Originally designed to accelerate data collection for motor-based BCIs, this application provides a fast, flexible cueing framework that can be repurposed for any paradigm that fits the same basic conditions: (1) repeated, clearly defined events or actions, (2) short trials with variable inter-trial intervals, and (3) a need to gather many labeled examples quickly for training and validation; (4) a need to avoid time-locked responses to sudden cue messages (e.g., visual ERPs due to sudden apparation of text in the screen). 

The app implements a continuous rotating-cross cue, enabling the acquisition of hundreds of trials in a single, brief session. While this structure was introduced for movement execution/attempt paradigms (supporting MRCP and related features), it also translates well to other experimental designs where the key goal is high-throughput, well-timestamped training data under a more natural, less rigid pacing than traditional block cues.

This makes the tool especially useful when you want to prototype decoders quickly, compare feature sets, or benchmark models under conditions that better approximate asynchronous/self-paced operation without sacrificing recording efficiency.

Reference
Crell, M. R., Kostoglou, K., Sterk, K., & Müller-Putz, G. R. (2025). A novel paradigm for fast training data generation in asynchronous movement-based BCIs. Frontiers in Human Neuroscience, 19, 1540155. https://doi.org/10.3389/fnhum.2025.1540155