IEEE transactions on bio-medical engineering
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IEEE Trans Biomed Eng · Apr 2017
Tracking Electroencephalographic Changes Using Distributions of Linear Models: Application to Propofol-Based Depth of Anesthesia Monitoring.
Tracking brain states with electrophysiological measurements often relies on short-term averages of extracted features and this may not adequately capture the variability of brain dynamics. The objective is to assess the hypotheses that this can be overcome by tracking distributions of linear models using anesthesia data, and that anesthetic brain state tracking performance of linear models is comparable to that of a high performing depth of anesthesia monitoring feature. ⋯ These techniques hold potential for anesthesia monitoring and may be generally applicable for tracking brain states.
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IEEE Trans Biomed Eng · Mar 2017
Dynamic Computation Offloading for Low-Power Wearable Health Monitoring Systems.
The objective of this paper is to describe and evaluate an algorithm to reduce power usage and increase battery lifetime for wearable health-monitoring devices. ⋯ Making correct offloading decisions for health monitoring devices can extend battery life and improve adherence.
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IEEE Trans Biomed Eng · Mar 2017
Intratidal Overdistention and Derecruitment in the Injured Lung: A Simulation Study.
Ventilated patients with the acute respiratory distress syndrome (ARDS) are predisposed to cyclic parenchymal overdistention and derecruitment, which may worsen existing injury. We hypothesized that intratidal variations in global mechanics, as assessed at the airway opening, would reflect such distributed processes. ⋯ Titration of airway pressures based on variations in intratidal mechanics may mitigate processes associated with injurious ventilation.
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IEEE Trans Biomed Eng · Feb 2017
Review-Omic and Electronic Health Record Big Data Analytics for Precision Medicine.
Rapid advances of high-throughput technologies and wide adoption of electronic health records (EHRs) have led to fast accumulation of -omic and EHR data. These voluminous complex data contain abundant information for precision medicine, and big data analytics can extract such knowledge to improve the quality of healthcare. ⋯ Big data analytics makes sense of -omic and EHR data to improve healthcare outcome. It has long lasting societal impact.
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IEEE Trans Biomed Eng · Jan 2017
ConceFT for Time-Varying Heart Rate Variability Analysis as a Measure of Noxious Stimulation During General Anesthesia.
Heart rate variability (HRV) offers a noninvasive way to peek into the physiological status of the human body. When this physiological status is dynamic, traditional HRV indices calculated from power spectrum do not resolve the dynamic situation due to the issue of nonstationarity. Clinical anesthesia is a typically dynamic situation that calls for time-varying HRV analysis. Concentration of frequency and time (ConceFT) is a nonlinear time-frequency (TF) analysis generalizing the multitaper technique and the synchrosqueezing transform. The result is a sharp TF representation capturing the dynamics inside HRV. Companion indices of the commonly applied HRV indices, including time-varying low-frequency power (tvLF), time-varying high-frequency power, and time-varying low-high ratio, are considered as measures of noxious stimulation. ⋯ Our proposed scheme of time-varying HRV analysis could contribute to the clinical assessment of analgesia under general anesthesia.