2.50
Hdl Handle:
http://hdl.handle.net/10755/211642
Type:
Research Study
Title:
EXPLORATIONS in aEEG ANALYSIS: SEARCHING FOR CYCLICITY
Abstract:
Purpose:  Describe varied approaches to graphical analysis of EEG signal from premature infants. Background: Amplitude-integrated EEG offers a limited channel brain function signal suitable for use in the clinical setting of the Neonatal Intensive Care Unit (NICU). The output is a graphical pattern of compressed data.  Raw EEG signal and amplifier impedance readings are also displayed and recorded.  The device has promise as a non-invasive measure of sleep wake cyclicity, neurodevelopmental maturation, and brain function background continuity. Analytical approaches described in the literature are limited to categorical descriptions of visual pattern display, or automated counts of EEG features such as bursts of high amplitude interspersed by periods of low signal power. The data of premature infants is characteristically non-stationary with seemingly chaotic changes in amplitude occurring over short time windows (e.g.10 second blocks).  Oversimplification of the data although practical may not be the optimal analytic approach to describe the complicated occurrences of brain function. Design and Methods:  Data from four premature infants with postmenstrual age range (26-32 weeks) was obtained during normal care conditions in the NICU as part of a descriptive within subject study. An FDA approved limited channel a-EEG device (CFM 6000, Natus Medical, San Carlos, CA) was used to record a single channel of continuous raw EEG (100 samples/second) after placement of three hydrogel scalp electrodes in P3-P4 location by modified International 10/20.  EEG signal is recorded as amplitude (µV) over time, impedance values are recorded in K-Ohms. Data was downloaded to disc and analyzed using MatLab R2010a (The Math Works, Natick, MA). Results: Preliminary explorations of background brain function data using varied techniques for qualitative graphical display of dynamic time and frequency data will be conducted including: phase diagrams and wavelet transformation analysis to decompose the signal. Each approach will attempt will search for frequency cycles of brain function as separate from noise. Implications: Complex signals such as premature brain function are poorly modeled by traditional techniques without loss of data richness and depth of cyclic structure.  Graphical explorations may enhance the understanding of underlying cycles within brain function signal.  Physiologic cycles and variability within a signal often reflect health of an organism. In the case of the preterm infant, cyclicity of neural patterns associated with sleep and wake states is paramount to normal brain development.
Keywords:
Premature infants; EEG outputs; Cyclicity
Repository Posting Date:
20-Feb-2012
Date of Publication:
20-Feb-2012
Other Identifiers:
5632
Sponsors:
Western Institute of Nursing

Full metadata record

DC FieldValue Language
dc.typeResearch Studyen_GB
dc.titleEXPLORATIONS in aEEG ANALYSIS: SEARCHING FOR CYCLICITYen_GB
dc.identifier.urihttp://hdl.handle.net/10755/211642-
dc.description.abstractPurpose:  Describe varied approaches to graphical analysis of EEG signal from premature infants. Background: Amplitude-integrated EEG offers a limited channel brain function signal suitable for use in the clinical setting of the Neonatal Intensive Care Unit (NICU). The output is a graphical pattern of compressed data.  Raw EEG signal and amplifier impedance readings are also displayed and recorded.  The device has promise as a non-invasive measure of sleep wake cyclicity, neurodevelopmental maturation, and brain function background continuity. Analytical approaches described in the literature are limited to categorical descriptions of visual pattern display, or automated counts of EEG features such as bursts of high amplitude interspersed by periods of low signal power. The data of premature infants is characteristically non-stationary with seemingly chaotic changes in amplitude occurring over short time windows (e.g.10 second blocks).  Oversimplification of the data although practical may not be the optimal analytic approach to describe the complicated occurrences of brain function. Design and Methods:  Data from four premature infants with postmenstrual age range (26-32 weeks) was obtained during normal care conditions in the NICU as part of a descriptive within subject study. An FDA approved limited channel a-EEG device (CFM 6000, Natus Medical, San Carlos, CA) was used to record a single channel of continuous raw EEG (100 samples/second) after placement of three hydrogel scalp electrodes in P3-P4 location by modified International 10/20.  EEG signal is recorded as amplitude (µV) over time, impedance values are recorded in K-Ohms. Data was downloaded to disc and analyzed using MatLab R2010a (The Math Works, Natick, MA). Results: Preliminary explorations of background brain function data using varied techniques for qualitative graphical display of dynamic time and frequency data will be conducted including: phase diagrams and wavelet transformation analysis to decompose the signal. Each approach will attempt will search for frequency cycles of brain function as separate from noise. Implications: Complex signals such as premature brain function are poorly modeled by traditional techniques without loss of data richness and depth of cyclic structure.  Graphical explorations may enhance the understanding of underlying cycles within brain function signal.  Physiologic cycles and variability within a signal often reflect health of an organism. In the case of the preterm infant, cyclicity of neural patterns associated with sleep and wake states is paramount to normal brain development.en_GB
dc.subjectPremature infantsen_GB
dc.subjectEEG outputsen_GB
dc.subjectCyclicityen_GB
dc.date.available2012-02-20T12:05:52Z-
dc.date.issued2012-02-20T12:05:52Z-
dc.date.accessioned2012-02-20T12:05:52Z-
dc.description.sponsorshipWestern Institute of Nursingen_GB
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