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 2006
ReviewIntegrating data, models, and reasoning in critical care.
Modern intensive care units (ICUs) employ an impressive array of technologically sophisticated instrumentation to provide detailed measurements of the pathophysiological state of each patient. Providing life support in the ICU is becoming an increasingly complex task, however, because of the growing volume of relevant data from clinical observations, bedside monitors, mechanical ventilators, and a wide variety of laboratory tests and imaging studies. ⋯ There is a critical need to integrate the disparate clinical information into a single, rational framework and to provide the clinician with hypothesis-driven displays that succinctly summarize a patient's trajectory over time. In this paper, we present our recent efforts towards the development of such an advanced patient monitoring system that aims to improve the efficiency, accuracy, and timeliness of clinical decision making in intensive care.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2006
Blind identification of the central aortic pressure waveform from multiple peripheral arterial pressure waveforms.
We introduce a blind identification technique to reconstruct the clinically more relevant central aortic pressure waveform from multiple less invasively measured peripheral arterial pressure waveforms. We conducted initial testing of the technique in two swine in which peripheral arterial pressure waveforms from the femoral and radial arteries and reference central aortic pressure were simultaneously measured during diverse hemodynamic conditions. We report an overall error between the estimated and measured central aortic pressure waveforms of 4.8%. Potential clinical applications of the technique may include critical care monitoring with respect to invasive catheter systems and emergency and home monitoring with respect to non-invasive arterial pressure transducers.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2006
ReviewIntelligent alarm processing into clinical knowledge.
Alarmed physiological monitors have become a standard part of the ICU. While the alarms generated by these monitors can be important indicators of an altered physiological condition, most are unhelpful to medical staff due to a high incidence of false and clinically insignificant alarms. ⋯ In this paper we review the current state of intelligent alarm processing and describe an integrated systems methodology to extract clinically relevant information from physiological data. Such a method would aid significantly in the reduction of false alarms and provide nursing staff with a more reliable indicator of patient condition.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2006
Comparative StudyComparison of heart rate variability signal features derived from electrocardiography and photoplethysmography in healthy individuals.
The heart rate variability (HRV) signal is indicative of autonomic regulation of the heart rate (HR). It could be used as a noninvasive marker in monitoring the physiological state of an individual. Currently, the primary method of deriving the HRV signal is to acquire the electrocardiogram (ECG) signal, apply appropriate QRS detection algorithms to locate the R wave and its peak, find the RR intervals, and perform suitable interpolation and resampling to produce a uniformly sampled tachogram. ⋯ We used autoregressive (AR) modeling, Poincare' plots, cross correlation, standard deviation, arithmetic mean, skewness, kurtosis, and approximate entropy (ApEn) to derive and compare different measures from both ECG and PPG signals. This study demonstrated that our PDA-based system was a convenient and reliable means for acquisition of PPG-derived and ECG-derived HRV signals. The excellent agreement between different measures of HRV signals acquired from both methods provides potential support for the idea of using PPGs instead of ECGs in HRV signal derivation and analysis in ambulatory cardiac monitoring of healthy individuals.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2006
Controlled Clinical TrialInformation flow to assess cardiorespiratory interactions in patients on weaning trials.
Nonlinear processes of the autonomic nervous system (ANS) can produce breath-to-breath variability in the pattern of breathing. In order to provide assess to these nonlinear processes, nonlinear statistical dependencies between heart rate variability and respiratory pattern variability are analyzed. ⋯ The results show lower complexity with an increase of information flow in group A than in group B. Furthermore, a more (weakly) coupled nonlinear oscillator behavior is observed in the series of group A than in B.