The Unlock Project aims to provide brain-computer interface (BCI) technologies to individuals suffering from locked-in syndrome, the complete or near- complete loss of voluntary motor function. While several BCI techniques have been demonstrated as feasible in a laboratory setting, limited effort has been devoted to translating that research into a system for viable home use. This is in large part due to the complexity of existing BCI software packages which are geared toward clinical use by domain experts. With Unlock, we have developed a Python-based modular framework that greatly simplifies the time and programming expertise needed to develop BCI applications and experiments. Furthermore, the entire Unlock system, including data acquisition, brain signal decoding, user interface display, and device actuation, can run on a single laptop, offering exceptional portability for this class of BCI.
In this talk, I will present the Unlock framework, starting with a high-level overview of the system then touching on the acquisition, communication, decoding, and visualization components. Emphasis will be placed on the app developer API with several examples from our current work with steady-state visually evoked potentials (SSVEP).