Automatic Sleep Scoring Stages using Real-Time EMG Signals
نویسندگان
چکیده
منابع مشابه
Automatic Sleep Stages Detection Based on EEG Signals Using Combination of Classifiers
Sleep stages classification is one of the most important methods for diagnosis in psychiatry and neurology. In this paper, a combination of three kinds of classifiers are proposed which classify the EEG signal into five sleep stages including Awake, N-REM (non-rapid eye movement) stage 1, N-REM stage 2, N-REM stage 3 and 4 (also called Slow Wave Sleep), and REM. Twenty-five all night recordings...
متن کاملautomatic sleep stages detection based on eeg signals using combination of classifiers
sleep stages classification is one of the most important methods for diagnosis in psychiatry and neurology. in this paper, a combination of three kinds of classifiers are proposed which classify the eeg signal into five sleep stages including awake, n-rem (non-rapid eye movement) stage 1, n-rem stage 2, n-rem stage 3 and 4 (also called slow wave sleep), and rem. twenty-five all night recordings...
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In this paper, a new method for automatic sleep stage classification based on time-frequency image (TFI) of electroencephalogram (EEG) signals is proposed. Automatic classification of sleep stages is an important part for diagnosis and treatment of sleep disorders. The smoothed pseudo Wigner-Ville distribution (SPWVD) based time-frequency representation (TFR) of EEG signal has been used to obta...
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BACKGROUND Electromyography (EMG) is the study of muscle function through the inquiry of electrical signals that the muscles emanate. EMG signals collected from the surface of the skin (Surface Electromyogram: sEMG) can be used in different applications such as recognizing musculoskeletal neural based patterns intercepted for hand prosthesis movements. Current systems designed for controlling t...
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We present a method for the detection of sleep stages using the EEG (electroencephalogram). The method consists of four steps: segmentation; parameter extraction; cluster analysis; and classi cation. The parameters we compared were the parameters of Hjorth, the harmonic parameters and the relative band energy. For cluster analysis we used a modi ed version of the K-means algorithm. It is shown ...
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ژورنال
عنوان ژورنال: International Journal of Research in Engineering, Science and Management
سال: 2021
ISSN: 2581-5792
DOI: 10.47607/ijresm.2021.465