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Signal Analysis for Neurocritical Patients

NCT03362346 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 156

Last updated 2018-06-06

No results posted yet for this study

Summary

The project uses big data analysis techniques such as wavelet transform and deep learning to analyze physiological signals from neurocritical patients and build a model to evaluate intracranial condition and to predict neurological outcome. By identification of correlations among these parameters and their trends, we may achieve early detection of anomalies and enhance the ability in judgement of current neurological condition and prediction of prognosis. By continuous input of the past and contemporary data in the ICU, the model will be modified repeatedly and its accuracy improves as the model grows. The model can be used to recognize abnormalities earlier and provide a warning system. Clinicians taking care of neurocritical patients can adjust their treatment policy and evaluate the outcome according to such system.

Conditions

  • Brain Injuries, Acute

Interventions

DEVICE

intracranial pressure monitoring

The patients may have either intracranial pressure (ICP) monitor insertion or external ventricular drainage that can be used as ICP monitor.

Sponsors & Collaborators

  • Far Eastern Memorial Hospital

    lead OTHER

Principal Investigators

  • Yi-Hsin Tsai, M.D. · Far Eastern Memorial Hospital

Eligibility

Min Age
20 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2017-12-18
Primary Completion
2018-05-24
Completion
2018-05-31

Countries

  • Taiwan

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT03362346 on ClinicalTrials.gov