EEG-equipped ebike hijacks your brain's threat response system

EEG-equipped ebike hijacks you...
The Ena ebike reads your brain activity and hijacks your threat response system in the name of safety
The Ena ebike reads your brain activity and hijacks your threat response system in the name of safety
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The Ena ebike reads your brain activity and hijacks your threat response system in the name of safety
The Ena ebike reads your brain activity and hijacks your threat response system in the name of safety

Ebikes offer all kinds of opportunities for smart software integration – just check out the Greyp 6.1 we rode recently, which can adjust its assistance rate to keep your heart in a certain cardio zone, or auto-capture video when its AI detects you've done something cool. But this is a new one: an ebike hooked up to an EEG brain-monitoring cap that sits under your helmet.

It's the work of researchers from the Exertion Games Lab at Australia's Monash University, a lab which has put forth two other fairly out-there ebike concepts as well. The Ava ebike project determines its assistance level based on how far forward you're leaning, and the Ari project uses smart city infrastructure to help you plan your speed on the road so you catch as many green lights as possible.

The latest is Ena, the brain-connected electroencephalogram (EEG) bike, and it asks the rider to wear a skull cap covered in electrodes. These electrodes monitor electrical activity in the occipital region at the rear of the brain as you ride.

"Ena monitors that the user's neural activity is between 0.76 and 1.19 microvolts, within the high alpha range of 10-12 Hz," says a team member. "These correspond to the rider's field of view being peripherally open, to afford high awareness of the environment."

A cable snake sends this data to a laptop, which is carried as you ride, and which interfaces with the bike's electronics. When the bike detects you're in a state of peripheral awareness, it turns on the electric motor. But when your field of awareness contracts – which happens automatically when your brain senses some kind of threat or "zooms in" to concentrate on something – it switches off your electric support. The goal here is safety; the bike can recognize danger as quickly as your brain can, and quickly acts to prevent you from accelerating toward it.

It’s an interesting approach, one the researchers describe as almost parental, only intervening when it feels you need it.

Would I want one? Heavens no. Apart from the annoyance of wearing an EEG cap and the bulky prototype electronics, the last thing I want from an ebike is for it to start behaving differently when I see something that registers as a threat. Not to mention, when you're tucked in behind somebody on the bike path, your awareness very much focuses in on the rider in front and what's immediately in front of them. Ebike brakes already switch off the motor in an instant; indeed, so does stopping pedaling, and those are two modes of operation the vast majority of people will be very familiar with.

Still, the idea of hijacking the brain's threat response mechanisms to teach vehicles to react at the speed of thought is an interesting one. Our biology might not have been designed for the speeds we can do in today's vehicles, but our threat recognition circuitry is pretty impressive, and perhaps something that vehicles can benefit from as machine learning ramps up its ability to read the roads for us.

Indeed, this ebike is far from an endpoint, as researcher Josh Andres alludes: "... using peripheral awareness as a neurological state for human-computer integration is viable, and it offers access to a user's pre-attentive processing state that the system can act upon to support a user experience." The question is, where might this tech be more useful?

The research is available online and outlined in the video below.

CHI 2020: Introducing Peripheral Awareness as a Neurological State for Human-Computer Integration

Source: Exertion Games Lab

1 comment
Bob Stuart
This is not a hijack, it is a wire-tap.