Application of Sample Entropy to analyze Consciousness in CLIS patients

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

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

Neural networks for personalized item rankings

Improved Personalized Rankings Using Implicit Feedback

Real-time Phase Detection for EEG-based tACS Closed-loop System

Stroke Rehabilitation and Parkinson’s Disease Tremor Reduction Using BCIs Combined With FES

Neural Networks for Implicit Feedback Datasets

Automated Quantification of the Resistance of Epithelial Cell Layers from an Impedance Spectrum

« Vorherige Seite — Nächste Seite »