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In this paper, a new codebook based learning method, Adaptive Multicodebook Fuzzy Neuro Generalized Learning Vector Quantization (FNGLVQ), is proposed. The main contribution of this paper is the use of multi codebook which is adaptive in nature to the distribution of the data. The number and position of the codebook is determined through clustering approach. In this research, a decision tree based...
Commonly sleep stages detection can be done using electroencephalogram (EEG) that is recorded in hospitals using Polysomnography (PSG) systems. PSG not only records brain signal but also electrocardiogram (ECG). In this paper an automatic sleep stages detection using FNGLVQ algorithm based solely on ECG signal is reported. We have compared two neural network algorithms' accuracies and implemented...
Background: The prevalence of sleep‐disordered breathing (SDB) in children with Chiari malformation type II (CM‐II), a known association of neural tube defects (NTD), has not been well documented. The aim of the present study was to assess the prevalence and possible predictive factors of SDB in patients with CM‐II.
Methods: The study included all patients with documented CM‐II who were routinely...
Sleep is an essential phase in human circadian rhythm with importance in restoring human vigour and vitality. Conventional sleep examination is done using Polysomnography with many sensors connected to various parts of human body. Recently, research in sleep is geared toward alternative feasibility of using only ECG signal. In this research, sleep stages classification using only features derived...
In this paper, a portable, easy to use, and real-time sleep stage classification device is presented. A simpler approach using raw features of ECG signals for sleep stage classification has been developed. Only one lead of ECG signal is required for operation which makes the device easily operable and only requiring user to attach 3 electrodes to the body. The device is constructed with singleboard...
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