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

Sunjing et al., 2017 - Google Patents

Heart sound signals based on CNN classification research

Sunjing et al., 2017

Document ID
15124054289670518483
Author
Sunjing
Lifu K
Weilian W
Songshaoshuai
Publication year
Publication venue
Proceedings of the 6th International Conference on Bioinformatics and Biomedical Science

External Links

Snippet

Heart sound signal can provide complex physiological and pathological information while diagnosing CHD (congenital heart disease). The main procedure includes pretreatment, Envelope extraction, classification and recognition. Pretreatment includes normalization, de …
Continue reading at dl.acm.org (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
    • A61B5/0402Electrocardiography, i.e. ECG
    • A61B5/0452Detecting specific parameters of the electrocardiograph cycle
    • 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
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • 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

Similar Documents

Publication Publication Date Title
Khan et al. Automatic heart sound classification from segmented/unsegmented phonocardiogram signals using time and frequency features
Li et al. Feature extraction and classification of heart sound using 1D convolutional neural networks
Nabih-Ali et al. A review of intelligent systems for heart sound signal analysis
Meziani et al. Analysis of phonocardiogram signals using wavelet transform
CN108470156B (en) Heart sound signal classification and identification method
CN108742697B (en) Heart sound signal classification method and terminal equipment
CN109833034A (en) The method and device of blood pressure data is extracted in a kind of pulse wave signal
CN101919704B (en) Heart sound signal positioning and segmenting method
CN113361385A (en) Heart sound classification method and system, readable storage medium and electronic device
Misal et al. Denoising of PCG signal by using wavelet transforms
Zeng et al. Automatic detection of heart valve disorders using Teager–Kaiser energy operator, rational-dilation wavelet transform and convolutional neural networks with PCG signals
Tariq et al. Multimodal lung disease classification using deep convolutional neural network
Sunjing et al. Heart sound signals based on CNN classification research
Elgendi et al. Detection of Heart Sounds in Children with and without Pulmonary Arterial Hypertension―Daubechies Wavelets Approach
Tariq et al. Automatic multimodal heart disease classification using phonocardiogram signal
CN116975693B (en) Method and system for detecting heart sounds based on deep learning and heterogeneous integration strategy
Akbari et al. Systolic murmurs diagnosis improvement by feature fusion and decision fusion
Kouras et al. Wavelet based segmentation and time-frequency caracterisation of some abnormal heart sound signals
Kumar et al. An adaptive approach to abnormal heart sound segmentation
CN116942172A (en) A wavelet dual-channel single-lead ECG denoising method based on encoding and decoding structure
Arora et al. A fusion framework based on cepstral domain features from phonocardiogram to predict heart health status
Yusuf et al. Feature Extraction of ECG Signals using Discrete Wavelet Transform and MFCC
Atteeq et al. Fetus heart beat extraction from mother's PCG using blind source separation
Moukadem et al. Study of Two Feature Extraction Methods to Distinguish between the First and the Second Heart Sounds.
Misal et al. Comparison of wavelet transforms for denoising and analysis of PCG signal