1. EEG-based finger movement classification with intrinsic time-scale decompositionMurside Degirmenci, Yilmaz Kemal Yuce, Matjaž Perc, Yalcin Isler, 2024, izvirni znanstveni članek Ključne besede: brain-computer interfaces, electroencephalogram, feature reduction, machine learning, finger movements classification, time series analysis
Objavljeno v DKUM: 16.04.2025; Ogledov: 0; Prenosov: 0
 Celotno besedilo (1,44 MB)
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2. EEG channel and feature investigation in binary and multiple motor imagery task predictionsMurside Degirmenci, Yilmaz Kemal Yuce, Matjaž Perc, Yalcin Isler, 2024, izvirni znanstveni članek Ključne besede: brain-computer interfaces, electroencephalogram, feature and channel investigation, feature selection, machine learning, motor imagery task classification
Objavljeno v DKUM: 19.12.2024; Ogledov: 0; Prenosov: 4
Celotno besedilo (859,70 KB)
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3. Statistically significant features improve binary and multiple motor imagery task predictions from EEGsMurside Degirmenci, Yilmaz Kemal Yuce, Matjaž Perc, Yalcin Isler, 2023, izvirni znanstveni članek Opis: In recent studies, in the field of Brain-Computer Interface (BCI), researchers have
focused on Motor Imagery tasks. Motor Imagery-based electroencephalogram
(EEG) signals provide the interaction and communication between the paralyzed
patients and the outside world for moving and controlling external devices
such as wheelchair and moving cursors. However, current approaches in the
Motor Imagery-BCI system design require.
Ključne besede: brain-computer interfaces, electroencephalogram, feature selection, machine learning, task classification
Objavljeno v DKUM: 10.09.2024; Ogledov: 31; Prenosov: 8
Celotno besedilo (1,15 MB)
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