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 2010
Heuristics to determine ventilation times of ICU patients from the MIMIC-II database.
Mechanical ventilation is an important life support tool for patients in intensive care units (ICU). For various research purposes related to patient hemodynamic and cardiopulmonary monitoring, it is important to know when a patient is on a ventilator. Unfortunately, the widely used MIMIC-II database contains results from user charted data, where the user did not always store ventilation on and off times explicitly and accurately. ⋯ Hence, we designed a simple set of rules to determine the ventilation times using multiple sources of mechanical ventilator-related settings and physiological measurements by expert heuristics. The rules worked well in comparison with nursing notes regarding ventilation events. We conclude that our rule sets for determining ventilation times may be useful in assisting with MIMIC-II database analysis.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2010
Analysis of heart rate variability dynamics during propofol and dexmedetomidine anesthesia.
It has been observed that heart rate variability (HRV) diminishes during anesthesia, but the exact mechanisms causing it are not completely understood. The aim of this paper was to study the dynamics of HRV during low dose propofol (N=9) and dexmedetomidine (N=8) anesthesia by using state-of-the-art time-varying methods, and thereby ultimately try to improve the safety of anesthesia. ⋯ For dexmedetomidine these changes are more considerable than for propofol. For dexmedetomidine the variability also seems to start decreasing right after loss of consciousness, whereas for propofol HRV continues increasing.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2010
PhysioDoloris: a monitoring device for analgesia / nociception balance evaluation using heart rate variability analysis.
Continuous Analgesia / Nociception balance evaluation during general anesthesia could be of precious help for the optimization of analgesic drugs delivery, limiting the risk of toxicity due to the use of opioid drugs, limiting the risk of post operative hyper algesia, and, probably, reducing time of recovery after surgical procedure. Heart Rate Variability analysis has been shown in several studies to measure the Autonomic Nervous System tone, which is strongly influenced by anesthetic drugs. ⋯ We have previously developed and evaluated a pain / analgesia measurement algorithm based on the magnitude analysis of the respiratory patterns on the RR series. In this paper, we present the development of a monitoring device (PhysioDoloris), based on the previously described technology, giving in real time an Analgesia Nociception Index (ANI) which can be used during general anesthesia in order to give to the anesthetist, a complementary tool for optimized drug delivery.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2010
A closed-loop brain computer interface for real-time seizure detection and control.
The worldwide prevalence of epilepsy is approximately 1%, and 25% of epilepsy patients cannot be treated sufficiently by available therapies. Brain stimulation with closed-loop seizure control has recently been proposed as an innovative and effective alternative. ⋯ A wireless communication feature also provided flexibility for subjects freeing from the hassle of wires. Experimental data from freely moving rats supported the functional possibility of a real-time closed-loop seizure controller.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2010
Effect of ECG quality measures on piecewise-linear trend detection for telehealth decision support systems.
Fledgling clinical decision support systems (DSSs) are being designed on the false assumption that consistent, good-quality signals are created in the unsupervised telehealth environment, but it has in fact been shown that signal quality is often very poor. Hence, it is important to investigate the detrimental impact of failing to recognize erroneous clinical parameter values. ⋯ The application of the same artifact detection also results in a significant improvement in trend fitting, when compared to a fitting of the reference HR values, by reducing the mean RMSE value of the error in the trend fit from 2.14 BPM to 0.78 BPM and standard error from 0.49 BPM to 0.10 BPM. As trend detection will be a component of future telehealth decision support systems, signal quality measures for unsupervised measurements are of paramount importance.