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Karimoi et al., 2014 - Google Patents

EEG signal classification using Bayes and Naïve Bayes Classifiers and extracted features of Continuous Wavelet Transform

Karimoi et al., 2014

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Document ID
2225315417130689446
Author
Karimoi R
Khalilzadeh M
Hossinezadeh A
Karimoi A
Publication year
Publication venue
Majlesi Journal of Multimedia Processing

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Snippet

ABSTRACT in this paper, we recommend a method of the signal processing for analyzing EEG. To this end,, the signal using the continuous wavelet transform (CWT) is decomposed into dominant scales and a set of statistical features is extracted from these scales, which …
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Classifications

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    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235Details of waveform analysis
    • A61B5/7264Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • A61B5/7267Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems involving training the classification device
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
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    • A61B5/7235Details of waveform analysis
    • A61B5/7253Details of waveform analysis characterised by using transforms
    • A61B5/726Details of waveform analysis characterised by using transforms using Wavelet transforms
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    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6232Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
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    • A61B5/40Detecting, measuring or recording for evaluating the nervous system
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    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • G06K9/6268Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
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    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6228Selecting the most significant subset of features
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    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
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    • A61B5/04Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0476Electroencephalography
    • A61B5/048Detecting the frequency distribution of signals
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    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
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    • A61B5/024Detecting, measuring or recording pulse rate or heart rate
    • A61B5/02411Detecting, measuring or recording pulse rate or heart rate of foetuses

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