Workload-adaptive control interface
An interface that reads your mental workload from EEG and takes over some of the work when you're overloaded.
2026–27In progressEEGMLHardware
The idea
EEG estimates a user’s mental workload during a demanding control task. When the user becomes overloaded, the system raises its level of automation. The team compares this EEG-triggered adaptation against fixed automation and against behavioral measures such as reaction time.
Example task
A user drives a rover through an obstacle course while also watching for warning indicators.
- Low workload: the user controls steering and speed.
- High workload: the rover switches on obstacle avoidance and simplifies the interface.
How we’ll measure it
- Collisions
- Completion time
- Missed warnings
- Unnecessary automation switches
- EEG workload detection compared with behavioral baselines