100 results for "signal classification" · page 5 of 10 · ranked by relevance
…raw Signal Processing ----------------- Classifiers: CNN (Convolutional Neural Network) Feature extraction: sliding windows…
Motor imagery EEG dataset from 8 healthy subjects performing cue-based motor imagination tasks (right hand, feet, rest). Recorded at 512 Hz with 16 electrodes using g.tec g.USBamp amplifier. Dataset comprises 60 trials (20 per class, 3 seconds each) and was developed to validate robust asynchronous EEG-based brain-computer interface control. Data are preprocessed and re-referenced to earlobe.
…into the design of EEG signal classification algorithms. ## Methodology Participants performed a…
This open-access EEG dataset comprises multi-session, multi-task recordings from 15 healthy participants performing resting state and graded difficulty levels of the MATB-II task. Acquired at 500 Hz using 62 active electrodes, the dataset includes 90 trials per participant across two sessions and is designed to support passive brain-computer interface research and mental workload estimation in neuroergonomic applications.
…We investigated the neural signals recorded using a 64-channel EEG system…
This dataset comprises electroencephalography recordings from 16 subjects viewing rapid serial visual presentations of gabor-like stimuli at two presentation rates (6.67 Hz and 20 Hz). Participants performed a concurrent fixation color change detection task while EEG data were acquired. The study investigates the dynamics of visual feature coding and neural mechanisms underlying perception and feature integration.
…Based on these signals, we obtained a maximum average classification accuracy of…
…raw ## Signal Processing - **Classifiers**: Convolutional Neural Network (CNN), Pearson correlation - **Feature extraction…
…at 256 Hz with binary classification of target and non-target events…
…and classification. The dataset consists of 256-channel EEG signals from 11…