Lab Streaming Layer (LSL)
Last updated
Last updated
Lab Streaming Layer (LSL) in the Neuphony desktop app enables real-time transfer of EEG data within the same Wi-Fi network. This feature is crucial for Brain-Computer Interface (BCI) and neurofeedback applications, allowing immediate data sharing and fostering interdisciplinary research. LSL supports custom coding and analysis, empowering users to develop tailored solutions and explore diverse applications in neuroscience. With its seamless communication protocol, LSL enhances the Neuphony app's capabilities, making it a versatile tool for real-time EEG data transfer and collaborative research across various platforms.
Lab Streaming Layer or LSL enables real-time transfer of EEG data within the same Wi-Fi network. This feature is crucial for Brain-Computer Interface (BCI) and neurofeedback applications, allowing immediate data sharing and fostering interdisciplinary research. It is a means of transmitting raw EEG data from the desktop app to the connected Wi Fi network.
SDK or Software Development Kit plays a similar role to LSL but is essentially a different technology. SDK is a toolbox built by the company that contains everything the user needs to program their own applications based on EEG. SDKs are complex to use but possess more power giving us precise control over how we use the setup.
LSL should be used when:
Prioritizing ease of use and open-source solutions.
Primary focus is on data analysis and visualization.
SDK should be used when:
We require fine-grained control over data acquisition on a specific device.
We need access to device-specific features not offered by LSL.
Start a default session and start recording.
After the recording has started, a button on the top stating ‘Start LSL’ will get activated. Click to initiate.
After starting the LSL, you may choose any third-party software to view or work upon it.
Start a session -> Start Recording -> Start LSL Stream Data into MATLAB tools like EEGLAB, Monkey Logic or Python's PsychoPy, etc.
Neuphony recommends the following visualizers:
BrainVision for Windows
Click here to learn more and download.
Open-Ephys for MacOS
