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
A Novel Grading Biomarker for the Prediction of Conversion From Mild Cognitive Impairment to Alzheimer's Disease.
Identifying mild cognitive impairment (MCI) subjects who will progress to Alzheimer's disease (AD) is not only crucial in clinical practice, but also has a significant potential to enrich clinical trials. The purpose of this study is to develop an effective biomarker for an accurate prediction of MCI-to-AD conversion from magnetic resonance images. ⋯ The evaluation on the ADNI dataset shows the efficacy of the proposed biomarker and demonstrates a significant contribution in accurate prediction of MCI-to-AD conversion.