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

Windmon et al., 2018 - Google Patents

Tussiswatch: A smart-phone system to identify cough episodes as early symptoms of chronic obstructive pulmonary disease and congestive heart failure

Windmon et al., 2018

View PDF
Document ID
3383480885609293759
Author
Windmon A
Minakshi M
Bharti P
Chellappan S
Johansson M
Jenkins B
Athilingam P
Publication year
Publication venue
IEEE journal of biomedical and health informatics

External Links

Snippet

Chronic obstructive pulmonary disease (COPD) and congestive heart failure (CHF) are leading chronic health concerns among the aging population today. They are both typically characterized by episodes of cough that share similarities. In this paper, we design …
Continue reading at ieeexplore.ieee.org (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00
    • G10L25/48—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 specially adapted for particular use
    • G10L25/51—Speech 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
    • G10L25/66—Speech 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
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L17/00—Speaker identification or verification
    • G10L17/26—Recognition of special voice characteristics, e.g. for use in lie detectors; Recognition of animal voices
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B7/00—Instruments for auscultation
    • A61B7/02—Stethoscopes
    • A61B7/04—Electric stethoscopes
    • 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
    • A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/06—Creation of reference templates; Training of speech recognition systems, e.g. adaptation to the characteristics of the speaker's voice
    • G10L15/063—Training
    • G10L2015/0635—Training updating or merging of old and new templates; Mean values; Weighting
    • G10L2015/0636—Threshold criteria for the updating

Similar Documents

Publication Publication Date Title
Windmon et al. Tussiswatch: A smart-phone system to identify cough episodes as early symptoms of chronic obstructive pulmonary disease and congestive heart failure
Vhaduri et al. Nocturnal cough and snore detection in noisy environments using smartphone-microphones
Swarnkar et al. Automatic identification of wet and dry cough in pediatric patients with respiratory diseases
Hassan et al. COVID-19 detection system using recurrent neural networks
Pramono et al. A cough-based algorithm for automatic diagnosis of pertussis
Amrulloh et al. Automatic cough segmentation from non-contact sound recordings in pediatric wards
JP2023164839A (en) Method for analysis of cough sound using disease signature to diagnose respiratory disease
JP6435257B2 (en) Method and apparatus for processing patient sounds
Vhaduri Nocturnal cough and snore detection using smartphones in presence of multiple background-noises
Liu et al. Cough signal recognition with gammatone cepstral coefficients
Vrindavanam et al. Machine learning based COVID-19 cough classification models-a comparative analysis
Anupam et al. Preliminary diagnosis of COVID-19 based on cough sounds using machine learning algorithms
Ulukaya et al. Overcomplete discrete wavelet transform based respiratory sound discrimination with feature and decision level fusion
Singh et al. Short unsegmented PCG classification based on ensemble classifier
Tang et al. Automated signal quality assessment for heart sound signal by novel features and evaluation in open public datasets
EP3562401B1 (en) Method of characterizing sleep disordered breathing
Dokur Respiratory sound classification by using an incremental supervised neural network
Swarnkar et al. Automated algorithm for wet/dry cough sounds classification
Patel et al. Lung Respiratory Audio Prediction using Transfer Learning Models
Abdollahpur et al. Cycle selection and neuro-voting system for classifying heart sound recordings
Vhaduri et al. Towards automatic cough and snore detection
Fischer et al. Classification of breath and snore sounds using audio data recorded with smartphones in the home environment
Huang et al. Fast diagnosis of bowel activities
Pessoa et al. Pediatric Respiratory Sound Classification Using a Dual Input Deep Learning Architecture
Janott et al. Snoring-an acoustic definition