Evaluating the DoC-Forest tool for Classifying the State of Consciousness in a Completely Locked-In Syndrome Patient

Sleep analysis in a CLIS patient using soft-clustering: a case study

Assessing consciousness in patients with disorders of consciousness using soft-clustering

Application of Soft-Clustering to Assess Consciousness in a CLIS Patient

Yes/No Classification of EEG data from CLIS patients

Longitudinal Analysis of the Connectivity and Complexity of Complete Locked-in Syndrome Patients Electroencephalographic signal

Motion Detection in Videos of Coherence Matrices in order to detect Consciousness States in CLIS-patients– an Approach

Using Time Domain and Pearson’s Correlation to Predict Attention Focus in Autistic Spectrum Disorder from EEG P300 Components

Extendable Hybrid approach to detect consciousness states in a CLIS patient using machine learning

Consciousness Detection in Complete Locked-in State Patients using Electroencephalogram Coherency and Artificial Neural Networks

Nächste Seite »