Decoding multi-class motor imagery and motor execution tasks using Riemannian geometry algorithms on large EEG datasets
Z Shuqfa, AN Belkacem, A Lakas - Sensors, 2023 - mdpi.com
The use of Riemannian geometry decoding algorithms in classifying
electroencephalography-based motor-imagery brain–computer interfaces (BCIs) trials is …
electroencephalography-based motor-imagery brain–computer interfaces (BCIs) trials is …
Hand Motor Imagery Identification Using Machine Learning Approaches in a Protocol Based on Visual Stimuli and Passive Movement
AX González-Cely, CF Blanco-Díaz… - 2023 IEEE …, 2023 - ieeexplore.ieee.org
In recent years, advancements in rehabilitation techniques have been made to leverage
biosignals and passive movement as integral components of physical interventions to …
biosignals and passive movement as integral components of physical interventions to …
Protocol design and testing to investigate Motor Imagery training using cues in different mediums: A pilot study
SS Baberwal, LA Magre… - 2023 20th …, 2023 - ieeexplore.ieee.org
A Brain-Computer Interface (BCI) system converts brain activities into control signals that
could be used to operate an interface such as an exoskeleton. One of the potential brain …
could be used to operate an interface such as an exoskeleton. One of the potential brain …
Yenikapı M1–Kirazlı M1 hattı için istasyon ve hat bazlı yolcu talep tahmini ve raylı ulaşım sistemlerinde sefer sıklığı belirlemede kritik başarı faktörlerinin çok kriterli …
M Nar - 2022 - acikerisim.sakarya.edu.tr
Nüfusun ve motorlu araçların hızlı artışı günümüzde ulaşım sorununu da beraberinde
getirmiştir. Bu sorun, yolcuların duraklarda bekleme sürelerini en aza indirmek ve yolcu …
getirmiştir. Bu sorun, yolcuların duraklarda bekleme sürelerini en aza indirmek ve yolcu …
EEG Classification Using Modified KNN Algorithm
BM Thejaswini, TY Satheesha… - … on Applied Intelligence …, 2023 - ieeexplore.ieee.org
Automatic classification of EEG signals is required for the early identification of various
disorders. In this research paper, statistical denoising and a modified KNN algorithm are …
disorders. In this research paper, statistical denoising and a modified KNN algorithm are …
Causal Representation Learning for Cross-Patient Seizure Classification
Automatic seizure type classification from electroencephalogram (EEG) data can help
clinicians to better diagnose epilepsy. Although many previous studies have focused on the …
clinicians to better diagnose epilepsy. Although many previous studies have focused on the …