In vitro evaluation of an axial flow pump: mock-pump interaction and an approach to control.

Continuous flow pump support has emerged as an alternative therapy in patients with congestive heart failure. For long-term applications, it is important to have a control system that changes the pump function according to the physiological conditions of the patient, thereby preventing risk situations. In the early stages of development, the evaluation of control algorithms for artificial blood pumps can be done in vitro using cardiovascular mock systems. A systemic cardiovascular mock loop was constructed and an axial flow pump was connected to it. The level of pump assistance was estimated using a pulsatility index (IPAo) obtained from the aortic pressure wave. An IPAo proportional-integral control system was implemented and its responses to peripheral resistance and systemic compliance changes were evaluated. IPAo is an indicator of the assistance level of a continuous flow pump operated at constant speed. The IPAo control algorithm responds by increasing the pump speed when peripheral resistance or systemic compliance is reduced. Control system operation around an IPAo fixed value provides a safety point for pump operation by maintaining aortic pressure pulsatility and avoiding ventricular suction. In vitro experimental results show that the IPAo can be taken into consideration in multiobjective control algorithm designs.

Prediction of epileptic seizures using accumulated energy in a multiresolution framework.

Records of brain electrical activity from intracranial EEG of four patients with different types of epilepsy are analyzed to predict the epileptic seizure onset. A method based on the evolution of the accumulated energy using wavelet analysis is introduced. This is an efficient method to predict epileptic seizures: from 13 preseizure signals, the seizure onset in 12 of those are predicted.

Nonlinear analyses of cell proliferation in the central nervous system reveal stochastic and deterministic components.

This paper analyzes the dynamics of cell proliferation in the developing central nervous system. Three different algorithms, Fano factor, Allan factor and detrended fluctuations analysis, are used to estimate de scaling exponent of space numerical series obtained by recording the number and position of proliferating cells along the cephalic-caudal axis of the system. It can be concluded that the dynamics of proliferation involves two component: (a) a random noncorrelated stochastic component representing a basal proliferating activity uniformly distributed along the cephalic-caudal axis and (b) a deterministic nonstationary component that imposes a defined global trend to the process. The deterministic nonstationary trend can be interpreted as the effect of a controlling influence operating along the cephalic-caudal axis. This result indicates that the proliferative activity is spatially organized along the cephalic-caudal axis of the system.

Detection of epileptic events in electroencephalograms using wavelet analysis.

This study deals with the problem of identification of epileptic events in electroencephalograms using multiresolution wavelet analysis. The following problems are analyzed: time localization and characterization of epileptiform events, and computational efficiency of the method. The algorithm presented is based on a polynomial spline wavelet transform. The multiresolution representation obtained from this wavelet transform and the corresponding digital filters derived allows time localization of epileptiform activity. The proposed detector is based on the multiresolution energy function. Electroencephalogram records from epileptic patients were analyzed, and results obtained are shown. Some comparisons with other methods are given.