Learn flowRS properly
Structured sequences that build on each other, for people who want the whole model.
Every module is written out in full. Where a module has a film, its page plays it and says which editor it shows.
flowRS Foundations
The core model — graphs, ports, media types, and the Rust a signal graph emits.
- The signal graph emits Rust
- Front panel and block diagram
- Ownership you can see
Measurement and Instruments
Signals, filters, and how flowRS talks to laboratory instruments safely.
- Signals and spectra
- Filter design
- Instrument protocols
Building with Agents
Using AI to author graphs without letting it near the hardware.
- The graph as a specification
- Verification is the job now
- Keeping the model outside the loop
Signals of the Brain
Open a real EEG, see the alpha rhythm appear when the eyes close, average a response to a cue and remove mains hum — each step checked against MNE-Python. For research, education and engineering development; not a medical device. Recordings: PhysioNet EEG Motor Movement/Imagery Dataset (ODC-By 1.0). Text adapted from Delta-Predictive Biosensing's learning corpus, © 2026 AuraSense Tech Corporation, CC BY 4.0.
- Open an EEG
- Alpha rises with eyes closed
- Average an event-related response
- Remove line noise