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 2007
Real-time development of patient-specific alarm algorithms for critical care.
The state-of-the-art monitoring systems for critical care measure vital signs and generate alerts based on the logic of general patient population models, but they lack the capabilities of accurately correlating physiological data with clinical events and of adapting to individual patient's characteristics that do not fit the population models. This research examines the feasibility of developing patient-specific alarm algorithms in real time at the bedside and evaluates the potential of these algorithms in helping improve patient monitoring. Modular components that facilitate real-time development of alarm algorithms were added to a system that simultaneously collects physiological data and clinical annotations at the bedside. ⋯ The performance of patient-specific alarm algorithms improved as training data increased. Neural networks with eight hours of training data on average achieved a sensitivity of 0.96, a specificity of 0.99, a positive predictive value of 0.79, and an accuracy of 0.99; these figures were 0.84, 0.98, 0.72, and 0.98 respectively for the classification trees. These results suggest that real-time development of patient-specific alarm algorithms is feasible using machine learning techniques.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2007
Automatic identification of spike-wave events and non-convulsive seizures with a reduced set of electrodes.
Epileptiform activity in the brain, whether localized or generalized, constitutes an important category of abnormal electroencephalogram (EEG). Seizures are episodes of relatively brief disturbances of mental, motor or sensory activity caused by paroxysmal cerebral activity. They are not always accompanied by the characteristic convulsions that we commonly associate with the word epilepsy. ⋯ The proposed signal processing algorithm is based on the detection of spike-wave events obtained from a wavelet analysis of the EEG signal, combined with an analysis of the complexity of the EEG using fractal dimension estimates. We show that this algorithm has excellent sensitivity and specificity. In particular, the fractal analysis is a key factor in the removal of falsely detected spike-wave events (false positives) that can be caused by voluntary or involuntary artifacts such as fast eyelid flutter.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2007
Randomized Controlled TrialA new method for evaluating the performance of depth-of-hypnosis indices - the D-value.
An alternative statistic, the D-value, is presented for the evaluation of the performance of EEG-based depth-of-hypnosis measures against the Observers' Assessment of Alertness/Sedation scale. The measures considered here are spectral entropy, approximate entropy, Lempel-Ziv complexity and Higuchi fractal dimension. The study is based on recordings from 45 patients, divided into three groups of 15 recordings each. ⋯ All the patients received stepwise increased dose of propofol. The study shows that the D-value is a promising and flexible statistic for the evaluation of the discriminative power of the EEG measures with respect to the OAA/S scale. The D-value indicates well the dependence of the performance of the measures on the EEG frequency band as well as on remifentanil concentration.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2007
Cuffless and noninvasive measurement of systolic blood pressure, diastolic blood pressure, mean arterial pressure and pulse pressure using radial artery tonometry pressure sensor with concept of Korean traditional medicine.
Parameters for noninvasive diagnosis and monitoring of cardiovascular disease. We developed a new method to measure blood pressure (BP) noninvasively without cuff. In Korean traditional medicine, the degree of the pulse depth is one of the important criteria to diagnosis. ⋯ According to the American National Standard for Electronic or Automated Sphygmomanometers, the mean difference (MD) should be +/- 5mmHg or less with a standard deviation (SD) of +/- 8mmHg or less. Hence, the results of MAP and PP were within the limits for the AAMI SP 10 criteria and the results of SBP and DBP were not within the limits for the AAMI SP 10 criteria. The preliminary results indicate the results are quite reliable and promising.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2007
Real-time evaluation of patient monitoring algorithms for critical care at the bedside.
Rapid interpretation of physiological time-series data and accurate assessment of patient state are crucial to patient monitoring in critical care. Algorithms that use artificial intelligence techniques have the potential to help achieve these tasks, but their development requires well-annotated patient data. ⋯ The alarm annotations in real time at the bedside indicate that about 89% of these alarms were clinically-relevant true positives; 6% were true positives without clinical relevance; and 5% were false positives. These findings show an improved specificity of the alarm algorithms in the newer generation of bedside monitoring systems and demonstrate that the designed data acquisition system enables real-time evaluation of patient monitoring algorithms for critical care.