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

Vrindavanam et al., 2021 - Google Patents

Machine learning based COVID-19 cough classification models-a comparative analysis

Vrindavanam et al., 2021

View PDF
Document ID
13091348764229353703
Author
Vrindavanam J
Srinath R
Shankar H
Nagesh G
Publication year
Publication venue
2021 5th International Conference on Computing Methodologies and Communication (ICCMC)

External Links

Snippet

COVID-19 continues to be a global pandemic and many a technological intervention are already in place for identification of COVID-19 patients. The paper focuses on the contactless detection of COVID-19 patients by analyzing their respective cough audio …
Continue reading at www.academia.edu (PDF) (other versions)

Classifications

    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00
    • G10L25/48Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 specially adapted for particular use
    • G10L25/51Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 specially adapted for particular use for comparison or discrimination
    • G10L25/66Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 specially adapted for particular use for comparison or discrimination for extracting parameters related to health condition
    • 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
    • A61B5/7264Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L17/00Speaker identification or verification
    • G10L17/26Recognition of special voice characteristics, e.g. for use in lie detectors; Recognition of animal voices
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L17/00Speaker identification or verification
    • G10L17/04Training, enrolment or model building
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
    • G06F19/345Medical expert systems, neural networks or other automated diagnosis
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00Speech recognition
    • G10L15/08Speech classification or search
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B7/00Instruments for auscultation
    • A61B7/02Stethoscopes
    • A61B7/04Electric stethoscopes
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/08Detecting, measuring or recording devices for evaluating the respiratory organs

Similar Documents

Publication Publication Date Title
Vrindavanam et al. Machine learning based COVID-19 cough classification models-a comparative analysis
Hassan et al. COVID-19 detection system using recurrent neural networks
Mouawad et al. Robust detection of COVID-19 in cough sounds: using recurrence dynamics and variable Markov model
Pramono et al. A cough-based algorithm for automatic diagnosis of pertussis
Vhaduri et al. Nocturnal cough and snore detection in noisy environments using smartphone-microphones
Jakovljević et al. Hidden markov model based respiratory sound classification
Mekyska et al. Robust and complex approach of pathological speech signal analysis
JP2023164839A (en) Method for analysis of cough sound using disease signature to diagnose respiratory disease
Liu et al. Detection of adventitious respiratory sounds based on convolutional neural network
Kranthi Kumar et al. COVID-19 disease diagnosis with light-weight CNN using modified MFCC and enhanced GFCC from human respiratory sounds
Anupam et al. Preliminary diagnosis of COVID-19 based on cough sounds using machine learning algorithms
Wei et al. A real-time robot-based auxiliary system for risk evaluation of COVID-19 infection
Grønnesby et al. Feature extraction for machine learning based crackle detection in lung sounds from a health survey
Singh et al. Short unsegmented PCG classification based on ensemble classifier
Patel et al. Lung Respiratory Audio Prediction using Transfer Learning Models
Usman et al. Heart rate detection and classification from speech spectral features using machine learning
Windmon et al. On Detecting Chronic Obstructive Pulmonary Disease (COPD) Cough using Audio Signals Recorded from Smart-Phones.
Gupta et al. Cough sound based COVID-19 detection with stacked ensemble model
Engin et al. Extraction of low-dimensional features for single-channel common lung sound classification
Das et al. Diagnosis of COVID-19 Using Auditory Acoustic Cues.
AL-Dhief et al. Voice Pathology Detection Using Decision Tree Classifier
Pessoa et al. Pediatric Respiratory Sound Classification Using a Dual Input Deep Learning Architecture
Campana et al. L 3-Net Deep Audio Embeddings to Improve COVID-19 Detection from Smartphone Data
EP4256553A1 (en) Detection of cognitive impairment
Bensid et al. Efficient Covid-19 disease diagnosis based on cough signal processing and supervised machine learning