WakeCap | OBCI-based Device for Drowsiness Detection

Hello All,

I’ve been fascinated since the beginning of OBCI. I would like to share some great news with you. I’ve been so eager to share this fascinating news with you since June, but I couldn’t until now because of the program’s regulation. Let’s just dive into the story.

The story began when I applied for a program called, Stars of Science. It’s one of the biggest program in the Arab world, which aims to motivate the Arab world’s next generation of aspiring science and technology innovators. I’ve been working on BCI-based applications in my PhD work. That’s why I applied to this program with an idea of building a portable-drowsiness detection system that features the following:

• Uses a single EEG channel
• Uses dry electrodes
• Novel algorithm for processing & measuring drowsiness level
• Real-time drowsiness measurement (using 1-sec window)
• Communicates with a smart device (iOS & Android) to show the drowsiness level in real-time.

Before I applied to the program, I worked on the algorithm that was tested on various datasets (EEG sleep dataset downloaded online) but I didn’t try to implement it on  a board. Therefore, I thought it would be a great opportunity to join the program to build such a system with the aforementioned features. That’s why I thought that OpenBCI would the ideal board to build a working prototype.

The program consists of 4 stages:

1. Idea Audition: This is where I have to convince three judges from different scientific background the feasibility and the novelty of the idea. Only 12 candidates will be selected out of all applicants. (This year there was more than 6000 applicants).
2. Engineering Stage: 2 months to get a prototype ready for testing where only 6 candidates will be qualified to the next stage out of the 12 candidates. In my case, I had many troubles throughout the way but I was able to make a working prototype by the end of this period, where it was tested by a sleep clinic professionals from Weill Cornell in Qatar. Long story short, I got the pass that my device has the potential to detect drowsiness efficiently.
3. Design Stage: This is where we need to re-design the whole prototype and make it ready to go to the market, only 4 out of the 6 candidates will be qualified for the next stage. For me, the major challenge was deciding what application I should go with. Since it’s a drowsiness-detection system, there many fields to chose from; however, I chose to integrate it with hardhat (and more specifically for crane operator but can be modified for miners, construction workers, and soldiers). There are two reasons behind my decision, first: there are need for such a system but no practical solution exist for this problem. Second: the hardhat is already a requirement for crane operator. It’s not like vehicle drivers, where you have to ask them to wear a hat or a band or something like that.
4. The Finale: This is the final episodes of the program, which will announce the rank of the 4 candidates based on the voting of expert judges (50%) and public voting (50%).

The finale will be aired live from Qatar on Friday November 20th, 2015, on MBC4 channel. The 4 candidates who makes it to the finale will be awarded a share of a $600,000 USD cash prize divided in to $300,000, $150,000, $100,000, $50,000 depending in the rank of the candidate.

So far, I was able to make it into the first place in both the Engineering Stage & the Design Stage, and I hope that I can get the first place in the finale. My goal is to use this money to develop WakeCap and startup a new venture.

Lastly, as an appreciation to OpenBCI, I’m willing to support OpenBCI’s new kickstarter with at least $2,250 for (OpenBCI Classroom Kit #1). I might get more kits in the future for an online class I do in Arabic about BCI to motivate young engineers.

I hope that my story motivates others to appreciate how helpful OpenBCI can be. It’s the best starting point for any BCI-based research, application, and even a prototype.