A new model for a Mind-Machine Interface (MMI) based on a Takagi-Sugeno Fuzzy System (T-SFS) is built in Node-RED platform, making full advantage of its low-code programming for event-driven applications and wiring together hardware devices, APIs and online services. The integrated by the Node-RED devices are a humanoid robot NAO, a non-humanoid Arduino-based robot and a non-invasive brain-aware device Emotiv EPOC, which is used for translating EEG signals into navigation commands for the robots via a wireless connection. The mind-machine interfacing can be used for learning or just for fun. The author is prof. Anna Lekova.

MMI and T-SFS are developed as separate Node-RED flows and can run on low-cost hardware such as Raspberry Pi, as well as in the cloud and Internet of Things (IoT). T-SFS is used for approximation reasoning over sensor data in terms of EEG signals that are differentiated according to bandwidth and the location of the scalp electrodes [10-20 EEG system]. T-S fuzzy inference is used as a universal function approximator and binds fuzzy sets for the recorded EEG signals to a control parameter of robot modules according to the scalar outputs in the premises of fuzzy rules.

The TSFS flow created in Node-RED are stored using JSON and will be imported soon in the Node-RED flow library to be shared with the community. The MMI flow is still under development.