EEGPhasePy is an open-source toolkit for real-time phase estimation from electroencephlography (EEG). It is currently in a work-in-progress state. For a brief intro to the potential applications of EEG phase estimation see https://pmc.ncbi.nlm.nih.gov/articles/PMC10881194/
The goal is to replicate the mainstream EEG phase estimation algorithms including: autoregressive (AR) (Zrenner et al., 2018) and educated temporal prediction (ETP) (Shrinpour et al., 2020). Along with several helper methods for offline analysis of phase estimation experiments, producing figures such as polar histograms or average +- std waveforms. The goal with this package as well is to include methods for overcoming challenges of applying phase estimation in real-time such as a jitter free timing function and auto-incoorporation of delay into all supported algorithms.