Patrick Karasinski

Learn More
Two multilayer neural networks were designed to discriminate vigilance states (waking, paradoxical sleep, and non-REM sleep) in the rat using a single parieto-occipital EEG derivation. After filtering (bandwidth 3.18-25 Hz) and digitization at 512 HZ, the EEG signal was segmented into eight second epochs. Five variables (three statistical, two temporal)(More)
New methods of data processing combined with advances in computer technology have revolutionized monitoring of patients under anesthesia. The development of systems based on analysis of brain electrical activity (EEG or evoked potentials) by neural networks has provided impetus to many investigators. Though not claiming to be the end-all in patient(More)
The time course of drug abstinence is not readily amenable to examination using intermittent observations, because abstinence is known to interfere with circadian rhythms of general activity. Accordingly, we propose a model for continuous assessment of spontaneous withdrawal without any intervention by the investigator. This model is based on the automatic(More)
A new method of analysis of sleep in the rat based on the electrocorticogram (ECoG) is described. Three states, awake (W), nonrapid eye movement (NREM) and rapid eye movement (REM) sleep are automatically classified by the system. After amplification of the ECoG over a restricted bandwidth (3.18-25 Hz) and sampling at 512 Hz, the data are processed in(More)
In this paper, we present a new computerised technique for the automatic construction of the latency intensity curve (LI curve). We take a pattern recognition approach determined by a priori information. We use knowledge gained from the audiogram and from physiological considerations. Therefore, we consider all recordings at different intensities as well as(More)
  • 1