Biking With Your Brain
Stressed-out cyclists may soon be able to find a city’s bike path of least resistance, thanks to a map that mines bikers’ brainwaves.
Photo via Wikimedia Commons
There are hundreds of maps, online, physical, or app-based, that can help you track your exercise and provide you with new outdoor running or cycling routes. Bike maps are especially important for cyclists who rely on the ability to find protected lanes and cyclist-friendly streets in order to remain safe while riding. However, one area all of these maps overlook is the degree of difficulty—not physical, but mental—cyclists can expect to experience on a given route, where tons of traffic or pothole-ridden pavement can make a simple bike commute seem like a matter of life and death.
Arlene Ducao seeks to narrow this gap in information with the Mindrider Map, which is built off of data collected from cyclists who wear a helmet that measures their brainwaves. According to Wired, Ducao helped develop the helmet (called Mindrider) as a grad student at Massachusetts Institute of Technology in 2010.
The setup is pretty straightforward and simple: An off-the-shelf EEG brainwave sensor made by NeuroSky is built into a standard helmet. Eight cyclists rode most of Manhattan (favoring north-south routes over east-west cross streets) during the months of September and October. Every second, the EEG sensors measured the rider’s level of focus. Attention rose when the rider focused on one thing (for example, a car about to swerve into the bike lane) and decreased when they’re less focused. Level of attention was ranked from 0 to 100, then correlated onto a color scale, from green to yellow to red.
With this information, the cyclists were able to create a map of Manhattan, and the result is an easy-to-read guide that shows relaxing cycling (the green) and stressful cycling (red).
There are some caveats to the study, which Ducao readily acknowledges. Primarily, each stretch of road was covered once, by one rider, and there was no control for factors like unusual traffic congestion, weather, or the rider’s emotions and natural level of attention, which all could have skewed results.
But with more Mindriders participating the data may begin to average out and the Mindrider Map may become quite a useful tool for making cities bike-friendlier.
You can see the Mindrider Map here.