Clear signal
When the signal is strong, the choice goes straight through. Someone the system is reading accurately is never slowed down.
Helping people communicate with an EEG brain-to-computer interface

Image created by ChatGPT
Cadence reads brain activity with EEG sensors worn against the scalp inside a soft cap. Nothing is implanted and no surgery is involved.
The challenge is to help someone compose and speak a sentence using one slow and sometimes unreliable signal. Cadence highlights available letters and commands one at a time, and the user produces a brain signal when the option they want is highlighted.
The result is an interactive prototype that responds differently depending on how confident the system is that a selection was intentional.
Cadence is an independent design exploration focused on trust, agency, and error recovery in brain-computer interface communication. It is designed to be efficient, cautious, and respectful of the person behind every selection.
This is the working prototype. The blue SELECT bar is the switch: tap it, click it, or press the spacebar to choose whatever is highlighted.
An EEG cap is only useful if someone is willing to put it on every morning. So the sensors are hidden inside something that looks like a hat rather than a medical device, in a range of styles, colors and textures.
Most communication interfaces assume every selection is deliberate. With a brain-generated signal, an accidental input could add the wrong letter, trigger a command, or erase a message that took several minutes to compose.
Asking users to confirm every action would reduce errors, but it would also make communication much slower and more tiring.
I designed an adaptive confirmation system. It keeps the interface efficient when the signal is clear and cautious when it is uncertain.
When the signal is strong, the choice goes straight through. Someone the system is reading accurately is never slowed down.
When the signal is weak, the system asks once before anything is added or changed.
Clear stays on the keyboard, so a message that came out wrong can always be discarded. Selecting it never wipes anything on its own: it raises a confirmation that opens on Cancel.
My first prototype required confirmation for both Speak and Clear. Testing the interaction revealed that confirming Speak added unnecessary effort. Speaking the message is the goal of the experience.
Clear is different. An accidental selection could erase several minutes of work, so it always requires confirmation.
Contrast was the part I could measure. These are the parts that decide whether the interface is usable at all.
How long the highlight rests on each key is a setting, not a fixed speed. It can be slowed down or sped up to match the person using it, which the accessibility guidelines require rather than suggest.
Every row and key is announced aloud as the highlight reaches it, including Cancel and Confirm, so the interface can be driven without watching it.
The screen reader says “Low-confidence signal. Please confirm.” instead of naming a button. Every label is written as a sentence, and the interface speaks up on its own whenever something changes.
Every key is 64 pixels tall and the switch is 72. The guidelines ask for 24, so nothing here is anywhere near the smallest a target is allowed to be.
I documented the approved values in the design system.
The thread

At what point does your speech get lost when saying it requires more of the machine to do the talking?

Brain-computer interfaces already turn attempted speech into text. This turns those same words into images, so a person who cannot speak can show what they feel rather than only spell it.