100 results for "wavelet analysis" · page 2 of 10 · ranked by relevance
…P300 latency jitter, brain-computer interface, covert attention, wavelet analysis, single epoch…
…Periodogram, Welch, Goertzel, Yule-AR, STFT, Discrete Wavelet Transform, PSD, CSP, ICA…
EmoEEG-MC is a multi-context emotional EEG dataset comprising 64-channel EEG and peripheral physiological recordings (PPG, GSR) from 60 participants exposed to video-induced and imagery-induced emotional stimuli. Seven emotion categories (joy, inspiration, tenderness, fear, disgust, sadness, neutral) were evoked and validated through subjective reports, enabling investigation of cross-context emotion decoding. The dataset supports research on neural mechanisms of emotion and generalization of affective computing models across contexts.
A multicenter intracranial electroencephalography (iEEG) dataset comprising segmented 3-second single-channel clips from epilepsy patients, annotated for graphoelement classification and artifact detection. The dataset includes clinical metadata such as seizure onset zone (SOZ) flags, electrode anatomy, and reviewer annotations, making it suitable for developing and validating automated signal classification algorithms in clinical neurophysiology.
…Each session includes 23 trials (8 adaptation trials excluded from analysis). 5…
…Periodogram, Welch Spectrum, Goertzel algorithm, Yule-AR Spectrum, FFT, PSD, Discrete Wavelet…
…Tangent Space, Time-Frequency (Morlet wavelet), TWFB (Time Window Filter Bank) - **Frequency…
…The corresponding MATLAB analysis code is available at https://github.com/a8k8nn0…
…A pipeline for MEG analysis. NeuroImage, 253, 119047. https://doi.org/10…
THINGS-EEG2 is a large-scale EEG dataset comprising recordings from 10 subjects viewing 16,540 distinct training images and 200 test images presented via rapid serial visual presentation at 5 Hz. The dataset includes 63-channel EEG data sampled at 1000 Hz across 4 sessions per subject, with approximately 32,540 training trials and 16,000 test trials, designed to support computational modeling of human visual object recognition. Stimuli are drawn from the THINGS database, and the dataset includes resting-state recordings and behavioral annotations for each trial.