micromed-io 0.2.7

A library to handle Micromed data

Micromed library

Library to handle Micromed data. It also provides some useful scripts.

Install

pip install micromed-io

Convert a Micromed (.trc) file to MNE (.fif) format

from micromed_io.to_mne import create_mne_from_micromed_recording
mne_raw = create_mne_from_micromed_recording("path/to/file.TRC")

Emulate Micromed TCP from .trc file

CLI tool

Use the following command:

mmio_tcp_emulator --file=../data/sample.TRC --address=localhost --port=5123
mmio_tcp_emulator --help

From python script

Download emulate_trc_tcpip.py from the gihub repo in scripts/

python emulate_trc_tcpip.py --file=../data/sample.TRC --address=localhost --port=5123

More details:

python emulate_trc_tcpip.py --help

Read and parse Micromed TCP live data

Download read_tcp_data.py from the gihub repo in scripts/

python read_tcp_data.py --address=localhost --port=5123

Note: Micromed TCP behaves as a client. If you want to try the emulate/read TCP script, launch the reader first that acts as server, then the emulator.

Read Micromed TCP in a sliding window buffer

If you plan to use the Micromed data as input of a decoder, you probably want epochs of format (n_channels, n_samples). Then the MicromedBuffer class is for you. The script read_tcp_to_epoch.py show you how to use it (see the PROCESS HERE comment). It uses a buffer that mimics the sliding window and triggers each time it is filled.

from micromed_io.buffer import MicromedBuffer
micromed_buffer = MicromedBuffer(epoch_duration=5, epoch_overlap=2.5)

Read TRC file

from micromed_io.trc import MicromedTRC
mmtrc = MicromedTRC("sample.TRC")

Then you have access to the trc data:

mmtrc.get_header()
mmtrc.get_markers()
mmtrc.get_data()
mmtrc.get_notes()

Note: get_data() might take times because it loads the brain data

TODO

• Include serial markers parsing
• Parse all info from Micromed header
• Emulate serial markers + notes
• Add tests

Please feel free to reach me if you want to contribute.