Before diving into the technical design of the device, I wanted to fully define its functionality and requirements.
Affordable. The main drawback of current neurofeedback treatment is that it’s expensive. Our device won’t cost more than $250, which is less than 3 sessions of neurofeedback.
Comfortable to wear. If a user has to wear the device for 30 minutes a day, it shouldn’t be obtrusive or unbearable to wear. That includes constraints on the weight and temperature of the device. Since many people have experience wearing bicycle helmets, they’re a good benchmark for the device’s weight. Most helmets weigh around 280 grams, so that is the upper weight limit for our device. The highest temperature that skin can be exposed to without suffering a burn is 140˚F. We’d like to steer clear of hot temperatures, so the temperature limit will be set to 80˚F.
Speedy. Brainwaves change quickly depending on a user’s mental state and reaction to stimuli. The device needs to be fast enough to keep up with those changes. In engineering terms, that means that the data needs to be sampled at a rate greater than or equal to the Nyquist frequency.
Accurate. To provide the correct feedback, the device needs to determine the brainwave category depending on the frequency of the EEG signal. To do this, it should be able to distinguish frequencies at least 0.5 Hz apart.
Easy for a child to use. Because one of the primary applications of this device is for childhood ADHD treatment, the software will likely be tailored for a younger user. Fortunately (or unfortunately?), many children today have extensive experience with electronic devices. There are a lot of best practices out there when it comes to designing for children—large target areas, simple text, engaging colors—but I will do more research on this as we continue to develop the software.