[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Chawla et al., 2006 - Google Patents

Modeling and feature extraction of ECG using independent component analysis

Chawla et al., 2006

Document ID
8926955390276862631
Author
Chawla M
Verma H
Kumar V
Publication year

External Links

Snippet

Independent Component Analysis (ICA) is a new technique for analyzing multi-variant data. The idea is to replace PCA (Principal component analysis), which is used as the preprocessing of many ICA algorithms. The purpose of applying ICA will be to segregate …
Continue reading at digital-library.theiet.org (other versions)

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04—Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0402—Electrocardiography, i.e. ECG
    • A61B5/0452—Detecting specific parameters of the electrocardiograph cycle
    • A61B5/04525—Detecting specific parameters of the electrocardiograph cycle by template matching
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7239—Details of waveform analysis using differentiation including higher order derivatives
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04—Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0476—Electroencephalography
    • A61B5/048—Detecting the frequency distribution of signals
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04—Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/04012—Analysis of electro-cardiograms, electro-encephalograms, electro-myograms
    • A61B5/04017—Analysis of electro-cardiograms, electro-encephalograms, electro-myograms by using digital filtering
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04—Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0488—Electromyography
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7203—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7232—Signal processing specially adapted for physiological signals or for diagnostic purposes involving compression of the physiological signal, e.g. to extend the signal recording period
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radiowaves
    • A61B5/053—Measuring electrical impedance or conductance of a portion of the body
    • A61B5/0531—Measuring skin impedance
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00496—Recognising patterns in signals and combinations thereof
    • G06K9/00503—Preprocessing, e.g. filtering
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00496—Recognising patterns in signals and combinations thereof
    • G06K9/00536—Classification; Matching

Similar Documents

Publication Publication Date Title
Elhaj et al. Arrhythmia recognition and classification using combined linear and nonlinear features of ECG signals
Chawla A comparative analysis of principal component and independent component techniques for electrocardiograms
Niknazar et al. Fetal ECG extraction by extended state Kalman filtering based on single-channel recordings
Abibullaev et al. A new QRS detection method using wavelets and artificial neural networks
Milanesi et al. Independent component analysis applied to the removal of motion artifacts from electrocardiographic signals
Malek et al. Automated detection of premature ventricular contraction in ECG signals using enhanced template matching algorithm
Kumar et al. Optimal selection of wavelet function and decomposition level for removal of ECG signal artifacts
Krishnaveni et al. Comparison of independent component analysis algorithms for removal of ocular artifacts from electroencephalogram
Prashar et al. Semiautomatic detection of cardiac diseases employing dual tree complex wavelet transform
Gupta et al. A simplistic and novel technique for ECG signal pre-processing
Wang et al. Fetal ECG signal extraction from long-term abdominal recordings based on adaptive QRS removal and joint blind source separation
Telezhkin et al. Wavelet-conversion in electrocardio signal processing
Diery et al. Automated ECG diagnostic P-wave analysis using wavelets
Darsana et al. Extracting Fetal ECG Signals Through a Hybrid Technique Utilizing Two Wavelet-Based Denoising Algorithms
Chawla Parameterization and R‐peak error estimations of ECG signals using independent component analysis
Chawla et al. Modeling and feature extraction of ECG using independent component analysis
Chawla Detection of indeterminacies in corrected ECG signals using parameterized multidimensional independent component analysis
Rahul et al. An enhanced T-wave delineation method using phasor transform in the electrocardiogram
Dembrani et al. Accurate detection of ECG signals in ECG monitoring systems by eliminating the motion artifacts and improving the signal quality using SSG filter with DBE
Petrėnas et al. Extraction of f-waves in electrocardiograms using echo state network based nonlinear adaptive filters
Algumaei et al. Novel approach for ECG separation using adaptive constrained IVABMGGMM
Khandait et al. ECG signal processing using classifier to analyses cardiovascular disease
Gupta et al. ECG signal analysis using autoregressive modelling with and without baseline wander
Abdi Atrial fibrillation fingerprinting
Desai Automated detection of cardiac health condition using linear techniques