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

Küçükakarsu et al., 2023 - Google Patents

A Novel Automatic Audiometric System Design Based on Machine Learning Methods Using the Brain's Electrical Activity Signals

Küçükakarsu et al., 2023

View HTML
Document ID
17192921073549236806
Author
Küçükakarsu M
Kavsaoğlu A
Alenezi F
Alhudhaif A
Alwadie R
Polat K
Publication year
Publication venue
Diagnostics

External Links

Snippet

This study uses machine learning to perform the hearing test (audiometry) processes autonomously with EEG signals. Sounds with different amplitudes and wavelengths given to the person tested in standard hearing tests are assigned randomly with the interface …
Continue reading at www.mdpi.com (HTML) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34—Computer-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
    • G06F19/345—Medical expert systems, neural networks or other automated diagnosis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/32—Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
    • G06F19/322—Management of patient personal data, e.g. patient records, conversion of records or privacy aspects
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions

Similar Documents

Publication Publication Date Title
Islam et al. Explainable artificial intelligence model for stroke prediction using EEG signal
Liu et al. Improving driver alertness through music selection using a mobile EEG to detect brainwaves
Jeong et al. In-ear EEG based attention state classification using echo state network
Nassif et al. COVID-19 detection systems using deep-learning algorithms based on speech and image data
Baradaran et al. Customized 2D CNN Model for the Automatic Emotion Recognition Based on EEG Signals
Gallardo-Antolín et al. Detecting deception from gaze and speech using a multimodal attention LSTM-based framework
Nakanishi et al. Biometrics using electroencephalograms stimulated by personal ultrasound and multidimensional nonlinear features
Khalilzad et al. Newborn cry-based diagnostic system to distinguish between sepsis and respiratory distress syndrome using combined acoustic features
Formoso et al. Detecting phase-synchrony connectivity anomalies in EEG signals. Application to dyslexia diagnosis
Narváez et al. Synthesis of normal heart sounds using generative adversarial networks and empirical wavelet transform
Abou-Abbas et al. EEG oscillatory power and complexity for epileptic seizure detection
Wu et al. Consciousness detection in a complete locked-in syndrome patient through multiscale approach analysis
You Classification of relaxation and concentration mental states with eeg
So et al. Swallow detection with acoustics and accelerometric-based wearable technology: A scoping review
Mattiev et al. Assessment of Model Accuracy in Eyes Open and Closed EEG Data: Effect of Data Pre-Processing and Validation Methods
Küçükakarsu et al. A Novel Automatic Audiometric System Design Based on Machine Learning Methods Using the Brain’s Electrical Activity Signals
Manta et al. Development of machine-learning models for tinnitus-related distress classification using wavelet-transformed auditory evoked potential signals and clinical data
Harezlak et al. Biometric identification based on eye movement dynamic features
Guerrero et al. Principal components analysis of eeg signals for epileptic patient identification
Alqatawneh et al. Statistical-hypothesis-aided tests for epilepsy classification
Rao et al. Investigating influences of medial olivocochlear efferent system on central auditory processing and listening in noise: a behavioral and event-related potential study
Ahad et al. Behavioral Pattern Analysis between Bilingual and Monolingual Listeners’ Natural Speech Perception on Foreign-Accented English Language Using Different Machine Learning Approaches
Zhu et al. Multi-Scale Recurrence Quantification Measurements for Voice Disorder Detection
Adama et al. Application of soft-clustering to assess consciousness in a CLIS patient
Guzek et al. Auditory Discrimination—A Missing Piece of Speech and Language Development: A Study on 6–9-Year-Old Children with Auditory Processing Disorder