Jirí Wild

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Proper classification of action potentials from extracellular recordings is essential for making an accurate study of neuronal behavior. Many spike sorting algorithms have been presented in the technical literature. However, no comparative analysis has hitherto been performed. In our study, three widely-used publicly-available spike sorting algorithms(More)
Both animal studies and studies using deep brain stimulation in humans have demonstrated the involvement of the subthalamic nucleus (STN) in motivational and emotional processes; however, participation of this nucleus in processing human emotion has not been investigated directly at the single-neuron level. We analyzed the relationship between the neuronal(More)
Changes in the ECG ST segment are often observed in patients with myocardial ischaemia. However, non-ischaemic changes in ST level are also common thereby limiting ischaemia detection accuracy. The aim of this study was to devise an algorithm and determine its accuracy in distinguishing between ischaemic and non-ischaemic changes in the ECG ST-segment,(More)
This paper focuses on wrapper-based feature selection for a 1-nearest neighbor classifier. We consider in particular the case of a small sample size with a few hundred instances, which is common in biomedical applications. We propose a technique for calculating the complete bootstrap for a 1-nearest-neighbor classifier (i.e., averaging over all desired(More)
The oculomotor role of the basal ganglia has been supported by extensive evidence, although their role in scanning eye movements is poorly understood. Nineteen Parkinsońs disease patients, which underwent implantation of deep brain stimulation electrodes, were investigated with simultaneous intraoperative microelectrode recordings and single channel(More)
Appropriate detection of clean signal segments in extracellular microelectrode recordings (MER) is vital for maintaining high signal-to-noise ratio in MER studies. Existing alternatives to manual signal inspection are based on unsupervised change-point detection. We present a method of supervised MER artifact classification, based on power spectral density(More)
Three dimensional echocardiography offers the benefit of non-invasive measurement of chamber volume at the cost of increased effort of data handling. Automated or semi-automated image analysis may help to reduce manual effort but can embody assumptions and limitations which have a significant effect on results. We used a laboratory balloon phantom to study(More)
Manual measurement of left ventricular volume from 3D echocardiographs is time consuming, and there is a clinical need for automatic methods. We describe a semi-automatic method which uses a 3D image gradient operator and a short-axis boundary detector. Six patients with cardiomyopathy were studied using 3D echocardiography and the images were analysed to(More)
Removal of plaque and debris from interproximal surfaces during toothbrushing has generally been difficult to achieve, in large part because traditional flat-bristled toothbrushes do not offer good interproximal penetration. As a result, a number of varying bristle designs have been developed, with the rippled-design brush shown to be particularly effective(More)
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