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Biomedical subjects

P Nickolls

Publications and source records attributed to P Nickolls.

5 recordsLinked to original sources
PubMed2004

Forces consistent with plateau-like behaviour of spinal neurons evoked in patients with spinal cord injuries.

Percutaneous electrical stimulation over tibialis anterior and triceps surae was performed in 14 patients with traumatic spinal cord injury (SCI) to look for evidence that 'extra contractions' can develop, beyond those due to activation of the motor axons beneath the stimulating electrodes. Criteria for the extra contractions included marked asymmetry of force with respect to stimulation, progressively rising force during stimulation of constant amplitude and frequency, and force remaining high after stimulation frequency had returned to the control level following a high-frequency burst. Twelve of the 14 patients showed evidence of such behaviour, more frequently in triceps surae than tibialis anterior. Force or electromyographic activity commonly outlasted the stimulation in these patients. There was no apparent correlation between the completeness or level of injury and the ability to induce the behaviour. Evidence of force potentiation and 'habituation' was also seen. Eleven of the 14 patients exhibited hyper-reflexia and reported spontaneous spasms, but there was no obvious association with the extra contractions. It is concluded that non-classical behaviour of neurons within the spinal cord can contribute to the extra contractions evoked by electrical stimulation over muscles in spinal cord-injured subjects. This central contribution is less easy to obtain than in intact healthy subjects, all of whom showed the phenomenon. These contractions are consistent with the activation of plateau potentials in spinal neurons and, if so, plateau potentials may contribute to a patient's clinical manifestations.

Adolescent↗
PubMed1993

Implantable cardioverter defibrillator electrogram recognition with a multilayer perceptron.

With the continuing development of new pacing and shock modalities, implantable cardioverter defibrillators must be able to recognize an increasingly wider range of arrhythmias so that therapy is delivered in an optimal way. Current rate-based systems can no longer meet this need. It is, therefore, necessary to develop new techniques that consider waveform morphology in addition to heart rate. Any developments, however, must be compatible with the strict power and space constraints imposed by implantable devices. Artificial neural networks offer a potentially viable way of meeting these objectives. In this article an artificial neural network based approach to the classification of arrhythmias from the ventricular intracardiac electrogram is described. It performs its classification on a set of easily extracted features that characterize waveform morphology and heart rate. Simulations showed that the artificial neural network performed better than a rate-based scheme similar to those used in some commercial devices.

Algorithms↗
PubMed1988

Interval-coded texture features for artifact rejection in automated cervical cytology.

In order to improve the separation between abnormal cells and noncellular artifacts in the CERVIFIP automated cervical cytology prescreening system, 22 different object texture features were investigated. The features were all statistical parameters of the pixel density histograms or one-dimensional filtered values of central and border regions of the object images. The features were calculated for 231 images (100 cells and 131 artifacts) detected as Suspect Cells by the current CERVIFIP and were then tested in hierarchical and linear discriminant classifiers. After selecting the two best features for use in a hierarchical classifier, 83% correct classification was achieved. One of these features was specifically designed to remove poorly focused objects. With maximum likelihood discrimination using all 22 features, an overall correct classification rate of 90% was obtained.

Cell Division↗
PubMed1987

Development of an imaging flow cytometer.

A cell analyzer that combines the characteristics of image cytometry and flow cytometry is being designed and constructed at the University of Sydney. This paper describes the image acquisition and processing components and some preliminary applications. Cells stained by a fluorescent dye and suspended in a liquid medium are conveyed by a hydraulic system to a flow channel assembly, where they are detected and illuminated by a laser beam. A two-dimensional charge-coupled device is used to acquire the cell images. Image processing and classification is to be carried out by a special-purpose computer comprising an array of four conventional microprocessors and a highly parallel processor consisting of an array of 32 X 32 processing elements. The analyzer will be capable of using morphologic, immunologic and biochemical information to classify and sort up to 500 cells per second. Because of its unique characteristics, the instrument will be of particular use in tumor heterogeneity studies.

Flow Cytometry↗