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 2012
Clinical TrialAnalysis of roots in ARMA model for the classification of patients on weaning trials.
One objective of mechanical ventilation is the recovery of spontaneous breathing as soon as possible. Remove the mechanical ventilation is sometimes more difficult that maintain it. ⋯ The optimal model was obtained with order 8, and statistical significant differences were obtained considering the values of angles of the first four poles and the first zero. The best classification was obtained between GF and GR, with an accuracy of 75.3% on the mean value of the angle of the first pole.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2012
Cortical potential imaging of somatosensory evoked potential induced by mechanical stimulation.
The objective evaluation of somatic sensations is expected without a patient's subjective opinions to reduce social problems such as those related to lawsuits for nerve injuries or malingering. In this study, the somatosensory evoked potential (SEP) using the mechanical stimulations of the tactile sensation was measured and analyzed in spatiotemporal domains. The cortical potential mapping projected onto the realistic-shaped model was estimated to improve the spatial resolution of the SEP maps by application of cortical dipole layer imaging. The experimentally obtained results suggest that the spatiotemporal distributions of the SEPs reflect the differences for positions, strengths, and patterns of somatosensory stimulations.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2012
Comparative StudyEvaluation of a smart alarm for intensive care using clinical data.
We describe and report the results of an evaluation of a smart alarm algorithm for post coronary artery bypass graft (CABG) patients. The algorithm (CABG-SA) was applied to vital sign data streams recorded in a surgical intensive care unit (SICU) at a hospital in the University of Pennsylvania Health System. In order to determine the specificity of CABG-SA, the alarms generated by CABG-SA were compared against the actual interventions performed by the staff of the critical care unit. Overall, CABG-SA alarmed for 55% of the time relative to traditional alarms while still generating alarms for 12 of the 13 recorded interventions.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2012
Discovering shared dynamics in physiological signals: application to patient monitoring in ICU.
Modern clinical databases include time series of vital signs, which are often recorded continuously during a hospital stay. Over several days, these recordings may yield many thousands of samples. In this work, we explore the feasibility of characterizing the "state of health" of a patient using the physiological dynamics inferred from these time series. ⋯ Each such "dynamic" captures a distinct pattern of evolution of BP and is possibly recurrent within the same time series and shared across multiple patients. Next, we examine the utility of this low-dimensional representation of BP time series for predicting mortality in patients. Our results are based on an intensive care unit (ICU) cohort of 480 patients (with 16% mortality) and indicate that the dynamics of time series of vital signs can be an independent useful predictor of outcome in ICU.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2012
Validation of heart rate extraction using video imaging on a built-in camera system of a smartphone.
As a smartphone is becoming very popular and its performance is being improved fast, a smartphone shows its potential as a low-cost physiological measurement solution which is accurate and can be used beyond the clinical environment. Because cardiac pulse leads the subtle color change of a skin, a pulsatile signal which can be described as photoplethysmographic (PPG) signal can be measured through recording facial video using a digital camera. In this paper, we explore the potential that the reliable heart rate can be measured remotely by the facial video recorded using smartphone camera. ⋯ The heart rate was extracted using frequency analysis of the raw trace signal and the analyzed signal from ICA. The accuracy of the estimated heart rate was evaluated by comparing with the heart rate from reference electrocardiogram (ECG) signal. Finally, we developed FaceBEAT, an iPhone application for remote heart rate measurement, based on this study.