Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
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Conf Proc IEEE Eng Med Biol Soc · Jan 2014
Randomized Controlled TrialAltered cortical causality after remifentanil administration in healthy volunteers: a novel approach for pharmaco-EEG.
Alterations in cortical causality information flow induced by remifentanil infusion in healthy volunteers was investigated in a placebo-controlled double-blind cross-over study. For each of the 21 enrolled male subjects, 2.5 minutes of resting electroencephalography (EEG) data were collected before and after infusion of remifentanil and placebo. Additionally, to assess cognitive function and analgesic effect, continuous reaction time (CRT) and bone pressure and heat pain were assessed, respectively. ⋯ Furthermore, several of the PSI features altered by remifentanil were correlated to changes in both CRT and pain scores. The results indicate that remifentanil administration influence the information flow between several brain areas. Hence, the EEG causality approach offers the potential to assist in deciphering the cortical effects of remifentanil administration.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2014
Adaptive thresholding with inverted triangular area for real-time detection of the heart rate from photoplethysmogram traces on a smartphone.
Photoplethysmogram (PPG) signals acquired by smartphone cameras are weaker than those acquired by dedicated pulse oximeters. Furthermore, the signals have lower sampling rates, have notches in the waveform and are more severely affected by baseline drift, leading to specific morphological characteristics. This paper introduces a new feature, the inverted triangular area, to address these specific characteristics. ⋯ We collected data from 24 volunteers and compared our algorithm in peak detection with two competing algorithms designed for PPG signals, Incremental-Merge Segmentation (IMS) and Adaptive Thresholding (ADT). A sensitivity of 98.0% and a positive predictive value of 98.8% were obtained, which were 7.7% higher than the IMS algorithm in sensitivity, and 8.3% higher than the ADT algorithm in positive predictive value. The experimental results confirmed the applicability of the proposed method.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2014
The mixing rate of the arterial blood pressure waveform Markov chain is correlated with shock index during hemorrhage in anesthetized swine.
Identifying the need for interventions during hemorrhage is complicated due to physiological compensation mechanisms that can stabilize vital signs until a significant amount of blood loss. Physiological systems providing compensation during hemorrhage affect the arterial blood pressure waveform through changes in dynamics and waveform morphology. We investigated the use of Markov chain analysis of the arterial blood pressure waveform to monitor physiological systems changes during hemorrhage. ⋯ A change in the mixing rate from baseline estimates was identified during hemorrhage for each animal (median time of 13 min, ~10% estimated blood volume, with minimum and maximum times of 2 and 33 min, respectively). The mixing rate was found to have an inverse correlation with shock index for all 7 animals (median correlation coefficient of -0.95 with minimum and maximum of -0.98 and -0.58, respectively). The Markov chain mixing rate of arterial blood pressure recordings is a novel potential biomarker for monitoring and understanding physiological systems during hemorrhage.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2014
Assessing the privacy policies in mobile personal health records.
The huge increase in the number and use of smartphones and tablets has led health service providers to take an interest in mHealth. Popular mobile app markets like Apple App Store or Google Play contain thousands of health applications. Although mobile personal health records (mPHRs) have a number of benefits, important challenges appear in the form of adoption barriers. ⋯ The results show important differences in both the mPHRs and the characteristics analyzed. A questionnaire containing six questions concerning privacy policies was defined. Our questionnaire may assist developers and stakeholders to evaluate the security and privacy of their mPHRs.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2014
A unified machine learning method for task-related and resting state fMRI data analysis.
Functional magnetic resonance imaging (fMRI) aims to localize task-related brain activation or resting-state functional connectivity. Most existing fMRI data analysis techniques rely on fixed thresholds to identify active voxels under a task condition or functionally connected voxels in the resting state. Due to fMRI non-stationarity, a fixed threshold cannot adapt to intra- and inter-subject variation and provide a reliable mapping of brain function. ⋯ The method does not require a fixed threshold for the final decision, and can adapt to fMRI non-stationarity. The proposed method was evaluated using experimental data acquired from multiple human subjects. The results indicate that the proposed method can provide reliable mapping of brain function, and is applicable to various quantitative fMRI studies.