Signal Analysis for Neurocritical Patients
Analysis of Physiological Signals From Neurocritical Patients in Intensive Care Units Using Wavelet Transform and Deep Learning
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Actual)
Enrollment
Contacts and Locations
Study Locations
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New Taipei City, Taiwan, 200
- Far Eastern Memorial Hospital
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
Inclusion Criteria:
- Age equal to or older than 20 years
- Neurocritical patients admitted to intensive care unit (ICU), including but not limited to traumatic brain injury, hemorrhagic stroke, ischemic stroke, brain infection, brain tumor and acute hydrocephalus.
- Patients who have undergone cranial surgery and had intracranial pressure monitor inserted or external ventricular drainage. The central monitor of ICU is able to collect the data continuously
Exclusion Criteria:
- Age younger than 20 years.
- Continuous monitoring of intracranial pressure is not feasible.
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
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Neurocritical patients
Patients with brain injury from trauma, ischemic stroke, hemorrhage stroke (intracerebral hemorrhage, subarachnoid hemorrhage), brain tumor with increased intracranial pressure, brain infection, hydrocephalus, among others.
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The patients may have either intracranial pressure (ICP) monitor insertion or external ventricular drainage that can be used as ICP monitor.
Other Names:
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Neurological status
Time Frame: Discharge out of the intensive care unit, averaged 2 weeks
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Glasgow coma scale/Mortality
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Discharge out of the intensive care unit, averaged 2 weeks
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Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Principal Investigator: Yi-Hsin Tsai, M.D., Far Eastern Memorial Hospital
Publications and helpful links
General Publications
- Diederik P. Kingma and Jimmy Lei Ba. Adam: A method for stochastic optimization. Conference paper at ICLR 2015.
- Michael Unser and Akram Aldroubi. (1996 Apr) A review of wavelets in biomedical applications. Proceedings of the IEEE 84(4): 626-638.
- LeCun Y, Bengio Y, Hinton G. Deep learning. Nature. 2015 May 28;521(7553):436-44. doi: 10.1038/nature14539.
- Christopher Torrence and Gilbert P. Compo. (1998 Jan) A practical guide to wavelet analysis. Bulletin of the American Meteorological Society 79(1):61-78.
- Theis, Fabian & Meyer-Base, Anke. (2010). Biomedical Signal Analysis - Contemporary Methods and Applications. Biomedical Signal Analysis: Contemporary Methods and Applications.
- Min S, Lee B, Yoon S. Deep learning in bioinformatics. Brief Bioinform. 2017 Sep 1;18(5):851-869. doi: 10.1093/bib/bbw068.
- Yi Mao, Wenlin Chen, Yixin Chen, Chenyang Lu, Marin Kollef, and Thomas Bailey. (2012) An integrated data mining approach to real-time clinical monitoring and deterioration warning. Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining Pages 1140-1148. doi>10.1145/2339530.2339709
Study record dates
Study Major Dates
Study Start (ACTUAL)
Study Start
Primary Completion (ACTUAL)
Primary Completion
Study Completion (ACTUAL)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (ACTUAL)
First Posted
Study Record Updates
Last Update Posted (ACTUAL)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- 106152-E
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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