TY  - BOOK
AU  - Murugappan,M.
AU  - Rajamanickam,Yuvaraj
ED  - SpringerLink (Online service)
TI  - Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders
SN  - 9783030978457
PY  - 2022///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - Biomedical engineering
KW  - Signal processing
KW  - Nervous system—Diseases
KW  - Radiology
KW  - Medical informatics
KW  - Computer vision
KW  - Biomedical Engineering and Bioengineering
KW  - Signal, Speech and Image Processing
KW  - Neurological Disorders
KW  - Health Informatics
KW  - Computer Vision
KW  - Diagnostic Techniques, Neurological -- instrumentation
KW  - Diagnosis, Computer-Assisted -- instrumentation
KW  - Signal Processing, Computer-Assisted -- instrumentation
KW  - Nervous System Diseases -- diagnostic imaging
KW  - Machine Learning
N1  - 1. Abnormal EEG detection using time-frequency images and convolutional neural network. -- 2. Physical action categorization pertaining to certain neurological disorders using machine learning based signal analysis -- 3. A comparative study on EEG features for neonatal seizure detection. -- 4. Hilbert huang transform (HHT) analysis of heart rate variability (HRV) in recognition of emotion in children with autism spectrum disorder (ASD) -- 5. Detection of tonic-clonic seizures using scalp EEG of spectral moments. -- 6. Investigation of the brain activation pattern of stroke patients and healthy individuals during happiness and sadness -- 7. A novel parametric non-stationary signal model for EEG signals and its application in epileptic seizure detection -- 8. Biomedical signal analysis using entropy measures: A case study of motor imaginary BCI in end-users with disability -- 9. Automatic detection of epilepsy using CNN-GRU hybrid model -- 10. Catalogic systematic literature review of hardware-accelerated neurodiagnostic -- 11. Wearable Real-time Epileptic Seizure Detection and Warning System -- 12. Analysis of Intramuscular Coherence of Lower Limb Muscles Activities using Magnitude Squared Coherence
N2  - Biomedical signals provide unprecedented insight into abnormal or anomalous neurological conditions. The computer-aided diagnosis (CAD) system plays a key role in detecting neurological abnormalities and improving diagnosis and treatment consistency in medicine. This book covers different aspects of biomedical signals-based systems used in the automatic detection/identification of neurological disorders. Several biomedical signals are introduced and analyzed, including electroencephalogram (EEG), electrocardiogram (ECG), heart rate (HR), magnetoencephalogram (MEG), and electromyogram (EMG). It explains the role of the CAD system in processing biomedical signals and the application to neurological disorder diagnosis. The book provides the basics of biomedical signal processing, optimization methods, and machine learning/deep learning techniques used in designing CAD systems for neurological disorders. Presents the concepts of CAD for various neurological disorders; Covers biomedical signal processing and machine learning/deep learning techniques; Includes case studies, real-time examples, and research directions
UR  - https://doi.org/10.1007/978-3-030-97845-7
ER  -