Simulated EEG and EMG data for Reference Phase Analysis evaluation.

This dataset comprises simulated EEG (Electroencephalography) signals recorded from 29 channels along with an EMG (Electromyography) signal. The signals have been artificially generated using real EEG and EMG signals as the basis. Five distinct source models were generated, each comprising a different number of sources. We created models with 2, 3, 4, 5, and 6 sources. Furthermore, we add additive noise to the signals encompassing SNRs ranging from 90 to 0 dB and a phase jitter ranging from 0.1 to 1.5 radians. We generated EEG and EMG signals using MATLAB and employed a forward model, created with FieldTrip, to convert signals from the source space to the electrode space. EEG measures were computed utilizing a linear mixture model. The simulated dataset aims to mimic the characteristics of real EEG and EMG signals, including their temporal dynamics, noise, and frequency spectra. It serves as a valuable resource for developing and testing signal processing algorithms, and brain-computer interfaces in the fields of neuroscience and biomedical engineering.