Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders

<p>1. Abnormal EEG detection using time-frequency images and convolutional neural network..-&nbsp;2. Physical action categorization pertaining to certain neurological disorders using machine learning based signal analysis.-&nbsp;3. A comparative study on EEG features for neonatal seizure detection..-&nbsp;4. Hilbert huang transform (HHT) analysis of heart rate variability (HRV) in recognition of emotion in children with autism spectrum disorder (ASD).-&nbsp;5. Detection of tonic-clonic seizures using scalp EEG of spectral moments..-&nbsp;6. Investigation of the brain activation pattern of stroke patients and healthy individuals during happiness and sadness.-&nbsp;7. A novel parametric non-stationary signal model for EEG signals and its application in epileptic seizure detection.-&nbsp;8. Biomedical signal analysis using entropy measures: A case study of motor imaginary BCI in end-users with disability.-&nbsp;9. Automatic detection of epilepsy using CNN-GRU hybrid model.-&nbsp;10. Catalogic systematic literature review of hardware-accelerated neurodiagnostic.-&nbsp;11. Wearable Real-time Epileptic Seizure Detection and Warning System.-&nbsp;12. Analysis of Intramuscular Coherence of Lower Limb Muscles Activities using Magnitude Squared Coherence.</p><p></p>