Nothing Special   »   [go: up one dir, main page]

Azami et al., 2012 - Google Patents

A new adaptive signal segmentation approach based on Hiaguchi's fractal dimension

Azami et al., 2012

View PDF
Document ID
14852436317682393752
Author
Azami H
Khosravi A
Malekzadeh M
Sanei S
Publication year
Publication venue
International Conference on Intelligent Computing

External Links

Snippet

In many non-stationary signal processing applications such as electroencephalogram (EEG), it is better to divide the signal into smaller segments during which the signals are pseudo-stationary. Therefore, they can be considered stationary and analyzed separately. In …
Continue reading at www.researchgate.net (PDF) (other versions)

Classifications

    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0476Electroencephalography
    • A61B5/048Detecting the frequency distribution of signals
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • 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
    • A61B5/7253Details of waveform analysis characterised by using transforms
    • A61B5/7257Details of waveform analysis characterised by using transforms using Fourier transforms
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • 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
    • A61B5/7253Details of waveform analysis characterised by using transforms
    • A61B5/726Details of waveform analysis characterised by using transforms using Wavelet transforms
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0402Electrocardiography, i.e. ECG
    • A61B5/0452Detecting specific parameters of the electrocardiograph cycle
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00496Recognising patterns in signals and combinations thereof
    • G06K9/00503Preprocessing, e.g. filtering
    • G06K9/0051Denoising
    • G06K9/00516Denoising by applying a scale-space analysis, e.g. using wavelet analysis
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/04012Analysis of electro-cardiograms, electro-encephalograms, electro-myograms
    • A61B5/04017Analysis of electro-cardiograms, electro-encephalograms, electro-myograms by using digital filtering
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • 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
    • A61B5/7239Details of waveform analysis using differentiation including higher order derivatives
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0488Electromyography
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • 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
    • A61B5/7203Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00496Recognising patterns in signals and combinations thereof
    • G06K9/00536Classification; Matching
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/05Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radiowaves
    • A61B5/053Measuring electrical impedance or conductance of a portion of the body
    • A61B5/0531Measuring skin impedance
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/04001Detecting, measuring or recording bioelectric signals of the body of parts thereof adapted to neuroelectric signals, e.g. nerve impulses
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • 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
    • A61B5/7225Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • 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
    • A61B5/7232Signal processing specially adapted for physiological signals or for diagnostic purposes involving compression of the physiological signal, e.g. to extend the signal recording period
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/40Detecting, measuring or recording for evaluating the nervous system
    • A61B5/4076Diagnosing or monitoring particular conditions of the nervous system
    • A61B5/4094Diagnosing or monitoring seizure diseases, e.g. epilepsy
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/44Detecting, measuring or recording for evaluating the integumentary system, e.g. skin, hair or nails
    • A61B5/441Skin evaluation, e.g. for skin disorder diagnosis

Similar Documents

Publication Publication Date Title
Kaur et al. A review on analysis of EEG signals
Islam et al. A wavelet-based artifact reduction from scalp EEG for epileptic seizure detection
Bono et al. Hybrid wavelet and EMD/ICA approach for artifact suppression in pervasive EEG
Dora et al. Adaptive single-channel EEG artifact removal with applications to clinical monitoring
Yadav et al. Model-based seizure detection for intracranial EEG recordings
Daud et al. Wavelet based filters for artifact elimination in electroencephalography signal: A review
JP7492572B2 (en) Medical system and method for detecting changes in electrophysiological evoked potentials - Patents.com
Ashraf et al. Variational mode decomposition for surface and intramuscular EMG signal denoising
Tibdewal et al. Power line and ocular artifact denoising from EEG using notch filter and wavelet transform
Allen A frequency domain Hampel filter for blind rejection of sinusoidal interference from electromyograms
Sheoran et al. Methods of denoising of electroencephalogram signal: A review
Uthayakumar et al. Multifractal-wavelet based denoising in the classification of healthy and epileptic EEG signals
Ren et al. MUAP extraction and classification based on wavelet transform and ICA for EMG decomposition
Sun Classification of imagery motor EEG data with wavelet denoising and features selection
Sharma et al. EMG classification using wavelet functions to determine muscle contraction
Al-Salman et al. Detection of k-complexes in EEG signals using a multi-domain feature extraction coupled with a least square support vector machine classifier
Azami et al. A new adaptive signal segmentation approach based on Hiaguchi’s fractal dimension
Ren et al. Noise reduction based on ICA decomposition and wavelet transform for the extraction of motor unit action potentials
Hu et al. Single-channel EEG signal extraction based on DWT, CEEMDAN, and ICA method
Pereyra et al. Wavelet Jensen–Shannon divergence as a tool for studying the dynamics of frequency band components in EEG epileptic seizures
Yong et al. Generalized morphological component analysis for EEG source separation and artifact removal
Kaushal et al. Better approach for denoising EEG signals
Karagiannis et al. Biomedical time series processing and analysis methods: The case of empirical mode decomposition
Behera et al. A statistical approach for ocular artifact removal in brain signals
Pramudita et al. Removing ocular artefacts in EEG signals by using combination of complete EEMD (CEEMD)—independent component analysis (ICA) based outlier data