average of 1 week.
Association between movement index and chronological age at video, a routinely collected clinical variable that influences neonatal arousal.
Through study completion, an average of 1 week.
Movement Index - Gestational age at birth
Zeitfenster: Through study completion, an average of 1 week.
Association between the movement index and gestational age at birth, a routinely collected clinical variable that influences neonatal arousal.
Through study completion, an average of 1 week.
Movement Index - Sleep state
Zeitfenster: Through study completion, an average of 1 week.
Association between the movement index and sleep state, a routinely collected clinical variable that influences neonatal arousal.
Through study completion, an average of 1 week.
Movement Index - EEG evidence of cerebral dysfunction
Zeitfenster: Through study completion, an average of 1 week.
Association between the movement index and, if obtained as part of routine clinical care, EEG evidence of cerebral dysfunction (a biomarker of encephalopathy).
Through study completion, an average of 1 week.

Andere Ergebnismessungen

Ergebnis Maßnahme
Maßnahmenbeschreibung
Zeitfenster
AI Anatomic Landmark Tracking - Post-Menstrual Age at Video
Zeitfenster: At study completion, an average of 1 week.
Assess performance of AI anatomic landmark tracking (median position error) across post-menstrual ages at the time of video recording.
At study completion, an average of 1 week.
AI Anatomic Landmark Tracking - Encephalopathy Status
Zeitfenster: At study completion, an average of 1 week.
Assess performance of AI anatomic landmark tracking (median position error) across encephalopathy statuses.
At study completion, an average of 1 week.
AI Anatomic Landmark Tracking - Caregiver-reported Race/Ethnicity
Zeitfenster: At study completion, an average of 1 week.
Assess performance of AI anatomic landmark tracking (median position error) across caregiver-reported race/ethnicity.
At study completion, an average of 1 week.
AI Anatomic Landmark Tracking - Sex
Zeitfenster: At study completion, an average of 1 week.
Assess performance of AI anatomic landmark tracking (median position error) and sex.
At study completion, an average of 1 week.
AI Anatomic Landmark Tracking - Lighting Conditions
Zeitfenster: At study completion, an average of 1 week.
Assess performance of AI anatomic landmark tracking (median position error) and lighting conditions (phototherapy, lights on/off, time of day).
At study completion, an average of 1 week.
Parent and Provider Feedback
Zeitfenster: At baseline and study completion (Day 1 - Day 7, on average).
Brief structured surveys administered to parents and clinical providers to assess acceptability, usability, and perceived burden of the bedside video monitoring system. Findings will inform system design refinements and support future bedside adoption and regulatory human factors documentation.
At baseline and study completion (Day 1 - Day 7, on average).

Mitarbeiter und Ermittler

Hier finden Sie Personen und Organisationen, die an dieser Studie beteiligt sind.

Sponsor

Artemis AI Labs

Ermittler

  • Hauptermittler: Benjamin Glicksberg, PhD, Icahn School of Medicine at Mount Sinai

Publikationen und hilfreiche Links

Die Bereitstellung dieser Publikationen erfolgt freiwillig durch die für die Eingabe von Informationen über die Studie verantwortliche Person. Diese können sich auf alles beziehen, was mit dem Studium zu tun hat.

Allgemeine Veröffentlichungen

Studienaufzeichnungsdaten

Diese Daten verfolgen den Fortschritt der Übermittlung von Studienaufzeichnungen und zusammenfassenden Ergebnissen an ClinicalTrials.gov. Studienaufzeichnungen und gemeldete Ergebnisse werden von der National Library of Medicine (NLM) überprüft, um sicherzustellen, dass sie bestimmten Qualitätskontrollstandards entsprechen, bevor sie auf der öffentlichen Website veröffentlicht werden.

Haupttermine studieren

Studienbeginn (Geschätzt)

1. Juni 2026

Primärer Abschluss (Geschätzt)

31. Mai 2027

Studienabschluss (Geschätzt)

31. Mai 2029

Studienanmeldedaten

Zuerst eingereicht

26. Mai 2026

Zuerst eingereicht, das die QC-Kriterien erfüllt hat

1. Juni 2026

Zuerst gepostet (Tatsächlich)

5. Juni 2026

Studienaufzeichnungsaktualisierungen

Letztes Update gepostet (Tatsächlich)

5. Juni 2026

Letztes eingereichtes Update, das die QC-Kriterien erfüllt

1. Juni 2026

Zuletzt verifiziert

1. Juni 2026

Mehr Informationen

Begriffe im Zusammenhang mit dieser Studie

Schlüsselwörter

Zusätzliche relevante MeSH-Bedingungen

Andere Studien-ID-Nummern

  • STUDY-25-01036

Plan für individuelle Teilnehmerdaten (IPD)

Planen Sie, individuelle Teilnehmerdaten (IPD) zu teilen?

NEIN

Beschreibung des IPD-Plans

Aggregate deidentified data and results will be shared. Individual participant video data will not be shared due to PHI concerns.

Arzneimittel- und Geräteinformationen, Studienunterlagen

Studiert ein von der US-amerikanischen FDA reguliertes Arzneimittelprodukt

Nein

Studiert ein von der US-amerikanischen FDA reguliertes Geräteprodukt

Ja

Produkt, das in den USA hergestellt und aus den USA exportiert wird

Nein

Diese Informationen wurden ohne Änderungen direkt von der Website clinicaltrials.gov abgerufen. Wenn Sie Ihre Studiendaten ändern, entfernen oder aktualisieren möchten, wenden Sie sich bitte an register@clinicaltrials.gov. Sobald eine Änderung auf clinicaltrials.gov implementiert wird, wird diese automatisch auch auf unserer Website aktualisiert .

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