Web Science and Digital Libraries Research Group

If you have not already heard of it, NeuroPype is a great tool for developing pipelines to perform sensor data acquisition, processing, analysis, and/or display.  Its Pipeline Designer, based on the Orange application, has a well-developed drag-and-drop interface that makes it easy for anyone from students to experienced clinicians to perform biosignal data analysis.  The NeuroPype - Academic Edition is also freely available to university researchers, faculty and students for non-commercial research. Although the current NeuroPype release comes with hundreds of nodes readily available for use, they may not always provide the functionality that you desire.  Luckily, NeuroPype makes it fairly easy for developers to write and deploy their own Python-based nodes to support their biosignal processing requirements.  In this tutorial, I will take you step-by-step in creating your first NeuroPype custom node.  Getting Started You must first create an account usi...

First of all, I would like to give credit to Matt Gray for going through the major hassle in figuring out the prerequisites and for the awesome documentation provided on how to Install and Use Lab Streaming Layer on Windows. In this blog, I will guide you how to install open source  Lab Stream Layer (LSL)  and stream data (eye tracking example using PupilLabs eye tracker) to  NeuroPype Academic edition . Though a basic version of LSL is available along with   NeuroPype, you will still need to complete following prerequisites before installing LSL. You can find installation instructions for LSL at  https://github.com/sccn/labstreaminglayer/blob/master/doc/BUILD.md . The intention of this blog is to provide an easier and more streamlined step-by-step guide for installing LSL and NeuroPype. LSL is low-level technology for exchange of time series between programs and computers. Figure:   LSL core components Source: ftp://sccn.ucsd.edu/pub/bcilab/l...