IEEE transactions on bio-medical engineering
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IEEE Trans Biomed Eng · Feb 2006
Microfabricated cylindrical multielectrodes for neural stimulation.
The effects of spinal cord injuries are likely to be ameliorated with the help of functional electrical stimulation of the spinal cord, a technique that may benefit from a new style of electrode: the cylindrical multielectrode. This paper describes the specifications for, fabrication techniques for, and in vitro evaluation of cylindrical multielectrodes. ⋯ The charge delivery capacity was determined by testing with safe (< or = 0.6 mC/cm2) and damaging levels (> or = 0.8 mC/cm2) of charge density. The results of these tests suggest that this electrode design could be used to stimulate neurons in the ventral horn of the spinal cord.
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IEEE Trans Biomed Eng · Jan 2006
Coupling arterial windkessel with peripheral vasomotion: modeling the effects on low-frequency oscillations.
Arterial pressure (AP) and heart rate (HR) waves have long been recognized as an important sign of cardiovascular regulation, however, the underlying interactions involving vasomotion, arterial mechanisms and neural regulation have not been clarified. With the aid of simple dynamical models consisting of active peripheral vascular districts (PVDs) fed by a compliant/resistant arterial tree, the relationship between local AP and flow and systemic AP waves were analyzed. A PVD was described as a nonlinear flow regulation loop. ⋯ The partial disruption of phase opposition by a common neural drive oscillating at a LF proximal to that of the PVDs unveiled LF waves in AP. Also, several PVDs with randomly different natural frequencies displayed a tendency to reciprocal cancellation, while a limited neurally induced phase alignment unmasked LF oscillations at systemic level. It is concluded that vasomotion, arterial compliances and, neural drives are all elements which may cooperate in forming AP waves.
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IEEE Trans Biomed Eng · Jan 2006
Clinical TrialHeart rate characteristics monitoring for neonatal sepsis.
While heart rate variability has been measured in many clinical settings and has offered insights into how HR is controlled, rarely has it offered unique information that has led to changes in patient management. We review our experience in developing continuous HR characteristics monitoring to aid in the early diagnosis of sepsis in premature infants in the neonatal intensive care unit. A predictive algorithm, developed at one center and validated at another, has led to diagnosis and treatment of this subacute and potentially catastrophic illness prior to appearance of symptoms of severe illness.
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IEEE Trans Biomed Eng · Jan 2006
Individual time-dependent spectral boundaries for improved accuracy in time-frequency analysis of heart rate variability.
Heart rate variability (HRV) is a major noninvasive technique for evaluating the autonomic nervous system (ANS). Use of time-frequency approach to analyze HRV allows investigating the ANS behavior from the power integrals, as a function of time, in both steady-state and non steady-state. Power integrals are examined mainly in the low-frequency and the high-frequency bands. ⋯ In order to determine the dynamic boundaries of the frequency bands more accurately, especially during autonomic challenges, we developed an algorithm for the detection of individual time-dependent spectral boundaries (ITSB). The ITSB was tested on recordings from a series of standard autonomic maneuvers with rest periods between them, and the response to stand was compared to the known physiological response. A major advantage of the ITSB is the ability to reliably define the mid-frequency range, which provides the potential to investigate the physiologic importance of this range.
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IEEE Trans Biomed Eng · Dec 2005
Decomposition of three-dimensional medical images into visual patterns.
In this paper, we present a method for the decomposition of a volumetric image into its most relevant visual patterns, which we define as features associated to local energy maxima of the image. The method involves the clustering of a set of predefined bandpass energy filters according to their ability to segregate the different features in the image, thus generating a set of composite-feature detectors tuned to the specific visual patterns present in the data. Clustering is based on a measure of statistical dependence between pairs of frequency features. We will illustrate the applicability of the method to the initialization of a three-dimensional geodesic active model.