Previously, we discussed how passive BCI-based workload monitoring compares with traditional methods and how this enables advanced Neuroergonomics.

But how would such functionality look in real life? A great deal of neuroadaptive applications can be found within the automotive sector.

Now that assistive AI software is closely integrated into driving systems, one may introduce neuroadaptive logic into these systems to customize and improve the driving experience. Starting with the user's preferences, by analyzing the driver's brain activity, a car could automatically adjust the seat position, steering wheel, mirrors and more.

Additionally, neuroadaptive logic can detect workload and other cognitive measures to provide supplementary information about the driver’s state to the AI and optimize its function and software intervention. When a high workload is detected, an automated system could decrease the cognitive demands of driving by offering navigational support, adjusting the temperature settings or just playing soothing music. Adaptive cruise control can also be optimized by regulating the car's speed in real-time.

Other cognitive aspects could be explored. For instance, drowsiness and fatigue can also be taken into account and could inform the system to alert the driver or take over secondary tasks like opening a window or turning on the radio.

Passive BCI-based workload optimizations are not limited to online driving applications. They can also be useful during the R&D phase, where the driver's mental workload can be monitored in real time to evaluate the ease of use and efficiency of the car's control systems and user interface.Similarly, car responsiveness, comfort and controllability can be evaluated, informing the process alongside preexisting R&D systems and tools, significantly speeding up any development.

In short, passive BCI has the potential to revolutionize the driving experience through the development of neuroadaptive AI systems. Stay tuned if you're interested in learning more about this exciting technology.