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Neonatal Neurological Observation With Video AI (NeoNOVA)

1 giugno 2026 aggiornato da: 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).

Panoramica dello studio

Stato

Non ancora reclutamento

Condizioni

Intervento / Trattamento

Descrizione dettagliata

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.

Tipo di studio

Osservativo

Iscrizione (Stimato)

200

Contatti e Sedi

Questa sezione fornisce i recapiti di coloro che conducono lo studio e informazioni su dove viene condotto lo studio.

Contatto studio

Backup dei contatti dello studio

Luoghi di studio

  • Stati Uniti
    • New York
      • New York, New York, Stati Uniti, 10029
        • Mount Sinai Hospital
        • Contatto:
        • Contatto:
        • Investigatore principale:
          • Benjamin Glicksberg, PhD
      • New York, New York, Stati Uniti, 10065
        • Weill Cornell Medicine / NewYork-Presbyterian Hospital
        • Contatto:
        • Investigatore principale:
          • Sushma Krishna, MD

Criteri di partecipazione

I ricercatori cercano persone che corrispondano a una certa descrizione, chiamata criteri di ammissibilità. Alcuni esempi di questi criteri sono le condizioni generali di salute di una persona o trattamenti precedenti.

Criteri di ammissibilità

Età idonea allo studio

  • Bambino
  • Adulto
  • Adulto più anziano

Accetta volontari sani

Sì

Metodo di campionamento

Campione non probabilistico

Popolazione di studio

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.

Descrizione

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

Piano di studio

Questa sezione fornisce i dettagli del piano di studio, compreso il modo in cui lo studio è progettato e ciò che lo studio sta misurando.

Come è strutturato lo studio?

Dettagli di progettazione

Coorti e interventi

Gruppo / Coorte
Intervento / Trattamento
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.
Dispositivo: 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.

Cosa sta misurando lo studio?

Misure di risultato primarie

Misura del risultato
Misura Descrizione
Lasso di tempo
AI Anatomic Landmark Tracking Accuracy
Lasso di tempo: 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.

Misure di risultato secondarie

Misura del risultato
Misura Descrizione
Lasso di tempo
Movement Index - Encephalopathy measured by modified Sarnat exam
Lasso di tempo: 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
Lasso di tempo: 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
Lasso di tempo: 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
Lasso di tempo: 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
Lasso di tempo: 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
Lasso di tempo: 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
Lasso di tempo: 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.

Altre misure di risultato

Misura del risultato
Misura Descrizione
Lasso di tempo
AI Anatomic Landmark Tracking - Post-Menstrual Age at Video
Lasso di tempo: 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
Lasso di tempo: 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
Lasso di tempo: 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
Lasso di tempo: 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
Lasso di tempo: 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
Lasso di tempo: 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).

Collaboratori e investigatori

Qui è dove troverai le persone e le organizzazioni coinvolte in questo studio.

Sponsor

Artemis AI Labs

Investigatori

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

Pubblicazioni e link utili

La persona responsabile dell'inserimento delle informazioni sullo studio fornisce volontariamente queste pubblicazioni. Questi possono riguardare qualsiasi cosa relativa allo studio.

Pubblicazioni generali

Studiare le date dei record

Queste date tengono traccia dell'avanzamento della registrazione dello studio e dell'invio dei risultati di sintesi a ClinicalTrials.gov. I record degli studi e i risultati riportati vengono esaminati dalla National Library of Medicine (NLM) per assicurarsi che soddisfino specifici standard di controllo della qualità prima di essere pubblicati sul sito Web pubblico.

Studia le date principali

Inizio studio (Stimato)

1 giugno 2026

Completamento primario (Stimato)

31 maggio 2027

Completamento dello studio (Stimato)

31 maggio 2029

Date di iscrizione allo studio

Primo inviato

26 maggio 2026

Primo inviato che soddisfa i criteri di controllo qualità

1 giugno 2026

Primo Inserito (Effettivo)

5 giugno 2026

Aggiornamenti dei record di studio

Ultimo aggiornamento pubblicato (Effettivo)

5 giugno 2026

Ultimo aggiornamento inviato che soddisfa i criteri QC

1 giugno 2026

Ultimo verificato

1 giugno 2026

Maggiori informazioni

Termini relativi a questo studio

Parole chiave

Termini MeSH pertinenti aggiuntivi

Altri numeri di identificazione dello studio

  • STUDY-25-01036

Piano per i dati dei singoli partecipanti (IPD)

Hai intenzione di condividere i dati dei singoli partecipanti (IPD)?

NO

Descrizione del piano IPD

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

Informazioni su farmaci e dispositivi, documenti di studio

Studia un prodotto farmaceutico regolamentato dalla FDA degli Stati Uniti

No

Studia un dispositivo regolamentato dalla FDA degli Stati Uniti

Sì

prodotto fabbricato ed esportato dagli Stati Uniti

No

Queste informazioni sono state recuperate direttamente dal sito web clinicaltrials.gov senza alcuna modifica. In caso di richieste di modifica, rimozione o aggiornamento dei dettagli dello studio, contattare register@clinicaltrials.gov. Non appena verrà implementata una modifica su clinicaltrials.gov, questa verrà aggiornata automaticamente anche sul nostro sito web .

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