Using a short-term parameter of heart rate variability to distinguish awake from isoflurane anesthetic states.
about
Review and classification of variability analysis techniques with clinical applicationsMonitoring depth of anesthesia using combination of EEG measure and hemodynamic variables.Sample entropy analysis of EEG signals via artificial neural networks to model patients' consciousness level based on anesthesiologists experience.HRV-derived data similarity and distribution index based on ensemble neural network for measuring depth of anaesthesia.Respiratory induced heart rate variability during slow mechanical ventilation : Marker to exclude brain death patients.The Nightingale Prize for best MBEC paper in 2011.Assessing the mean strength and variations of the time-to-time fluctuations of resting-state brain activity.The Nightingale Award 2008.Multivariate short-term heart rate variability: a pre-diagnostic tool for screening heart disease.A Heartbeat Away From Consciousness: Heart Rate Variability Entropy Can Discriminate Disorders of Consciousness and Is Correlated With Resting-State fMRI Brain Connectivity of the Central Autonomic Network
P2860
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P2860
Using a short-term parameter of heart rate variability to distinguish awake from isoflurane anesthetic states.
description
2008 nî lūn-bûn
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2008年学术文章
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2008年学术文章
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name
Using a short-term parameter o ...... isoflurane anesthetic states.
@en
Using a short-term parameter o ...... isoflurane anesthetic states.
@nl
type
label
Using a short-term parameter o ...... isoflurane anesthetic states.
@en
Using a short-term parameter o ...... isoflurane anesthetic states.
@nl
prefLabel
Using a short-term parameter o ...... isoflurane anesthetic states.
@en
Using a short-term parameter o ...... isoflurane anesthetic states.
@nl
P2093
P1476
Using a short-term parameter o ...... m isoflurane anesthetic states
@en
P2093
Chi-Hsiang Huang
Hsiao-Lung Chan
Hui-Hsun Huang
Yi-Hui Lee
P304
P356
10.1007/S11517-008-0342-Y
P577
2008-04-15T00:00:00Z