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Intelligent Biosignal Analysis Methods

This book describes recent efforts in improving intelligent systems for automatic biosignal analysis. It focuses on machine learning and deep learning methods used for classification of different organism states and disorders based on biomedical signals such as EEG, ECG, HRV, and others.

Bibliographic Details
Main Author: Jović, Alan
Format: eBook
Language:English
Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
Subjects:
Optimal Shrinkage
Machine Learning
Eye Blinks Rate
Surgery Image
Neural Network-based Refinement
Covariate Shift
Skin Conductance Level
Accuracy
Phase-locked Value (plv)
Electroencephalogram (eeg)
N/a
Individual Differences
Smell
Window Duration
Feature Selection
Wine Sensory Analysis
Signal Quality Index
Galvanic Skin Response
Deep Learning
Frequency Band Fusion
Emotion
T-end Annotation
Wearable Sensors
Residual Network
Fatigue Detection
Cross-participant
Sleep Staging
Inter-participant
Stress
Feature Extraction
Emotion Recognition
Mish
Eeg Features
Tsqi
Emotional State
Inter-subject Variability
Brain Functional Connectivity
Photoplethysmography (ppg)
Information Technology Industries / Bicssc
Convolution Neural Network (cnn)
Psychophysics
Fall Detection
Accelerometer
Classifiers
Autonomic Nervous System
Sensitivity
Spatial Transformer Networks
Non-stationarity
Myocardial Infarction
Eeg
Non-local Attention Mechanism
K-fold Validation
Heart Rate
Olfactory Training
Sleep Stage Scoring
Mental Workload
Residual Attention
Event-centered Data Segmentation
Cnn
Wearable Device
Alzheimer's Disease
Disgust
Deap
Electroencephalography (eeg)
Electrocardiogram
Drowsiness Classification
Electrocardiography
Drowsiness Detection
Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
Description
Summary:This book describes recent efforts in improving intelligent systems for automatic biosignal analysis. It focuses on machine learning and deep learning methods used for classification of different organism states and disorders based on biomedical signals such as EEG, ECG, HRV, and others.
Item Description:Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
Physical Description:1 electronic resource (256 p.)
ISBN:books978-3-0365-1691-2
9783036516912
9783036516929

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