Skip to main content

A toolkit for EEG phase estimation

Project description

EEGPhasePy

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/

Plan

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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

eegphasepy-0.0.1.tar.gz (6.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

eegphasepy-0.0.1-py3-none-any.whl (5.5 kB view details)

Uploaded Python 3

File details

Details for the file eegphasepy-0.0.1.tar.gz.

File metadata

  • Download URL: eegphasepy-0.0.1.tar.gz
  • Upload date:
  • Size: 6.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.3

File hashes

Hashes for eegphasepy-0.0.1.tar.gz
Algorithm Hash digest
SHA256 dbbecced286404b7c886758f65b73b66ede74c48f38bca42eef3cc25d1498a6f
MD5 29df9d76b95d6302f5a42b71a563c65b
BLAKE2b-256 af9c9e038b397a6c77a8829147ad88590843d3c30a0b4e170f00c2c43052ce9b

See more details on using hashes here.

File details

Details for the file eegphasepy-0.0.1-py3-none-any.whl.

File metadata

  • Download URL: eegphasepy-0.0.1-py3-none-any.whl
  • Upload date:
  • Size: 5.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.3

File hashes

Hashes for eegphasepy-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 a3861e561809aa1a5d236113553b943b207271ea38c942722735ae6fb4e1abab
MD5 50b19bee5ba301327edd30ff283ce7e2
BLAKE2b-256 7679c542dc0a0b6963ab49d80c3a007c7a2e51967e733b2e8ad728d67f73128a

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page