IEEE transactions on bio-medical engineering
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IEEE Trans Biomed Eng · Jul 2006
Simulation analysis of conduction block in myelinated axons induced by high-frequency biphasic rectangular pulses.
Nerve conduction block induced by high-frequency biphasic rectangular pulses was analyzed using a lumped circuit model of the myelinated axon based on Frankenhaeuser-Huxley (FH) equations. At the temperature of 37 degrees C, axons of different diameters (2-20 microm) can be blocked completely at supra-threshold intensities when the stimulation frequency is above 10 kHz. However, at stimulation frequencies between 6 kHz and 9 kHz, both nerve block and repetitive firing of action potentials can be observed at different stimulation intensities. ⋯ Larger diameter axons have a lower threshold intensity to induce conduction block. When temperature is reduced from 37 degrees C to 20 degrees C, the lowest frequency to completely block large axons (diameters 10-20 microm) decreased from 8 kHz to 4 kHz. This simulation study can guide future animal experiments as well as optimize stimulation waveforms for electrical nerve block in clinical applications.
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IEEE Trans Biomed Eng · Jul 2006
Clinical TrialWeaning from mechanical ventilation: a retrospective analysis leading to a multimodal perspective.
Practitioners' decision for mechanical aid discontinuation is a challenging task that involves a complete knowledge of a great number of clinical parameters, as well as its evolution in time. Recently, an increasing interest on respiratory pattern variability as an extubation readiness indicator has appeared. Reliable assessment of this variability involves a set of signal processing and pattern recognition techniques. ⋯ The contribution of this analysis is threefold: 1) to serve as a review of the state of the art on the so-called weaning problem from a signal processing point of view; 2) to provide insight into the applied processing techniques and how they fit into the problem; 3) to propose additional methods and further processing in order to improve breathing pattern regularity assessment and weaning readiness decision. Results on experimental data show that sample entropy outperforms other complexity assessment methods and that multidimensional classification does improve weaning prediction. However, the obtained performance may be objectionable for real clinical practice, a fact that paves the way for a multimodal signal processing framework, including additional high-quality signals and more reliable statistical methods.
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IEEE Trans Biomed Eng · Jul 2006
Controlled Clinical TrialAutomated left ventricular segmentation in cardiac MRI.
We present an automated left ventricular (LV) myocardial boundary extraction method. Automatic localization of the LV is achieved using a motion map and an expectation maximization algorithm. The myocardial region is then segmented using an intensity-based fuzzy affinity map and the myocardial contours are extracted by cost minimization through a dynamic programming approach. The results from the automated algorithm compared against the experienced radiologists using Bland and Altman analysis were found to have consistent mean bias of 7% and limits of agreement comparable to the inter-observer variability inherent in the manual method.
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IEEE Trans Biomed Eng · Jul 2006
Controlled Clinical TrialA robust method for ECG-based estimation of the respiratory frequency during stress testing.
A robust method is presented for electrocardiogram (ECG)-based estimation of the respiratory frequency during stress testing. Such ECGs contain highly nonstationary noise and exhibit changes in QRS morphology which, when combined with the dynamic nature of the respiratory frequency, make most existing methods break down. The present method exploits the oscillatory pattern of the rotation angles of the heart's electrical axis as induced by respiration. ⋯ The method is evaluated by means of both simulated signals, and ECG/airflow signals recorded from 14 volunteers and 20 patients during stress testing. The resulting respiratory frequency estimation error is, for simulated signals, equal to 0.5% +/- 0.2%, mean +/- SD (0.002 +/- 0.001 Hz), whereas the error between respiratory frequencies of the ECG-derived method and the airflow signals is 5.9% +/- 4% (0.022 +/- 0.016Hz). The results suggest that the method is highly suitable for analysis of noisy ECG signals recorded during stress testing.
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Existing approaches used to develop compact low-power multichannel wireless neural recording systems range from creating custom-integrated circuits to assembling commercial-off-the-shelf (COTS) PC-based components. Custom-integrated-circuit designs yield extremely compact and low-power devices at the expense of high development and upgrade costs and turn-around times, while assembling COTS-PC-technology yields high performance at the expense of large system size and increased power consumption. To achieve a balance between implementing an ultra-compact custom-fabricated neural transceiver and assembling COTS-PC-technology, an overlay of a neural interface upon the TinyOS-based MICA2 platform is described. ⋯ The neural signals are received and forwarded to a client PC over a serial connection. This data rate can be divided for recording on up to 6 channels, with a resolution of 8 bits/sample. This work demonstrates the strengths and limitations of the TinyOS-based sensor technology as a foundation for chronic remote biological monitoring applications and, thus, provides an opportunity to create a system that can leverage from the frequent networking and communications advancements being made by the global TinyOS-development community.