Dear MNE-NIRS development team,
We are writing to request support for fNIRS data processing pipelines including signal quality assessment when data is collected with Lab Streaming Layer (LSL). LSL provides a standardized format that includes raw channels, timestamps, and metadata, making it particularly valuable for researchers working across different proprietary fNIRS systems (LUMO, NIRx, etc.). In our case, we are working on real-time analysis of fNIRS data and are compelled to use LSL to have instant access to the data stream. However, with LUMO systems, we currently must save data in the .lufr format, then convert it to SNIRF through a MATLAB conversion script before we can process it with the MNE-NIRS package. This multi-step conversion process is cumbersome and incompatible with real-time analysis workflows. Native LSL support in MNE-Python would enable real-time fNIRS data analysis, provide a vendor-neutral solution for various fNIRS systems, eliminate unnecessary format conversion steps, and benefit the broader fNIRS research community. Would it be possible to consider adding LSL support in a future release? We would be happy to provide additional details about our use case or contribute to testing if that would be helpful. Thank you for your consideration and for your excellent work on the MNE-NIRS package.
Best regards,
David