The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In the past several studies have evaluated the human sleep onset (wake to sleep transition) using the electroencephalographic (EEG) measurements. This paper has evaluated the detection accuracy of sleep stages for multiple features based on the EEG alpha activity, during SO in healthy, insomniac and schizophrenic patients. The features include topographic features such as Directed Transfer Function,...
Sleep spindle detection using supervised learning methods such as Artificial Neural Networks and Support Vector Machines had been researched in the past. Supervised learning methods such as the above are prone to overfitting problems. In this research paper, we explore the detection of sleep spindles using the Random Forest classifier which is known to over fit data to a much lower extent when compared...
Manual scoring of arousals is generally conducted by sleep experts in spite of being time-consuming and subjective. Our objective of this study was to develop an algorithm for automatic detection of sleep arousals without distinguishing between the types of arousal and sleep disorder groups. The processed and analysed data multiple overnight Polysomnography (PSG) recordings, consisting of 9 human...
This study examined the electroencephalogram functional connectivity (coherence) and effective connectivity (flow of information) of selected brain regions during three different attentive states: awake, meditation and drowsiness. For the estimation of functional connectivity (coherence), Welch and minimum variance distortionless response (MVDR) methods were compared. The MVDR coherence was found...
A comparison of coupling (information flow) and coherence (connectedness) of the brain regions between human awake, meditation and drowsiness states was carried out in this study. The Directed Transfer Function (DTF) method was used to estimate the coupling or brain's flow of information between different regions during each condition. Welch and Minimum Variance Distortionless Response (MVDR) methods...
The characterisation of functional interdependencies of the autonomic nervous system (ANS) stands an evergrowing interest to unveil electroencephalographic (EEG) and Heart Rate Variability (HRV) interactions. This paper presents a biosignal processing approach as a supportive computational resource in the estimation of sleep dynamics. The application of linear, non-linear methods and statistical tests...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.