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 2008
Algorithm for automatic beat detection of cardiovascular pressure signals.
Pressure beat detection is an integral part of most analysis techniques for arterial blood pressure (ABP), intracranial pressure (ICP), and pulse oximetry (SpO(2)) signals. Beat detection has been used to estimate heart rate in the ABP signal, to classify ICP morphologies, and to estimate blood pressure using pulse oximeter waveforms. This paper describes an algorithm that was developed to detect pressure peak beats in ABP, ICP, and SpO(2) signals. When compared to the expert annotation of several signals consisting of over 42,500 pressure beats, the algorithm detected pressure peaks with an average sensitivity of 99.6% +/- 0.27 and an average positive predictivity of 98.6% +/- 1.1.
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Low bandwidth has long been a reason for the unsuitability of wireless internet in telemedicine. However with the advent of extended third generation wireless as an economically accessible high speed network, more opportunities are being created in this area of telemedicine. This paper explores the opportunity created by the latest wireless broadband technology for remote monitoring of patients in the home.
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Acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) contribute to the morbidity and mortality of intensive care patients worldwide, and have large associated human and financial costs. We identified a reference data set of 624 mechanically-ventilated patients in the MIMIC-II intensive care database with and without low PaO(2)/FiO(2) ratios (termed respiratory instability), and developed prediction algorithms for distinguishing these patients prior to the critical event. In the end, we had four rule sets using mean airway pressure, plateau pressure, total respiratory rate and oxygen saturation (SpO(2)), where the specificity/sensitivity rates were either 80%/60% or 90%/50%.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2008
Hypnotic administration for anesthesia using sliding-mode control.
Nowadays general anesthesia is maintained using as the controller the human intervention, relying only on the quick and certain response of the anesthesiologist to the surrounding conditions, in order to provide the adequate state of anesthesia for the three main components - hypnosis, analgesia and paralysis. One of the most advantageous breakthroughs in anesthesia has been the appearance of depth of anesthesia monitors, assisting anesthesiologists in the hard job of knowing the hypnotic state of a patient. This information allows a way of closing the loop for administration of the hypnotic drug, and a more secure maintenance of hypnosis. The objective of this work was to apply sliding-mode control techniques to the model structure of the hypnotic in the human body (measured by the effect), and evaluate the robustness of this method to expected deviations from the average patient.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2008
Investigation of photoplethysmogram morphology for the detection of hypovolemic states.
Medics and first responders to emergencies are often faced with monitoring and assessing victims with very limited resources. Therefore, there is an inherent need for a real-time ambulatory monitoring capability that is portable and low power. This is particularly important for physiological monitoring of life-threatening conditions such as internal hemorrhaging. ⋯ In this paper, we compared the PPG morphology with pulse transit time (PTT), which has been investigated for clinical and ambulatory applications. The indicators were tested on data obtained from experiments using lower body negative pressure (LBNP) as a model to simulate hemorrhage in humans. The results of this study indicate that PPG morphology is associated with pulse pressure (systolic minus diastolic blood pressure) and is therefore a promising feature for detection and real-time tracking of hypovolemic states.