Drowsy driving takes a back seat in this young teen’s science fair project.
According to the Foundation for Traffic Safety, drowsy driving accounts for up to 6,000 fatal car crashes a year, but 14-year-old Katherine Wu is working to change that statistic for the better.
An eighth grade student at Takoma Park Middle School in North Potomac, MD, Wu was named a Broadcom Maths, Applied Science, Technology, and Engineering Rising Stars (MASTERS) finalist earlier this month for her engineering project that she hopes will help prevent drowsy driving.
The road to achieving a final spot in the Broadcom MASTERS competition, for middle school students in sixth, seventh, and eighth grade, is far from easy.
First, thousands of students across the country compete at local fairs in their home states and only the top 10 per cent at each fair receive nominations to become a Broadcom MASTERS semifinalist. This year’s 300 semifinalists were selected from a pool of over 2,000 applicants and the top 30 finalists were whittled from that semifinalist pool.
But the reward is an all-expenses-paid trip to Washington DC for a chance to compete for a $US25,000 grand prize among other awards. Katherine Wu is one of the 12 female Broadcom MASTERS finalists this year for her design of a device that could provide safer roads in the future.
“It should use input from the driver to determine his/her drowsiness level then give out warning signals when the drowsiness level hits certain criteria,” Wu told Business Insider. “The device should be small, safe, easy to use, and economically feasible.”
To identify the point when an alert driver becomes a drowsy driver, Wu uses a type of technology, that most eighth graders would have a problem pronouncing, called an electroencephalogram (EEG), which physicians often use to identify epilepsy. Below is a more complex version of an EEG.
By measuring electrical wave activity through electrodes on the scalp, EEGs can identify when a person is asleep, awake, or somewhere in between. Delta waves, for example, are the longest type of EEG wave and occur in adults during certain sleep cycles.
Wu is studying a different frequency range that are alpha and beta waves.
“The different EEG waves reflect drowsiness. Alpha waves occur while people are drowsy. Beta waves occur while people are awake. A higher Alpha/Beta ratio represents a drowsier person,” said the 14-year old.
In the example below, the subject is in a relaxed state, producing alpha waves shown on the bottom half of the chart.
Drivers also tend to blink their eyes more frequently when drowsy, which EEGs can also measure. So, to pinpoint drowsiness Wu uses a device called a MindWave Mobile headset that reads data through an EEG electrode located on the driver’s forehead, above the left eye.
Below, an EEG measures the number of times a subject blinks his eyes.
Wu’s headset transmits the data to a small, inexpensive microcomputer that processes it into visual and auditory alerts for the driver with software Wu developed.
Right now, Wu is getting feedback from volunteers on how to improve the overall feel, fit, and wear-ability of the device. There’s still work to do, she says, before it will become a real product, but she is determined.
She said that her seventh grade teacher, “taught me that it is important to make a difference in others’ lives, no matter how small the difference is.”
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