Topic: real-time processing

Develop embedded hardware and software for intelligent sensors and edge AI. Work spans FPGA and HDL design, board layout and commissioning, sensor interfaces, real-time processing and deployment of models on resource-constrained systems.

Portable biosensors become more popular every year. In this context, I propose NeuriGUI, a modular and cross-platform graphical interface that connects to those biosensors for real-time processing, exploring and storing of electrophysiological signals. The NeuriGUI acts as a common entry point in brain-computer interfaces, making it possible to plug in downstream third-party applications for real-time analysis of the incoming signal. NeuriGUI is 100% free and open source.

Brain-computer interfaces (BCIs) are a powerful tool in both clinical applications and basic science research. Traditionally, BCIs rely on electrical signals collected by electrode arrays, which usually suffer from instability due to electrode movements and cell loss [1]. Recent approaches to address this issue continuously update BCI decoders [2]. By reliably identifying the same cells over days, using $Ca^{+2}$ imaging as BCI input may circumvent these limitations, and enable simultaneous recording from large neuronal populations over extended periods. Nonetheless, $Ca^{+2}$ imaging data typ