Your Brain Transmits
Your neurons send information from one to another using electrical pulses. As those signals make their way to your scalp, the FocusCalm headband records them through sensors on your forehead…and that’s just the beginning.
FocusCalm Can Measure How Calm and Focused You Are
Much like a heart rate monitor can read your pulse, the FocusCalm headband detects the electrical activity in your brain.
When you are focused and calm, your brain gives off a specific signal that we measure using our AI algorithm. Then, we quantify your FocusCalm Score based on 1250 data points in your brainwave signals.
A low score means your mind looks busy and active. A high score means you are focused and calm. The best score you can get is 100, the lowest is 0…And most of the time, you’ll hover around 50.
You CAN train your brain.
The idea of neuroplasticity is that activities like meditation, neurofeedback, and brain games can train your brain to be more focused and calm.
It’s like learning any new skill… The more you practice, the better you get at focusing and calming your mind.
With the positive feedback you get from FocusCalm, your brain learns to prefer being relaxed and alert. And because the FocusCalm app tracks your score over time, you can see just how much you’re improving.
Other consumer EEG products, even the more popular ones, have trouble keeping connection with mobile devices. This makes the entire function of the product useless. Consistent connection is one of the first things our customers notice with FocusCalm and is why many people switch to FocusCalm.
Garbage in, garbage out. If the raw EEG signal isn’t accurate, the algorithms and training efficacy won’t be there. We have 3rd party lab testing showing FocusCalm’s raw EEG signal has a > 95% correlation match with a 16-channel g.tec nautilus with EEG cap.
Frequency band algorithms work well when you target different areas of the brain. You can achieve far greater accuracy when using machine learning algorithms that don’t impose our assumptions about frequency bands. A beta/theta algorithm looks at 2 features. FocusCalm’s algo looks at over 1000 features in the raw signal to quantify what’s best described as cognitive workload. Our AI out-of-sample testing resulted in 95% classification accuracy.
That being said, the most correlated bands to our algorithm are alpha and theta while the algorithm is taking information from the whole signal. Because the sensors are at Fp1, Fp2, and Fpz and we’re training users to enter a state of calm relaxation, we haven’t found any contraindications based on the existing literature or our neurofeedback partners feedback.
We’ve proven the effectiveness of FocusCalm. Peer-reviewed publications from universities are under review, we’ve published whitepapers on studies with adults and students, and are constantly working with our partners on new studies. Additionally, our training content and methods are based on fMRI studies done with F1 drivers, 1000 of meditators, and sports psychologists.
Part of why FocusCalm has been so effective for our users is that it combines guided meditation with neurofeedback games and executive function (memory, sustained attention, pattern recognition, decision making, etc.) training. FocusCalm combines these exercises to first teach a user to relax, then strengthen their ability to get into that relaxed state, and finally challenge their ability to use that calm state during active tasks. This reinforces the transferability of the skills they’re learning. This concept is based on the training method used by F1 drivers who are trained by Formula Medicine in Italy, who use FocusCalm.